INGEGNERIA AGRARIA OPTIMIZATION OF BIOENERGY SOLUTIONS AT DIFFERENT FARM SCALES

INGEGNERIA AGRARIA OPTIMIZATION OF BIOENERGY SOLUTIONS AT DIFFERENT FARM SCALES
Alma Mater Studiorum – Università di Bologna
DOTTORATO DI RICERCA IN
INGEGNERIA AGRARIA
Ciclo XXV
Meccanica Agraria - AGR / 09
OPTIMIZATION OF BIOENERGY SOLUTIONS AT
DIFFERENT FARM SCALES
Presentata da: RAFEEK NOSHY THABET YACOPE
Coordinatore dottorato
Relatori
Prof. Ing. Adriano Guarnieri
Prof. Ing. Giovanni Molari
Prof. Dr. Giuliano Vitali
Esame finale anno 2013
Keywords:
Biogas;
Design of on-farm biogas system;
Linear programming optimization;
Mathematical modeling;
On-farm sustainability of energy.
ABSTRACT
RAF is a bio-energetic descriptive model integrates with MAD model to support Integrated
Farm Management. RAF model aimed to enhancing economical, social and environmental
sustainability of farm production in terms of energy via convert energy crops and animal
manure to biogas and digestate (bio-fertilizers) by anaerobic digestion technologies,
growing and breeding practices. The user defines farm structure in terms of present crops,
livestock and market prices and RAF model investigates the possibilities of establish on-farm
biogas system (different anaerobic digestion technologies proposed for different scales of
farms in terms of energy requirements) according to budget and sustainability constraints to
reduce the dependence on fossil fuels. The objective function of RAF (Z) is optimizing the
total net income of farm (maximizing income and minimizing costs) for whole period which
is considered by the analysis.
The main results of this study refers to the possibility of enhancing the exploitation of the
available Italian potentials of biogas production from on-farm production of energy crops
and livestock manure feedstock by using the developed mathematical model RAF integrates
with MAD to presents reliable reconcile between farm size, farm structure and on-farm
biogas systems technologies applied to support selection, applying and operating of
appropriate biogas technology at any farm under Italian conditions.
Also the main results indicates to the flexibility and ability of RAF model to offers reliable
Key design elements (preliminary design) of on-farm biogas production system, and it is
worth to mention that, accurate description, calculation and optimization of this Key design
elements are the crucial factor to selection, applying and operating of appropriate biogas
technology at any farm under Italian conditions.
LIST OF CONTENTS
1. INTRODUCTION ............................................................................................................ 1
1.1. Biogas is a promising energy carrier ............................................................................................ 1
1.2. Comparative advantages and disadvantages of biogas ............................................................... 2
1.2.1. Comparative advantages ...................................................................................................... 2
1.2.2. Comparative disadvantages .................................................................................................. 6
1.3. Current situation and potentials of biogas production in Italy .................................................... 7
1.3.1. National target of nREAP for bioenergy until 2020 .............................................................. 9
1.3.2. Italian potentials of biogas production ................................................................................. 9
1.4. Mathematical modeling and optimization of anaerobic digestion............................................ 10
1.5. Objective of the study ................................................................................................................ 13
1.5.1. Description of RAF model ................................................................................................... 15
2. REVIEW OF LITERATURE .............................................................................................. 17
2.1. Anaerobic digestion (AD) ........................................................................................................... 17
2.1.1. Biomass types and characteristics related to AD................................................................ 18
2.1.2. Theory of AD ....................................................................................................................... 22
2.1.3. Factors controlling the AD .................................................................................................. 26
2.1.4. Operational parameters controlling the AD ....................................................................... 30
2.1.5. Evaluation parameters of biogas plants ............................................................................. 32
2.2. Different technologies of agricultural biogas plants .................................................................. 33
2.2.1. Different scales of agricultural biogas plants...................................................................... 33
2.3. Main components of biogas plants ............................................................................................ 37
2.3.1. Feedstock handling system ................................................................................................. 40
2.3.2. Storage of feedstock ........................................................................................................... 42
2.3.3. Systems of feeding .............................................................................................................. 43
2.3.4. Heating system of digester ................................................................................................. 48
2.3.5. Digesters ............................................................................................................................. 49
2.3.6. Stirring systems ................................................................................................................... 63
2.3.7. Biogas storage ..................................................................................................................... 66
2.3.8. Digestate storage ................................................................................................................ 69
2.4. Biogas characteristics ................................................................................................................. 70
2.5. Biogas utilization ........................................................................................................................ 71
2.5.1. Biogas preparation before utilization ................................................................................. 72
2.5.2. Direct combustion............................................................................................................... 73
2.5.3. Internal combustion............................................................................................................ 73
2.5.4. Gas turbines ........................................................................................................................ 74
2.5.5. Fuel cells.............................................................................................................................. 75
2.5.6. Combined heat and power (CHP) ....................................................................................... 76
2.5.7. Biogas upgrading (biomethane production) ....................................................................... 81
2.6. Economical considerations to establish on-farm biogas system ............................................... 83
2.6.1. Fixed costs (costs of construction)...................................................................................... 83
2.6.2. Variable costs (operating costs) .......................................................................................... 84
3. MATERIAL AND METHODS .......................................................................................... 85
3.1. Material ...................................................................................................................................... 85
3.1.1. Farm characteristics under study ....................................................................................... 85
3.2. Methods ..................................................................................................................................... 86
3.2.1. Linear programming ........................................................................................................... 86
3.2.2. Description of MAD model ................................................................................................. 87
3.2.3. Description of RAF model ................................................................................................... 94
3.2.4. On-farm agricultural production module ........................................................................... 96
I
3.2.5. On-farm livestock nutrition requirements module ............................................................ 98
3.2.6. On-farm energy consumption module ............................................................................. 101
3.2.7. On-farm labor requirements module ............................................................................... 105
3.2.8. On-farm account balance module .................................................................................... 106
3.2.9. Design of on-farm biogas system module ........................................................................ 106
3.2.10. The objective function .................................................................................................... 130
3.2.11. GAMS solver.................................................................................................................... 130
4. RESULTS AND DISCUSSION ........................................................................................ 131
4.1. Case studies.............................................................................................................................. 131
4.1.1. Case study (A) ................................................................................................................... 131
4.1.2. Case study (B).................................................................................................................... 136
5. SUMMARY AND CONCLUSION .................................................................................. 141
6. RECOMMENDATIONS ............................................................................................... 149
7. REFERENCES ............................................................................................................. 151
8. APPENDICES ............................................................................................................. 165
II
LIST OF TABLES
Table 1.1: Italian potentials of bioenergy .................................................................................. 9
Table 2.1: Bio-wastes suitable for biological treatment .......................................................... 19
Table 2.2: The characteristics of some digestible feedstock types ......................................... 20
Table 2.3: Problematic materials, contaminants and pathogens of some AD substrates
categories ................................................................................................................ 22
Table 2.4: Thermal stages and typical hydraulic retention times............................................ 26
Table 2.5: Operational parameters of biogas plants ............................................................... 32
Table 2.6: Main characteristics of anaerobic digesters technologies in agricultural biogas
plants ....................................................................................................................... 50
Table 2.7: Comparison between different technologies of agricultural anaerobic digesters . 50
Table 2.8: Composition of raw biogas ..................................................................................... 70
Table 2.9: Theoretical gas production ..................................................................................... 71
Table 2.10: Methane production from different feedstock materials .................................... 71
Table 2.11: Different technologies for utilization and upgrading of biogas ............................ 72
Table 2.12: Different uses of heat and power produced from on-farm CHP unit ................... 78
Table 2.13: Estimated fixed costs of establish on-farm biogas system, based on installed
electrical capacity of on-farm CHP unit ................................................................ 84
Table 2.14: Estimated variable costs of operating on-farm biogas system, based on electrical
energy generated from on-farm CHP unit ............................................................ 84
Table 3.1: List of macro-activities used by model related to land use .................................... 89
Table 3.2: List of livestock related to macro activities ............................................................ 89
Table 3.3: Indexes list of RAF model ........................................................................................ 96
Table 4.1: Description of farm structure for the hypothetical case study (A) (pre-optimization
input data from GUI) ............................................................................................ 132
Table 4.2: Optimum output data of hypothetical case study (A) .......................................... 132
Table 4.3: Description of farm structure for the hypothetical case study (B) (pre-optimization
input data from GUI) ............................................................................................ 137
Table 4.4: Optimum output data of hypothetical case study (B) .......................................... 137
III
LIST OF FIGURES
Fig. ‎1.1: The sustainable cycle of biogas from AD ..................................................................... 5
Fig. ‎1.2: Energy use by source and bioenergy contribution in Italy in 2009.............................. 7
Fig. 1.3: Number and distribution of biogas plants by feedstock until 31 December 2010 ...... 8
Fig. 1.4: The outlines of RAF model, main results and recommendations of optimization
process ........................................................................................................................ 16
Fig. 2.1: Biochemical conversion technologies for anaerobic digestion and alcohol
fermentation .............................................................................................................. 17
Fig. 2.2: Specific methane yield from different types of AD substrates .................................. 21
Fig. 2.3: The main steps of AD process .................................................................................... 23
Fig. 2.4: Biogas yield after addition of substrate-batch test.................................................... 24
Fig. 2.5: Relative yield of biogas, depending on temperature and hydraulic retention time . 27
Fig. 2.6: Household-scale digesters: (A) Floating-drum plant, (B) Fixed-dome plant and (C)
Balloon plant ............................................................................................................. 34
Fig. 2.7: Scheme of farm-scale biogas plant uses energy crops, manure slurry and organic
residues as feedstock and including different pathways of biogas utilization .......... 36
Fig. 2.8: Centralized biogas plant ............................................................................................. 37
Fig. 2.9: Main processing steps of anaerobic technologies ..................................................... 38
Fig. 2.10: Main components of biogas plant ........................................................................... 38
Fig. 2.11: Processing stages of agricultural biogas plants........................................................ 39
Fig. 2.12: Agricultural co-digestion biogas plant using manure and maize silage ................... 40
Fig. 2.13: Mechanical system for separation solid wastes by using trommel (left) and
problematic material, which was separated from feedstock (right) ....................... 42
Fig. 2.14: Bunker silo, made of concrete and silage is covered by plastic foils ....................... 43
Fig. 2.15: Manure slurry tank ................................................................................................... 43
Fig. 2.16: Centrifugal (rotating) pump ..................................................................................... 44
Fig. 2.17: Rotary lobe pump ..................................................................................................... 44
Fig. 2.18: Progressing cavity pump .......................................................................................... 44
Fig. 2.19: Stop-valves (left) and pumping system (right) ......................................................... 45
Fig. 2.20: Pumping systems...................................................................................................... 45
Fig. 2.21: Loader feeding maize silage into the container ....................................................... 46
Fig. 2.22: Screw pipe conveyors ............................................................................................... 46
Fig. 2.23: (A) Wash-in shaft, (B) feed pistons and (C) feed conveyors system for feeding
feedstock into the digester ...................................................................................... 47
Fig. 2.24: Feeding container equipped with screw conveyor, mixing and crushing tools....... 48
Fig. 2.25: Heating system of biogas plant (left) and heating pipes, installed inside the
digester (right).......................................................................................................... 49
Fig. 2.26: Covered lagoon digester .......................................................................................... 51
Fig. 2.27: Plug flow digester ..................................................................................................... 53
Fig. 2.28: Complete mix digester ............................................................................................. 54
Fig. 2.29: Fixed film digester .................................................................................................... 56
Fig. 2.30: Up-flow Anaerobic Sludge Blanket digester (UASB) ................................................ 57
Fig. 2.31: Garage-type batch digester, loaded by loader ........................................................ 59
Fig. 2.32: Vertical dry digester ................................................................................................. 60
Fig. 2.33: Horizontal dry digester ............................................................................................. 61
Fig. 2.34: Horizontal dry digesters run in parallel .................................................................... 62
IV
Fig. 2.35: Submersible motor propeller stirrer ........................................................................ 64
Fig. 2.36: Vertical hanging paddle stirrers ............................................................................... 64
Fig. 2.37: Horizontal hanging paddle stirrers ........................................................................... 64
Fig. 2.38: diagonal paddle stirrers............................................................................................ 65
Fig. 2.39: Hydraulic stirring system .......................................................................................... 66
Fig. 2.40: Pneumatic stirring system ........................................................................................ 66
Fig. 2.41: Biogas tight membranes .......................................................................................... 67
Fig. 2.42: Safety pressure valves .............................................................................................. 67
Fig. 2.43: Gas cushion tank ...................................................................................................... 68
Fig. 2.44: Gas balloon tank ....................................................................................................... 68
Fig. 2.45: High pressure tank of biogas .................................................................................... 69
Fig. 2.46: Covered digestate storage tank ............................................................................... 70
Fig. 2.47: Biogas burner for steam boiler ................................................................................ 73
Fig. 2.48: Biogas Otto-generator.............................................................................................. 74
Fig. 2.49: Dual fuel-generator .................................................................................................. 74
Fig. 2.50: Gas turbines ............................................................................................................. 75
Fig. 2.51: Gas turbine process with heat recovery in a steam turbine downstream .............. 75
Fig. 2.52: Simplified scheme of a fuel cell ................................................................................ 76
Fig. 2.53: CHP unit equipped with gas-Otto engine................................................................. 77
Fig. 2.54: CHP unit equipped with pilot Injection gas engine .................................................. 78
Fig. 2.55: Gas micro turbine ..................................................................................................... 79
Fig. 2.56: Schematic construction of an alpha stirling containing two pistons, one hot, one
cold and a regenerator in the connecting pipe........................................................ 80
Fig. 2.57: ORC unit.................................................................................................................... 81
Fig. 2.58: Biogas upgrading unit ............................................................................................... 82
Fig. 2.59: Biofuels in comparison: Range of a personal car, running on biofuels produced on
feedstock / energy crops from one hectare arable land ......................................... 82
Fig. 3:1 MAD flow-chart ........................................................................................................... 88
Fig. 3:2 MAD architecture ........................................................................................................ 88
Fig. 3.3: Pathway of data processing in RAF model ................................................................. 95
Fig. 3.4: RAF model architecture.............................................................................................. 95
Fig. 3.5: Main components of on-farm biogas system, using silage and manure feedstock 107
V
ACRONYMS
Technical terms
Description
AD
BTTP
CSTR
CH4
CO
CO2
C/N
CHP
DM
e.g.
FF
GHG
GUI
HRT
LSU
MSW
Mtoe
NH3
ORC
PINGE
ppm
SRT
TS
VFA
VS
Anaerobic digestion
Block type thermal power
Completely stirred tank reactor
Methane
Carbon monoxide
Carbon dioxide
Carbon to nitrogen ratio
Combined heat and power
Dry matter
Exempli gratia “for example”
Fresh feedstock
Greenhouse gases
Graphical use interface
Hydraulic retention time
Livestock unit
Municipal solid waste
Million tons of oil equivalent
Ammonia
Organic Rankine cycle
Pilot injection natural gas engine
Parts per million
Solids retention time
Total solids
Volatile fatty acids
Volatile solids
Conversion units
KiloWatt (kW)
MegaWatt (MW)
GigaWatt (GW)
TeraWatt (TW)
1 Joule (J)
1Wh
1 cal
1 British Thermal Unit (BTU)
1 cubic meter (m³)
1 bar
1 millibar
1 psi
1 torr
1 millimeter mercury (0°C)
1 hectopascal (hPa)
= 1000 Watts
= 1000 kW
= 1 million kW
= 1 thousand million kW
= 1 Watt second = 278 x 10-6 Wh
= 3600 J
= 4.18 J
= 1055 J
= 1000 liter (L)
= 100000 Pascal (Pa)
= 100 Pa
= 6894.76 Pa
= 133.32 Pa
= 133.32 Pa
= 100 Pa
VI
DISCLAIMER
For clear distinguish between technical terms “Mass and Volume” of the same materials
used as feedstock for biogas production per unit of time, the author used the technical term
“Volume” for express the inner-volume of different components of on-farm biogas system,
while used the technical term “Quantity” for express the volume of feedstock and
substrates used for biogas production per unit of time.
VII
Introduction
1. INTRODUCTION
1.1. Biogas is a promising energy carrier
Biogas is a non-conventional, promising renewable energy carrier, which combines the
disposal of organic waste with the formation of a valuable energy carrier, methane. On the
other hand biogas energy characterized as the best way of derive energy from polluted
wastes, clean, eco-friendly, money saver, time saver, and minimizes expenditure of the
foreign currency for the import of fossil fuels.
Currently, accumulation of organic wastes considers one of the most environmental
problems in our society. In most industrial countries, they are applying sustainable waste
management; moreover the one of the major political priorities is reduction accumulation
of organic wastes, which leads to Intensify efforts of reduce pollution, Greenhouse Gas
emissions (GHG) and to mitigate global climate changes. The aim of sustainable waste
management is produce energy, recycling of nutrients and organic matter Instead of
uncontrolled waste dumping, which no longer acceptable today (Kossmann et al., 1999 and
Al Seadi et al., 2008).
One of the most important and modern technologies, which dealing with recycling of
organic wastes is Anaerobic Digestion (AD) of digestible organic waste (agricultural byproducts and wastes, animal manure and slurries), which converts these substrates to
renewable energy carrier (biogas), reduce the GHG, produce an excellent natural fertilizer
for agriculture purposes and achievement many social and economic benefits for the
producer and consumer of biogas (Dennis and Burke, 2001).
AD is a microbiological process of anaerobic decomposition (in the absence of oxygen) of
the organic matter, which produces biogas in air-proof reactor tanks, commonly named
digesters. Biogas produced in many natural environments and widely applied today. There is
a wide range of micro-organisms are decomposition the organic matter in anaerobic
process, which has two main end products: biogas and digestate. Biogas is a combustible
gas; mainly it is a mix of methane, carbon dioxide and small amounts of other gases and
trace elements. Digestate is the decomposed substrate, which rich in nutrients and suitable
1
Introduction
to be used as plant fertilizer (Kossmann et al., 1999; Kramer, 2004 and Al Seadi et al.,
2008).
The first production of biogas was in UK in 1895. Since then, the biogas production process
was developed and applied widely for wastewater treatment and sludge stabilization. The
energy crisis in the mid of 70s of twenty century has been created a new dimensions of
biogas production and use. Currently, the interesting of biogas is grow up, due to
international efforts for partially replacing of the fossil fuels by renewable energy because
its benefits such as realized environmentally sustainability, recycling of agricultural byproducts and residues, animal manure and other organic wastes (Kossmann et al., 1999;
Dennis and Burke, 2001 and Al Seadi et al., 2008).
Today, In Asia alone (especially in China, India, Nepal and Vietnam), millions of families uses
small-scale digesters to produce biogas for multi purposes (such as cooking and lighting).
Multi thousands of agricultural biogas plants have been established in Europe and North
America, many of them using the latest technologies within this area, and their number is
continuously growing (Kossmann et al., 1999; Dennis and Burke, 2001 and Al Seadi et al.,
2008).
1.2. Comparative advantages and disadvantages of biogas
Biogas production and use has multi environmental and socioeconomic benefits for
domestic and commercial use.
1.2.1. Comparative advantages
1.2.1.1. Socioeconomic and environmental benefits
1. One of the main sources of renewable energy:
Production process of biogas from biomass is permanently renewable (unlike fossil
fuels), where solar energy storage during photosynthesis in biomass and biomass
converts during AD to biogas, which improves the energy balance of the state and also
make an positive contribution for protection the natural resources and environment
(Al Seadi et al., 2008 and European Biomass Association, 2009).
2
Introduction
2. Participation in reduction of greenhouse gas emissions and mitigation of global
warming:
Combustion of fossil fuels (such as coal, crude oil and natural gas) releases emissions
of carbon dioxide (CO2 is one of the most important GHG) into the atmosphere, which
causes global warming. The combustion of biogas also releases CO2, but the main
difference between biogas and fossil fuels is that, the carbon in biogas was recently
absorbed from the atmosphere during photosynthetic process of plants, so that the
carbon cycle of biogas is thus closed within a very short time (between one and
several years), while carbon cycle of fossil fuels closed within a very long
time(between thousands and millions years), so that using of biogas helps to reduce
global warming (European Biomass Association, 2009 and Esfandiari and
Khosrokhavar, 2011).
3. Reduced quantities and risk of imported fossil fuels:
The countries, which do not have high reserves of fossil fuels depending on import
large quantities of fossil fuels, which concentrated in few geographical areas of our
planet. Import of fossil fuels is risky, such as transport for long-distance, leakage of oil
or gas and volatility of prices, which creates a permanent insecure status due to
dependency on import of energy. Most European countries are strongly dependent on
fossil energy imports from regions rich in fossil fuel sources such as Russia and the
Middle East. Most of European countries have great potentials to produce biogas from
AD, depending on national and regional biomass resources, which will increase
security of national energy supply and reduce dependency on imported expensive
fuels (Kossmann et al., 1999 and Al Seadi et al., 2008).
4. Organic wastes are valuable resource of renewable energy:
European countries produce large quantities of organic wastes from industry,
agriculture and households and convert this organic wastes to biogas presents an
excellent way for energy production, followed by recycling of the digested substrate
as fertilizers. AD can also contribute to reducing the volume of waste and of costs for
3
Introduction
waste disposal (Kossmann et al., 1999; Al Seadi et al., 2008 and European Biomass
Association, 2009).
5. Creation of jobs:
Biogas production from AD consists of many processes such as collection and
transport of AD feedstock, manufacture of technical equipment, construction,
operation and maintenance of biogas plants, all this process depending on trained
labors. From the other hand development of a national biogas sector lead to the
establishment of new enterprises, which increases the income in rural areas and
creates new jobs (Kossmann et al., 1999; Kramer, 2004 and European Biomass
Association, 2009).
6. Biogas is flexible and versatile:
Biogas is flexible energy and suitable for multi uses such as direct use for cooking and
lighting, but in many countries biogas is used nowadays for combined heat and power
generation (CHP) or it is upgraded and fed into natural gas grids, used as vehicle fuel
or in fuel cells (Kossmann et al., 1999; Kramer, 2004; Al Seadi et al., 2008 and
European Biomass Association, 2009).
7. Minimum water requirements:
AD process requires the lowest amount of water for processing when compared with
other biofuels. This is an important aspect related to the expected future water
scarcity in many regions of the world (Kramer, 2004 and European Biomass
Association, 2009).
1.2.1.2. Benefits for the producers
1. Additional source of income for farmers:
Biogas production technologies are economically and attractive for farmers and
provides them additional income. The farmers get also a new and important social
role as energy suppliers and waste treatment operators (Al Seadi et al., 2008 and
European Biomass Association, 2009).
4
Introduction
2. Digestate is an excellent fertilizer:
After production of biogas, the by-product of AD is digested, which consider a valuable
soil fertilizer, rich in nitrogen, phosphorus, potassium and micronutrients, and can be
applied on soils with the usual equipment for application of manure. Compared with
raw animal manure or compost, digestate has improved fertilizer efficiency due to
higher homogeneity and nutrient availability, better C / N ratio and significantly
reduced pathogenesis and odors (Kramer, 2004 and Lukehurst et al., 2010).
3. Closed nutrient cycle of biogas:
The biogas production from AD provides a closed nutrient and carbon cycle from the
production of feedstock to use of digestate as fertilizers (Fig. 1.1). When the methane
(CH4) is combustion the carbon dioxide (CO2) is released to the atmosphere and
retaken by vegetation during photosynthesis. Some carbon compounds still remains in
the digestate, which increase the carbon content of soils, when digestate is use as
fertilizer (Kossmann et al., 1999; Al Seadi et al., 2001; Al Seadi et al., 2008 and
Lukehurst et al., 2010).
Fig. 1.1: The sustainable cycle of biogas from AD (as cited
in Al Seadi et al., 2001)
5
Introduction
4. Biogas produces from multi feedstocks:
Biogas could be produced from multi feedstocks such as wet biomass, which has
moisture content more than 60 % (e.g. sewage sludge, animal slurries, flotation sludge
from food processing etc.). Currently, many of energy crops (grains, maize, rapeseed),
have been widely used as feedstock for biogas production in countries like Austria,
Germany and Italy. Besides energy crops, all kinds of agricultural by-products and
wastes, damaged crops, unsuitable for food or resulting from unfavorable growing
and weather conditions, can be used to produce biogas and fertilizer (Kossmann et
al., 1999; Kramer, 2004 and Lukehurst et al., 2010).
5. Disposal of odors and insects:
Animal dung and many organic wastes are sources of unpleasant odors and attract
insects, but AD reduces these odors by up to 80 % (Kossmann et al., 1999; Al Seadi et
al., 2008 and Lukehurst et al., 2010).
6. Improve Veterinary safety:
Use a digestate as fertilizer improves veterinary safety compared with application of
untreated manure and slurries. In general, the aim of sanitation is to inactivate
pathogens, weed seeds and other biological hazards and to prevent disease
transmission by use AD process of organic waste by save way (Kossmann et al., 1999;
Al Seadi et al., 2008 and Lukehurst et al., 2010).
1.2.2. Comparative disadvantages
According to Huisman et al. (2007); Grieg-Gran et al. (2009) and Bond and Templeton
(2011) there are a few disadvantages of biogas:

The process of digestion reduces the total solids content in the feedstock (energy
crops, by-products and manure yield) and thus there is a volume loss of the organic
waste compared to composting, however both can produce a fertilizer;

Biogas contains contaminant gases which can be corrosive to gas engines and boilers;

Digestate must meet high standards in order to be used on land without detrimental
effect on agricultural uses especially with food crops;
6
Introduction

Biogas plants and gas upgrading plants both have a relatively high heat and energy
requirements, which required some of the biogas yield to be used on-site;

Will only produce a limited quantity of energy demand and is dependent upon
location in proximity to feedstock and energy users;

There is little or no control on the rate of gas production, although the gas can, to
some extent be stored and used as required;

Small- and middle-scale of anaerobic technologies for the treatment of solid waste in
middle- and low-income countries is still relatively new;

Experts are required for the design and construction, depending on the scale of biogas
plant and may also for operating and maintenance;

Reuse of produced energy (e.g. transformation into, fire / light, heat and power)
needs to be established;

High sensitivity of methanogenic bacteria to a large number of chemical compounds
and fluctuation of temperature and steering during the digestion process;

Unwanted odor can be emitted from sulphurous compounds.
1.3. Current situation and potentials of biogas production in Italy
Currently, the use of biomass for energy purposes contributes for just 3.5 % to the final
national energy consumption (180.2 Mtoe1) but with a production equal to about 6.2 Mtoe,
bioenergy represent 29.5 % of the whole amount of energy from renewable sources in Italy
(21,1 Mtoe). The biogas contribution to the total bioenergy production is about 8 % (8.4 %
of the electricity production from biomass sources, Fig. 1.2) (ENEA, 2010).
Fig. 1.2: Energy use by source and bioenergy contribution in Italy in 2009
(as cited in ENEA, 2010)
1
Million tons of oil equivalent
7
Introduction
Regional distribution of Italian biogas sector shows that, biogas plants are mainly located in
the northern regions and more than 60 % are related with the agriculture and zoo-technical
sector as illustrated in Fig. (1.3). 50 % of agriculture and zoo-technical biogas plants use codigestion mixture of energy crops, by-products, residues and animal manure.
Fig. 1.3: Number and distribution of biogas plants
by feedstock until 31 December 2010 (as
cited in CRPA, 2011)
According to ENEA (2010) could summarize the current state of biogas in Italy as follow:

Biogas production in 2009 was about 0. 499 Mtoe;

78 % of biogas production coms from MSW2 Landfills (228 plants);

451 plants feed by a mixture of different substrates (from agroindustry, agro-zootechnical residues and sewage sludge);

The total installed capacity is about 507.7 MW (including landfills);

A recent growing trend of biogas sector comes from the growing of the agro-industrial
and zoo-technical biogas production.
2
Municipal solid waste
8
Introduction
1.3.1. National target of nREAP for bioenergy until 2020
The National Renewable Energy Action Plan (nREAP) sets for bioenergy in Italy a target by
2020 equal to 9.82 Mtoe (0.834 Mtoe of biogas), in order to cover 19 % of electricity, 54 %
of heating and cooling and 87 % of transport fuel of the total consumption from renewable
energy sources (ENEA, 2010).
The capacity of renewable energy produced in 2009 (6.238 Mtoe, including 0. 499 Mtoe
from biogas) equal to 63.5 % compared to the target set for 2020 by the nREAP (9.82 Mtoe).
Such a target could seem ambitious, but is considerably smaller than the estimated
potentials (24 - 30 Mtoe / year, see Table 1.1) for bioenergy in Italy, able to cover up to 13 17 % of the total energy demand (ITABIA, 2009 and ENEA, 2010).
Table 1.1: Italian potentials of bioenergy (author elaboration
cited in ITABIA, 2009)
Biomass
Residues from agricultural and agro-industrial
Residues from forestry and wood industry
Municipal solid waste
Livestock manure
Firewood
Energy crop
Total
Mtoe / year
5
4.3
0.3
10 - 12
2-4
3-5
24 - 30
1.3.2. Italian potentials of biogas production
If we sum all quantities of energy crops (over set-aside lands) plus agricultural residues,
livestock manure, agroindustry residues, MSW and sewage sludge, we could roughly
estimate a potential of about 65 million m3 / year of feedstock available for biogas
production (CRPA, 2011).
A total of 1.3 million m3 of biogas / day can be produced only from livestock manure that
could result in a total biomethane production of 237 million m 3 / year which is about 10
times more than the actual needs of methane used for transports in Italy (CRPA, 2011).
9
Introduction
1.4. Mathematical modeling and optimization of anaerobic digestion
Mathematical models are describing anaerobic digestion systems by using mathematical
concepts and language. The process of developing a mathematical model is
termed mathematical modeling. Mathematical models can take many forms, including but
not limited to dynamical systems, statistical models, differential equations, or game
theoretic models. These and other types of models can overlap, with a given model
involving a variety of abstract structures. In general, mathematical models may
include logical models, as far as logic is taken as a part of mathematics. In many cases, the
quality of a scientific field depends on how well the mathematical models developed on the
theoretical side agree with results of repeatable experiments. Lack of agreement between
theoretical mathematical models and experimental measurements often leads to important
advances as better theories are developed. There are two types of anaerobic digestion
mathematical models:

Descriptive models;

Controlling models.
Optimization is finding an alternative with the most cost effective or highest achievable
performance under the given constraints, by maximizing desired factors and minimizing
undesired ones. In comparison, maximization means trying to attain the highest or
maximum result or outcome without regard to cost or expense. Practice of optimization is
restricted by the lack of full information, and the lack of time to evaluate what information
is available. In computer simulation (mathematical modeling) of biogas systems,
optimization is achieved usually by using linear programming techniques of operations
research.
Batstone et al. (2002) mention that structured model includes multiple steps describing
biochemical as well as physic-chemical processes. The biochemical steps include
disintegration from homogeneous particulates to carbohydrates, proteins and lipids;
extracellular hydrolysis of these particulate substrates to sugars, amino acids, and long chain
fatty acids (LCFA), respectively; acidogenesis from sugars and amino acids to volatile fatty
acids (VFAs) and hydrogen; acetogenesis of LCFA and VFAs to acetate; and separate
10
Introduction
methanogenesis steps from acetate and hydrogen / CO2. The physic-chemical equations
describe ion association and dissociation, and gas-liquid transfer. Implemented as a
differential and algebraic equation (DAE) set, there are 26 dynamic state concentration
variables, and 8 implicit algebraic variables per reactor vessel or element. Implemented as
differential equations (DE) only, there are 32 dynamic concentration state variables.
Lindmark (2005) implemented a Biogasopt-project, aimed to improve the biogas process by
focusing on some key issues in the process, namely pretreatment of the incoming substrate,
mixing inside the digester and membrane filtration of the process water. The Process can be
split up into three different parts (pretreatment, digestion and sludge treatment) which can
be improved and optimized independently of each other but still leads to an overall
efficiency increase of the process.
Fiorese et al. (2008) proposed a method to evaluate the AD plants convenience on a given
territory by an economic, energy and emissive point of view. A mathematical model is
formulated in order to optimize biomass use by finding the optimal AD plants’ number,
capacity, location, and the corresponding biomass collection basin. The method is applied to
the district of Cremona, one of the most important Italian farming areas. The optimal
solution is achieved by widespread AD plants over the territory in order to exploit biomass
locally. Biomass transportation is minimized for its high costs are not balanced by
economies of scale. AD plants in Cremona yield positive returns in economic terms, as
energy produced and GHG emissions avoided (7 % reduction with respect to 2003). The
robustness of this result has been confirmed by sensitivity analysis of the plant and
transportation costs. The final result is crucial for local planning of biomass exploitation:
local governments can encourage the development of conversion plants at municipal level
without the need for centralized decisions.
Aworanti et al. (2011) developed a mathematical model for the prediction of the behavior
of microbial processes. The development of the models was based upon a material balance
analysis of the digester operation, substrate utilization, cell growth and product formation.
The model was solved using Runge kutta numerical technique embedded in polymath
software. The digesters’ operations simulated with a starting valve of 300 g / dm3 as the
concentration of the substrate and 1.5 g / dm3 as the concentration of the cell, within a
11
Introduction
period of 13 days. The results of the simulation show that the substrate concentration
shows exponential decline from (300 g / dm3 to 6.88 g / dm3), the cells growth shows
exponential trend from (1.5 g / dm3 to 39 g / dm3) The rate of growth of cell was increased
from (0.5 g / dm3 - 2.53 g / dm3), death increased from (0.015 g / dm3 to 0.161 g / dm3) over
the 13 days and the biogas production which is the product also follow the exponential
trend from (zero concentration to 219 g / dm3). In all the model does the prediction well on
all the parameters simulated, so it was can be used to predict the product formation rate as
well as the design of reactor or digester.
Dewil et al. (2011) mention that although anaerobic digestion is a widely applied
technology, the process is not yet fully understood because of its high complexity and an
optimization of the current technology is still needed. The design and control of digester
systems is still generally performed by rule-of-thumb since no tools are currently available
for an accurate evaluation of performance. The application of mathematical models is a
prerequisite to improve digester performance and hence much attention is focused on the
development of accurate models.
Budhijanto et al. (2012) developed a mathematical model based on a simplified mechanism
of anaerobic digestion for analyze the digestion phenomena quantitatively and objectively
in order to make quick decisions in the optimization of the installed digesters in the field.
The data from field measurements were used to fit the mathematical model for predicting
the rate of biogas production and the selectivity of methane production over carbon dioxide
formation. Simulation using the model led to more systematic field trials to improve the
digester performance. The analysis resulted in two useful hints for the practical
improvement of the digesters. Firstly, the selectivity of methane over carbon dioxide was
significantly affected by the ratio of water and manure in the slurry. Secondly, the
conversion of the organic matters into biogas could be increased by recycling a portion of
the digester effluent.
Normak et al. (2012) were used IWA Anaerobic Digestion Model No.1 (ADM1) to simulate
the anaerobic digestion process of cattle slurry. The model was applied to 200 l single stage
completely stirred tank reactor. The simulation results of pH, biogas flow rate, acetate and
methane concentration were under study. Ammonia inhibition constant was optimized
12
Introduction
during this study to improve modeling results compared to measurements of acetate
concentration. Maximum methane yield during experiment was 291 l / kg VS added at organic
loading rate 2.0 kg VS / m3 . day.
Subramani and Nallathamb (2012) developed a pilot scale model of 20 liters capacity to
evaluate the maximum yield of biogas from domestic sewage and kitchen waste. The
organic loading and hydraulic retention time of 25 days studied to improve the production
of biogas. A computer program developed for optimum allocation of the above factors to
generate more biogas based on the feedstock effluent samples characteristics, such as pH,
total solids, volatile solids, volatile fatty acid contents, number of days and alkalinity. A
various digestion options and operational factors analyzed to make the commercial
production of biogas. The study aimed to use biogas instead of coal and petroleum which
are non-renewable resources and fast depleting.
Vindiš et al. (2012) developed a system for multi-criteria evaluation of energy crops for
biogas production. First, a deterministic simulation system consisting of deterministic
production simulation models was built. Simulation model results were further evaluated
using a qualitative multi-attribute modeling methodology DEX (supported by the software
tool DEX-i). Analysis showed that by using the current model the most relevant alternative
crop for biogas production is maize. Maize results in the best DEX-i multicriteria evaluation
appropriate. The best alternatives for maize are sorghum, sunflower, and sugar beet, with
multicriteria evaluation being less appropriate.
1.5. Objective of the study
Due to continued rapid growth of the Italian biogas sector during the last years and for
improving the exploitation of the Italian potentials of biogas production from on-farm
production of energy crops and livestock manure feedstock to meet the growing demand of
energy, there is a need to address the following problems:

Farm size (different farm scales) and farm structure (on-farm crops and livestock
distribution and production) suitable for establish on-farm biogas system to cover the
on-farm thermal and electrical energy requirements;
13
Introduction

Selection of appropriate technology from different available technologies of anaerobic
digestion, biogas production and use, for applying at different farm scales with
different farm structures.
As previously mentioned there are many mathematical models processing the different
biogas problems and improving the biogas production, but there is a need to develop a
mathematical model to reconcile between farm size, farm structure and on-farm biogas
systems technologies applied to support selection and applying of appropriate biogas
production technology at any farm under Italian conditions.
The objective of this study is enhancing the exploitation of the available Italian potentials of
biogas production from on-farm production of energy crops and livestock manure feedstock
by develop a mathematical model (RAF) integrates with (MAD3) model already has been
developed for optimize the following on-farm variables, related to anaerobic digestion and
biogas production and use (Fig. 1.4):

Allocated surface areas, distribution and production of different on-farm crops under
different farm sizes (scales) (optimum data of MAD);

Number of on-farm LSU4 (from different available types of farm livestock) (optimum
data of MAD);

Key design elements5 of on-farm biogas production system (directs and helps to select
the suitable technologies of on-farm biogas system) (optimum data of RAF);

On-farm labor requirements (optimum data of RAF and MAD);

The total net income of farm (optimum data of RAF and MAD).
3
MAD is a bio-economical model aimed to optimize resources of a farm holding (surfaces, livestock, labor,
etc.) to approach an objective function aimed to maximize net income.
4
Livestock unit
5
Some references refer to key design elements as “design criteria”
14
Introduction
1.5.1. Description of RAF model
The outlines of RAF model could be summarized as following (Fig. 1.4):
1. RAF is a bio-energetic descriptive model in terms of sets of equations (or inequalities)
run by uses GAMS code and GUI (Graphical Use Interface) works under MATLAB
environment for optimize the objective function (Z) (optimization the total net income
of farm for whole period which is considered by analysis);
2. RAF model support Integrated Farm Management (IFM) by enhancing economical,
social and environmental sustainability of farm production;
3. RAF model supports decision maker, engineers and farmers;
4. RAF model investigates the possibilities of establish on-farm biogas system (different
anaerobic digestion (AD) technologies proposed for different scales of farms in terms
of energy requirements) for reduce the dependency on fossil fuels and recycling the
agricultural and animal by-products for produce energy and digestate (bio-fertilizers);
5. The output data of optimization process presents a preliminary design of on-farm
biogas production system which contains the key design elements (e.g. dimensions,
quantities, capacities of main components of on-farm biogas production system);
6. The output data of optimization process could be presented in form of
recommendations for the best investment in energy from different on-farm potentials
under different farm sizes (scales).
15
Introduction
Fig. 1.4: The outlines of RAF model, main results and recommendations of
optimization process
16
Review of literature
2. REVIEW OF LITERATURE
2.1. Anaerobic digestion (AD)
The biochemical conversion technologies depending on obtain energy from chemical
reactions by the action of enzymes, fungi and micro-organisms, which are decomposition
biomass under specific conditions for producing bioenergy carriers such as biogas and
ethanol. The biochemical conversion technologies are fit for use with the biomass contains
values of C / N ratio less than 30 and moisture content more than 30 % on the basis of drymass (Lampinen, 2005).
Two such processes are widely used, and have been used for millennia: anaerobic digestion
(acid fermentation) and alcohol fermentation. Their conversion technologies for energy
products are illustrated in Fig. (2.1).
Fig.
2.1:
Biochemical
conversion
technologies
for
anaerobic digestion and alcohol fermentation
(author elaboration cited in Lampinen, 2005)
In the field of renewable energy, an anaerobic digestion refers to bio-chemical conversion
technology, designed for convert organic matter to energy. Biogas is a kind of gas that is
produced during the anaerobic processing of organic matter such as energy crops and byproducts, manure or even municipal waste materials. Biogas typically consists mainly of
methane, with a significant proportion of carbon dioxide, and smaller quantities of other
gases such as nitrogen and hydrogen (Kramer, 2004; Lampinen, 2005 and European
Biomass Association, 2009).
17
Review of literature
AD is a biochemical decomposition process of organic matter in absence of oxygen, by
various types of anaerobic microorganisms. The outputs of AD process are the biogas and
the digestate. When the substrate of AD is consists of mixture from two or more feedstock
types (e.g. energy crops and by-products, animal slurries and organic wastes from food
industries), the process is called “co-digestion” and it is common in most biogas applications
currently (Kossmann et al., 1999; Kramer, 2004; Lampinen, 2005 and Al Seadi et al., 2008).
2.1.1. Biomass types and characteristics related to AD
Many types of organic matters can be used as substrates (feedstock) for biogas production
from AD. According to Bio Fuel Cells Concepts for Local Energy (2000); Dennis and Burke
(2001); Al Seadi et al. (2008) and European Biomass Association (2009) the most common
biomass types used in European biogas production are listed below and tabulated in Table
(2.1):

Energy crops (e.g. maize, sorghum, miscanthus, clover and etc.), agricultural byproducts and wastes;

Animal by-products and wastes;

Digestible organic wastes from food and agro-industries (vegetable and animal origin);

Organic fraction of municipal waste and from catering (vegetable and animal origin);

Sewage sludge.
Using animal manure and slurries as feedstocks for AD process have some advantages
according to their characteristics:

Contain a naturally content of anaerobic bacteria;

Contain high moisture content (4 – 12 % dry matter in slurries on the basis of wetmass), which acting as solvent for the other substrates and improve mixing and
flowing of mixture;

Available in cheap price;

Easy to collect and use from animal farms.
18
Review of literature
Table 2.1: Bio-wastes suitable for biological treatment (author elaboration cited in Al Seadi
et al., 2008 and European Waste Catalogue, 2009)
Waste Code
02 00 00
03 00 00
04 00 00
15 00 00
19 00 00
20 00 00
6
Waste description
Wastes from agriculture,
horticulture, aquaculture,
forestry, hunting and fishing,
food preparation and
processing
Wastes form wood processing
and the production of panels
and furniture, pulp, paper and
cardboard
Wastes from the leather, fur
and textile industries
Wastes packing; absorbents,
wiping cloths, filter materials
and protective clothing not
otherwise specified
Wastes from waste
management facilities, offsite waste water treatment
plants and the preparation of
water intended for human
consumption and water for
industrial use
Municipal wastes (household
waste and similar
commercial, industrial and
institutional wastes) including
separately collected fractions
Waste sources
Wastes from agriculture, horticulture, aquaculture, forestry, hunting
and fishing
Wastes from the preparation and processing of meat, fish and other
foods of animal origin
Wastes from the fruit, vegetables, cereals, edible oils, cocoa, tea and
tobacco preparation and processing: conserve production; yeast and
yeast extract production, molasses preparation and fermentation
Wastes from sugar processing
Wastes from the dairy products industry
Wastes from the baking and confectionery industry
Wastes from the production of alcoholic and non-alcoholic beverages
(except coffee, tea and cocoa)
Wastes from wood processing and the production of panels and
furniture
Wastes from pulp, paper and cardboard production and processing
Wastes from the leather and fur industry
Wastes from the textile industry
Packaging (including separately collected municipal packaging waste)
Wastes from anaerobic treatment of waste
Wastes from waste water treatment plants not otherwise specified
Wastes from the preparation of water intended for human
consumption or
water for industrial use
Separately collected fractions (except 15 01)
Garden and park wastes (including cemetery waste)
Other municipal wastes
Due to the diversity of substrates characteristics, so substrates could be classify into various
categories according to various criteria such as: dry matter content (DM) or total solids
content (TS), C / N ratio, methane yield and etc., Table (2.2) gives an overview of the
characteristics of some digestible feedstock types. Substrates which contain DM content
lower than 20 % are used for wet digestion (wet fermentation) this category includes animal
slurries and manure besides various wet organic wastes from food industries. When the DM
content is high up to 35 %, it is called dry digestion (dry fermentation), and it is mainly use
for energy crops and silages (Kossmann et al., 1999; Bio Fuel Cells Concepts for Local
Energy, 2000; Dennis and Burke, 2001; Lfu, 2007; Al Seadi et al., 2008 and Hopwood,
2011).
6
The 6-digit code refers to the correspondent entry in the European Waste Catalogue (EWC) adopted by the
European Commissions.
19
Review of literature
Table 2.2: The characteristics of some digestible feedstock types (author elaboration cited in
Al Seadi, 2001)
Type of
feedstock
Organic
content
Pig slurry
Carbohydrates,
Proteins &
lipids
Cattle
slurry
Poultry
slurry
Stomach/
intestine
content
Whey
7
Conc.
whey
Flotation
sludge
Carbohydrates,
Proteins &
lipids
Carbohydrates,
Proteins &
lipids
Carbohydrates,
Proteins &
lipids
75 – 80 %
lactose
20 – 25 %
protein
75 – 80 %
lactose
20 – 25 %
protein
65 – 70 %
proteins
30 – 35 %
lipids
DM
(%)
VS %
of DM
Biogas
3
yield (m /
kg of VS)
Unwanted
physical
impurities
Other unwanted
matters
Antibiotics,
disinfectants
3 - 10
3-8
70 - 80
0.25 - 0.50
Wood shavings,
bristles, water,
sand,
cords & straw
6 - 20
5 - 12
80
0.20 - 0.30
Bristles, soil, water,
Straw & wood
Antibiotics,
+
disinfectants & NH4
3 - 10
10 - 30
80
0.35 - 0.60
Grit, sand &
feathers
Antibiotics,
+
disinfectants & NH4
3-5
15
80
0.40 - 0.68
Animal tissues
Antibiotics &
disinfectants
-
8 - 12
90
0.35 - 0.80
Transportation
impurities
-
-
20 - 25
90
0.80 - 0.95
Transportation
impurities
-
-
-
-
-
Animal tissues
Heavy metals,
Disinfectants &
organic pollutants
Ferment &
slops
Carbohydrates
4 -10
1-5
80 - 95
0.35 - 0.78
Non-degradable
fruit
remains
-
Straw
Carbohydrates
&
lipids
80 100
70 - 90
80 - 90
0.15 - 0.35
Sand & grit
-
Garden
wastes
-
100 150
60 - 70
90
0.20 - 0.50
Soil & cellulosic
components
Pesticides
Grass
-
20 - 25
90
0.55
Grit
Pesticides
15 - 25
90
0.56
Grit
-
Grass
silage
Fruit
wastes
7
C/N
ratio
-
12 25
10 25
-
35
15 - 20
75
0.25 - 0.50
-
-
Fish oil
30 – 50 %
lipids
-
-
-
-
-
-
Soya
oil /
margarine
90 % vegetable
oil
-
-
-
-
-
-
Alcohol
40 % alcohol
-
-
-
-
-
-
Food
remains
-
-
10
80
0.50 - 0.60
Bones, plastic
Disinfectants
Organic
household
waste
-
-
-
-
-
Plastic, metal,
stones,
Wood & glass
Heavy metals &
organic pollutants
Sewage
sludge
-
-
-
-
-
-
Heavy metals &
organic pollutants
Concentrated
20
Review of literature
Substrates contain high amounts of lignin, cellulose and hemicelluloses need to pretreatment to reduce lignin content at substrate and enhance the digestibility of cellulose
and hemicelluloses crops (Bio Fuel Cells Concepts for Local Energy, 2000; Al Seadi et al.,
2008 and Frandsen et al., 2011).
The production quantity of methane considers one of the most important criteria to
evaluate the different types of AD substrates (Fig. 2.2). The animal manure has relatively
low methane productivity, so that in practical application the animal manure is not digested
alone, but mixed with other co-substrates, which have high methane productivity, in order
to enrich the biogas production. Mainly, co-substrates, which added for co-digestion with
manure and slurries, are oily residues from food, fishing and feed industries, alcohol wastes,
from brewery and sugar industries, or even specially cultivated energy crops (British Biogen,
2000; Monnet, 2003 ; Patel, 2006 and Al Seadi et al., 2008).
Fig. 2.2: Specific methane yield from different types of AD substrates (as cited in
PRAßL, 2007 cited in Al Seadi et al., 2008)
The substrates of AD could contain some contaminants (such as chemical, biological or
physical pollutants). The common contaminants for some types of AD substrates are
illustrated in Table (2.3). Animal wastes require special attention if used as substrate for AD.
Regulation 1774 / 2002 of the European parliament laid down health rules regarding
handling and utilization of animal by-products not intended for human consumption.
Quality control of all AD substrates types is essential in order to ensure a safe recycling of
21
Review of literature
digestate as fertilizer. (Al Seadi, 2001; European Parliament, 2002; Al Seadi et al., 2008 and
Rapport et al., 2008).
Table 2.3: Problematic materials, contaminants and pathogens of some AD substrates
categories (author elaboration cited in Al Seadi et al., 2008)
Risk
Safe
Hygienic risks
Feedstock
Communal residue
material
Greenery and grass
cuttings
-
Industrial residue
materials
Vegetable waste,
mash and etc.
Renewable raw
materials
Beet leaves and
straw
Corn silage and
grass silage
Slaughter wastes
-
Miscellaneous
-
Risks of
contaminants
Bio-waste and roadside greenery
Expired foodstuff and foods with transport
damage
Fluid dung and solid dung
Agricultural residues
Contains problem
materials
-
Residue from
vegetable oil
production
Copper and
zinc
-
-
-
-
-
-
Rumen, stomachintestinal contents,
separated fats,
blood flour and etc.
Industrial kitchen waste and household
waste
Separatedfats
-
2.1.2. Theory of AD
AD is a microbiological process of anaerobic decomposition (in the absence of oxygen) of
the organic matter. The main outputs of this process are biogas and digestate. Biogas is a
combustible gas, mainly consists of methane and carbon dioxide mixture. Digestate is the
decomposed substrate, resulted from the production of biogas (Kossmann et al., 1999; Bio
Fuel Cells Concepts for Local Energy, 2000; British Biogen, 2000; Al Seadi, 2001; Dennis and
Burke, 2001; Monnet, 2003; Patel, 2006; Al Seadi et al., 2008; Baldwin et al., 2009 and
Crolla and Kinsley, 2011).
During AD, so little heat is produced on the contrary of the aerobic decomposition (in
presence of oxygen), like it is the case of composting. The energy, which is chemically
bounded in the substrate, remains mainly in the produced biogas, in form of methane
(British Biogen, 2000; Monnet, 2003; Patel, 2006 and Baldwin et al., 2009).
22
Review of literature
The biogas formation is a result of sequential steps, in which the raw materials is
continuously broken down into smaller units. Specific species of micro-organisms are
involved in each separately step. These micro-organisms decompose the products
sequentially from the previous steps. The simple diagram of the AD process, illustrated in
Fig. (2.3), focuses on the four main process steps: hydrolysis, acidogenesis, acetogenesis,
and methanogenesis (Kossmann et al., 1999; Al Seadi, 2001; Dennis and Burke, 2001;
Batstone et al., 2002; Monnet, 2003; Al Seadi et al., 2008; Baldwin et al., 2009 and
Donoso-Bravo et al., 2009).
The steps of AD process (Fig. 2.3) runs parallel in time and space, in the digester. The speed
of the decomposition process is determined by the slowest Interaction of the chain (Fig.
2.4). During decomposition of vegetable substrates, which containing cellulose, hemicellulose and lignin, hydrolysis is the slowest Interaction, which determined the speed of
process. During hydrolysis step, relatively small amount of biogas is produced. Biogas
production reaches its peak during methanogenesis (Al Seadi, 2001; Batstone et al., 2002;
Monnet, 2003; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and WTERT, 2009).
Fig. 2.3: The main steps of AD process (as cited in WTERT, 2009)
23
Review of literature
Fig. 2.4: Biogas yield after addition of substrate-batch test
(as cited in Lfu, 2007 cited in Al Seadi et al., 2008)
2.1.2.1. Hydrolysis
Theoretically hydrolysis is the first step of AD, during this step the complex organic matters
(polymers) are decomposed into smaller units (mono- and oligomers). During hydrolysis
step, polymers like carbohydrates, lipids, nucleic acids and proteins are converted to
glucose, glycerol, purines and pyridines (Al Seadi, 2001; Batstone et al., 2002; Monnet,
2003; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and WTERT, 2009).
Hydrolytic microorganisms excrete hydrolytic enzymes, which converting biopolymers into
simpler and soluble compounds as it is shown below:
Lipids lipasefatty acids, glycerol;
Polysaccharide cellulase, cellobiase, xylanase & amylasemonosaccharide;
Proteins proteaseamino acids.
An assortment of microorganisms are involved in hydrolysis, those microorganisms excreted
exoenzymes, which decompose the undissolved particulate material. The outputs from
hydrolysis are further decomposed by the microorganisms involved and used for their own
metabolic processes (Al Seadi, 2001; Batstone et al., 2002; Monnet, 2003; Al Seadi et al.,
2008; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and WTERT, 2009).
24
Review of literature
2.1.2.2. Acidogenesis
During acidogenesis, the outputs of hydrolysis are converted to methanogenic substrates by
acidogenic (fermentative) bacteria. Simple sugars, amino acids and fatty acids are degraded
into acetate, carbon dioxide and hydrogen (70 %) as well as into volatile fatty acids (VFA)
and alcohols (30 %) (Al Seadi, 2001; Batstone et al., 2002; Monnet, 2003; Al Seadi et al.,
2008; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and WTERT, 2009).
2.1.2.3. Acetogenesis
During acetogenesis, outputs from acidogenesis are converted into methanogenic
substrates (outputs from acidogenesis can’t be directly converted to methane by
methanogenic bacteria during acidogenesis step). During methanogenesis, hydrogen is
converted into methane by bacteria. Acetogenesis and methanogenesis are usually run
parallel, as symbiosis of two groups of organisms (Al Seadi, 2001; Batstone et al., 2002;
Monnet, 2003; Al Seadi et al., 2008; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and
WTERT, 2009).
2.1.2.4. Methanogenesis
The production of methane and carbon dioxide from intermediate outputs is carried out by
methanogenic bacteria. 70 % of the formed methane originates from acetate, while the
remaining 30 % is produced from conversion of hydrogen (H) and carbon dioxide (CO2),
according to the following equations:
Acetic acid methanogenic bacteriamethane + carbon dioxide;
Hydrogen + carbon dioxide methanogenic bacteriamethane + water.
Methanogenesis is a critical step in the entire anaerobic digestion process. Methanogenesis
is severely affected by operation conditions. Composition of feedstock, feeding rate,
temperature, and pH are examples of factors influencing the methanogenesis process.
Digester overloading, temperature changes or large entry of oxygen can result in
termination of methane production (Al Seadi, 2001; Batstone et al., 2002; Monnet, 2003;
Al Seadi et al., 2008; Baldwin et al., 2009; Donoso-Bravo et al., 2009 and WTERT, 2009).
25
Review of literature
2.1.3. Factors controlling the AD
There are some vital parameters, which control the efficiency of AD, thus it is crucial provide
appropriate conditions for growing of anaerobic microorganisms. The growth and activity of
anaerobic microorganisms are significantly affected by surrounding conditions such as
exclusion of oxygen, constant temperature, pH-value, nutrient supply, stirring intensity,
moreover presence and amount of inhibitors (e.g. ammonia). The methane bacteria are
fastidious anaerobes, so that the presence of oxygen into the digestion process must be
strictly avoided (Kossmann et al., 1999; Dennis and Burke, 2001 and Al Seadi et al., 2008).
2.1.3.1. Temperature
The AD process could be done at different ranges of temperatures, the AD according to
temperature classify into three ranges: psychrophilic, mesophilic, and thermophilic (see
Table 2.4). There is a direct relation between the process temperature and the hydraulic
retention time (HRT) (Massart et al., 2008; Baldwin et al., 2009; Vindis et al., 2009;
Hopwood, 2011 and Cioabla et al., 2012).
Table 2.4: Thermal stages and typical hydraulic retention times (author elaboration cited in
Al Seadi et al., 2008)
Thermal stage
Psychrophilic
Mesophilic
Thermophilic
Process temperatures (°C)
< 20
From 30 to 42
From 43 to 55
HRT (day)
From 70 to 80
From 30 to 40
From 15 to 20
Stability of the temperature is crucial for AD process. In practice, the temperature of process
is selected according to the type of feedstock used. The necessary temperature of process is
usually generated by floor or wall heating systems, inside the digester. Fig. (2.5) illustrated
the rates of relative biogas production depending on temperature and hydraulic retention
time (Biogas Process for Sustainable Development, 1992; Monnet, 2003; Massart et al.,
2008; Baldwin et al., 2009; Vindis et al., 2009; Hopwood, 2011 and Cioabla et al., 2012).
26
Review of literature
Fig. 2.5: Relative yield of biogas, depending on
temperature and hydraulic retention time (as
cited in Lfu, 2007 cited in Al Seadi et al., 2008)
According to Al Seadi et al. (2008); Baldwin et al. (2009) and Vindis et al. (2009) the
advantages of thermophilic process compared to psychrophilic and mesophilic processes:

More effective for pathogens sterilization;

Growth rate of methanogenic bacteria is increasing at high temperature;

Reduced retention time of AD process, making the process faster and more efficient;

Better decomposition of solid substrates and better substrate utilization;

Better possibility for separating liquid and solid fractions.
The thermophilic process also has some disadvantages (Al Seadi et al., 2008; Baldwin et al.,
2009 and Vindis et al., 2009):

Larger degree of imbalance;

Larger energy demand due to high temperature;
 Higher risk of ammonia inhibition.
2.1.3.2. PH-value
The PH-value is the measure of acidity / alkalinity of a solution and is expressed in parts per
million (ppm). The PH value of the AD substrate affects on the growth rate of methanogenic
microorganisms, and also affects on the decomposition of some important compounds for
the AD process (ammonia, sulphide, organic acids). The methane formation occurs within
27
Review of literature
relatively narrow PH interval, from 5.5 to 8.5, with an optimum interval from 7.0 to 8.0 for
most methanogens. Acidogenic microorganisms usually have lower value of optimum PH
(Kossmann et al., 1999; Dennis and Burke, 2001; Monnet, 2003; Lfu, 2007 and Al Seadi et
al., 2008).
The value of pH in AD process is mainly controlled by the bicarbonate buffer system.
Therefore, the PH value inside digesters depends on the partial pressure of CO2 and on the
concentration of alkaline and acid components in the liquid phase. If accumulation of base
or acid occurs, the buffer capacity counteracts these changes in PH, up to a certain level.
When the buffer capacity of the system is exceeded, drastic changes in PH-values occur,
completely inhibiting the AD process. For this reason, the PH-value is not recommended as a
stand-alone process monitoring parameter (Dennis and Burke, 2001; Monnet, 2003; Lfu,
2007).
2.1.3.3. Ammonia
Ammonia (NH3) has a significant role in the AD process. NH3 is an important nutrient,
serving as a precursor to foodstuffs and fertilizers and is normally encountered as a gas,
with the characteristic pungent odor. Proteins are the main source of ammonia for the AD
process. Too high concentration of ammonia inside the digester, is considered inhibit for AD
process, due to methanogenic bacteria are especially sensitive to ammonia inhibition. This is
common to AD of animal slurries, due to their high concentration of ammonia, originating
from urine. For its inhibitory effect, ammonia concentration should be kept below 80 mg / l.
(Kossmann et al., 1999; British Biogen, 2000; Dennis and Burke, 2001; Ohio State
University Extension, 2006; Al Seadi et al., 2008 and Westerma et al., 2008).
2.1.3.4. Nutrients
Sufficient concentration of nutrients is required to achieve optimum growth of bacteria. The
carbon to phosphorus ratio should be less than 187. A non-lignin C / N ratio from 20 to 25 is
optimum for digester performance. Typically, excreted manure has a C / N ratio around 10
(British Biogen, 2000; Dennis and Burke, 2001; Monnet, 2003; Ohio State University
Extension, 2006; Al Seadi et al., 2008 and Balasubramaniyam et al., 2008).
28
Review of literature
2.1.3.5. C / N ratio
Microorganisms need both nitrogen and carbon for composition their cells. Experiments
indicated that metabolic activity of methanogenic bacteria can be optimized at a C / N ratio
range from 8 to 20 (see Table 2.2), whereby the optimum point varies from case to case,
depending on the nature of the substrate (Kossmann et al., 1999; Al Seadi, 2001; Dennis
and Burke, 2001; Lehtomäki, 2006; Al Seadi et al., 2008 and Biogas Training Center, 2011).
2.1.3.6. Toxic Materials
Toxic materials such as fungicides, antibacterial agents and heavy metals (iron, cobalt,
copper, manganese, molybdenum, and zinc) can have an adverse effect on anaerobic
digestion. The AD process can deal with small quantities of toxic materials without negative
affect on the efficiency of AD process (Steffen et al., 1998; British Biogen, 2000; Dennis and
Burke, 2001; Monnet, 2003 and Nels, 2011).
2.1.3.7. Agitation (stirring)
Many types of substrates and various types of AD reactors require some sort of substrate
agitation or mixing in order to maintain process stability in the digester. According to
Kossmann et al. (1999); Monnet (2003) and Massart et al. (2008) the most important
objectives of agitation are:

Mixing of fresh substrate and bacterial population (inoculation);

Preclusion of scum formation and sedimentation;

Avoidance of pronounced temperature gradients within the digester;

Provision of a uniform bacterial population density;

Prevention of the formation of dead spaces that would reduce the effective digester
volume.
2.1.3.8. Dilution
Dilution with water required to reduce the concentration of certain constituents such as
nitrogen and sulfur that produces ammonia and hydrogen sulfide, which are inhibitory to
the anaerobic digestion process. High solids digestion creates high concentrations of end
products that inhibit anaerobic decomposition. Therefore, some dilution can have positive
29
Review of literature
effects. The best reduction efficiencies occur at concentrations of approximately 6 to 8 %
total solids (Steffen et al., 1998; Dennis and Burke, 2001; Monnet, 2003 and Ndegwa et al.,
2005).
2.1.4. Operational parameters controlling the AD
2.1.4.1. Hydraulic retention time (HRT)
The HRT is the average time interval when the substrate is kept inside the digestion
chamber. HRT is correlated to the digestion chamber volume and the volume of substrate
fed per time unit, according to the following equation (Steffen et al., 1998; Kossmann et al.,
1999; Dennis and Burke, 2001; Monnet, 2003 and Al Seadi et al., 2008):
𝐻
(2.1)
Where:
HRT = Hydraulic Retention Time (day);
VDC = Inner-volume of digestion chamber (m3);
DMU = Discharge of pumping and mixing unit (m3 / day).
The retention time of substrate in the digester is dependent upon the type and
characteristics of substrate. Generally, although most wet AD plants operate on a
continuous basis, the aim would be for the material to remain within the digester from 20 to
40 days (see Table 2.4). Longer retention times are possible, but require greater tank
capacity and see a reduction in biogas output over time. As a greater proportion of solid
material, such as crops, is added the retention time needs to be increased to achieve
optimum biogas output and material throughput (Biogas Process for Sustainable
Development, 1992; Patel, 2006; United States Department of Agriculture, 2007; Massart
et al., 2008; Baldwin et al., 2009 and Hopwood, 2011).
2.1.4.2. Solids retention time (SRT)
The SRT is important factor controlling the conversion of solids to gas. It is also important
factor in maintaining digester stability. Although the calculation of solids retention time is
often improperly stated, it is the quantity of solids maintained in the digester divided by the
30
Review of literature
quantity of solids wasted each day. The SRT can be calculating according to the following
equation (Dennis and Burke, 2001; Lehtomäki, 2006; Massart et al., 2008 and Baldwin et
al., 2009):
(2.2)
Where:
SRT = Solids retention time (day);
VDC = Inner-volume of digestion chamber (m3);
TSC = Total solids concentration in the digester (kg / m3);
QDW = Daily quantity of wasted (m3 / day);
TSW = Total solids concentration of the waste (kg / m3).
2.1.4.3. Digestion chamber loading
Digestion chamber (inside the digester) loading refers to the amount of feedstock (usually
mass of total solids or volatile solids) feeding into the digestion chamber per day per m3 of
digestion chamber volume. Increasing the digestion chamber loading will reduce the
digestion chamber size but will also reduce the percentage of volatile solids converted to
gas. In general better digestion can be achieved at lower loadings. Thermophilic reactors
appear to achieve greater conversions at high loadings while mesophilic reactors appear to
achieve greater conversions at lower loadings. In typical anaerobic digester the digestion
chamber loading is from 1 to 5 kg / m3. day (What Size Digester Do I Need, 1996; Bio Fuel
Cells Concepts for Local Energy, 2000; Dennis and Burke, 2001; United States Department
of Agriculture, 2007; Balasubramaniyam et al., 2008; Massart et al., 2008 and Westerma
et al., 2008).
The digestion chamber loading can be calculated if the HRT and influent waste
concentration is known according to the following equation:
(2.3)
Where:
LDC = Digestion chamber loading (kg of TS or VS / m3 of digestion chamber volume. day);
31
Review of literature
CIW= Influent waste concentration (kg of TS or VS / m3 of digestion chamber volume);
HRT = Hydraulic Retention Time (day).
2.1.5. Evaluation parameters of biogas plants
A number of parameters, which illustrated in Table (2.5), can be used for evaluation of
biogas plants and for comparing different systems (Werner et al., 1989; Kossmann et al.,
1999 and Al Seadi et al., 2008).
There are two main categories of parameters can be found:

Operating data, this can be determined by measurement;

Parameters, which can be calculated from the measured data.
Table 2.5: Operational parameters of biogas plants (author elaboration cited in Al Seadi et
al., 2008)
Symbol
Unit
Temperature
Operational pressure
Parameter
T
P
°C
bar
Capacity, throughput
V
m3/day; ton/day
Reactor volume
Gas quantity
Retention time (hydraulic,
minimum guaranteed)
VR
V per day
V per year
HRT
MGRT
Organic load
Methane concentration in biogas
Specific biogas yield
Specific biogas production
CH4
m
3
m3/day
day
kg or
ton/m³.day
%
%
m3/m3
Gross energy
kWh
Electricity production
Output to grid
Efficiency of BTTP
kWh
kWh
%
η
Station supply thermal / electric
kWh
kWh/m³ Input
kWh/GV
Specific station supply thermal /electric
Energy production
Plant efficiency
kWh
η
%
Availability
%
Utilization
%
Total investment
€
Subsidies
€
Subsidy percentage
%
Specific investments
€/m³ reactor
€/GV
€/m³ Input; €/GV
Specific treatment costs
Determination
Measurement during operation
Measurement during operation
Measurement
Determined by construction
Measurement during operation and conversion to
Nm³
Calculation from operating data
Calculation from operating data
Measurement during operation
Calculation from operating data
Calculation from operating data
Determination from the quantity of biogas and
methane concentration
Measurement at the BTTP generator
Measurement after the BTTP generator
Calculation from operating data
Basis of planning, afterwards measurement
during operation
Calculation from operating data
Sum of energy that can be sensibly utilized.
Calculation from operating
data
Net energy drawn from gross energy
Percentage of hours in a year in which a plant is
fully functioning
Ratio of the real quantity input to the projected
capacity
All expenses caused by the biogas plant
Pre-determined
Percentage of all subsidies in relation to total
investments
Only sensible when primarily manure from animal
husbandry is used
Calculation
32
Review of literature
2.2. Different technologies of agricultural biogas plants
There are several technical and operational alternatives to choose from the different
technologies applied from smaller to larger scale according to factors, such as investment
and operational costs, workload, the end-use of digestate intended and goals for energy
production etc. In small household plants very simple technological solutions are used. On
farm-scale the technology becomes somewhat more elaborate, but the aim is to still keep it
simple and easy-to-use, while on large, centralized scale the biogas plant may consist of
several different processing units the operation of which requires more monitoring and
knowhow (Sasse, 1988; FAO, 1996; Kossmann et al., 1999; Centre for Energy Studies
Institute of Engineering, 2001; Buxton, 2010 and Hopwood, 2011).
2.2.1. Different scales of agricultural biogas plants
There are differ sizes (scales) and technologies of agricultural biogas plants. Small and often
self-made biogas plants are used in tropical countries for treating wastes from the
household farming and cooking. In industrial countries with intensive agriculture the biogas
plants are significantly bigger and more advanced, equipped with modern technology to
increase digester capacity and to apply process control for stable operation (Sasse, 1988;
FAO, 1996; Kossmann et al., 1999; Centre for Energy Studies Institute of Engineering,
2001; Al Seadi et al., 2008; Buxton, 2010 and Hopwood, 2011).
Generally, agricultural biogas plants can be classified into three different scales according to
size:

Household biogas plants;

On-farm biogas plants;

Centralized biogas plants.
2.2.1.1. Household-scale of biogas plants
Household biogas plants are small, very simple and manually operated (Fig. 2.6). This type of
biogas plants can be effectively operated under warm climate conditions, while
implementation in temperate to cold areas may require temperature control. The biogas
yield from household biogas plants is usually using for cooking and lighting. For example in
33
Review of literature
China, there were 30 million biogas plants in rural areas until year 2010, most of them are
household digesters with volume of 4 - 10 m3, produces up to 2 m3 of biogas per day (Sasse,
1988; FAO, 1996; Kossmann et al., 1999; Nagamani and Ramasamy, 1999; Centre for
Energy Studies Institute of Engineering, 2001; Al Seadi et al., 2008; Buxton, 2010 and
World Energy Outlook, 2010).
Fig. 2.6:
Household-scale digesters: (A) Floating-drum
plant, (B) Fixed-dome plant and (C) Balloon
plant (author elaboration cited in Sasse, 1988)
2.2.1.2. Farm-scale of biogas plants (On-farm biogas plants)
Farm-scale biogas plants are integrates with crop production and / or with animal
husbandry, with herbal biomass and manure as the usual feedstock. Farm-scale biogas
plants have simple technology and basic automation to maintain a stable process, while
larger biogas plants for farm cooperatives may also use more advanced and complex
technologies. Agricultural biogas plants are classified into three categories according to
electrical energy productive capacity of on-farm CHP unit (Philip, 2005; Institut für
Energetik und Umwelt et al., 2006; Plöchl and Heiermann, 2006; Al Seadi et al., 2008 and
Hopwood, 2011):

Small scale ≤ 70 kWhel;

Medium scale 70 - 150 kWhel;

Large scale 150 - 500 kWhel.
34
Review of literature
According to the above classification, the small to medium scale would be applicable on
single farms, while medium to large scale would most likely be of farm cooperatives (Philip,
2005; Plöchl and Heiermann, 2006 and Hopwood, 2011).
Farm-scale biogas plants usually aims to closing the energy and nutrient cycles in the farm
and offer a good basis for sustainable energy supply. General scheme of a farm-scale biogas
plant is illustrated in Fig. (2.7), with co-digestion of energy crops and manure slurry. The
main products of the biogas plant in Fig. (2.7) are heat, electricity and digestate. Depending
on the on-farm requirements and pricing situation for the energy, the energy produced is
either used on-farm to replace energy from grid or sold to the grid (electricity and heating).
Possibly other practices, such as biogas upgrading to bio-methane for fuel, reuse of fibers
from manure for bedding and use of irrigation as a means of applying mechanically
separated liquid fraction of digestate on fields, can be applied (Centre for Energy Studies
Institute of Engineering, 2001; Philip, 2005; Institut für Energetik und Umwelt et al., 2006;
Plöchl and Heiermann, 2006; Al Seadi et al., 2008 and Hopwood, 2011).
Farm cooperative biogas plants usually focus on closing nutrient cycles on the cooperating
farms with possible re-division of the manure nutrients, i.e. farms with excess phosphorus
may receive less phosphorus in digestate than they deliver the plant in the raw manure,
while farms with phosphorus requirement receive more phosphorus in digestate than they
deliver to the plant. Also in addition to animal farms, some farms in the cooperative may be
crop producers, providing the plant with some crops and receiving digestate. For example in
Germany, Denmark and Holland, many agricultural biogas plants use energy crops with less
or no manure and use the digestate for the crop production. The energy produced in farm
cooperative biogas plants is usually sold to the network (electricity networks and / or
thermal networks) or utilized in adjacent companies, such as greenhouses. Biogas upgrading
to bio-methane is also possible (FAO, 1996; Philip, 2005; Institut für Energetik und Umwelt
et al., 2006; Al Seadi et al., 2008 and Hopwood, 2011).
35
Review of literature
Fig. 2.7: Scheme of farm-scale biogas plant uses energy crops, manure slurry and organic
residues as feedstock and including different pathways of biogas utilization (as
cited in Plöchl and Heiermann, 2006)
2.2.1.3. Centralized-scale of biogas plants
In centralized biogas plants (Fig. 2.8), the technologies applied usually more complex than in
biogas plants focusing on agricultural materials of one or a few farms. Moreover, the raw
materials are often collected from several sources and the feed mixture may contain diverse
materials from agriculture, municipalities and industry. The choice of technology varies
case-specifically depending on the raw materials available, the aims of the processing (e.g.
energy production, fertilizer production, stabilization of waste materials, reduction of
environmental load), the costs for investment and operation, subsidy systems available, etc.
Centralized biogas plants may produce heat or heat and power depending on the casespecific conditions, but the economy of scale may also make bio-methane production more
attractive than in smaller biogas plants. Currently, on large farms or centralized plants have
two or three digesters with volume of several thousands of cubic meters and CHP units with
total electrical productive capacity from 500 to 1000 kWhel (Philip, 2005; Institut für
Energetik und Umwelt et al., 2006; Plöchl and Heiermann, 2006; Al Seadi et al., 2008 and
European Biomass Association, 2009).
36
Review of literature
Fig. 2.8: Centralized biogas plant (as cited in European
Biomass Association, 2009)
2.3. Main components of biogas plants
A biogas plant consists of several of components. The design of such a plant depends to a
large extent on the types and amounts of feedstock supplied (Institut für Energetik und
Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
The main processing steps in a biogas plant are illustrated in Fig. (2.9). the processing steps
illustrated in italics are not common for agricultural biogas plants. The difference between
dry and wet AD is only theoretical, since microbiological processes always take place in fluid
media. The limit between dry and wet digestion is determined by the substrate pumpability.
DM content (total solids) of substrate above 15 % that means the material is not pumpable
and the AD in this case is defined as dry digestion, while DM content (total solids) of
substrate is less 15 % the AD in this case is defined as wet digestion (Dennis and Burke,
2001; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008 and
Hopwood, 2011).
37
Review of literature
Fig. 2.9: Main processing steps of anaerobic technologies (as cited in Lfu,
2007 cited in Al Seadi et al., 2008)
The main component of a biogas plant is the anaerobic digester, which integrates with the
other components of biogas plant as illustrated in Fig. (2.10) (Sasse, 1988; Kossmann et al.,
1999; Dennis and Burke, 2001; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007
and Al Seadi et al., 2008).
Fig. 2.10: Main components of biogas plant (author elaboration)
According to Dennis and Burke (2001); Institut für Energetik und Umwelt et al., (2006); Lfu,
(2007) and Al Seadi et al. (2008) in agricultural biogas plants, could distinguished four
different processing stages, which illustrated in Figs. (2.11 & 2.12) as follows:
38
Review of literature
1. Pre-digestion stage (storage, conditioning, transport and insertion of feedstock)
includes the storage tank for manure (2), the collection bins (3), the sanitation tank
(4), the drive-in storage tanks (5) and the solid feedstock feeding system (6);
2. The anaerobic digestion (biogas production) stage includes the biogas production in
the digester (7);
3. Storage and utilization of digestate stage includes the storage tank of digestate (10)
and the utilization of digestate as fertilizer for agricultural purposes (11);
4. Storage and utilization of biogas stage (biogas storage, conditioning and utilization)
includes the gas storage tank (8) and on-farm CHP unit (9).
Fig. 2.11: Processing stages of agricultural biogas plants (author
elaboration cited in JÄKEL, 2002 cited in Al Seadi et al., 2008)
39
Review of literature
Fig. 2.12: Agricultural co-digestion biogas plant using manure and maize
silage (as cited in Lorenz, 2008 cited in Al Seadi et al., 2008)
2.3.1. Feedstock handling system
2.3.1.1. Receiving unit of feedstock
Efficient transport and supply of feedstock (crop yield, by-products and manure) is
important to ensure a stable and continuous supply of feedstock, of suitable quality and
quantities. In many cases, the biogas plants receive additional feedstock (co-substrates),
produced by neighboring farms, industries or households. Particular attention is needed for
feedstock types classified as wastes, for which it may be necessary to fulfill regulatory
obligations (depending on the waste category), as well as legal and administrative
conditions. From the other hand, receiving unit equipped with some visual equipment
(manual or robotic) for sorting and removal of bulky or potentially harmful items (Institut
für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008 and Rapport et al.,
2008).
40
Review of literature
2.3.1.2. Conditioning of feedstock
The main aims of conditioning are fulfill the demands of sanitation, increase feedstock
digestibility and biogas yield (Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007; Genesis Projects Corp, 2007; Al Seadi et al., 2008 and
Rapport et al., 2008).
Conditioning of feedstock includes:
1. Feedstock sorting and separation of problematic material:
This is an initial and necessary step for sorting and separating impurities and
problematic materials from the feedstock substrate. Silage considers clean feedstock
type, while manure and household wastes contains sands, stones and other physical
impurities. These impurities are usually separated by sedimentation in storage tanks
(in the case of sand sedimentation occur inside the digester) and they have to be
removed from the bottom of the tanks from time to time. sometimes, could use pretank outfitted with special grills, which able to retain stones and other physical
impurities before pumping the feedstock into the main storage tank, is used in many
cases (Lfu, 2007; Genesis Projects Corp, 2007; Al Seadi et al., 2008 and; Rapport et
al., 2008).
Domestic wastes can contain various impurities (such as packing wastes of plastic,
metals, wood, glass and other non-digestible materials, Fig. 2.13 right), which can
cause clogging pipes, damage for pumps and even the digesters. These impurities
could be removed by a separate collection system of household wastes (collect wastes
in different Homogeneous groups e.g. organic, metals, plastic, paper and etc.) or they
can be removed from bulk collected wastes by using mechanical sorters (Screens,
rotating trommels, magnetic separation and etc.) and manual methods (use only for
small quantities of wastes) (Lfu, 2007; Genesis Projects Corp, 2007; Al Seadi et al.,
2008 and; Rapport et al., 2008).
41
Review of literature
Fig. 2.13: Mechanical system for separation solid wastes by using trommel (left) and
problematic material, which was separated from feedstock (right) (as cited in
Rapport et al., 2008)
2. Crushing (particle size reduction):
Crushing of feedstock material aims to prepare the surfaces of the particles for
biological decomposition and the subsequent methane production. In general, the
decomposition process is faster when the particle size is smaller. Particle size
reduction can take place by mechanical and / or biological ways (Genesis Projects
Corp, 2007; Al Seadi et al., 2008 and Rapport et al., 2008).
3. Mashing:
Mashing of feedstock is necessary in order to obtain feedstock with a higher moisture
content, which can be handled by pumps. The advantage of using digestate for
mashing lies in the reduction of fresh water consumption and in the inoculation of the
substrate with AD micro-organisms from the digester. Use of fresh water should
always be avoided due to high costs (Al Seadi et al., 2008).
2.3.2. Storage of feedstock
Storage of feedstock mainly aims to compensate the seasonal fluctuations of feedstock
supply and It is also facilitates mixing of different co-substrates for continuous feeding of
the digester. The type of store depends on the type of feedstock. Types of stores can be
mainly classified into bunker silos for solid feedstock (e.g. corn (maize) silage, Fig. 2.14) and
storage tanks for liquid feedstock (e.g. liquid manure and slurries, Fig. 2.15). Usually, bunker
silos have the capacity for store feedstock from six months up to more than one year, while
42
Review of literature
storage tanks for manure have the capacity to store feedstock from several days up to
several months. The dimensioning of the storage facilities is determined by the quantities to
be stored, delivery intervals and the daily amounts fed into the digester (Electrigaz
Technologies Inc., 2007; Al Seadi et al., 2008 and Kirchmeyr et al., 2009).
Fig. 2.14: Bunker silo, made of concrete and silage is covered by
plastic foils (as cited in Purdue Dairy Page, 2012)
Fig. 2.15: Manure slurry tank (as cited in Department of
Environmental Protection, 2009)
2.3.3. Systems of feeding
After storage and pre-treatment, AD feedstock is feed into the digester. There are two
categories of feedstock, pumpable and non-pumpable. The pumpable feedstock category
includes animal slurries and liquid organic wastes (e.g. flotation sludge, cattle wastes, fish
oil). Feedstock types which are non-pumpable (e. g. fibrous materials, grass, maize silage,
manure with high straw content) can be tipped / poured by a loader into the feeding system
and then fed into the digester (e.g. by a screw pipe system) (Electrigaz Technologies Inc.,
2007; Genesis Projects Corp, 2007; Rapport et al., 2008 and Kirchmeyr et al., 2009).
43
Review of literature
2.3.3.1. Pumps
Pumps used to transfer the pumpable feedstock substrate from the storage tank to the
digester. There are two main types of pumps are frequently used: centrifugal (rotating)
pumps (Fig. 2.16), and positive displacement pumps (rotary lobe pumps, Fig. 2.17 and
progressing cavity pumps, Fig. 2.18). Centrifugal pumps are often submerged, but they can
also be positioned in a dry shaft, next to the digester. Positive displacement pumps are
more resistant to pressure than centrifugal pumps. They are self-sucking, works in two
directions and reach relatively high pressures, with a diminished conveying capacity.
However through their lower price, centrifugal pumps are more frequently chosen than
positive displacement pumps (Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007 and Al Seadi et al., 2008).
Fig. 2.16: Centrifugal (rotating) pump (as cited in LfU,
2007)
Fig. 2.17: Rotary lobe pump (as cited in Institut für
Energetik und Umwelt et al., 2006)
Fig. 2.18: Progressing cavity pump (as cited in Lfu, 2007)
44
Review of literature
The selection of appropriate pumps and pumping technology depends on the characteristics
of the feedstock to be handled by pumps (type of material, DM content, particle size, and
level of preparation). Pressure pipes, for filling or mixing, should have a diameter of at least
150 mm, while pressure free pipes, like overflow or outlet pipes, should have at least 200
mm for transporting manure and 300 mm if the straw content is high (Institut für Energetik
und Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
The pumps should be equipped with stop-valves (Fig. 2.19), which allow feeding and
emptying of digesters and pipelines. In many cases the entire feedstock transport within the
biogas plant is realized by one or two pumps, located in a pumping station (Fig. 2.20)
(Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
Fig. 2.19: Stop-valves (left) and pumping system (right) (as
cited in Rutz, 2006 cited in Al Seadi et al., 2008)
Fig. 2.20: Pumping systems (as cited in Vogelsang, 2012)
2.3.3.2. Feeding equipment of solid feedstock
The feeding system of solid feedstock (e.g. grass, maize silage, manure with high straw
content, vegetable residues etc.) consists of transport equipment (e.g. loaders and tractors,
which transports feedstock from Bunker silo to containers, Fig. 2.21) and a conveying
system (e.g. screw pipe conveyors, Fig. 2.22), which convey the feedstock from containers
45
Review of literature
to digester automatically) (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al
Seadi et al., 2008).
Screw conveyors can be conveying feedstock in all directions. The only precondition is free
of large stones and other physical impurities. For optimal operation, coarse feedstock
should be crushed, in order to be fit into the screw windings. On the other hand there are
three different systems of screw conveyors are commonly used: wash-in shaft, feed pistons
and feed conveyor screws, which illustrated in Fig (2.23) (Institut für Energetik und Umwelt
et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
Fig. 2.21: Loader feeding maize silage into the container (as cited in Institut für
Energetik und Umwelt et al., 2006)
Fig. 2.22: Screw pipe conveyors (as cited in Wam India
Private Limited, 2012)
46
Review of literature
Fig. 2.23: (A) Wash-in shaft, (B) feed pistons and (C) feed conveyors system for feeding
feedstock into the digester (author elaboration cited in Institut für
Energetik und Umwelt et al., 2006)
1. Wash-in shaft:
Wash-in shafts, load by front or wheel loaders, which allow large quantities of
feedstock to be delivered any time, directly to the digester (Fig. 2.23 A) (Institut für
Energetik und Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
2. Feed pistons:
Feed pistons system (Fig. 2.23 B) uses for feed the feedstock directly into the digester
by hydraulic cylinders, which push the feedstock through an opening in the wall of the
digester. This system is use for reducing the risk of floating layer formation. This
system is equipped with counter rotating mixing rollers for crush long fiber materials
(e.g. air-dried silage) (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al
Seadi et al., 2008).
3. Feed screws conveyor:
Feed screw conveyor (Fig. 2.23 C) uses for feed the feedstock under the level of the
liquid in the digester. This system has the advantage of preventing gas leaking during
feeding process. This system sometimes equipped with mixing and crushing tools (Fig.
2.24) (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al.,
2008).
47
Review of literature
Fig. 2.24: Feeding container equipped with screw
conveyor, mixing and crushing tools (as cited
in Agrinz, 2006 cited in Al Seadi et al., 2008)
2.3.4. Heating system of digester
One of the most important conditions for high biogas production is keep constant
temperature of AD process. Temperature fluctuations must be kept as low as possible, large
fluctuations of temperature lead to imbalance of the AD process, and in worst cases lead to
failure of process (Electrigaz Technologies Inc., 2007; Al Seadi et al.; Kirchmeyr et al., 2009
and Frandsen et al. ,2011).
The reasons of temperature fluctuations are:
1. Add new feedstock, with different temperature of the process temperature;
2. Formation of various temperature layers due to insufficient heating system or stirring;
3. Extreme outdoor temperatures;
4. Failure of power system.
Digesters must be isolated and heated by external heating sources in order to achieve and
maintain a constant temperature of AD process and to compensate of heat losses (Institut
für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008 and Frandsen et al.
,2011).
48
Review of literature
The feedstock heating can be done during the feeding process (pre-heating) or inside the
digester, by heating system (Fig. 2.25). Pre-heating the feedstock during feeding process has
the advantage of avoiding temperature fluctuations inside the digester. Many biogas plants
use a combination of both types of feedstock heating (Institut für Energetik und Umwelt et
al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008 and Frandsen
et al., 2011).
Fig. 2.25: Heating system of biogas plant (left) and heating pipes, installed inside
the digester (right) (as cited in REHAU, 2010)
2.3.5. Digesters
Digester considers the core of biogas production system, where the decomposition of
substrate occurs, in absence of oxygen for produce biogas. In European climates anaerobic
digesters have to be isolated and heated. There are a various types of on-farm biogas
digesters, which can be made of different materials such as concrete, steel, brick or plastic,
shaped like silos, troughs, basins or ponds, and they may be placed underground or on the
surface. The size of digesters varies from few cubic meters in the case of small household
installations to several thousands of cubic meters, like in the case of large commercial
plants, often with several digesters (Kossmann et al., 1999; Dennis and Burke, 2001; Lfu,
2007 and Al Seadi et al., 2008).
The selection of biogas digester depending on the dry matter content of the digested
substrate. There are two AD technologies systems: wet digestion (liquid digestion), when
the average dry matter content (DM) of the substrate is less than 15 % and dry digestion
(solid digestion), when the DM content of the substrate is more than 15 % (usually from 20
to 40 %). Wet digestion is applied for feedstock like manure and sewage sludge, while dry
49
Review of literature
digestion is applied for solid animal manure, with high straw content, household waste and
solid municipal bio-waste, green cuttings and grass from landscape maintenance or energy
crops (Electrigaz Technologies Inc., 2007; Al Seadi et al., 2008; Rapport et al., 2008 and
Kirchmeyr et al., 2009).
There are several different types of digesters technologies uses for agricultural biogas plants
as illustrated in Tables (2.6 and 2.7):
Table 2.6: Main characteristics of anaerobic digesters technologies in agricultural biogas
plants (author elaboration cited in Institut für Energetik und Umwelt et al., 2006
and Lfu, 2007)
Characteristics
Construction of digester
Temperature in digester
Environment in digester
Process stages
Loading (feeding) strategy
Technologies
Covered lagoon, plug flow, complete mix, fixed film, UASB, vertical,
Horizontal and etc.
Psychrophilic, mesophilic and thermophilic
Wet and dry
one-stage, two-stages and multiple stages
batch, continuous and semi-batch
Table 2.7: Comparison between different technologies of agricultural anaerobic digesters
(author elaboration cited in Electrigaz Technologies Inc., 2007)
Technology
Wet digestion
Dry digestion
Digester type
Covered lagoon
Plug flow
Complete mix
Fixed film
UASB
Batch
Vertical
Horizontal
Feedstock type
Thin manure
Thick manure
Liquid & solid
Liquid
Liquid
Agricultural and
municipal feedstock
HRT (day)
20 - 200
20 - 40
20 - 80
1 - 20
0.5 - 2
20-30
20 - 40
20 - 40
biogas yield
Poor
Poor
Good
Good
Good
Good
Good
Good
Technology level
Low
Low
Medium
High
High
Medium
High
High
2.3.5.1. Wet anaerobic digesters
Wet digesters systems are used substrate, which contains adequate fluid to be pumped (less
than 15 % dry matter). On the other hand wet digesters can also digest solid feedstock, if
they are equipped with adequate feeding equipment of solid feedstock. Bacterial
decomposition of solids ensures that the substrate inside the digester remains liquid
(Kossmann et al., 1999; Dennis and Burke, 2001; Institut für Energetik und Umwelt et al.,
2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008; Rapport et al.,
2008 and Kirchmeyr et al., 2009).
50
Review of literature
A- Batch systems:
Wet digesters can run in batches or continuously. In batch systems the digesters are filled,
mixed, left to digest, partially emptied and refilled. They are not emptied completely to
ensure inoculation of fresh feedstock batches with bacteria from the previous batch. Batch
systems works in one-stage or two-stages. These systems exist, but they are not common
(Dennis and Burke, 2001; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008
and Rapport et al., 2008).
B- Continuous systems:
Continuous systems are digesters that are fed daily and produce digestate daily. Continuous
systems works in one-stage (wet or dry) or two-stages (wet-dry or dry-wet) or multiple
stages. There are many types of continuous wet digesters (Institut für Energetik und
Umwelt et al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008 and
Rapport et al., 2008):
1-Covered lagoon digester:
Usually consists of a rectangular earthen lagoon covered with a flexible membrane to collect
biogas (Fig. 2.26). Feedstock needs to be thin (contains less than 3 % of DM). The covered
lagoon digester may be mixed with recirculation but is generally not mechanically mixed.
Feedstock enters at one end, pushing substrate out through an overflow pipe, maintaining a
consistent liquid level. The lagoons operate at psychrophilic or ground temperatures.
Consequently, the reaction rate is affected by seasonal variations in temperature. The
residence time of substrate (HRT) from 20 to 200 days (Dennis and Burke, 2001; Covered
Lagoon, 2003 and Electrigaz Technologies Inc., 2007).
Fig. 2.26: Covered lagoon digester (as cited in Covered Lagoon, 2003)
51
Review of literature
Main components:

Solids separator;

Usually two lagoons: primary (covered) and secondary (volume storage);

Floating lagoon cover;

Biogas utilization system.
Advantages:

Inexpensive;

Simple and easy to install;

Low technology applied compared with more mechanical systems.
Disadvantages:

Requires significant area;

Poor mixing of feedstock;

Poor yield of biogas;

Has a high HRT;

Poor solids degradation;

Nutrients and solids accumulate in bottom of lagoon, which lead to reducing useable
volume of lagoon;

Bacteria wash out.
2- Plug flow digester:
The plug flow digester can be a horizontal or vertical reactor. Usually horizontal digester
consists of rectangular tank that are half buried with a hard or flexible membrane cover
installed to collect the biogas produced (Fig. 2.27). The feedstock needs to be relatively thick
(contains 8 – 12 % of DM) to ensure that feedstock movement maintains the plug flow
effect. These digesters are generally not mechanically mixed. Feedstock enters at one end,
pushing older substrate forward until it exits. Some systems will re-circulate substrate from
the end of tank to inoculate the new material entering and speed up the degradation
process. The residence time of substrate (HRT) from 20 to 40 days (Dennis and Burke, 2001;
Anaerobic Digester, 2003; Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008 and Rapport et al., 2008).
52
Review of literature
Fig. 2.27: Plug flow digester (as cited in Anaerobic Digester, 2003)
Main components:

Mixing tank;

Digester equipped with heat exchanger and biogas recovery system;

Effluent storage structure;

Biogas utilization system.
Advantages:

Inexpensive;

Simple to install and operate;

Fit for livestock manure digestion;

Works well with scrape systems (systems of manure collection from Corrals);

Produces high quality fertilizers.
Disadvantages:

Feedstock must contains more than 8 % of DM;

Susceptible to contaminants (can’t be used with sand bedding);

Poor mixing of feedstock;

Poor yield of biogas;

Nutrients and solids accumulate in bottom of digester, which lead to reducing useable
volume of digester;

Poor solids degradation;

Membrane-top subject to weather (wind and snow);

Bacteria wash out.
3- Complete mix digester:
A complete mix organic digester is also known as a completely stirred tank reactor (CSTR,
Fig. 2.28). A single (one-stage) CSTR is the most common on-farm digester type with
53
Review of literature
continuous feeding of manure and / or energy crops (e.g. maize and / or grass silage). The
biogas plant with CSTR technology may also be two- or multi-stages. CSTR usually vertical
circular tanks with hard or flexible membrane cover that store biogas. Tanks can be
designed in a vertical (top mounted mixer) or flat (side mixers) configuration. CSTR are
always mechanically stirred. The fresh feedstock enters the tank and is immediately mixed
with the existing, partially digested material. Biogas production proceeds without any
interruption from the loading and unloading of the waste material. To optimize the
digestion process of the anaerobic bacteria, the digester should be kept at a constant
temperature. Typically, a portion of the biogas generated is used to heat the contents of the
digester, or the coolant from a biogas-powered generator is returned to a heat exchanger
inside the digester tank. The residence time of substrate (HRT) from 20 to 80 days (Institut
für Energetik und Umwelt et al., 2006; Lehtomäki, 2006; Electrigaz Technologies Inc., 2007;
Lfu, 2007; Al Seadi et al., 2008 and Rapport et al., 2008).
Fig. 2.28: Complete mix digester (as cited in Lfu, 2007)
Main components:

Mixing tank;

Digester equipped with mixing, heating and biogas recovery systems;

Effluent storage system;

Biogas utilization system.
Advantages:

Efficient;

Can digest different feedstocks contains different levels of dry matter;

Can digest energy crops and by-products with animal manure;
54
Review of literature

Good mixing of feedstocks;

Good solid degradation;

Can be used with either flush or scrape systems;

Works well with flush and scrape systems (systems of manure collection from Corrals);

The manure tanks, which already exist in farms could be converted to biogas digesters
by equip them with isolation, stirring and heating systems which leading to construct
cheap digester of biogas.
Disadvantages:

Relatively expensive;

No guarantee on how much time the material remains in the tank (HRT);

Requires mechanical mixing system;

Bacteria wash out.
4- Fixed film digester:
A fixed film digester (Fig. 2.29) also called attached growth digesters or anaerobic filters.
Fixed film digester usually consists of a column packed with media, such as wood chips or
small plastic rings. Methane-forming microorganisms grow on the media called a bio-film.
Usually, effluent is recycled to maintain a constant upward flow. A solids separator is
needed to remove particles from the manure before feeding the digester. Efficiency of this
system depends on the efficiency of the solids separator; therefore, influent manure
concentration should be adjusted to maximize separator performance, (usually, 1 to 5 %
total solids concentration of influent manure). The residence time of substrate (HRT) from 1
to 20 days (Dennis and Burke, 2001; Institut für Energetik und Umwelt et al., 2006;
Electrigaz Technologies Inc., 2007; Lfu, 2007 and EXTENSION, 2012).
55
Review of literature
Fig. 2.29: Fixed film digester (as cited in EXTENSION, 2012)
Main components:

Solids separator;

Influent recycling pumps;

Digester system;

Biogas utilization system.
Advantages:

Efficient;

Good solid degradation;

Works with dilute feedstock;

Low HRT (< 20 days);

Low bacteria wash out.
Disadvantages:

Expensive;

Cannot digest feedstock contains high concentration of solids;

Requires efficient system of solids separation;

Susceptible to plugging problems by manure solids;

Some potentials of biogas production are lost due to removing manure solids.
5- Up-flow Anaerobic Sludge Blanket (UASB):
UASB usually, circular tanks with hard tops, but can be found as a rectangle tanks (Fig. 2.30).
UASB are mixed by recirculation of influent. UASB have been designed for agri-food waste
water treatment. Wastewater is distributed into the tank at appropriately spaced inlets. The
wastewater passes upwards through an anaerobic sludge bed where the microorganisms in
56
Review of literature
the sludge come into contact with wastewater substrates. The sludge bed is composed of
microorganisms that naturally form granules (pellets) of 0.5 to 2 mm diameter that have a
high sedimentation velocity and thus resist wash-out from the system even at high hydraulic
loads. The upward motion of released biogas bubbles causes hydraulic turbulence that
provides reactor mixing without any mechanical steering. At the top of the reactor, the
water phase is separated from sludge solids and gas in a three-phase separator (also known
the gas-liquid-solids separator). The three-phase-separator is commonly a gas cap with a
settler situated above it. Below the opening of the gas cap, baffles are used to deflect gas to
the gas-cap opening. The residence time of substrate (HRT) from 0.5 to 2 days (Dennis and
Burke, 2001; Institut für Energetik und Umwelt et al., 2006; Lehtomäki, 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007 and Rapport et al., 2008).
Fig. 2.30: Up-flow Anaerobic Sludge Blanket digester (UASB) (as cited in
Anaerobic Granular Sludge Bed Reactor Technology, 2003)
Main components:

Mixing tank;

Digester equipped with heating and biogas recovery systems;

Effluent storage system;

Biogas utilization system.
Advantages:

High efficient;

Can treat heavy loaded wastewater;

Good retention of bacteria.
57
Review of literature
Disadvantages:

High expensive;

Not designed to accept high concentrations of suspended solids;

Complex operating;

Not widespread for agricultural applications;

Doesn’t digest fats.
2.3.5.2. Dry anaerobic digesters
Dry digesters are systems digest not pumpable feedstock (contains 20 – 40 % dry matter or
more) and the digesters equipped with the feeding equipment of solid feedstock. After
digestion process the digestate expelled in solid form. Solid digesters may run in batches or
continuously (Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006;
Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008; Rapport et al., 2008 and
Kirchmeyr et al., 2009).
A- Batch systems:
Batch operation is usually used for raw materials with high DM (TS) content, such as solid
manure and silage. A garage type is the most common batch reactor (Fig. 2.31). It is filled
with a mixture of new feedstock and digestate (for give inoculum) by using e.g. a front
loader and then closed for biogas producing under airtight conditions. Due to the stirring of
feedstock inside the digester is unavailable, leachate is collected via chamber drain and
sprayed back on top of the pile to provide a mixing or inoculating effect. Fermentation
occurs at mesophilic temperatures at 34 – 37 °C, which are regulated through heated floors
and walls. Finally opened and emptied just to start a new cycle again with new feedstock. As
the biogas production thus varies depending on the stage of the operational cycle, it is usual
to have at least three parallel batches in different stages of operation: one being filled, one
in biogas producing phase and one being emptied. The residence time of substrate (HRT)
from 20 to 30 days (Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006;
Lehtomäki, 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008;
Rapport et al., 2008; ZORG, 2012).
58
Review of literature
Fig. 2.31: Garage-type batch digester, loaded by loader (as cited in ZORG, 2012)
Main components:

Digester equipped with a system of draining, recycling and spraying of leachate,
heating and biogas recovery systems;

digestate storage system;

Biogas utilization system.
Advantages:

Efficient;

Can digest dry feedstocks contains high levels of dry matter;

Can digest energy crops and by-products with animal manure;

Good solid degradation;

No wash out of bacteria.
Disadvantages:

High expensive;

Uneven gas production and lack of stability in the microbial population;

Need to 3 digesters -at least- works in parallel (at different stages of digestion) to
overcome the volatility of biogas production;

No guarantee on how much time the material remains in the tank (HRT).
B- Continuous systems:
In continuous dry digesters, feedstock is constantly fed into the digester. The substrate
moves through the digester either mechanically or by the pressure of the newly feed
substrate, which pushing out the digested material. Unlike batch-type digesters, continuous
59
Review of literature
digesters produce biogas without interruption and biogas production is constant and
predictable. Continuous digesters could be vertical or horizontal and could be single or
multiple tanks systems. Completely mixed digesters are typically vertical digesters while
plug-flow digesters are horizontal (Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007 and Al Seadi et al., 2008).
1- Vertical dry digesters:
Vertical cylindrical digester (Fig. 2.32) is fed from the top with chopped feedstock and where
digested digestate are removed from the bottom. Fresh feedstock material is processed into
small pieces and mixed with digested material and fed to the digester using a screw feeding
system to ensure bacterial inoculation at the top of the digester. There is a vertical plug flow
from the top to the bottom. A screw removes material from the bottom. The residence time
of substrate (HRT) from 20 to 40 days (Electrigaz Technologies Inc., 2007; Lfu, 2007; Zaher
et al., 2007; Al Seadi et al., 2008; Rapport et al., 2008 and Ontario, 2011).
Fig. 2.32: Vertical dry digester (as cited in Zaher et al., 2007)
Main components:

Digester equipped with feeding equipment of solid feedstock, heating and biogas
recovery systems;

digestate storage system;

Biogas utilization system.
Advantages:

Efficient;

Can digest dry feedstocks contains high levels of dry matter;
60
Review of literature

Digester has a relatively small size compared with wet digesters systems and produce
high biogas yield;

Alternative to traditional production method of smelly composting, and producing
high quality compost.
Disadvantages:

High expensive;

Feedstock needs to size reduction by chopping for accelerating digestion;

Has complex mechanical structure and maintenance;

No mixing of substrate lead to reduction the potentials of biogas yield;

Poor Solids degradation.
2- Horizontal dry digesters:
Horizontal digesters (Fig. 2.33) consist of horizontal cylindrical shape and equipped with a
heating system, gas dome, manure pipes and stirring system. This type of digesters is usually
manufactured in one piece of stainless steel, so that they are limited in size and volume. The
standard type for small scale digester is a horizontal steel tank with volume from 50 to 150
m3, which uses as a main digester for small biogas plants or as pre-digester for larger plants,
for increase the digestion efficiency of main digester. There are also alternative digesters
made of concrete, with volume up to 1000 m3. Horizontal digesters can also run in parallel
(Fig. 2.34), in order to produce more biogas yield. Horizontal continuous flow digesters are
usually used for dry feedstock like chicken manure, grass, maize silage or manure with a
high straw content. The residence time of substrate (HRT) from 20 to 40 days (Institut für
Energetik und Umwelt et al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi
et al., 2008; Rapport et al., 2008 and Nordic Folkecenter, 2010).
Fig. 2.33: Horizontal dry digester (as cited in Nordic Folkecenter, 2010)
61
Review of literature
Fig. 2.34: Horizontal dry digesters run in parallel (as cited in
Nordic Folkecenter, 2010)
Main components:

Digester equipped with feeding equipment of solid feedstock, stirring, heating and
biogas recovery systems;

digestate storage system;

Biogas utilization system.
Advantages:

Efficient;

Good mixing of feedstocks;

Can digest dry feedstocks contains high levels of dry matter;

Digester has a small size compared with wet digesters systems and produce high
biogas yield;

Alternative to traditional production method of smelly composting, and producing
high quality compost;

Good Solids degradation.
Disadvantages:

High expensive;

Feedstock needs to size reduction by chopping for accelerating digestion;

Has complex mechanical structure and maintenance;

Has a limited productivity.
62
Review of literature
2.3.6. Stirring systems
The indirect stirring could occur by feeding of fresh feedstock and the subsequent thermal
convection streams as well as by the up-flow of gas bubbles. As indirect stirring is not
sufficient for optimal operation of the digester, active stirring must be applied by using
mechanical, hydraulic or pneumatic equipment. Up to 90 % of biogas plants use mechanical
stirring equipment for increasing the digestion efficiency and biogas yield (Sasse, 1988;
Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al
Seadi et al., 2008).
The substrates inside the digester must be stirred several times per day for mixing the new
feedstock with the existing substrate inside the digester. Moreover, stirring prevents
formation the layers of floating sediments, facilitates the up-flow of gas bubbles and
homogeneity distribution of heat and nutrients through the whole mass of substrate
(Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007 and Al
Seadi et al., 2008).
2.3.6.1. Mechanical stirring
According to rotation speed, mechanical stirrers can be fast, medium and slow running
stirrers. Submersible motor propeller stirrers (Fig. 2.35) are frequently used in vertical
digesters. They are completely immersed in the feedstock and usually have two or three
wings, geometrically optimized propellers. Paddle stirrers have a vertical, horizontal or
diagonal axis (Figs. 2.36, 2.37 & 2.38). The motor is positioned outside the digester.
Junctions, where the shaft passes the digester ceiling, membrane roof or the digester wall,
have to be tight. (Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006;
Lfu, 2007 and Al Seadi et al., 2008).
63
Review of literature
Fig. 2.35: Submersible motor propeller stirrer
(as cited in Wilo Mixers, 2011)
Fig. 2.36: Vertical hanging paddle stirrers (as cited in Lfu, 2007)
Fig. 2.37: Horizontal hanging paddle stirrers (as cited in Lfu, 2007)
64
Review of literature
Fig. 2.38: diagonal paddle stirrers (as cited in Lfu, 2007)
2.3.6.2. Hydraulic stirring
Hydraulic stirring system (Fig. 2.39) works by press the feedstock by pumps through
horizontal or additional vertical vents into the digester. Hydraulically stirred systems have
the advantage that the mechanical parts of the stirrers are placed outside the digester,
subject to lower wear and can be easily maintained. Hydraulic stirring is appropriate for
destruction of floating layers of sediments (Wellinger, 1999; Institut für Energetik und
Umwelt et al., 2006; Lfu, 2007 and Al Seadi et al., 2008).
2.3.6.3. Pneumatic stirring
Pneumatic stirring system (Fig. 2.40) uses the produced biogas, by injection the biogas from
the bottom of the digester through the mass of the feedstock. The bubbles of rising gas
cause a vertical movement and stir the feedstock. Pneumatic stirring not frequently used in
agricultural biogas plants, as the technology is not appropriate for destruction of floating
layers of sediments (Wellinger, 1999; Institut für Energetik und Umwelt et al., 2006; Lfu,
2007 and Al Seadi et al., 2008).
65
Review of literature
Fig. 2.39: Hydraulic stirring system (as cited in Lfu, 2007)
Fig. 2.40: Pneumatic stirring system (as cited in Wellinger, 1999)
2.3.7. Biogas storage
A biogas storage system essentially required to provides a constant gas pressure to the CHP
unit. Biogas is typically generated at unstable rate during the anaerobic digestion process
and the fluctuation of biogas production is increasing when inhomogeneous feedstocks are
digesting such as agricultural residues and food wastes. Correct selection and dimensioning
of biogas storage facility brings substantial contribution to the efficiency, reliability and
safety of the biogas plant while ensuring constant supply of biogas and minimizing biogas
losses (Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al
Seadi et al., 2008 and ZORG, 2012).
The use of digesters is integrates with the use of innovative or non-traditional biogas
storage options. The simplest biogas storage is established on top of digesters, using a gas
tight membrane (Fig. 2.41), which consists of one or two membranes (the external
66
Review of literature
membrane forms the outer shape and the internal membrane seals the digester gas-tight).
For safety reasons, biogas holders must be equipped with safety valves (under-pressure and
over-pressure, Fig. 2.42) to avoid unsafe biogas pressure levels (negative or positive) into
digester. Usually, a capacity from one to two days is recommended for use the biogas tight
membranes (Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006; Lfu,
2007; Al Seadi et al., 2008; SATTLER AG & Ceno Membrane Technology GmbH, 2010 and
ZORG, 2012).
Fig. 2.41: Biogas tight membranes (as cited in SATTLER AG
& Ceno Membrane Technology GmbH, 2010)
Fig. 2.42: Safety pressure valves (as cited in ZORG, 2012)
67
Review of literature
2.3.7.1. Low pressure tanks
Low pressure storage facilities of biogas are most common use. They have a pressure range
from 0.05 to 50 mbar and made of special membranes, which must meet a number of safety
requirements. The membrane tanks are installed on the top of the digesters as a covers or
as external gas holders as gas domes. External low-pressure tanks can be designed in the
shape of membrane cushions (Fig. 2.43) or gas balloons (Fig. 2.44). (Institut für Energetik
und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008; SATTLER AG & Ceno Membrane
Technology GmbH, 2010 and ZORG, 2012).
Fig. 2.43: Gas cushion tank (as cited in SATTLER AG &
Ceno Membrane Technology GmbH, 2010)
Fig. 2.44: Gas balloon tank (as cited in SATTLER AG &
Ceno Membrane Technology GmbH, 2010)
68
Review of literature
2.3.7.2. Medium and high pressure tanks
Biogas can also be stored in medium and high pressure tanks made of steel (Fig. 2.45) at
pressures between 5 and 250 bar. These kinds of storage types have high operation costs
and high energy consumption. (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al
Seadi et al., 2008; SATTLER AG & Ceno Membrane Technology GmbH, 2010 and ZORG,
2012).
Fig. 2.45: High pressure tank of biogas (as
cited in ZORG, 2012)
2.3.8. Digestate storage
After the digestion process is complete, the digestate is dewatered and uses as fertilizer, it is
transported away from the biogas plant, through pipelines or with special vacuum tankers,
and temporarily stored in storage tanks placed e.g. out in the fields, where the digestate is
applied. The total capacity of these tanks must be enough to store the production of
digestate for several months. Digestate can be stored in concrete tanks or in lagoon ponds,
covered by natural or artificial floating layers or by membrane covers (Fig 2.46) (Lehtomäki,
2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al.,
2009; Lukehurst et al., 2010 and Frandsen, 2011).
69
Review of literature
Fig. 2.46: Covered digestate storage tank (as
cited in Lukehurst et al., 2010)
2.4. Biogas characteristics
The characteristics of biogas vary depending on feedstock types, digestion systems,
temperature of digestion, hydraulic retention time etc. Table (2.8) illustrated some average
biogas composition values. Considering biogas with the standard methane content of 60 %,
the caloric value (heating value) is 6 kWh / m³ (21 MJ / m³) while the calorific value of
natural gas contains 99 % methane is 9 kWh / m³, on the other hand one m3 of biogas will
produce approximately 1.7 kWh of electricity and 2 kWh of heat from CHP unit has power
conversion efficiency 60 %. The biogas density is 1.265 kg / m³ similar to the air (1.29 kg /
m³). Theoretical methane production is varies according to their biochemical composition,
as illustrated in Table (2.9) (Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Genesis Projects Corp, 2007; Lfu, 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009 and Frandsen et al. ,2011).
Table 2.8: Composition of raw biogas (author elaboration cited in
Electrigaz Technologies Inc., 2007)
Compound
Methane
Carbon dioxide
Water vapor
Oxygen
Nitrogen
Ammonia
Hydrogen
Hydrogen sulphide
Chemical symbol
CH4
CO2
H2O
O2
N2
NH3
H2
H2S
Content (Vol. - %)
50 -75
20 - 45
2 (20°C) - 7 (40°C)
<2
<2
<1
<1
<1
70
Review of literature
Table 2.9: Theoretical gas production (author elaboration cited in Al Seadi et al., 2008)
Substrate
Raw protein
Raw fat
Carbohydrates
Liter of gas / kg TS
700
1200 to 1250
790 to 800
CH4 (%)
70 to 71
67 to 68
50
CO2 (%)
29 to 30
32 to 33
50
The methane production from the AD depends on the source of substrate, as illustrated in
Table (2.10).
Table 2.10: Methane production from different feedstock materials (author elaboration
cited in Al Seadi et al., 2008)
Feedstock
Liquid cattle manure
Liquid pig manure
Distillers grains with soluble
Cattle manure
Pig manure
Poultry manure
Beet
Organic waste
Sweet sorghum
Forage beet
Grass silage
Corn silage
8
Biogas yield (m³ / ton of FF )
25
28
40
45
60
80
88
100
108
111
172
202
Methane content (%)
60
65
61
60
60
60
53
61
54
51
54
52
2.5. Biogas utilization
Utilizations of biogas are varying according to the nature of the biogas source and the local
demand; different uses of biogas are illustrated in Table (2.11) (Institut für Energetik und
Umwelt et al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG, 2012).
8
FF=fresh feedstock
71
Review of literature
Table 2.11: Different technologies for utilization and upgrading of biogas (author elaboration
cited in Electrigaz Technologies Inc., 2007 and Frandsen et al., 2011)
Utilization of biogas
Heat production only
Power production
only
Combined heat and
power generation
(CHP)
Biogas upgrading
Technologies
Biogas burners and boilers
Internal combustion
Gas turbines
Fuel cells
Otto and diesel engines
adapted for biogas
Gas turbines and micro
turbines
Stirling motors
Organic Rankine cycle
(ORC)
Pressure Swing Adsorption
(PSA)
Absorption:
Water scrubbing
Organic physical scrubbing
Chemical scrubbing
Membrane technology
Cryoprocesses
In situ enrichment
Ecological lung
Cost
Low
Medium
High
Very high
Efficiency
Medium
Medium
Medium
High
Complexity
Low
Medium
High
High
Reliability
High
High
Medium
Low
Medium
High
Medium
High
High
High
High
Medium
Medium
High
High
Medium
High
High
High
Medium
Very high
High
High
Variable
Very high
High
High
Variable
Very high
Very high
Very high
Very high
High
High
High
High
High
High
High
High
Variable
Variable
Variable
Variable
2.5.1. Biogas preparation before utilization
Biogas is not absolutely pure, but contains impurities such as water droplets, dust, mud and
traces of unwanted gases (such as carbon dioxide (CO2), hydrogen sulphide (H2S), and
ammonia (NH3), which cause corrosion of metals in the presence of water and high
temperature). All this contaminants have to be removed, depending on the utilizations of
the biogas. Solid particles in the biogas and sometimes oil-like components are filtered out
of the biogas by the usual dust filters. Sludge and foam components are separated in
cyclones. The separation can be improved by injecting water into the biogas before the
cyclone, process water can be used. For removing the traces of unwanted gases, scrubbing,
adsorption, absorption, and drying are applied. In the case of biogas is just burning, e.g., in a
gas burners, no necessity exist for the purification of the biogas but the exhaust air after
burning might to be decontaminated (Institut für Energetik und Umwelt et al., 2006;
Electrigaz Technologies Inc., 2007; Lfu, 2007; Kirchmeyr et al., 2009; Frandsen et al.,2011
and ZORG, 2012).
72
Review of literature
2.5.2. Direct combustion
The simplest way of utilizing biogas is direct combustion in burners or boilers (Fig. 2.47), to
produce heat. This technology has low investment and maintenance costs and is well-known
and reliable. For small scale biogas plants located at a site with a high heat demand, it is
probably the best alternative, at least in countries with rather low price for electricity
produced with biogas. The heat demand at a farm during summer can, as a monthly
average, be about 20 % compared with a winter month. In boilers, the requirements for
biogas quality are low but it is recommended to reduce the level of hydrogen sulphide
content below 1.00 ppm, which allows the exhaust gases to maintain a dew point around
150 °C (Institut für Energetik und Umwelt et al., 2006; Electrigaz Technologies Inc., 2007;
Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG,
2012).
Fig. 2.47: Biogas burner for steam boiler (as cited in
Electrigaz Technologies Inc., 2007)
2.5.3. Internal combustion
One of the most common technologies of power generation is internal combustion engines,
which can be used to burn biogas for generate electricity that can be sold to the power grid.
Engines are available in sizes from a few kilowatts up to several megawatts. Gas engines can
either be Otto-engines (spark ignition) or dual fuel engines. Otto generators (Fig. 2.48) are
equipped with normal ignition systems and a gas / air mixing system that provides a
combustible mixture to the engine. Dual fuel generators (Fig. 2.49) with injection of diesel
(10 % and up) used as a pilot fuel to ignite biogas during combustion. Internal combustion
73
Review of literature
engines are very popular in small scales because they have good electric efficiencies up to
40 % (Institut für Energetik und Umwelt et al., 2006; Electrigaz Technologies Inc., 2007;
Lfu, 2007; Al Seadi et al., 2008 and Frandsen et al., 2011).
Fig. 2.48: Biogas Otto-generator (as cited in
Alibaba.com, 2012)
Fig. 2.49: Dual fuel-generator (as cited in
DIRECTINDUSTRY, 2012)
2.5.4. Gas turbines
Modern gas turbines (Figs. 2.50 and 2.51) are derivatives from aviation gas turbine, which
exhaust gases are directly expanded through the turbine and the plant size is often above
800 kWhel. The fact that the exhaust gases expand directly in the turbine wheel, poses strict
fuel purity requirements. In recent years also small scale engines, so called micro-turbines in
the range of 25 to 200 kWhel have been successfully introduced in biogas applications. They
74
Review of literature
have efficiencies comparable to small Otto-engines with low emissions and allow recovery
of low pressure steam which is interesting for industrial applications (Institut für Energetik
und Umwelt et al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG, 2012).
Fig. 2.50: Gas turbines (as cited in Gas Turbines, 2008)
Fig. 2.51: Gas turbine process with heat recovery in a steam
turbine downstream (as cited in ZORG, 2012)
2.5.5. Fuel cells
The fuel cells (Fig. 2.52) are electrochemical devices that convert the chemical energy of a
reaction directly into electrical energy. The basic physical structure (building block) of a fuel
cell consists of an electrolyte layer in contact with a porous anode and cathode on both
sides with continuously fed of fuel (Hydrogen) to the anode and air (Oxygen) to the cathode.
Fuel cells have a potential to become the small scale power plant of the future.
Nevertheless, widespread commercial use is yet to be achieved. Fuel cells have a potential
to reach very high efficiencies (more than 60 %) and low emissions. Fuel cells still considered
in the realm of research and development. Currently, fuel cells do not offer the reliability
75
Review of literature
necessary to ensure economic feasibility of biogas projects. It will take many years before
the fuel cell can surpass the internal combustion engine as a reliable biogas energy
conversion technology (Institut für Energetik und Umwelt et al., 2006; Electrigaz
Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al., 2009; Frandsen et
al., 201 and ZORG, 2012).
Fig. 2.52: Simplified scheme of a fuel cell (as cited in
www.fueleconomy.gov., 2012)
2.5.6. Combined heat and power (CHP)
CHP generation is a common utilization of biogas in many countries with a developed biogas
sector, and it is considered a very efficient of biogas utilization for energy production. The
most common types of CHP plants are block type thermal power plants (BTTP) with
combustion motors that are coupled to a generator. The total efficiency of CHP unit is
considered the sum of the electrical and thermal efficiencies, is within the range 85 - 90 %
with modern CHPs and only 10 - 15 % of the energy of the biogas is wasted. But the
electrical efficiency (maximum 40 %) is still very low (from 1 m3 biogas only 2.4 KWh, electric
current can be produced). Most common CHP plants are Otto or ordinary diesel engines
using biogas as fuel. Other technologies of CHP are gas turbines, Stirling motors and organic
Rankine cycle (ORC) (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et
al., 2008; Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG, 2012).
76
Review of literature
2.5.6.1. Gas-Otto engines
Gas-Otto motors (Fig. 2.53) are developed specifically for using biogas according to the Otto
principle. In gas-Otto engine air and fuel are mixed before entering engine cylinders where
the mixture is fired by spark plugs. Gas-Otto motors require biogas with minimum 45 %
methane content. Small engines, up to 100 kWhel are usually Otto engines. Gas-Otto engines
can be operated with biogas or natural gas. Usually with diesel engines 35 - 45 % of the
energy content of the fuel can be converted into electricity, depending on the size of the
unit, in comparison with similar size the efficiency of Otto-engines is in general lower, about
27 - 38 % (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG, 2012).
Fig. 2.53: CHP unit equipped with gas-Otto
engine (as cited in BSRIA, 2010)
2.5.6.2. Pilot-injection gas engines
The pilot injection engine (also called pilot injection natural gas engine, PINGE, or dual fuel
engine) is based on the diesel engine principle (Fig. 2.54). In diesel engines converted to
biogas the fuel-air mixing is basically similar to Otto-engines. Since biogas does ignite by the
cylinder compression unlike diesel fuel, a small amount of diesel is used to ignite the
mixture, usually; the oil injection is 2 - 5 % during normal conditions. Different uses of heat
and power produced from on-farm CHP unit illustrated in Table (2.12) (Institut für Energetik
und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al., 2009; Frandsen
et al., 2011 and ZORG, 2012).
77
Review of literature
Fig. 2.54: CHP unit equipped with pilot Injection gas engine
(as cited in HAZEN AND SAWYER, 2012)
Table 2.12: Different uses of heat and power produced from on-farm CHP unit (author
elaboration cited in Kirchmeyr et al., 2009)
Heat
 Usually, 1 / 3 of the heat is used for heating the
digesters (process heat);
 2 / 3 can be used for external needs;
 Heat transport through district heating system;
 Alternative: Micro gas with CHP generation at
the heatsink site;
 Power-heat-cooling coupling.
Electricity
 Produced electricity can be used as process
energy and sold to grid;
 About 7 - 10 % of the produced electricity from
biogas, are used for biogas production process;
 Due to the height prices of electricity, after
consuming of the process electricity and meets
the on-farm requirements of electricity, all surplus
of the electrical production from biogas plant is
sold to electrical grid.
2.5.6.3. Gas turbines and micro turbines
In a gas turbine compressed fuel-air mixture burns continuously and the velocity of the hot
gases rotate a turbine, which is connected to a generator and producing electricity.
Electrical efficiency is usually somewhat lower than in Otto or diesel engines. In small units,
micro turbines (Fig. 2.55), hot exhaust gases can be used for heating and in big units exhaust
gases can generate steam which can rotate a turbine generating power. The electric
capacity of biogas micro turbines is typically below 200 kWhel. The cost of biogas microturbines is high and the research work in this area is therefore aiming cost reduction for
future models (Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al.,
2008; Kirchmeyr et al., 2009; Frandsen et al., 2011 and ZORG, 2012).
78
Review of literature
Fig. 2.55: Gas micro turbine (as cited in WBDC, 2012)
2.5.6.4. Stirling motors
The Stirling motor (Fig. 2.56) operates with external combustion. The combustion takes
place outside the engine and combustion products do not come into contact with the
internal parts of the engine, almost any kind of fuel can be used as heat source. Based on
the principle that changes of gases temperature leads to changes of gases pressure and
volume. The pistons of the engine are moved by gas expansion caused by heat injection
from an external energy source. The required heat can be provided from various sources
such as a gas burner, running on biogas. In comparison to internal combustion engine,
Stirling engine is quieter, and more reliable with less need for maintenance. The electrical
efficiency of the Stirling engine is of 24-28 %, which is lower than Gas-Otto engines (Institut
für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al.,
2009; Frandsen et al., 2011 and ZORG, 2012).
79
Review of literature
Fig. 2.56: Schematic construction of an alpha stirling containing
two pistons, one hot, one cold and a regenerator in the
connecting pipe (as cited in Frandsen et al., 2011)
2.5.6.5. Organic Rankine cycle (ORC)
The Organic Rankine cycle (Fig. 2.57) works like steam turbine by using an organic matter
instead of water as working fluid. ORC suits the low temperatures and small scales. The heat
source can be a motor’s exhaust pipe, waste heat from an industrial processes or the
burning of biogas or other types of fuels. The working organic fluid is expanded in a turbine
in the form of overheated vapor under high pressure. The pressure then drops and power is
delivered to the high speed generator. The expanded vapor still has usable heat that is
supplied to the cold working fluid in the recuperator (heat exchanger). Afterwards the vapor
is condensed in the condenser and the fluid is pressurized to the required high pressure. The
liquid is then warmed in the already mentioned recuperator and then vaporized and
overheated in the boiler. The boiler is heated by the external heat that the ORC converts to
electricity. For biogas plants it can be difficult to get full advantage of heat produced all year
around. Recovering the waste heat in such cases can increase the electricity generation
further. Use of external combustion engines like Stirling motors or ORC are ways to do it
(Spliethoff and Schuster 2006; Lfu, 2007 and Frandsen et al., 2011).
80
Review of literature
Fig. 2.57: ORC unit (as cited in Spliethoff and Schuster 2006)
2.5.7. Biogas upgrading (biomethane production)
Biogas must undergo to upgrading process (Fig. 2.58) before injection into the natural gas
grid or to utilization as vehicle fuel. Upgrading process aims to remove all contaminants as
well as CO2 and increase the content of methane from usual 50 - 75 % (in biogas) to more
than 97 %. Technologies such as pressure swing absorption and water scrubbing are used to
remove CO2 from the biogas stream and converting it to biomethane (upgraded biogas).
Biogas upgrading technologies are becoming increasingly attractive as it does not have the
heat losses and emission issues related to the internal combustion engine and electrical
energy generation. Moreover, the final product is identical to natural gas and can be
transported efficiently using the existing natural gas grid. Unlike natural gas, which
contributes greenhouse gas emissions to the atmosphere, the combustion of upgraded
biogas actually reduces greenhouse gas emissions to the atmosphere by displacing natural
gas (Institut für Energetik und Umwelt et al., 2006; Electrigaz Technologies Inc., 2007; Lfu,
2007; Al Seadi et al., 2008; Kirchmeyr et al., 2009 and Frandsen et al., 2011).
81
Review of literature
Fig. 2.58: Biogas upgrading unit (as cited in FLOTECH, 2010)
2.5.7.1. Biogas as vehicle fuel
Utilization of biogas in the transport sector is a technology with great potentials and with
important socio-economic benefits. Upgraded biogas (biomethane) is considered to have
the highest potentials as vehicle fuel, even when compared to other biofuels. Fig. (2.59)
illustrated a comparison between transport biofuels, in terms of covered distance by an
automobile, when running on the respective biofuel, produced on energy crops cultivated
on one hectare arable land (Electrigaz Technologies Inc., 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009 and Frandsen et al., 2011).
Fig. 2.59: Biofuels in comparison: Range of a personal car,
running on biofuels produced on feedstock /
energy crops from one hectare arable land (as
cited in Fnr, 2008 cited in Al Seadi et al., 2008)
82
Review of literature
2.5.7.2. Biomethane for grid injection
Upgraded biogas (biomethane) can be injected and distributed through the natural gas grid,
after it has been compressed to the pipeline pressure. In many EU countries, the access to
the gas grid is guaranteed for all biogas suppliers (Electrigaz Technologies Inc., 2007; Al
Seadi et al., 2008; Kirchmeyr et al., 2009 and Frandsen et al., 2011).
2.6. Economical considerations to establish on-farm biogas system
In the anaerobic digestion process the biogas production process and subsequent
cogeneration process of thermal and electrical energy are undoubtedly the decisive
moments of the entire process. Proper management of these processes is crucial for the
economic viability of this industry. The estimated costs of construction and management of
on-farm biogas system must be particularly careful considering the many variables that
effect on the correct functioning specially for selection of appropriate technology applying
(Karellas et al., 2010 and Ragazzoni, 2011).
2.6.1. Fixed costs (costs of construction)
Fixed costs (see Table 2.13) of on-farm biogas system depending on the characteristics of
technology applied of digestion process (from simple to sophisticated technology equipped
with measurements and controlling systems), size (dimensions) of the biogas system (the
cost of energy unit produced decreasing with increasing power capacity of installed CHP
unit) and the feedstock materials used for biogas production (silage of energy crops, manure
slurry, agricultural by-product and residues and agro-industrial waste, etc.) (Karellas et al.,
2010 and Ragazzoni, 2011).
Recent researches results indicate to fixed costs fluctuate in relation to the abovementioned variables, between 3000 and 7000 euro / kWel of on-farm CHP unit capacity. The
range of these values seems rather large, but also confirmed by surveys applied at samples
of new installed on-farm biogas plants (Karellas et al., 2010 and Ragazzoni, 2011).
83
Review of literature
According to the power capacity of installed CHP unit, the on-farm biogas plants could be
classified into three categories:

Small scale < 250 kWhel;

Medium scale 250 - 500 kWhel;

Large scale > 500 kWhel.
Table 2.13: Estimated fixed costs of establish on-farm biogas system, based on installed
electrical capacity of on-farm CHP unit (author elaboration cited in Ragazzoni,
2011)
< 250 kWhel
Components of biogas Plant
Concrete constructions
Mechanical and electrical components
CHP unit
Total
Minimum
2300
2000
1200
5500
250 - 500 kWhel
Maximum
3000
2500
1500
7000
Euro / kWel
Minimum
Maximum
2000
2300
1500
2000
1000
1200
4500
5500
> 500 kWhel
Minimum
1400
1000
600
3000
Maximum
2000
1500
1000
4500
2.6.2. Variable costs (operating costs)
Variable costs (see Table 2.14) are the costs related to the management and operating of
the plant. Generally, for investment at biogas projects the payback period of invested capital
is from 6 - 7 years (Karellas et al., 2010 and Ragazzoni, 2011).
Table 2.14: Estimated variable costs of operating on-farm biogas system, based on electrical
energy generated from on-farm CHP unit (author elaboration cited in Ragazzoni,
2011)
Expenditure trends
Management
Repair and periodic maintenance
Operating and services
Chemical and physical analysis
Overheads
Total
Minimum (Euro / kWhel)
Maximum (Euro / kWhel)
0.009
0.006
0.020
0.002
0.010
0.047
0.010
0.009
0.040
0.003
0.012
0.074
It should be mention that, according to the Italian law the biogas plant has a power capacity
of CHP unit less than 100 kWhel , can be establish without official permit
from
administrative authorities, while the biogas plant has a power capacity of CHP unit more
than 300 kWhel loses the right of obtain subsidies and incentives.
84
Material and methods
3. MATERIAL AND METHODS
3.1. Material
RAF is a bio-energetic descriptive model integrates with MAD model (Vitali et al., in press)
to support Integrated Farm Management (IFM). RAF model aimed to enhancing economical,
social and environmental sustainability of farm production in terms of energy via converting
energy crops and animal manure to biogas and digestate (bio-fertilizers) by using anaerobic
digestion (AD) technologies, growing and breeding practices. The user defines farm
structure in terms of present crops, livestock, market prices, etc. and RAF model investigates
the possibilities of establishing on-farm biogas unit (different anaerobic digestion (AD)
technologies proposed for different scales of farms in terms of energy requirements)
according to budget and sustainability constraints for reduce the dependence on fossil fuels.
The objective function of RAF (Z) is optimizing the total net income of farm (maximizing
income and minimizing costs) for whole period which is considered by analysis.
3.1.1. Farm characteristics under study
The farm under study should be has a set of conditions as follows:

The farm consists of one unit with specific borders to distinguish from the other
farms;

Farm production should be oriented to conventional or organic production (mixing
between conventional and organic is not allowed);

Farm applying integrated co-production of agricultural and livestock products;

Farm managed by the owner himself without rent, brokers and agents;

Farm has a potentials for applying and using renewable energy (bioenergy) with
conventional energy or replace it;

The family labor (for free) is not considered;

Inter-cropping and cultivation of more than one type of crops at the same site is not
considered;

Erosion and soil degradation is not considered;

Natural areas income and costs are not considered.
85
Material and methods
3.2. Methods
3.2.1. Linear programming
Linear programming (LP) is a mathematical technique use in computer modeling
(simulation) to find the best possible solution in allocating limited resources (energy,
machines, materials, money, personnel, space, time, etc.) to achieve maximum profit or
minimum cost. However, it is applicable only where all relationships are linear and can
accommodate only a limited class of cost functions. For problems involving more complex
cost functions, another technique called 'mixed integer modeling' is employed (Schulze,
1998; Miller, 2007 and Rosenthal, 2012).
LP is the most commonly applied form of constrained optimization. Constrained
optimization is much harder than unconstrained optimization.
The main elements of any constrained optimization problem are:

Variables (also called decision variables). The values of the variables are not known
when you start the problem. The variables usually represent things that you can adjust
or control, for example the rates at which manufacture items. The aim is to find values
of the variables that provide the best value of the objective function;

Constraints. These are mathematical expressions that combine the variables to
express limits on the possible solution. For example, they may express the idea that
the number of workers available to operate a particular machine is limited, or that
only a certain amount of feedstock is available per day;

Variable bounds. Only rarely are the variables in an optimization problem permitted to
take on any value from minus infinity to plus infinity. Instead, the variables usually
have bounds. For example, zero and 100 might bound the production rate of widgets
on a particular machine;

Objective function. This is a mathematical expression that combines the variables to
express your aim. It may represent profit, for example. You will be required to either
maximize or minimize the objective function.
86
Material and methods
In LP, all of the mathematical expressions for the objective function and the constraints are
linear. The programming in linear programming is an archaic use of the word
“programming” to mean “planning”. So you might think of linear programming as “planning
with linear models”. You might imagine that the restriction to linear models severely limits
your ability to model real-word problems, but this isn’t so. An amazing range of problems
can be modeled using linear programming, everything from airline scheduling to least-cost
petroleum processing and distribution. LP is very widely used. For example, IBM estimated
that in 1970, 25 % of all scientific computation was devoted to linear programming (Schulze,
1998; Miller, 2007 and Rosenthal, 2012).
Linear programming is by far the most widely used method of constrained optimization. The
largest optimization problems in the world are LPs having millions of variables and hundreds
of thousands of constraints. With recent advances in both solution algorithms and computer
power, these large problems can be solved in practical period of time (Schulze, 1998; Miller,
2007 and Rosenthal, 2012).
3.2.2. Description of MAD model
MAD (Figs. 3.1 & 3.2) is a bio-economical model aimed to optimize resources of a farm
holding (surfaces, livestock, labor, etc.) to approach an objective function (Z) aimed to
maximize net income of farm for whole period which is considered by analysis (see
mathematical programming, simplex method) (Vitali et al., in press).
87
Material and methods
Fig. 3:1 MAD flow-chart (as cited in Vitali et al., in press)
Fig. 3:2 MAD architecture (as cited in Vitali et al., in press)
88
Material and methods
3.2.2.1. MAD activities
MAD considers four different levels of details (Vitali et al., in press):
Level 1: Super activity

LSU - livestock units, has been described by the animal breeding method;

NAT - natural surfaces (woods, meadows), has been described from main natural
species presents in such environment;

ARB - tree crops, has been described from planted species and irrigation systems;

SEM - arable crops and open field horticulture, has been described in terms of rotation
schemes.
Level 2: Macro activity
This set of activities (Tables 3.1 & 3.2) gives details of super activities and macro activities
with similar agro-technical activities (land use and livestock) (Vitali et al., in press).
Table 3.1: List of macro-activities used by model related to land use
Super
NAT
NAT
SEM
SEM
SEM
SEM
SEM
IMP
IMP
IMP
Macro
BO
PR
SA
FO
CR
RI
IN
AR
VT
AB
Land use
Wood
Meadow
Naturalized (set-aside)
Forage
Cereals
Rice
Intensive crop
Fruit tree plant
Grapevine
Low input tree plant
Table 3.2: List of livestock related to macro activities
Super
ZOO
ZOO
ZOO
ZOO
Macro
EL
EC
OC
SU
Livestock type
Dairy cattle
Meat cattle
Sheeps and goats
Swines
89
Material and methods
Level 3: RICA-entry (rubrica)
Such a level corresponds to crop and activity families used by RICA-database (it: rubriche).
Such families however are not homogeneous: some entries correspond to a very specific
crop (e.g. durum wheat) while others collect several crops very different from market
viewpoint (e.g. apple, cherry and peach are all together in a unique activity called
'temperate fruit’) (Vitali et al., in press).
Level 4: Crop production
When specified at the above levels, technical parameters cannot include productions, yields
and related market prices. To solve this problem each activity has been linked to one
specific crop depending on region, which also reflects main Italian DOPs 9 (typical of a
territory). It means that for one region, there will be just one crop product (Vitali et al., in
press).
3.2.2.2. Farm parameterization
MAD has been developed to evaluate the optimal farm structure for whole period which is
considered by analysis (10 years).
In MAD a farm is described by regional administrative (NUT210) and environmental
collocation (climate and slope).
Farm production is oriented to conventional or organic.
Farm eco-economic regime described by subsidy policy into three possible values:

No subsidies;

Actual subsidies (included for conventional and organic);

PAC1411 (included for greening conventional and organic).
9
Denominazione di origine protetta
Nomenclature of territorial units for statistics of EUROSTAT
11
Politica agricola comunitaria
10
90
Material and methods
3.2.2.3. Farm activity partitioning

Preliminary (pre-optimization) initial condition (parameters of super-activity);

Tree crops intermediate granularity;

Total Arable area;

Livestock intermediate granularity.
3.2.2.4. Farm main products
In this section the yearly yield of farm commercial products of crops (tons) and livestock (kg)
are calculated (Vitali et al., in press):

Tree crops yield;

Field crops yield;

Livestock products (meat and milk).
3.2.2.5. Farm secondary products

Straw production;

Fresh residues of tree crops;

Manure production.
3.2.2.6. Livestock feeding
Diet requirements for livestock includes forage units (fu) requirements for energetic
balance, ruminant functionality (for herbivorous), and protein requirements (pr) more
relevant for granivorous (swines). Both parameters are calculated through two separate
constraints, one to avoid minimum level of nutrition, the second to avoid any excess.
Moreover diet nutrition requirements for livestock comes from on-farm production of
forage crops and / or purchased from market (Vitali et al., in press).
3.2.2.7. Fertility balance (N12)
On-farm N requirements for trees and field crops, comes from on-farm manure production
and / or N purchased from market. Add quantities of N fertilizers are calculated through two
12
Nitrogen
91
Material and methods
separate constraints, one to avoid minimum level of N fertilizers (required for trees and field
crops), the second to avoid any excess defined by Legal N load.
3.2.2.8. Labor requirements
On-farm Labor requirements contains: labor requirements for trees crops, field crops, and
livestock breeding (h / ha and h / lsu).
3.2.2.9. Farm account balance
According to Vitali et al. (in press) farm net-income comes from subtract of the total costs
(contains fixed and variable costs) from total gross margin (contains income of farm
production and subsidies). Fixed costs come from RICA database and variable costs contain:

Costs of seeds;

Costs of fertilizers;

Costs of pesticide and chemicals;

Costs of machinery;

Costs of fuel;

Costs labor;

Costs of feedstocks for animal diet nutrition.
Gross margin contain:

Gross margin of trees crops (for main production only);

Gross margin of field crops (for main and secondary production);

Gross margin of livestock production (for main production only);

Subsidies.
Prices change over time, so they are updated by means of a tax rate applied from an initial
price and referring to an initial year which can be different for each resource.
3.2.2.10. Pre- and Post-processing

Pre-computed parameters
o Administrative budget (fixed costs come from RICA database);
o Business-as-usual budget (subsides);
92
Material and methods
o Organic certification budget (related to variable costs of farm structure );
o CAP14 budget (subsides);

Derived Indexes (post-optimization)
3.2.2.11. Environmental model
In MAD the environmental component has not an active role, as it is used to calculate
environmental parameters and related indicators. Different orientations (conventional,
organic) should result in different optimal farm structures with different income and
possibly different level of carbon storage / emission. This approach can so be used to verify
the existence of a correlation between orientation and GHG13 emission reduction of net
income.
The environmental model in MAD is computed in post-optimization. The variable described
hereafter describe C14 fluxes on an annual basis, which are related to transformation
processes in vegetal and animal farm compartment, both under natural regime and
management, all being related to GHG emissions (Vitali et al., in press).
13
14

C assimilated in natural surfaces;

C assimilated in trees crops;

C assimilated in field crops;

C accumulated in woody tissue;

C in natural woody residuals;

C in trees pruning;

C in crop residuals;

C in manure;

C emissions by livestock breeding;

C potential accumulation in humus;

C maximum in humus;

C emissions from farm management.
Greenhouse gases
Carbon
93
Material and methods
3.2.3. Description of RAF model
RAF is a bio-energetic descriptive model in terms of sets of equations (or inequalities) runs
by using GAMS code and GUI (Graphical Use Interface) works under MATLAB environment
for optimization the objective function (Z) (maximization the net income for whole period
which is considered by analysis). Model equations are used as constraints in terms of energy
via convert energy crops and animal manure to biogas (energy carrier) and digestate (biofertilizer) by using anaerobic digestion (AD) technologies, agricultural growing and animal
breeding practices.
The different variables, parameters and indexes of RAF model could be distinguished in four
sets as illustrated in Fig. (3.3):

Variables and parameters in lowercase for non-optimization data (pre-optimization
input data);

Variables in uppercase for optimization (output data of optimization);

Variables in lowercase for post-optimization (calculating after optimization from
optimum data) uses as a key design elements of on-farm biogas system;

Indexes in subscript (while in GAMS they become literal values).
RAF model (Fig. 3.4) consists of 6 modules as shown below:
1- On-farm agricultural production module (from MAD model) (eqs. from 3.1 to 3.3);
2- On-farm livestock nutrition requirements module (from MAD model) (eqs. from 3.4 to
3.8);
3- On-farm energy consumption module (eqs. from 3.9 to 3.14);
4- On-farm labor requirements module (eq. 3.15 );
5- On-farm account balance module (eq. 3.16);
6- Design of on-farm biogas system module (eqs. from 3.17 to 3.54).
94
Material and methods
Fig. 3.3: Pathway of data processing in RAF model
Fig. 3.4: RAF model architecture
95
Material and methods
3.2.3.1. Indexes list of RAF model
Indexes list of RAF model can be tabulated in Table (3.3):
Table 3.3: Indexes list of RAF model
Index
15
ca  tree crop index
ce energy crop index
cg greenhouses crop index
cm market diet index
cs  field crop index
cz forage crop index
di diet nutrient index
sy system index
zo zoo index
List of index
Cherries, poplar, grapevine, olive-tree and etc.
Alfalfa, maize, sorghum and etc.
tomatoes, pepper, cucumber and etc.
alfalfa, maize, sorghum and etc.
Alfalfa, maize, sorghum, sunflower, wheat and etc.
Alfalfa, maize, sorghum and etc.
forage unit and protein
psychrophilic, mesophilic and thermophilic
Dairy cattle, non-dairy cattle, buffalos, pigs and etc.
3.2.4. On-farm agricultural production module
This module discusses, calculates and optimizes the different on-farm areas allocated to
cultivate different crops and trees (for different purpose), for realized the optimum total net
income of on-farm agricultural productive activities.
3.2.4.1. Total surface area of farm
Constraint of the total surface area of farm (sau), consists of sum of allocated surface areas
for agricultural production to cultivate different crops (for different purposes), allocated
surface areas for different facilities to serve agricultural production, livestock production
and energy (from biogas) production, surface area of set-aside and surface area of natural
surface (Vitali et al., in press), calculating according to the following equation:
𝑠𝑎𝑢
𝐺
𝑠 𝑠
𝑠𝑢
(3.1)
Where:
sau = Total surface area of farm (ha);
SAG = Allocated surface area for on-farm agricultural production (ha), SAG ≥ 0, see eq. (3.2);
SLS = Allocated surface area for on-farm livestock production (ha), SLS ≥ 0, see eq. (3.3);
sgs = Allocated surface area for on-farm biogas system (ha), see eq. (3.50);
15
User should mention in how many years the trees go at regime, plant duration and planting costs
96
Material and methods
sun = Surface area of natural surface (ha).
3.2.4.2. Allocated surface area for on-farm agricultural production
Constraint of allocated surface area for on-farm agricultural production (SAG), consists of
sum of different allocated surface areas to cultivate different crops (for different purposes,
such as greenhouses, food, forage, energy and trees) (Vitali et al., in press), calculating
according to the following equation:
𝐺
∑𝑐𝑠
𝑐𝑠
∑𝑐𝑔
𝑐𝑔
∑𝑐𝑎 𝑠𝑢𝑡𝑐𝑎 ;
𝐺 ≤ 𝑠𝑎𝑎
(3.2)
Where:
SAG = Allocated surface area for on-farm agricultural production (ha), SAG ≥ 0;
SCScs = Allocated surface area for field crops cultivation (ha), SCScs ≥ 0;
SCScg = Allocated surface area for greenhouses cultivation (ha), SCScg ≥ 0;
sutca = Allocated surface area for trees (ha);
saa = On-farm available surface arable area (ha).
3.2.4.3. Allocated surface area for on-farm livestock production
Constraint of allocated surface area for on-farm livestock production (SLS), contains
breeding corrals, milking chambers, young calves isolation corrals, pregnant animals
isolation corrals and other facilities related to on-farm livestock production (Wand and
Doris, 2011 and Eurostat, 2012), calculating according to the following equation:
∑
𝑎𝑢
(3.3)
Where:
SLS = Allocated surface area for on-farm livestock production (ha), SLS ≥ 0,
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
aluzo = Surface area required per livestock unit for different on-farm breeding and
production facilities (ha / lsu), see appendix Table (8.1).
97
Material and methods
3.2.5. On-farm livestock nutrition requirements module
Forage requirements for livestock includes forage units (fu) requirements for energetic
balance, ruminant functionality (for herbivorous), and protein requirements (pr) more
relevant for granivorous (swines). Both parameters are optimized through two separate
constraints, one to avoid minimum level of nutrition, the second to avoid any excess.
3.2.5.1. Total nutrition required for livestock
Constraint array of total nutrition required (MDD di) (from on-farm available production of
forage and purchased from market) in terms of diet nutrients (fu and cp) for livestock
feeding, based on dry matter content (Harris, 1997; Jacobs, 2002; Moran, 2005;
Department of Primary Industries, 2010; The Merck Veterinary Manual, 2010 and MLA,
2012), calculating according to the following equation:
∑
𝑧
,
34
Where:
MDDdi = Total nutrition required (from on-farm available production of forage and
purchased from market) in terms of diet nutrients for livestock feeding, based on
dry matter content (fu / year and cp / year), MDDdi ≥ 0;
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
Fdzzo,di = Nutrition required for livestock unit in terms of diet nutrients, based on dry matter
content (fu / lsu . year and cp / lsu . year), see appendix Table (8.2);
fu = Forage unit, is a forage value of 1 kg of barley (unit);
cp = Crude protein (kg).
3.2.5.2. Available nutrition for livestock from on-farm production of forage crops
Constraint array of available nutrition for livestock from on-farm production of forage crops
in terms of diet nutrients, based on dry matter content (fu and cp) (MDAdi) (Balliette, 1998;
Strohbehn and Loy, 2007 and Hall et al., 2009), calculating according to the following
equation:
∑𝑐
𝑐
𝑠𝑐
,
35
98
Material and methods
Where:
MDAdi = Available nutrition for livestock from on-farm production of forage crops in terms
of diet nutrients, based on dry matter content (fu / year and cp / year), MDA di ≥ 0;
MSZcz = Mass of forage crops (silage), based on dry matter content (ton / year), MSZ cz ≥ 0,
MSZcz ϵ MSFcz;
fdscz,di = Nutrients content of forage crops available for livestock feeding in terms of diet
nutrients, based on dry matter content (fu / ton and cp / ton), see appendix Table
(8.3);
fu = Forage unit, is a forage value of 1 kg of barley (unit);
cp = Crude protein (kg).
3.2.5.3. Nutrition purchased for livestock from market
Constraint array of nutrition purchased from market for livestock feeding in terms of diet
nutrients (fu and cp), based on dry matter content (MDP di) (Vitali et al., in press), calculating
according to the following equation:
∑𝑐𝑚
𝑐𝑚
𝑐𝑚,
36
Where:
MDPdi = Nutrition purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content (fu / year and cp / year), MDPdi ≥ 0;
MBPcm = Mass of diet feedstock purchased from market for livestock feeding, based on dry
matter content (ton / year), MBPcm ≥ 0;
fdmcm,di = Nutrients content of diet feedstock purchased from market for livestock feeding
in terms of diet nutrients, based on dry matter content (fu / ton and cp / ton), see
appendix Table (8.4).
fu = Forage unit, is a forage value of 1 kg of barley (unit);
cp = Crude protein (kg).
3.2.5.4. Minimum requirements of nutrition for livestock
Constraint array of guarantee the enough supply of nutrition for livestock, calculating
according to the following equation:
99
Material and methods
37
Where:
MDAdi = Available nutrition for livestock from on-farm production of forage crops in terms
of diet nutrients, based on dry matter content (fu / year and cp / year), MDA di ≥ 0,
see eq. (3.5);
MDPdi = Nutrition purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content (fu / year and cp / year), MDPdi ≥ 0, see eq. (3.6);
MDDdi = Total nutrition required (from on-farm available production of forage and
purchased from market) in terms of diet nutrients for livestock feeding, based on
dry matter content (fu / year and cp / year), MDDdi ≥ 0, see eq. (3.4);
fu = Forage unit, is a forage value of 1 kg of barley (unit);
cp = Crude protein (kg).
3.2.5.5. Maximum tolerance of nutrition for livestock
Constraint array of maximum tolerance of nutrition to avoid the surplus supply of nutrition,
calculating according the following equation:
≤
𝑥
38
Where:
MDAdi = Available nutrition for livestock from on-farm production of forage crops in terms
of diet nutrients, based on dry matter content (fu / year and cp / year), MDA di ≥ 0,
see eq. (3.5);
MDPdi = Nutrition purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content (fu / year and cp / year), MDPdi ≥ 0, see eq. (3.6);
fdx = Surplus tolerance factor of diet nutrients for livestock feeding = 5 % = 0.05;
MDDdi = Total nutrition required (from on-farm available production of forage and
purchased from market) in terms of diet nutrients for livestock feeding, based on
dry matter content (fu / year and cp / year), MDDdi ≥ 0, see eq. (3.4);
fu = Forage unit, is a forage value of 1 kg of barley (unit);
cp = Crude protein (kg).
100
Material and methods
3.2.6. On-farm energy consumption module
Energy inputs can be characterized as direct or indirect (embedded) energy:

Direct energy inputs are fuel and lubricants used in feed processing and for energizing
of delivery machinery. The electrical energy is used for milking, milk cooling, water
heating and pumping, lighting, ventilation, air heating, electrical fencing, manure
handling, office and personnel working environment and etc. Conventional electricity
consumption represents around 25 % of the fossil fuels consumed at the dairy farms
and about 60 % of this energy comes from diesel fuel (Bulletin of the International
Dairy Federation, 2010).

Indirect energy is embedded in the products used on the farm. Indirect energy inputs
are:
o Animal Feeding:
Depending on the livestock diet the impact of the feed production can vary due to the
process to produce concentrates is more energy consuming than to produce fodder
(Barnett and Russell, 2010). Pasture requires the lowest energy demand (0.84 MJ
(0.23 kWh) / kg of dry matter (DM)) due to machines are used only for cultivation and
fertilization operations.
o Energy of Building:
There are three ways to calculate the indirect energy input of buildings:
1- Estimation of indirect energy input by use of published calculation results of similar
building types (e.g. on square meter and life-span basis). The advantage is easy and
fast calculation, the disadvantage - possible lack of precision if no publications for
adequate buildings are available and / or calculations do not discriminate between
construction and operating energy input.
2- Calculation of the indirect energy input of a whole building based on construction
elements ready-calculated on square meter or running meter basis. The advantage is
that during the planning phase of a new building alternative construction solutions
101
Material and methods
can be compared relatively fast. This approach is not very suitable for existing
agricultural buildings, if the construction elements can only be identified by
destructive investigations and / or if the building is too old to fit the construction
elements and materials presently used. Due to there are many ways to assemble a
construction parts from different materials a profound data base of construction
elements is a precondition.
3- Calculation of a whole building based on construction materials and real input used.
This can easily be done on buildings under construction following up the material or
book-keeping data. This is nearly impossible when the book-keeping material of the
erection phase is not available anymore or contains insufficient data. Average indirect
energy input for farm buildings (80 years) by Gaillard et al. (1997) is 153 MJ / m2 .
year.
o Energy of machinery:
Indirect energy input for machinery depends on the intensity of use, the date and
location of manufacture and the span life of machinery. Machines are normally at the
end of their life time recycled and only the manufacturing and maintenance energy is
used for agricultural production.
3.2.6.1. On-farm thermal energy consumed for greenhouses warming
Constraint of on-farm thermal energy consumed for greenhouses warming (ETG), in Italy
there are four main climate areas (south, middle, north and west coast) for greenhouses
production (Ross, 2001; NSW Government, 2010 and Campiotti et al., 2011), calculating
according to the following equation:
𝐸 𝐺
∑𝑐𝑔
𝑐𝑔
𝑒𝑡ℎ
25
39
Where:
ETG = On-farm thermal energy consumed for greenhouses warming (kWhth / year), ETG ≥ 0;
SCScg = Allocated surface area for greenhouses cultivation (ha), SCScg ≥ 0;
eth = Thermal energy required for greenhouses warming (kWhth / ha . year), see appendix
Table (8.5);
102
Material and methods
1.25 = The heating efficiency is 80 % for biogas heating system (1.25 = 100 / 80).
3.2.6.2. On-farm thermal energy consumed for livestock production
Constraint of on-farm thermal energy consumed for livestock production (livestock corrals
warming, hot water for washing milking equipment, sterilization and etc.) (ETD) (Hyper
Physics, 2000; Hörndahl, 2008 and The Engineering Tool Box, 2010), calculating according
to the following equation:
𝐸
∑
𝑒𝑡
25
3 0
Where:
ETD = On-farm thermal energy consumed for livestock production (kWhth / year), ETD ≥ 0;
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
etlzo = Thermal energy required for livestock unit (kWhth / lsu . year), see appendix Table
(8.6);
1.25 = The heating efficiency is 80 % for biogas heating system (1.25 = 100 / 80).
3.2.6.3. Total on-farm thermal energy consumed
Constraint of total on-farm thermal energy consumed (ETC), refers to total thermal energy
consumption for different on-farm facilities (greenhouses warming, livestock corrals
warming, hot water for washing milking equipment, sterilization and etc.), calculating
according to the following equation:
𝐸
𝐸 𝐺
𝐸
3
Where:
ETC = Total on-farm thermal energy consumed (kWhth / year), ETC ≥ 0;
ETG = On-farm thermal energy consumed for greenhouses warming (kWhth / year), ETG ≥ 0,
see eq. (3.9);
ETD = On-farm thermal energy consumed for livestock production (kWhth / year), ETD ≥ 0,
see eq. (3.10).
103
Material and methods
3.2.6.4. On-farm electrical energy consumed for greenhouses
Constraint of on-farm electrical energy consumed for greenhouses (EEG), refers to electrical
energy consumption for different greenhouses equipment (lighting, heating, cooling,
motors, pumps, fans for ventilation and etc.), in Italy there are four main climate areas
(south, middle, north and west coast) for greenhouses production (EC&M, 2002; für
Mikrofonaufnahmetechnik und Tonstudiotechnik, 2002; Worldwide Power Products, 2008;
Campiotti et al., 2011; All About Circuits, 2012 and Campiotti et al., 2012), calculating
according to the following equation:
𝐸𝐸𝐺
∑𝑐𝑔
𝑐𝑔
𝑒𝑒ℎ
3 2
Where:
EEG = On-farm electrical energy consumed for greenhouses (kWhel / year), EEG ≥ 0;
SCScg = Allocated surface area for greenhouses cultivation (ha), SCScg ≥ 0;
eeh = Electrical energy required for greenhouses (kWhel / ha . year), see appendix Table
(8.7).
3.2.6.5. On-farm electrical energy consumed for livestock production
Constraint of on-farm electrical energy consumed for livestock production (EED), refers to
electrical energy consumption for different livestock production equipment (lighting,
heating, cooling, milking equipment, motors, pumps, fans for ventilation and etc.) (EC&M,
2002; für Mikrofonaufnahmetechnik und Tonstudiotechnik, 2002; Commercial Energy
Advisor, 2008; Worldwide Power Products, 2008 and All About Circuits, 2012), calculating
according to the following equation:
𝐸𝐸
∑
𝑒𝑒
3 3
Where:
EED = On-farm electrical energy consumed for livestock production (kWhel / year), EED ≥ 0;
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
eelzo = Electrical energy required for livestock unit (kWhel / lsu . year), see appendix Table
(8.8).
104
Material and methods
3.2.6.6. Total on-farm electrical energy consumed
Constraint of total on-farm electrical energy consumed (EEC), refers to total electrical
energy consumption for different on-farm equipment (lighting, heating, cooling, milking
equipment, motors, pumps, fans for ventilation and etc.), calculating according to the
following equation:
𝐸𝐸
𝐸𝐸𝐺
𝐸𝐸
3 4
Where:
EEC = Total on-farm electrical energy consumed (kWhel / year), EEC ≥ 0;
EEG = On-farm electrical energy consumed for greenhouses (kWhel / year), EEG ≥ 0, see eq.
(3.12);
EED = On-farm electrical energy consumed for livestock production (kWhel / year), EED ≥ 0,
see eq. (3.13).
3.2.7. On-farm labor requirements module
3.2.7.1. Total number of labor required for operate on-farm biogas system
Constraint of total number of workers required for operating and maintenance of on-farm
biogas system (LGS) (Lovrenčec, 2010), calculating according to the following equation:
𝐺
𝐸𝐸
𝑟𝑒
3 5
Where:
LGS = Total number of workers required for operating and maintenance of on-farm biogas
system (worker / year), LGS ≥ 0;
EEA = Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year), EEA ≥ 0, see eq. (3.53);
lre = Number of workers required for operating and maintenance of biogas system in terms
of workers required for produced electrical energy unit (5-7 worker / kWhel = 1 worker /
2 GWhel), see appendix Table (8.9).
105
Material and methods
3.2.8. On-farm account balance module
3.2.8.1. Total net income of on-farm biogas system in year t
Constraint of total net income of on-farm biogas production in year t, based on electrical
energy production from on-farm CHP unit (VGC), (Karellas et al., 2010; Ragazzoni, 2011 and
Vitali et al., in press) calculating according to the following equation:
𝐺
𝐸𝐸
𝑝𝑒
− 𝑣𝑐𝑒
−
𝑐
𝑒𝑐𝑝
3 6
Where:
VGC = Total net income of on-farm biogas production in year t, based on electrical energy
production from on-farm CHP unit (euro / year), VGC ≥ 0;
EEA = Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year), EEA ≥ 0, see eq. (3.53);
pem = Market price of electrical energy in year t (0.25 euro / kWhel generated from CHP
unit);
vce = Variable costs of biogas system in year t, based on electrical energy generated from onfarm CHP unit (0.04 euro / kWhel generated from CHP unit);
fcg = Fixed costs of biogas system in year t, based on electrical capacity of on-farm CHP unit
(500 euro / kWhel . year of electrical CHP unit capacity);
ecp = Electrical capacity of on-farm CHP unit of biogas (kWhel).
3.2.9. Design of on-farm biogas system module
This module (Fig. 3.5) discusses, calculates and optimize the different design
criteria
(variables) of on-farm biogas system uses biomass (co-digestion feedstock) in terms of
quantities of energy crops and animal manure slurry available for biogas production by
biochemical conversion technologies and use the produced biogas as source of energy
(thermal and electrical) for meets the different on-farm energy requirements, in order to
achieve on-farm self-sufficiency of energy, as a step to achieving the integrated agricultural
sustainability.
106
Material and methods
Fig. 3.5: Main components of on-farm biogas system, using silage and manure feedstock
107
Material and methods
Section I: Calculating constraints and dimensioning variables for on-farm biogas system
design
3.2.9.1. Total mass of on-farm fresh silage available for livestock feeding and biogas
production
Dimensioning variable of total mass of on-farm fresh silage available for livestock feeding
and biogas production, produced from different on-farm crops (mfs), due to the seasonal
production of fresh silage, it needs to storage in bunker silo to ensure continuous supply of
silage for livestock feeding and biogas production throughout the year (default storage
period for silage is 6 months or defined by user) (Kaiser et al., 2004 and Mickan, 2006),
calculating according to the following equation:
𝑠
∑𝑐
𝐹𝑐
∑𝑐𝑒
𝐺𝑐𝑒
𝑠𝑝𝑠
3 7
Where:
mfs = Total mass of on-farm fresh silage (refers to storage capacity of bunker silo for 6
months as default storage period) available for livestock feeding and biogas
production (ton);
MSFcz = Mass of fresh silage from different on-farm crops available for livestock feeding
(contains TS from 30 to 40 % and MC from 60 to 70 %) (ton / year), MSFcz ϵ mfs, see
appendix Table (8.10);
MSGce = Mass of fresh silage from different on-farm crops available for biogas production
(contains TS from 30 to 40 % and MC from 60 to 70 %) (ton / year), MSGce ϵ mfs,
see appendix Table (8.10);
sps = Default storage period of silage (0.5 year).
3.2.9.2. Mass of on-farm air-dried silage available for biogas production
Constraint array of mass of air-dried silage available for biogas production, produced from
different on-farm energy crops (MDGce) (Kaiser et al., 2004 and Mickan, 2006), calculating
according to the following equation:
108
Material and methods
𝑠
𝑐𝑒
𝐺𝑐𝑒
𝑠
3 8
Where:
MDGce = Mass of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (ton / year), MDGce ≥ 0, MDGce ϵ MSGce;
MSGce = Mass of fresh silage from different on-farm crops available for biogas production
(contains TS from 30 to 40 % and MC from 60 to 70 %) (ton / year), MSGce ≥ 0, see
eqs. (3.17);
dds = Density of air-dried silage (contains TS from 70 to 90 % and MC from 10 to 30 %) (0.26
ton / m³) (1 ton of air-dried silage = 3.85 m3, so 1 m3 = 0.26 ton);
dfs = Density of fresh silage (contains TS from 30 to 45 % and MC from 55 to 70 %) (0.6 ton /
m³).
3.2.9.3. Quantity of on-farm air-dried silage available for biogas production
Dimensioning variables array of quantity of on-farm air-dried silage available for biogas
production, produced from on-farm energy crops (qdgce) (Kaiser et al., 2004 and Mickan,
2006), calculating according to the following equation:
𝑞
𝑐𝑒
𝑐𝑒
𝑠
3 9
Where:
qdgce = Quantity of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (m3 / year), qdgce ϵ MSGce, see eq. (3.17);
MDGce = Mass of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (ton / year), see eq. (3.18);
dds = Density of air-dried silage (contains TS from 70 to 90 % and MC from 10 to 30 %) (0.26
ton / m³) (1 ton of air-dried silage = 3.85 m3, so 1 m3 = 0.26 ton).
3.2.9.4. Mass of on-farm manure slurry available for biogas production
Constraint array of mass of on-farm manure slurry produced from livestock and available for
biogas production (MMSzo), refers to the mass of livestock excrements in terms of manure
slurry (contains TS from 8 to 12 % and MC from 88 to 92 %) (Landry et al., 2002; Arora and
109
Material and methods
Licht, 2004; Miner et al., 2005; Ohio State University Extension, 2006 and Biogas Training
Center, 2011), calculating according to the following equation:
𝑎𝑚
𝑠𝑚𝑒
3 20
Where:
MMSzo = Mass of on-farm manure slurry available for biogas production (contains TS from 8
to 12 % and MC from 88 to 92 %) (ton / year), MMSzo ≥ 0;
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
almzo = Average live mass of livestock unit (kg of lsu mass / lsu), see appendix Table (8.11);
smezo = Average specific mass of excrements (kg of manure slurry / kg of lsu mass . day), see
appendix Table (8.11);
365 = Number of days per year (day / year);
1000 = Conversion factor from kg to ton (kg / ton).
Observation:
On-farm biogas production system needs to integrate with manure slurry collection system
in livestock corrals (such as flushed or scraped free-stall barns and dry-lots) and store the
collected manure slurry in tank or lagoon. On the other hand use the straw as a manure bed
(for absorption the animal urine) in livestock corrals is not allowed in case of applying onfarm biogas production and manure slurry collection systems (due to the high C / N ratio of
straw it is not suitable for anaerobic digestion) and instead of use the manure bed as onfarm organic fertilizer for soil could be use the digestate produced from anaerobic digestion
of silage and manure slurry as on-farm bio-fertilizer rich with soil nutrients.
3.2.9.5. Mass of on-farm air-dried manure available for biogas production
Constraint array of mass of on-farm air-dried manure available for biogas production
(MDMzo) (Landry et al., 2002; Arora and Licht, 2004; Miner et al., 2005 and Ecochem,
2011), calculating according to the following equation:
110
Material and methods
𝑐
32
Where:
MDMzo = Mass of on-farm air-dried manure available for biogas production (ton / year),
MDMzo ≥ 0, MDMzo ϵ MMSzo;
MMSzo = Mass of on-farm manure slurry available for biogas production (contains TS from 8
to 12 % and MC from 88 to 92 %) (ton / year), MMSzo ≥ 0, see eq. (3.20);
cfm = The conversion factor (in terms of mass) from manure slurry to air-dried manure
(contains 85 % of TS content and 15 % of MC) = 12 %.
3.2.9.6. Quantity of on-farm manure slurry available for biogas production
Dimensioning variables array of quantity of on-farm manure slurry available for biogas
production (qmszo) (Landry et al., 2002; Arora and Licht, 2004; Miner et al., 2005; Ohio
State University Extension, 2006 and Ecochem, 2011), calculating according to the
following equation:
𝑞 𝑠
𝑚𝑠
3 22
Where:
qmszo = Quantity of on-farm manure slurry available for biogas production (contains TS from
8 to 12 % and MC from 88 to 92 %) (m3 / year);
MMSzo = Mass of on-farm manure slurry available for biogas production (contains TS from 8
to 12 % and MC from 88 to 92 %) (ton / year), see eq. (3.20);
dms = Density of manure slurry (contains TS from 8 to 12 % and MC from 88 to 92 %) (1 ton
/ m3).
3.2.9.7. Total mass of on-farm feedstock available for biogas production
Dimensioning variable of total mass of on-farm feedstock available for biogas production
(mfg), refers to the sum of mass of on-farm air-dried silage available for biogas production
and mass of on-farm manure slurry available for biogas production, calculating according to
the following equation:
111
Material and methods
∑𝑐𝑒
𝐺𝑐𝑒
∑
3 23
Where:
mfg = Total mass of on-farm feedstock available for biogas production (ton / year);
MDGce = Mass of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (ton / year), see eq. (3.18);
MMSzo = Mass of on-farm manure slurry available for biogas production (contains TS from 8
to 12 % and MC from 88 to 92 %) (ton / year), see eq. (3.20).
3.2.9.8. Total quantity of on-farm feedstock available for biogas production
Dimensioning variable of total quantity of on-farm feedstock available for biogas production
(qfg), refers to the sum of quantity of on-farm air-dried silage available for biogas
production and quantity of on-farm manure slurry available for biogas production, according
to the following equation:
𝑞
∑𝑐𝑒 𝑞
𝑐𝑒
∑ 𝑞 𝑠
3 24
Where:
qfg = Total quantity of on-farm feedstock available for biogas production (m3 / year);
qdgce = Quantity of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (m3 / year), see eq. (3.19);
qmszo = Quantity of on-farm manure slurry available for biogas production (contains TS from
8 to 12 % and MC from 88 to 92 %) (m3 / year), see eq. (3.22);
The best volumetric mixture ratio of ∑ceqdgce : ∑zoqmszo is 3 m3 : 1 m3 respectively (0.78 ton
of air-dried silage : 1 ton of manure slurry) for obtain the maximum biogas yield in codigestion process (Saev and Simeonov, 2009 and Xie, 2011).
3.2.9.9. Concentration of total solids at the Inlet of mixing unit
Service variable of concentration of total solids at the Inlet of mixing unit (ism), in case of codigestion (using mixed substrate consists of air-dried silage and manure slurry), there is a
need to calculating the concentration of TS for mixed substrate at the Inlet of mixing unit (Al
Seadi, 2001; Amours and Savoie, 2005; Mickan, 2006; Al Seadi et al., 2008; Gottstein,
2010; Biogas a Renewable Biofuel, 2011; Biomass Energy Center, 2011; Extension, 2011;
112
Material and methods
Delaval Global, 2012; Hollis, 2012; KWS, 2012 and The Dow Chemical Company, 2012),
according to the following equation:
𝑠
∑𝑐𝑒
𝑔𝑐𝑒
𝑠𝑠𝑐𝑒
∑
𝑚𝑠
𝑠𝑚
𝑚 𝑔
00
3 25
Where:
ism = Concentration of TS (dry matter content) at the Inlet of mixing unit before dilution
with water for mixed substrate consists of air-dried silage and manure slurry on the
basis of wet-mass (%);
qdgce = Quantity of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (m3 / year), see eq. (3.19);
tssce = Mass of TS for air-dried silage (ton / m3), see appendix Table (8.12);
qmszo = Quantity of on-farm manure slurry available for biogas production (contains TS from
8 to 12 % and MC from 88 to 92 %) (m3 / year), see eq. (3.22);
tsmzo = Mass of TS for manure slurry (ton / m3), see appendix Table (8.12);
mfg = Total mass of on-farm feedstock available for biogas production (ton / year), see eq.
(3.23).
3.2.9.10. Dilution ratio of substrate required for biogas production
Service variable of dilution ratio of substrate required for biogas production (drg), refers to
the ratio of concentration of TS in diluted substrate at the outlet of mixing unit to
concentration of TS in substrate before dilution at the Inlet of mixing unit (What Size
Digester Do I Need, 1996; An and Preston, 1999; Kossmann et al., 1999; Ciborowski, 2001;
Dennis and Burke, 2001; United States Department of Agriculture, 2007; Al Seadi et al.,
2008; Balasubramaniyam et al., 2008; Westerma et al., 2008; Gottstein, 2010; Babaee and
Shayegan, 2011; Biogas a Renewable Biofuel, 2011; Biomass Energy Center, 2011;
Extension, 2011; Delaval Global, 2012; Hollis, 2012; KWS, 2012 and The Dow Chemical
Company, 2012), calculating according to the following equation:
113
Material and methods
𝑟
𝑠
𝑠𝑚
3 26
00
Where:
drg = Dilution ratio of substrate required for biogas production (%);
ots = Concentration of TS (dry matter content) in diluted substrate at the outlet of mixing
unit, on the basis of wet-mass (8 %);
ism = Concentration of TS (dry matter content) at the Inlet of mixing unit before dilution
with water for mixed substrate consists of air-dried silage and manure slurry on the
basis of wet-mass (%), see eq. (3.25);
Observation:
its = Concentration of TS (dry matter content) in unmixed substrate (air-dried silage or
manure slurry only) before dilution at the Inlet of mixing unit, on the basis of wet-mass
(%), see appendix Table (8.13);
In case of use one type of feedstock (use silage or manure slurry only) can use (its), but in
case of co-digestion (use mixed substrate of silage and manure slurry) can use (ism) instead
of (its), see eq. (3.25).
3.2.9.11. Total Quantity of water required for substrate dilution
Dimensioning variable of total quantity of water required for substrate dilution (qwd) (Al
Seadi et al., 2008; Gottstein, 2010; Biogas a Renewable Biofuel, 2011; Biomass Energy
Center, 2011; Extension, 2011; Delaval Global, 2012; Hollis, 2012; KWS, 2012 and The Dow
Chemical Company, 2012), calculating according to the following equation:
𝑞𝑤
𝑞
𝑔
−
3 27
Where:
qwd = Total quantity of water required for substrate dilution (m 3 / year) = (ton / year);
qfg = Total quantity of on-farm feedstock available for biogas production (m3 / year), see eq.
(3.24);
drg = Dilution ratio of substrate required for biogas production (%), see eq. (3.26).
114
Material and methods
3.2.9.12. Total quantity of diluted substrate input to digester
Dimensioning variable of total quantity of diluted substrate input to digester (qsd), refers to
the sum of substrates quantities (air-dried silage and manure slurry available for biogas
production) and water quantities required for diluted this substrates (for realize the dilution
ratio required for biogas production), calculating according to the following equation:
𝑞𝑠
𝑞
3 28
𝑞𝑤
Where:
qsd = Total quantity of diluted substrate input to digester (m 3 / year);
qfg = Total quantity of on-farm feedstock available for biogas production (m3 / year), see eq.
(3.24);
qwd = Total quantity of water required for substrate dilution (m 3 / year) = (ton / year), see
eq. (3.27).
3.2.9.13. Biogas yield generated, based on biogas yield per mass unit of fresh silage from
energy crops
Constraint array of biogas yield generated, based on biogas yield per mass unit of fresh
silage from energy crops (GCUce) (Banks, 2009; Centre and Redman, 2010; Knitter et al.,
2010; NNFCC, 2010; Dimpl and Blunck, 2011; Hopwood, 2011 and Shokri, 2011), calculating
according to the following equation:
𝐺
𝑐𝑒
𝐺𝑐𝑒
𝑦𝑐𝑐𝑒
3 29
Where:
GCUce = Biogas yield generated, based on biogas yield per mass unit of fresh silage from
energy crops (m3 / year), GCUce ≥ 0;
MSGce = Mass of fresh silage from different on-farm crops available for biogas production
(contains TS from 30 to 40 % and MC from 60 to 70 %) (ton / year), MSGce ≥ 0,
MSGce ϵ mfs, see eq. (3.17);
gycce = Biogas yield generated per mass unit of fresh silage from energy crops (m 3 / ton), see
appendix Table (8.14).
115
Material and methods
3.2.9.14. Biogas yield generated, based on biogas yield per livestock unit
Constraint array of biogas yield generated, based on biogas yield per livestock unit (GLU zo)
(British Biogen, 2000; Anaerobic Digestion, 2010; Knitter et al., 2010; NNFCC, 2010;
Timmerman and Rulkens, 2010; Irish Farmers Journal, 2011 and Biogas Technologies,
2012), calculating according to the following equation:
𝐺
3 30
𝑦
Where:
GLUzo = Biogas yield generated, based on biogas yield per livestock unit (m 3 / year), GLUzo ≥
0;
LSUzo = Number of livestock units (lsu), LSUzo ≥ 0;
gylzo = Biogas yield generated from livestock unit (m3/ lsu . year), see appendix Table (8.15).
3.2.9.15. Total on-farm biogas yield
Constraint of total on-farm biogas yield (GFA), refers to the sum of biogas yield generated,
based on biogas yield per mass unit of fresh silage from energy crops and biogas yield
generated, based on biogas yield per livestock unit, calculating according to the following
equation:
𝐺𝐹
∑𝑐𝑒 𝐺
𝑐𝑒
∑ 𝐺
33
Where:
GFA = Total on-farm biogas yield (m3 / year), GFA ≥ 0;
GCUce = Biogas yield generated, based on biogas yield per mass unit of fresh silage from
energy crops (m3 / year), GCUce ≥ 0, see eq. (3.29);
GLUzo = Biogas yield generated, based on biogas yield per livestock unit (m 3 / year), GLUzo ≥
0, see eq. (3.30).
3.2.9.16. Total Mass of on-farm air-dried digestate after dewatering
Constraint of total mass of on-farm air-dried digestate after digestion process and
dewatering (MDI) (Lehtomäki, 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi
et al., 2008; Kirchmeyr et al., 2009; Lukehurst et al., 2010 and Frandsen, 2011), calculating
116
Material and methods
by subtract the mass of biogas produced from the mass of air-dried feedstock (silage and
manure) used for biogas production, according to the following equation:
𝐼
∑𝑐𝑒
𝐺𝑐𝑒 − 𝐺
𝑎
𝑐𝑒
∑
− 𝐺
𝑎
3 32
Where:
MDI = Total Mass of on-farm air-dried digestate after dewatering (ton / year), MDI ≥ 0;
MDGce = Mass of on-farm air-dried silage available for biogas production (contains TS from
70 to 90 % and MC from 10 to 30 %) (ton / year), MDGce ≥ 0, see eq. (3.18);
GCUce = Biogas yield generated, based on biogas yield per mass unit of fresh silage from
energy crops (m3 / year), GCUce ≥ 0, see eq. (3.29);
dga = Density of biogas (0.001265 ton /m3);
MDMzo = Mass of on-farm air-dried manure available for biogas production (ton / year),
MDMzo ≥ 0 see eq. (3.21);
GLUzo = Biogas yield generated, based on biogas yield per livestock unit (m 3 / year), GLUzo ≥
0, see eq. (3.30);
Section II: Calculating of post-optimization values (key design elements16 of on-farm
biogas system)
3.2.9.17. Inner-surface area of bunker silo
Post-optimization calculating of inner-surface area of bunker silo (sbs), refers to the surface
area required for storage on-farm production of fresh silage as a feedstock for livestock
feeding and biogas production for specific storage period (default storage period for silage is
6 months or defined by user) (Huhnke, 1990; Electrigaz Technologies Inc., 2007; Al Seadi et
al., 2008 and Kirchmeyr et al., 2009), calculating according to the following equation:
𝑠 𝑠
𝑚 𝑠
𝑠
𝑠
3 33
Where:
sbs = Inner-surface area of bunker silo for storage fresh silage for livestock feeding and
biogas production (ha);
16
Some references refer to key design elements as “design criteria”
117
Material and methods
mfs = Total mass of on-farm fresh silage (refers to storage capacity of bunker silo for 6
months as default storage period) available for livestock feeding and biogas
production (ton), see eq. (3.17);
dfs = Density of fresh silage stored in the bunker silo (contains TS from 30 to 40 % and MC
from 60 to 70 %) (0.6 ton / m³);
hbs = Default height of bunker silo (3 m);
10000 = Surface area of hectare (m2 / ha).
3.2.9.18. Inner-volume of manure slurry tank or lagoon
Post-optimization calculating of inner-volume of manure slurry tank or lagoon (with
cylindrical, square or rectangular shape) (vmt), refers to the capacity of manure slurry tank
or lagoon required to storage the manure slurry from few days to few weeks for biogas
production (Landry et al., 2002; Arora and Licht, 2004; Miner et al., 2005; Ohio State
University Extension, 2006 and Biogas Training Center, 2011), calculating according to the
following equation:
𝑣 𝑡
∑
𝑠 𝑚
𝑚𝑠
3 34
Where:
vmt = Inner-volume of manure slurry tank or lagoon (with cylindrical, square or rectangular
shape) (m3);
MMSzo = Mass of on-farm manure slurry available for biogas production (contains TS from 8
to 12 % and MC from 88 to 92 %) (ton / year), see eq. (3.20);
spm = Default storage period of manure slurry (40 days);
1.15 = Factor of operational inner-volume of manure slurry tank or lagoon (operational
inner-volume should be more than 15 % of theoretical inner-volume);
dms = Density of manure slurry (contains TS from 8 to 12 % and MC from 88 to 92 %) (1 ton
/ m3);
365 = Number of days per year (day / year).
118
Material and methods
3.2.9.19. Inner-surface area of manure slurry tank or lagoon
Post-optimization calculating of inner-surface area of manure slurry tank or lagoon (with
cylindrical, square or rectangular shape) (smt) (Landry et al., 2002; Arora and Licht, 2004;
Miner et al., 2005; Ohio State University Extension, 2006 and Biogas Training Center,
2011), calculating by dividing the inner-volume of manure slurry tank or lagoon, over the
height of manure slurry tank or depth of lagoon, according to the following equation:
𝑠 𝑡
𝑚
𝑚
3 35
Where:
smt = Inner-surface area of manure slurry tank or lagoon (with cylindrical, square or
rectangular shape) (ha);
vmt = Inner-volume of manure slurry tank or lagoon (with cylindrical, square or rectangular
shape) (m3), see eq. (3.34);
hmt = Default height of manure slurry tank or depth of lagoon (4 m);
10000 = Surface area of hectare (m2 / ha).
3.2.9.20. Discharge of pumping and mixing unit
Post-optimization calculating of discharge of pumping and mixing unit (dmu), refers to the
daily quantity of diluted substrate input to digester (Institut für Energetik und Umwelt et
al., 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007 and Al Seadi et al., 2008), calculating
according to the following equation:
𝑢
𝑠
3 36
Where:
dmu = Discharge of pumping and mixing unit (m3 / day);
qsd = Total quantity of diluted substrate input to digester (m 3 / year), see eq. (3.28);
1.15 = Factor of operational discharge of pumping and mixing unit (operational discharge
should be more than 15 % of theoretical discharge);
365 = Number of days per year (day / year).
119
Material and methods
3.2.9.21. Inner-volume of digestion chamber
Post-optimization calculating of inner-volume of digestion chamber (with cylindrical shape)
(vdc), refers to the capacity of digestion chamber (inside the digester) required to digest
diluted substrate input to digester during the hydraulic retention time (hrt depending on
temperature of digestion process) (Sasse, 1988; Werner et al., 1989; Biogas Process for
Sustainable Development, 1992; Kossmann et al., 1999; Wellinger, 1999; Dennis and
Burke, 2001; Monnet, 2003; Al Seadi et al., 2008; TATEDO, 2009 and Biogas Training
Center, 2011), calculating according to the following equation:
𝑣 𝑐
𝑢 ℎ𝑟𝑡𝑠
3 37
Where:
vdc = Inner-volume of digestion chamber (with cylindrical shape) (m3);
dmu = Discharge of pumping and mixing unit (m3 / day), see eq. (3.36);
hrtsy = Hydraulic retention time, retention time is defined by the user or use default (40 days
for mesophilic system), see appendix Table (8.16).
3.2.9.22. Inner-surface area of digester
Post-optimization calculating of Inner-surface area of digester (with cylindrical shape) (sdi)
(Sasse, 1988; Werner et al., 1989; Biogas Process for Sustainable Development, 1992;
Kossmann et al., 1999; Wellinger, 1999; Dennis and Burke, 2001; Monnet, 2003; Al Seadi
et al., 2008; TATEDO, 2009 and Biogas Training Center, 2011), calculating by dividing the
inner-volume of digestion chamber over the digestion chamber height, according to the
following equation:
𝑠
𝑐
𝑐
3 38
Where:
sdi = Inner-surface area of digester (with cylindrical shape) (ha);
vdc = Inner-volume of digestion chamber (with cylindrical shape) (m3), see eq. (3.37);
hdc = Default height of digestion chamber (4 m);
10000 = Surface area of hectare (m2 / ha).
120
Material and methods
3.2.9.23. Inner-volume of biogas storage chamber (biogas tight membranes)
Post-optimization calculating of inner-volume of biogas storage chamber (vgs), refers to the
capacity of biogas storage chamber required to storage the produced biogas and established
on the top of digestion chamber (low-pressure biogas tight membranes with dome shape).
Usually, capacity from one to two days is recommended for use the biogas tight membranes
(Kossmann et al., 1999; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi
et al., 2008; TATEDO, 2009; SATTLER AG & Ceno Membrane Technology GmbH, 2010 and
ZORG, 2012), calculating according to the following equation:
𝑣 𝑠
𝑠
𝑠
3 39
Where:
vgs = Inner-volume of biogas storage chamber (low-pressure biogas tight membranes with
dome shape) (m3);
sdi = Inner-surface area of digester (with cylindrical shape) (ha), see eq. (3.38);
dst = Distance between the static liquid surface in the digestion chamber and the top of
biogas storage chamber (low-pressure biogas tight membranes with dome shape) (3
m).
10000 = Surface area of hectare (m2 / ha);
1.15 = Factor of operational inner-volume of biogas chamber (operational inner-volume
should be more than 15 % of theoretical inner-volume).
3.2.9.24. Total inner-volume of digester
Post-optimization calculating of total inner-volume of digester (vdi), refers to sum of the
inner-volume of digestion chamber (with cylindrical shape) and inner-volume of biogas
storage chamber (low-pressure biogas tight membranes with dome shape) (Dennis and
Burke, 2001; Monnet, 2003; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al
Seadi et al., 2008; TATEDO, 2009; SATTLER AG & Ceno Membrane Technology GmbH,
2010; Biogas Training Center, 2011 and ZORG, 2012), calculating according to the following
equation:
121
Material and methods
𝑣
𝑣 𝑐
𝑣 𝑠
3 40
Where:
vdi = Total inner-volume of digester (m3);
vdc = Inner-volume of digestion chamber (with cylindrical shape) (m3), see eq. (3.37);
vgs = Inner-volume of biogas storage chamber (low-pressure biogas tight membranes with
dome shape) (m3), see eq. (3.39).
3.2.9.25. Specific gas yield
Post-optimization calculating of specific gas yield (sgy, service variable), refers to the daily
volume of biogas produced from each cubic meter of total inner-volume of digester. sgy
ranges from 0.2 under psychrophilic conditions to 0.6 under thermophilic conditions
(Werner et al., 1989; Biogas Process for Sustainable Development, 1992; Rosillo-Calle et
al., 2007 and Nels, 2011), calculating according to the following equation:
𝑠 𝑦
𝐹𝐴
34
Where:
sgy = Specific gas yield (m3 of biogas / m3 of total inner-volume of digester. day), see
appendix Table (8.17);
GFA = Total on-farm biogas yield (m3 / year), see eq. (3.31);
vdi = Total inner-volume of digester (m3), see eq. (3.40);
365 = Number of days per year (day / year).
3.2.9.26. Digestion chamber loading, based on the daily mass of total solids input to
digestion chamber
Post-optimization calculating of digestion chamber loading, based on the daily mass of TS
input to digestion chamber (lts, service variable), refers to the daily mass of TS per each
cubic meter of inner-volume of digestion chamber (What Size Digester Do I Need, 1996; An
and Preston, 1999; Kossmann et al., 1999; Ciborowski, 2001; Dennis and Burke, 2001;
United States Department of Agriculture, 2007; Al Seadi et al., 2008; Balasubramaniyam et
122
Material and methods
al., 2008; Westerma et al., 2008 and Babaee and Shayegan, 2011), calculating according to
the following equation:
𝑡𝑠
𝑚 𝑔
𝑠
𝑐
3 42
Where:
lts = Digestion chamber loading, based on the daily mass of TS input to digestion chamber
(kg of TS / m3 of inner-volume of digestion chamber . day);
mfg = Total mass of on-farm feedstock available for biogas production (ton / year), see eq.
(3.23);
qwd = Total Quantity of water required for substrate dilution (m 3 / year) = (ton / year), see
eq. (3.27);
ots = Concentration of TS (dry matter content) in diluted substrate at the outlet of mixing
unit, on the basis of wet-mass (8 %);
vdc = Inner-volume of digestion chamber (with cylindrical shape) (m3), see eq. (3.37);
1000 = Conversion factor from ton to kg (kg / ton);
365 = Number of days per year (day / year).
Observation:
In general better digestion can be achieved at lower loadings. Thermophilic reactors appear
to achieve greater conversions at high loadings while mesophilic reactors appear to achieve
greater conversions at lower loadings.
3.2.9.27. Digestion chamber loading, based on the daily mass of volatile solids input to
digestion chamber
Post-optimization calculating of digestion chamber loading, based on the daily mass of VS
input to digestion chamber (lvs, service variable), refers to the daily mass of VS per each
cubic meter of inner-volume of digestion chamber (Kossmann et al., 1999; Bio Fuel Cells
Concepts for Local Energy, 2000; Ciborowski, 2001; Dennis and Burke, 2001;
Balasubramaniyam et al., 2008; Massart et al., 2008; Westerma et al., 2008; Babaee and
Shayegan, 2011), calculating according to the following equation:
123
Material and methods
𝑣𝑠
𝑡𝑠 𝑐𝑣𝑠
3 43
Where:
lvs = Digestion chamber loading, based on the daily mass of VS input to digestion chamber
(kg of VS / m3 of inner-volume of digestion chamber . day);
lts = Digestion chamber loading, based on the daily mass of TS input to digestion chamber
(kg of TS / m3 of inner-volume of digestion chamber . day), see eq. (3.42);
cvs = Concentration of VS in TS content of substrate, on the basis of wet-mass (85 %).
Observation:

Completely mixed mesophilic anaerobic digester at an organic loading rate of 1.0 kg /
m3 of inner-volume of digestion chamber . day, achieved a peak VS conversion to gas
of 64 %;

Operated completely mixed thermophilic digesters at loadings of 6.5 to 10.78 kg / m3
of inner-volume of digestion chamber . day, achieved 50 % VS conversion to gas;

In typical anaerobic digester the digestion chamber loading is between 1 to 5 kg / m 3
of inner-volume of digestion chamber . day.
3.2.9.28. Gasholder capacity
Post-optimization calculating of low-pressure gasholder capacity (ghc), depends on the
relative rates of biogas generation and biogas consumption (Sasse, 1988; Kossmann et al.,
1999; Institut für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008;
SATTLER AG & Ceno Membrane Technology GmbH, 2010 and ZORG, 2012). The gasholder
must be designed to:

Cover the peak (maximum) consumption rate of biogas (gmc), ghc ≥ gmc;

Holds the biogas produced during the longest zero-consumption period (gzc), ghc ≥
gzc.
124
Material and methods
𝑝𝑐
𝑝𝑝
3 44
𝑐 𝑡 𝑐
𝐹𝐴
𝑔 𝑐
3 45
Where:
gpc = Biogas peak consumption (m3);
gmc = Maximum hourly biogas consumption (m3/ h);
tmc = Time of maximum consumption (h);
gpp = Biogas peak production (m3);
GFA = Total on-farm biogas yield (m3 / year), see eq. (3.31);
8760 = number of hours per year (h / year);
gzc = Maximum zero-consumption period of biogas (10 h).
The larger value of gpc or gpp determines the capacity of the gasholder. Moreover a safety
margin of 10 – 20 % should be taken into consideration for calculating the gasholder
capacity, according to the following equation:
ℎ𝑐
𝑎𝑥
𝑝𝑐, 𝑝𝑝
5
3 46
Where:
ghc = Gasholder capacity (m3);
1.15 = Safety margin for gasholder capacity.
3.2.9.29. Ratio of the digester volume to gasholder capacity
Post-optimization calculating of the ratio of inner-volume of digester to gasholder capacity
(dvg, service variable) is a major factor with regard to the basic design of the biogas plant.
For a typical agricultural biogas plant, the dvg amounts to somewhere between 3:1 and
10:1, with 5:1 to 6:1 occurring most frequently (Sasse, 1988; Kossmann et al., 1999; Institut
für Energetik und Umwelt et al., 2006; Lfu, 2007; Al Seadi et al., 2008; SATTLER AG & Ceno
Membrane Technology GmbH, 2010 and ZORG, 2012), calculating according to the
following equation:
125
Material and methods
𝑣
3 47
𝑔 𝑐
Where:
dvg = Ratio of the digester volume to gasholder capacity;
vdi = Total inner-volume of digester (m3), see eq. (3.40);
ghc = Gasholder capacity (m3), see eq. (3.46).
3.2.9.30. Inner-volume of digestate tank
Post-optimization calculating of inner-volume of digestate tank (vdt), refers to the capacity
of digestate tank required to storage the digestate after digestion and dewatering processes
(Lehtomäki, 2006; Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008;
Kirchmeyr et al., 2009; Lukehurst et al., 2010 and Frandsen, 2011), calculating according to
the following equation:
𝑣 𝑡
𝑠
3 48
Where:
vdt = Inner-volume of digestate tank (m3);
MDI = Total mass of on-farm air-dried digestate after dewatering (ton / year), see eq. (3.32);
spd = Default storage period of digestate is 3 months (0.25 year);
ddi = Density of digestate (contains TS 90 % and MC 10 %) (1.1 ton / m3);
1.15 = Factor of operational inner-volume of digestate tank (operational inner-volume
should be more than 15 % of theoretical inner-volume).
3.2.9.31. Inner-surface area of digestate tank
Post-optimization calculating of inner-surface area of digestate tank (sdt) (Lehtomäki, 2006;
Electrigaz Technologies Inc., 2007; Lfu, 2007; Al Seadi et al., 2008; Kirchmeyr et al., 2009;
Lukehurst et al., 2010 and Frandsen, 2011), calculating according to the following equation:
126
Material and methods
3 49
𝑠 𝑡
Where:
sdt = Inner-surface area of digestate tank (ha);
vdt = Inner-volume of digestate tank (m3), see eq. (3.48);
hdt = Height of digestate tank (3 m);
10000 = Surface area of hectare (m2 / ha).
3.2.9.32. Allocated surface area for on-farm biogas system
Post-optimization calculating of the allocated surface area for on-farm biogas system (sgs),
consists of sum of allocated surface areas for different facilities to serve on-farm biogas and
energy production (Vitali et al., in press), calculating according to the following equation:
𝑠 𝑠
𝑠 𝑠
𝑠 𝑡
𝑠
𝑠 𝑡
0
3 50
Where:
sgs = Allocated surface area for on-farm biogas system (ha);
sbs = Inner-surface area of bunker silo for storage fresh silage for livestock feeding and
biogas production (ha), see eq. (3.33);
smt = Inner-surface area of manure slurry tank or lagoon (with cylindrical, square or
rectangular shape) (ha), see eq. (3.35);
sdi = Inner-surface area of digester (with cylindrical shape) (ha), see eq. (3.38);
sdt = Inner-surface area of digestate tank (ha), see eq. (3.49);
1.10 = Factor of operational surface area of biogas system (operational surface area should
be more than 10 % of theoretical surface area), including the inner-surface area of
pumping and mixing unit, inner-surface area of on-farm CHP unit of biogas, innersurface area of gasholder and the inner-surface area of other facilities related to
biogas system.
3.2.9.33. Total net productive capacity of thermal energy from on-farm CHP unit of biogas
Constraint of total net productive capacity of thermal energy from on-farm CHP unit of
biogas (ETA) (Kaiser et al., 2004; Mickan, 2006; Kirchmeyr et al., 2009; Knitter et al., 2010;
127
Material and methods
NNFCC, 2010; Biomass Energy Center, 2011 and Hopwood, 2011), calculating by multiply
total on-farm biogas yield to specific conversion factor of biogas to net thermal energy,
according to the following equation:
𝐸
𝐺𝐹
35
𝑐 𝑡 𝑢 𝑡
Where:
ETA = Total net productive capacity of thermal energy from on-farm CHP unit of biogas
(kWhth / year), ETA ≥ 0;
GFA = Total on-farm biogas yield (m3 / year), GFA ≥ 0, see eq. (3.31);
cft = Conversion factor of biogas to thermal energy = 2 kWh th / m3;
uft = Factor of useful thermal energy available for on-farm different uses. Usually, 33 % of
the thermal energy produced is used for heating substrate inside the mixing unit and
the digester and 67 % of the thermal energy produced is available for on-farm
different uses = 0.67.
3.2.9.34. Surplus thermal energy produced from on-farm CHP unit of biogas
Post-optimization calculating of surplus thermal energy produced from on-farm CHP unit of
biogas (ets), by subtract total on-farm thermal energy requirements from total net
productive capacity of thermal energy from on-farm CHP unit of biogas, calculating
according to the following equation:
𝑒𝑡𝑠
𝐸
− 𝐸
;𝐸
𝐸
3 52
Where:
ets = Surplus thermal energy produced from on-farm CHP unit of biogas (kWhth / year);
ETA = Total net productive capacity of thermal energy from on-farm CHP unit of biogas
(kWhth / year), see eq. (3.51);
ETC = Total on-farm thermal energy consumed (kWhth / year), see eq. (3.11).
128
Material and methods
3.2.9.35. Total net productive capacity of electrical energy from on-farm CHP unit of
biogas
Constraint of total net productive capacity of electrical energy from on-farm CHP unit of
biogas (EEA) (Kaiser et al., 2004; Mickan, 2006; Kirchmeyr et al., 2009; Knitter et al., 2010;
NNFCC, 2010; Biomass Energy Center, 2011 and Hopwood, 2011), calculating by multiply
total on-farm biogas yield to specific conversion factor of biogas to net electrical energy,
according to the following equation:
𝐸𝐸
𝐺𝐹
3 53
𝑐 𝑒 𝑢 𝑒
Where:
EEA = Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year), EEA ≥ 0;
GFA = Total on-farm biogas yield (m3 / year), GFA ≥ 0, see eq. (3.31);
cfe = Conversion factor of biogas to electrical energy = 1.7 kWhel / m3;
ufe = Factor of useful electrical energy available for on-farm different uses. Usually, 10 % of
the electrical energy produced is used for operate the biogas system and 90 % of the
electrical energy produced is available for on-farm different uses = 0.9.
3.2.9.36. Surplus electrical energy produced from on-farm CHP unit of biogas
Post-optimization calculating of surplus electrical energy produced from on-farm CHP unit of
biogas, which available for sell to the national electrical network (ees), by subtract total onfarm electrical energy requirements from total net productive capacity of electrical energy
from on-farm CHP unit of biogas, calculating according to the following equation:
𝑒𝑒𝑠
𝐸𝐸
− 𝐸𝐸 ; 𝐸𝐸
𝐸𝐸
3 54
Where:
ees = Surplus electrical energy produced from on-farm CHP unit of biogas, which available
for sell to the national electrical network (kWhel / year);
EEA = Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year), see eq. (3.53);
EEC = Total on-farm electrical energy consumed (kWhel / year), see eq. (3.14).
129
Material and methods
3.2.10. The objective function
The optimization process aims to maximize (Z), which refers to the total net income of farm
for whole time which is considered by analysis, according to the following equation:
∑
𝐼𝑁
𝑡𝑟
3 55
Where:
Z = The objective function for optimization;
VIN = Total net income of farm in year t (euro);
trn = Interest rate at year t (3%);
t = Reference year of farm account.
3.2.11. GAMS solver
The suggested GAMS solver to the RAF model is BDMLP solver.
130
Results and discussion
4. RESULTS AND DISCUSSION
4.1. Case studies
For apply the RAF model and extracting the results, 2 hypothetical case studies based on
realistic values have been developed.
4.1.1. Case study (A)
4.1.1.1. Farm parameterization
The parameterizations of hypothetical case study (A) of farm are:

Farm undergo to north Italy conditions (climate and slope);

Farm oriented to conventional agriculture (non-organic) and livestock production
(dairy cattle);

Farm gets actual subsidies;

The period considered by analysis is 10 years.
4.1.1.2. Main products of farm

Field crops yield (food, feed and energy crops);

Livestock products (main products: milk and meat, and by-product: manure).
4.1.1.3. Apply on-farm biogas technology
For realized the sustainable development at the field of on-farm energy required and reduce
the costs of on-farm energy consumed, the farm planning to establish an on-farm biogas
system depends on co-digestion of energy crops and animal manure slurry for meets onfarm requirements of energy, moreover produce digestate (bio-fertilizers) for meets the onfarm requirements of fertilizers.
4.1.1.4. Description of farm structure
Farm structure can be defined by the way farm and their resources are organized to
produce farm products (crops and livestock products). Description of farm structure for the
hypothetical case study (A) is tabulated in Table (4.1):
131
Results and discussion
Table 4.1: Description of farm structure for the hypothetical case study (A) (pre-optimization
input data from GUI17)
Technical term
sau
SCScs
SCScz
SCSce
SCScg
sun
LSUzo
pem
Description
Total surface area of farm
Allocated surface area for field crops cultivation
Allocated surface area for forage crops (medica, frumento-duro & altreforaggere), SCScz ϵ SCScs
Allocated surface area for energy crops (alfalfa, maize & sorghum), SCSce ϵ SCScs
Allocated surface area for greenhouses cultivation
Surface area of natural surface (meadow)
Number of livestock units
Market price of electrical energy
Value and unit
50 ha
35 ha
20 ha
15 ha
0 ha
15 ha
50 dairy cows
0.25 euro / kWhel
4.1.1.5. Results of optimization process
The main results of hypothetical case study (A) are tabulated in Table (4.2):
Table 4.2: Optimum output data of hypothetical case study (A)
Eq.
18
Tech.
19
Value
13.82
22.07
3.2
SCScs
3.3
3.3
LSUzo
SLS
3.4
MDDdi
3.5
MDAdi
3.6
MDPdi
3.9
3.10
3.11
3.12
3.13
3.14
ETG
ETD
ETC
EEG
EED
EEC
10491.09 fu
1316.19 cp
8.90 fu
19683.80 cp
0
49218.75
49218.75
0
52500
52500
3.15
LGS
1
3.16
VGC
20192.40
3.17
mfs
261.14
3.18
MDGce
217.07
3.19
qdgce
834.88
3.20
MMSzo
1218.73
52.50
0.105
10500 fu
21000 cp
Description and unit
Allocated surface area of maize cultivation for biogas production (ha)
Allocated surface area of medica, frumento-duro and altre-foraggere cultivation for
forage (ha)
Number of livestock units (ldairy cows)
Allocated surface area for on-farm livestock production (ha)
Total nutrition required (from on-farm available production of forage and purchased
from market) in terms of diet nutrients for livestock feeding, based on dry matter
content (fu / year and cp / year)
Available nutrition for livestock from on-farm production of forage crops in terms of
diet nutrients, based on dry matter content (fu / year and cp / year)
Nutrition purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content (fu / year and cp / year)
On-farm thermal energy consumed for greenhouses warming (kWhth / year)
On-farm thermal energy consumed for livestock production (kWhth / year)
Total on-farm thermal energy consumed (kWhth / year)
On-farm electrical energy consumed for greenhouses (kWhel / year)
On-farm electrical energy consumed for livestock production (kWhel / year)
Total on-farm electrical energy consumed (kWhel / year)
Total number of workers required for operating and maintenance of on-farm biogas
system (worker / year)
Total net income of on-farm biogas production in year t, based on electrical energy
production from on-farm CHP unit (euro / year)
Total mass of on-farm fresh silage (refers to storage capacity of bunker silo for 6
months as default storage period) available for livestock feeding and biogas
production (ton)
Mass of on-farm air-dried silage available for biogas production (contains TS from 70
to 90 % and MC from 10 to 30 %) (ton / year)
Quantity of on-farm air-dried silage available for biogas production (contains TS from
3
70 to 90 % and MC from 10 to 30 %) (m / year)
Mass of on-farm manure slurry available for biogas production (contains TS from 8 to
17
Graphical use interface
Equation number
19
Technical term
18
132
Results and discussion
Eq.
18
Tech.
19
Value
3.21
MDMzo
146.24
3.22
qmszo
1218.73
3.23
3.24
mfg
qfg
1435.80
2053.62
3.25
ism
19.65
3.26
3.27
3.28
drg
qwd
qsd
40.71
2991.22
5044.84
3.29
GCUce
110204.93
3.30
3.31
3.32
GLUzo
GFA
MDI
30450
140654.93
186.26
3.33
sbs
0.01451
3.34
vmt
153.59
3.35
smt
0.0038
3.36
3.37
3.38
dmu
vdc
sdi
15.89
635.78
0.0159
3.39
vgs
182.78
3.40
3.41
vdi
sgy
818.57
0.4708
3.42
lts
1.52
3.43
lvs
1.29
3.45
3.46
3.47
3.48
3.49
3.50
gpp
ghc
dvg
vdt
sdt
sgs
160.56
184.64
4.43
48.45
0.0016
0.0394
3.51
ETA
188477.60
3.52
ets
139258.85
3.53
EEA
215202.04
3.54
ees
162702.04
Description and unit
12 % and MC from 88 to 92 %) (ton / year)
Mass of on-farm air-dried manure available for biogas production (ton / year)
Quantity of on-farm manure slurry available for biogas production (contains TS from 8
3
to 12 % and MC from 88 to 92 %) (m / year)
Total mass of on-farm feedstock available for biogas production (ton / year)
3
Total quantity of on-farm feedstock available for biogas production (m / year)
Concentration of TS (dry matter content) at the Inlet of mixing unit before dilution
with water for mixed substrate consists of air-dried silage and manure slurry on the
basis of wet-mass (%)
Dilution ratio of substrate required for biogas production (%)
3
Total quantity of water required for substrate dilution (m / year) = (ton / year)
3
Total quantity of diluted substrate input to digester (m / year)
Biogas yield generated, based on biogas yield per mass unit of fresh silage from
3
energy crops (m / year)
3
Biogas yield generated, based on biogas yield per livestock unit (m / year)
3
Total on-farm biogas yield (m / year)
Total Mass of on-farm air-dried digestate after dewatering (ton / year)
Inner-surface area of bunker silo for storage fresh silage for livestock feeding and
biogas production (ha)
Inner-volume of manure slurry tank or lagoon (with cylindrical, square or rectangular
3
shape) (m )
Inner-surface area of manure slurry tank or lagoon (with cylindrical, square or
rectangular shape) (ha)
3
Discharge of pumping and mixing unit (m / day)
3
Inner-volume of digestion chamber (with cylindrical shape) (m )
Inner-surface area of digester (with cylindrical shape) (ha);
Inner-volume of biogas storage chamber (low-pressure biogas tight membranes with
3
dome shape) (m )
3
Total inner-volume of digester (m )
3
3
Specific gas yield (m of biogas / m of total inner-volume of digester. day)
Digestion chamber loading, based on the daily mass of TS input to digestion chamber
3
(kg of TS / m of inner-volume of digestion chamber . day)
Digestion chamber loading, based on the daily mass of VS input to digestion chamber
3
(kg of VS / m of inner-volume of digestion chamber . day)
3
Biogas peak production (m )
3
Gasholder capacity (m )
Ratio of the digester volume to gasholder capacity
3
Inner-volume of digestate tank (m )
Inner-surface area of digestate tank (ha)
Allocated surface area for on-farm biogas system (ha)
Total net productive capacity of thermal energy from on-farm CHP unit of biogas
(kWhth / year)
Surplus thermal energy produced from on-farm CHP unit of biogas (kWhth / year)
Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year)
Surplus electrical energy produced from on-farm CHP unit of biogas, which available
for sell to the national electrical network (kWhel / year)
133
Results and discussion
4.1.1.6. Recommendations of biogas technology apply for case study (A)
A- Anaerobic digester
According to the output data of optimization from RAF model for case study (A) could
recommend use the wet anaerobic digestion process with mesophilic continuous system
equipped with completely stirred tank reactor (CSTR) integrates with pumping system
equipped with positive displacement pumps (progressing cavity pumps), suitable for codigestion process for feedstock contains high content of silage with animal manure slurry.
CSTR usually vertical circular tanks with hard or flexible membrane cover that store biogas.
Tanks can be designed in a vertical (top mounted mixer) or flat (side mixers) configuration.
CSTR are always mechanically stirred. The fresh feedstock enters the tank and is
immediately mixed with the existing, partially digested material. Biogas production
proceeds without any interruption from the loading and unloading of the waste material. To
optimize the digestion process of the anaerobic bacteria, the digester should be kept at a
constant temperature. Typically, a portion of the biogas generated is used to heat the
contents of the digester, or the coolant from a biogas-powered generator is returned to a
heat exchanger inside the digester tank. The temperature of the substrate inside digester is
around 36 °C and the residence time of substrate (HRT) is around 35 days under mesophilic
system.
Main components of CSTR:

Mixing tank;

Digester equipped with mixing, heating and biogas recovery systems;

Effluent storage system;

Biogas utilization system.
Advantages of CSTR:

Efficient;

Can digest different feedstocks contains different levels of dry matter;

Can digest energy crops and by-products with animal manure;

Good mixing of feedstocks;
134
Results and discussion

Good solid degradation;

Can be used with either flush or scrape systems;

Works well with flush and scrape systems (systems of manure collection from Corrals);

The manure tanks, which already exist in farms could be converted to biogas digesters
by equip them with isolation, stirring and heating systems which leading to construct
cheap digester of biogas.
Disadvantages of CSTR:

Relatively expensive;

No guarantee on how much time the material remains in the tank (HRT);

Requires mechanical mixing system;

Bacteria wash out.
B- Combined heat and power (CHP) unit
According to the output data of optimization from RAF model for case study (A) could
recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel, see eq.
(3.16).
C- Total costs and income of on-farm biogas system
In case of establish on-farm biogas system with the recommended (CSTR) digester type, the
total fixed costs of establish the on-farm biogas system are 250000 Euro (25000 Euro / year),
while the variable costs are 86081 Euro (8608.1 Euro / year) during the span life of on-farm
biogas system (10 years). The total costs (fixed and variable) of on-farm biogas system are
336081 Euro (33608.1 Euro / year), see Tables (2.13 and 2.14) and eq. (3.16).
The total net income of on-farm biogas system is 201924.3 Euro (20192.4 Euro / year) during
span life, presents 60 % of the total costs of on-farm biogas system.
135
Results and discussion
4.1.2. Case study (B)
4.1.2.1. Farm parameterization
The parameterizations of hypothetical case study (B) of farm are:

Farm undergo to north Italy conditions (climate and slope);

Farm oriented to conventional agriculture (non-organic) and livestock co-breeding
production (meat cattle and pigs);

Farm gets actual subsidies;

The period considered by analysis is 10 years.
4.1.2.2. Main products of farm

Field crops yield (food, feed and energy crops);

Tree crops yield (wood);

Livestock products (main product: meat and by-product: manure).
4.1.2.3. Apply on-farm biogas technology
For realized the sustainable development at the field of on-farm energy required and reduce
the costs of on-farm energy consumed, the farm planning to establish an on-farm biogas
system depends on co-digestion of energy crops and animal manure slurry for meets onfarm requirements of energy, moreover produce digestate (bio-fertilizers) for meets the onfarm requirements of fertilizers.
4.1.2.4. Description of farm structure
Farm structure can be defined by the way farm and their resources are organized to
produce farm products (crops and livestock products). Description of farm structure for the
hypothetical case study (B) is tabulated in Table (4.3):
136
Results and discussion
Table 4.3: Description of farm structure for the hypothetical case study (B) (pre-optimization
input data from GUI)
Technical term
sau
SCScs
SCScz
SCSce
SCScg
sutca
Description
Total surface area of farm
Allocated surface area for field crops cultivation
Allocated surface area for forage crops (medica, altre-foragger & frumentoduro), SCScz ϵ SCScs
Allocated surface area for energy crops (alfalfa, maize & sorghum), SCSce ϵ SCScs
Allocated surface area for greenhouses cultivation
Allocated surface area for trees (wood)
LSUzo
Number of livestock units
pem
Market price of electrical energy
Value and unit
50 ha
45 ha
35 ha
10 ha
0 ha
5 ha
150 meat calf &
200 pig
0.25 euro / kWhel
4.1.2.5. Results of optimization process
The main results of hypothetical case study (B) are tabulated in Table (4.4):
Table 4.4: Optimum output data of hypothetical case study (B)
Eq.
20
Tech.
21
Value
13.87
35.18
3.2
SCScs
3.3
3.3
LSUzo
SLS
3.4
MDDdi
3.5
MDAdi
3.6
MDPdi
3.9
3.10
3.11
3.12
3.13
3.14
ETG
ETD
ETC
EEG
EED
EEC
47202.79 fu
5921.97 cp
47.20 fu
104328.02 cp
0
98437.50
98437.50
0
78750
78750
3.15
LGS
1
3.16
VGC
22558.70
3.17
mfs
299.50
3.18
MDGce
217.90
3.19
qdgce
838.11
3.20
MMSzo
2742.15
20
21
157.50
0.189
47250 fu
110250 cp
Description and unit
Allocated surface area of maize cultivation for biogas production (ha)
Allocated surface area of medica, altre-foragger and frumento-duro cultivation for
forage (ha)
Number of livestock units (meat calf)
Allocated surface area for on-farm livestock production (ha)
Total nutrition required (from on-farm available production of forage and purchased
from market) in terms of diet nutrients for livestock feeding, based on dry matter
content (fu / year and cp / year)
Available nutrition for livestock from on-farm production of forage crops in terms of
diet nutrients, based on dry matter content (fu / year and cp / year)
Nutrition purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content (fu / year and cp / year)
On-farm thermal energy consumed for greenhouses warming (kWhth / year)
On-farm thermal energy consumed for livestock production (kWhth / year)
Total on-farm thermal energy consumed (kWhth / year)
On-farm electrical energy consumed for greenhouses (kWhel / year)
On-farm electrical energy consumed for livestock production (kWhel / year)
Total on-farm electrical energy consumed (kWhel / year)
Total number of workers required for operating and maintenance of on-farm biogas
system (worker / year)
Total net income of on-farm biogas production in year t, based on electrical energy
production from on-farm CHP unit (euro / year)
Total mass of on-farm fresh silage (refers to storage capacity of bunker silo for 6
months as default storage period) available for livestock feeding and biogas
production (ton)
Mass of on-farm air-dried silage available for biogas production (contains TS from 70
to 90 % and MC from 10 to 30 %) (ton / year)
Quantity of on-farm air-dried silage available for biogas production (contains TS from
3
70 to 90 % and MC from 10 to 30 %) (m / year)
Mass of on-farm manure slurry available for biogas production (contains TS from 8 to
Equation number
Technical term
137
Results and discussion
Eq.
20
Tech.
21
Value
3.21
MDMzo
329.05
3.22
qmszo
2742.15
3.23
3.24
mfg
qfg
2960.06
3580.26
3.25
ism
14.70
3.26
3.27
3.28
drg
qwd
qsd
54.42
2998.52
6578.79
3.29
GCUce
110630.76
3.30
3.31
3.32
GLUzo
GFA
MDI
68512.50
179143.26
321.21
3.33
sbs
0.01664
3.34
vmt
345.58
3.35
smt
0.0086
3.36
37
3.38
dmu
vdc
sdi
20.72
829.10
0.0207
3.39
vgs
238.36
3.40
3.41
vdi
sgy
1067.47
0.4598
3.42
lts
1.57
3.43
lvs
1.33
3.45
3.46
3.47
3.48
3.49
3.50
gpp
ghc
dvg
vdt
sdt
sgs
204.50
235.17
4.53
83.72
0.0028
0.0537
3.51
ETA
240051.97
3.52
ets
141614.47
3.53
EEA
274089.20
3.54
ees
195339.20
Description and unit
12 % and MC from 88 to 92 %) (ton / year)
Mass of on-farm air-dried manure available for biogas production (ton / year)
Quantity of on-farm manure slurry available for biogas production (contains TS from
3
8 to 12 % and MC from 88 to 92 %) (m / year)
Total mass of on-farm feedstock available for biogas production (ton / year)
3
Total quantity of on-farm feedstock available for biogas production (m / year)
Concentration of TS (dry matter content) at the Inlet of mixing unit before dilution
with water for mixed substrate consists of air-dried silage and manure slurry on the
basis of wet-mass (%)
Dilution ratio of substrate required for biogas production (%)
3
Total quantity of water required for substrate dilution (m / year) = (ton / year)
3
Total quantity of diluted substrate input to digester (m / year)
Biogas yield generated, based on biogas yield per mass unit of fresh silage from
3
energy crops (m / year)
3
Biogas yield generated, based on biogas yield per livestock unit (m / year)
3
Total on-farm biogas yield (m / year)
Total Mass of on-farm air-dried digestate after dewatering (ton / year)
Inner-surface area of bunker silo for storage fresh silage for livestock feeding and
biogas production (ha)
Inner-volume of manure slurry tank or lagoon (with cylindrical, square or rectangular
3
shape) (m )
Inner-surface area of manure slurry tank or lagoon (with cylindrical, square or
rectangular shape) (ha)
3
Discharge of pumping and mixing unit (m / day)
3
Inner-volume of digestion chamber (with cylindrical shape) (m )
Inner-surface area of digester (with cylindrical shape) (ha);
Inner-volume of biogas storage chamber (low-pressure biogas tight membranes with
3
dome shape) (m )
3
Total inner-volume of digester (m )
3
3
Specific gas yield (m of biogas / m of total inner-volume of digester. day)
Digestion chamber loading, based on the daily mass of TS input to digestion chamber
3
(kg of TS / m of inner-volume of digestion chamber . day)
Digestion chamber loading, based on the daily mass of VS input to digestion chamber
3
(kg of VS / m of inner-volume of digestion chamber . day)
3
Biogas peak production (m )
3
Gasholder capacity (m )
Ratio of the digester volume to gasholder capacity
3
Inner-volume of digestate tank (m )
Inner-surface area of digestate tank (ha)
Allocated surface area for on-farm biogas system (ha)
Total net productive capacity of thermal energy from on-farm CHP unit of biogas
(kWhth / year)
Surplus thermal energy produced from on-farm CHP unit of biogas (kWhth / year)
Total net productive capacity of electrical energy from on-farm CHP unit of biogas
(kWhel / year)
Surplus electrical energy produced from on-farm CHP unit of biogas, which available
for sell to the national electrical network (kWhel / year)
138
Results and discussion
4.1.2.6. Recommendations for case study (B)
A- Anaerobic digester
According to the output data of optimization from RAF model for case study (B) could
recommend use the wet anaerobic digestion process with continuous system equipped
with plug flow digester integrates with pumping system equipped centrifugal (rotating)
pumps, suitable for co-digestion process for feedstock contains relative low content of
silage with animal manure slurry.
The plug flow digester is usually horizontal digester consists of rectangular tank that are half
buried with a hard or flexible membrane cover installed to collect the biogas produced. The
feedstock needs to be relatively thick (contains 8 – 12 % of DM) to ensure that feedstock
movement maintains the plug flow effect. These digesters are generally not mechanically
mixed. Feedstock enters at one end, pushing older substrate forward until it exits. Some
systems will re-circulate substrate from the end of tank to inoculate the new material
entering and speed up the degradation process. The residence time of substrate (HRT) from
20 to 40 days.
Main components of plug flow digester:

Mixing tank;

Digester equipped with heat exchanger and biogas recovery system;

Effluent storage structure;

Biogas utilization system.
Advantages of plug flow digester:

Relatively Inexpensive;

Simple to install and operate;

Fit for livestock manure digestion;

Works well with scrape systems (systems of manure collection from Corrals);

Produces high quality fertilizers.
Disadvantages:

Feedstock must contains more than 8 % of DM;

Susceptible to contaminants (can’t be used with sand bedding);
139
Results and discussion

Poor mixing of feedstock;

Poor yield of biogas;

Nutrients and solids accumulate in bottom of digester, which lead to reducing useable
volume of digester;

Poor solids degradation;

Membrane-top subject to weather (wind and snow);

Bacteria wash out.
B- Combined heat and power (CHP) unit
According to the output data of optimization from RAF model for case study (B) could
recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel, see eq.
(3.16).
C- Total costs and income of on-farm biogas system
In case of establish on-farm biogas system with the recommended (CSTR) digester type, the
total fixed costs of establish the on-farm biogas system are 250000 Euro (25000 Euro / year),
while the variable costs are 109635.7 Euro (10963.6 Euro / year) during the span life of onfarm biogas system (10 years). The total costs (fixed and variable) of on-farm biogas system
are 359635.7 Euro (45963.6 Euro / year), see Tables (2.13 and 2.14) and eq. (3.16).
The total net income of on-farm biogas system is 325587.3 Euro (32558.7 Euro / year) during
span life, presents 90 % of the total costs of on-farm biogas system.
140
Summary and conclusion
5. SUMMARY AND CONCLUSION
5.1. Introduction
Biogas is a non-conventional, promising renewable energy carrier, which combines the
disposal of organic waste with the formation of a valuable energy carrier, methane. On the
other hand biogas energy characterized as the best way of derive energy from polluted
wastes, clean, eco-friendly, money saver, time saver, and minimizes expenditure of the
foreign currency for the import of fossil fuels.
One of the most important and modern technologies, which dealing with recycling of
organic wastes is Anaerobic Digestion (AD) of digestible organic waste (agricultural byproducts and wastes, animal manure and slurries), which converts these substrates to
renewable energy carrier (biogas), reduce the GHG, produce an excellent natural fertilizer
for agriculture purposes and achievement many social and economic benefits for the
producer and consumer of biogas (Dennis and Burke, 2001).
AD is a microbiological process of anaerobic decomposition (in the absence of oxygen) of
the organic matter, which produces biogas in air-proof reactor tanks, commonly named
digesters. Biogas produced in many natural environments and widely applied today. There is
a wide range of micro-organisms are decomposition the organic matter in anaerobic
process, which has two main end products: biogas and digestate. Biogas is a combustible
gas; mainly it is a mix of methane, carbon dioxide and small amounts of other gases and
trace elements. Digestate is the decomposed substrate, which rich in nutrients and suitable
to be used as plant fertilizer (Kossmann et al., 1999; Kramer, 2004 and Al Seadi et al.,
2008).
5.2. Current situation and potentials of biogas in Italy
Currently, the use of biomass for energy purposes contributes for just 3.5 % to the final
national energy consumption (180.2 Mtoe22) but with a production equal to about 6.2 Mtoe,
bioenergy represent 29.5 % of the whole amount of energy from renewable sources in Italy
22
Million tons of oil equivalent
141
Summary and conclusion
(21,1 Mtoe). The biogas contribution to the total bioenergy production is about 8 % (8.4 %
of the electricity production from biomass sources) (ENEA, 2010).
Regional distribution of Italian biogas sector shows that, biogas plants are mainly located in
the northern regions and more than 60 % are related with the agriculture and zoo-technical
sector. 50 % of agriculture and zoo-technical biogas plants uses co-digestion mixture of
energy crops, by-products, residues and animal manure.
According to ENEA (2010) could summarize the current state of biogas in Italy as follow:

Biogas production in 2009 was about 0. 499 Mtoe;

78 % of biogas production coms from MSW23 Landfills (228 plants);

451 plants feed by a mixture of different substrates (from agroindustry, agro-zootechnical residues and sewage sludge);

The total installed capacity is about 507.7 MW (including landfills);

A recent growing trend of biogas sector comes from the growing of the agro-industrial
and zoo-technical biogas production.
If we sum all quantities of energy crops (over set-aside lands) plus agricultural residues,
livestock manure, agroindustry residues, MSW and sewage sludge, we could roughly
estimate a potential of about 65 million m3 / year of feedstock available for biogas
production (CRPA, 2011).
A total of 1.3 million m3 of biogas / day can be produced only from livestock manure that
could result in a total biomethane production of 237 million m 3 / year which is about 10
times more than the actual needs of methane used for transports in Italy (CRPA, 2011).
5.3. Objective of the study
Due to continued rapid growth of the Italian biogas sector during the last years and for
improving the exploitation of the Italian potentials of biogas production from on-farm
production of energy crops and livestock manure feedstock to meet the growing demand of
energy, there is a need to address the following problems:
23
Municipal solid waste
142
Summary and conclusion

Farm size (different farm scales) and farm structure (on-farm crops and livestock
distribution and production) suitable for establish on-farm biogas system to cover the
on-farm thermal and electrical energy requirements;

Selection of appropriate technology from different technologies of anaerobic
digestion, biogas production and use, for applying at different farm scales with
different farm structures.
As previously mentioned there are many mathematical models processing the different
biogas problems and improving the biogas production, but there is a need to develop a
mathematical model to reconcile between farm size, farm structure and on-farm biogas
systems technologies applied to support selection and applying of appropriate biogas
technology at any farm under Italian conditions.
The objective of this study is enhancing the exploitation of the available Italian potentials of
biogas production from on-farm production of energy crops and livestock manure feedstock
by develop a mathematical model RAF integrates with MAD24 model for optimize the
following on-farm variables, related to anaerobic digestion and biogas production and use:

Allocated surface areas, distribution and production of different on-farm crops under
different farm sizes (scales) (optimum data of MAD);

Number of on-farm LSU25 (from different available types of farm livestock) (optimum
data of MAD);

Key design elements of on-farm biogas production system (directs and helps to select
the suitable technologies of on-farm biogas system) (optimum data of RAF);

On-farm labor requirements (optimum data of RAF and MAD);

The total net income of farm (optimum data of RAF and MAD).
24
MAD is a bio-economical model aimed to optimize resources of a farm holding (surfaces, livestock, labor,
etc.) to approach an objective function aimed to maximize net income.
25
Livestock unit
143
Summary and conclusion
5.3.1. Description of RAF model
The outlines of RAF model could be summarized as following:
1. RAF is a bio-energetic descriptive model in terms of sets of equations (or inequalities)
run by uses GAMS code and GUI (Graphical Use Interface) works under MATLAB
environment for optimize the objective function (Z) (optimization the total net income
of farm for whole period which is considered by analysis);
2. RAF model support Integrated Farm Management (IFM) by enhancing economical,
social and environmental sustainability of farm production;
3. RAF model support decision maker, engineers and farmers;
4. RAF model investigates the possibilities of establish on-farm biogas system (different
anaerobic digestion (AD) technologies proposed for different scales of farms in terms
of energy requirements) for reduce the dependence on fossil fuels and recycling the
agricultural and animal by-products for produce energy and digestate (bio-fertilizers);
5. The output data of optimization process presents a preliminary design of on-farm
biogas production system which contains the key design elements (e.g. dimensions,
quantities, capacities of main components of on-farm biogas production system);
6. The output data of optimization process could be presented in form of
recommendations for the best investment in energy from different on-farm potentials
under different farm sizes (scales).
5.4. Main results of the study
For apply the RAF model and extracting the results, hypothetical case studies based on
realistic values have been developed.
5.4.1. Case study (A)
Farm undergo to north Italy conditions (climate and slope) and oriented to conventional
agriculture (non-organic) and livestock production (dairy cattle). Farm gets actual subsidies
and the period considered by analysis is 10 years.
The main products of farm are field crops yield (food, feed and energy crops) and livestock
products (main products: milk and meat, and by-product: manure).
144
Summary and conclusion
The farm planning to establish an on-farm biogas system depends on co-digestion of energy
crops and animal manure slurry for meets on-farm requirements of energy, moreover
produce digestate (bio-fertilizers) for meets the on-farm requirements of fertilizers.
Farm structure can be defined as follows:

Total surface area of farm is 50 ha;

Allocated surface area for field crops cultivation is 35 ha;

Allocated surface area for forage crops (medica, frumento-duro & altre-foraggere) is
20 ha;

Allocated surface area for energy crops (alfalfa, maize & sorghum) is 15 ha;

Surface area of natural surface (meadow) is 15 ha;

Number of livestock units is 50 dairy cows;

Market price of electrical energy is 0.25 euro / kWhel.
According to the results of optimization process could give the following recommendations
of biogas technology apply for case study (A):

Recommend use the wet anaerobic digestion process with mesophilic continuous
system equipped with completely stirred tank reactor (CSTR) integrates with pumping
system equipped with positive displacement pumps (progressing cavity pumps),
suitable for co-digestion process for feedstock contains high content of silage with
animal manure slurry;

Recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel.

The total costs (fixed and variable) of on-farm biogas system are 336081 Euro (33608.1
Euro / year), while the total net income of on-farm biogas system is 201924.3 Euro
(20192.4 Euro / year) during span life (10 years), presents 60 % of the total costs of onfarm biogas system.
145
Summary and conclusion
5.4.2. Case study (B)
Farm undergo to north Italy conditions (climate and slope) and oriented to conventional
agriculture (non-organic) and livestock co-breeding production (meat cattle and pigs). Farm
gets actual subsidies and the period considered by analysis is 10 years.
The Main products of farm are field crops yield (food, feed and energy crops), tree crops
yield (wood) and livestock products (main product: meat and by-product: manure).
The farm planning to establish an on-farm biogas system depends on co-digestion of energy
crops and animal manure slurry for meets on-farm requirements of energy, moreover
produce digestate (bio-fertilizers) for meets the on-farm requirements of fertilizers.
Farm structure can be defined as follows:

Total surface area of farm is 50 ha;

Allocated surface area for field crops cultivation is 45 ha;

Allocated surface area for forage crops (medica, altre-foragger & frumento-duro) is 35
ha;

Allocated surface area for energy crops (alfalfa, maize & sorghum) is 10 ha;

Allocated surface area for trees (wood) is 5 ha;

Numbers of livestock units are 150 meat calf & 200 pig;

Market price of electrical energy is 0.25 euro / kWhel.
According to the results of optimization process could give the following recommendations
of biogas technology apply for case study (B):

Recommend use the wet anaerobic digestion process with continuous system
equipped with plug flow digester integrates with pumping system equipped centrifugal
(rotating) pumps, suitable for co-digestion process for feedstock contains relative low
content of silage with animal manure slurry;

Recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel;

The total costs (fixed and variable) of on-farm biogas system are 359635.7 Euro
(45963.6 Euro / year), while the total net income of on-farm biogas system is 325587.3
146
Summary and conclusion
Euro (32558.7 Euro / year) during span life, presents 90 % of the total costs of on-farm
biogas system.
5.5. Conclusion
The main results of this study refers to the possibility of enhancing the exploitation of the
available Italian potentials of biogas production from on-farm production of energy crops
and livestock manure feedstock by using the developed mathematical model RAF integrates
with MAD model for optimize the objective function (Z) (optimization the total net income of
farm for whole period which is considered by analysis) and presents reliable reconcile
between farm size, farm structure and on-farm biogas systems technologies applied to
support selection, applying and operating of appropriate biogas technology at any farm
under Italian conditions.
Also the main results indicates to the flexibility and ability of RAF model to offers reliable
Key design elements26 (preliminary design) of on-farm biogas production system, which
includes:

Dilution ratio of substrate required for biogas production;

Total quantity of diluted substrate input to digester;

Inner-surface area of bunker silo for storage fresh silage for livestock feeding and
biogas production;

Inner-volume and inner-surface area of manure slurry tank or lagoon;

Discharge of pumping and mixing unit;

Inner-volume of digestion chamber;

Inner-surface area of digester;

Inner-volume of biogas storage chamber (low-pressure biogas tight membranes with
dome shape);
26

Total inner-volume of digester;

Specific gas yield;

Digestion chamber loading, based on the daily mass of TS input to digestion chamber;

Digestion chamber loading, based on the daily mass of VS input to digestion chamber;
Some references refer to key design elements as “design criteria”
147
Summary and conclusion

Biogas peak production;

Gasholder capacity;

Ratio of the digester volume to gasholder capacity;

Inner-volume and inner-surface area of digestate tank;

Allocated surface area for on-farm biogas system;

Total on-farm biogas yield;

Total on-farm thermal energy consumed;

Total on-farm electrical energy consumed;

Total net productive capacity of thermal energy from on-farm CHP unit of biogas;

Surplus thermal energy produced from on-farm CHP unit of biogas;

Total net productive capacity of electrical energy from on-farm CHP unit of biogas;

Surplus electrical energy produced from on-farm CHP unit of biogas, which available
for sell to the national electrical network;

Total net income of on-farm biogas production in year t, based on electrical energy
production from on-farm CHP unit.
The accurate description, calculation and optimization of this above mentioned Key design
elements are the crucial factor to selection, applying and operating of appropriate biogas
technology at any farm under Italian conditions.
148
Recommendations
6. RECOMMENDATIONS
6.1. Case study (A)
According to the results of optimization process could give the following recommendations
of biogas technology apply for case study (A):

Recommend use the wet anaerobic digestion process with mesophilic continuous
system equipped with completely stirred tank reactor (CSTR) integrates with pumping
system equipped with positive displacement pumps (progressing cavity pumps),
suitable for co-digestion process for feedstock contains high content of silage with
animal manure slurry;

Recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel.

The total costs (fixed and variable) of on-farm biogas system are 336081 Euro (33608.1
Euro / year), while the total net income of on-farm biogas system is 201924.3 Euro
(20192.4 Euro / year) during span life (10 years), presents 60 % of the total costs of onfarm biogas system.
149
Recommendations
6.2. Case study (B)
According to the results of optimization process could give the following recommendations
of biogas technology apply for case study (B):

Recommend use the wet anaerobic digestion process with continuous system
equipped with plug flow digester integrates with pumping system equipped centrifugal
(rotating) pumps, suitable for co-digestion process for feedstock contains relative low
content of silage with animal manure slurry;

Recommend use on-farm CHP unit of biogas with electrical capacity (ecp) 50 kWhel;

The total costs (fixed and variable) of on-farm biogas system are 359635.7 Euro
(45963.6 Euro / year), while the total net income of on-farm biogas system is 325587.3
Euro (32558.7 Euro / year) during span life, presents 90 % of the total costs of on-farm
biogas system.
150
References
7. REFERENCES
Alibaba.com. (2012). 150-600kw Biogas generator sets. [online] Available at:
<http://www.alibaba.com/productgs/534724763/150_600kw_Biogas_generator_sets.html> [Accessed 17 August
2012].
All About Circuits. (2012). Calculating Power Factor. [online] Available at:
<http://www.allaboutcircuits.com/vol_2/chpt_11/3.html> [Accessed 7 November
2012].
Al Seadi, T. (2001). Good Practice in Quality Management of AD Residues from Biogas
Production. Report made for the International Energy Agency, Task 24 - Energy from
Biological Conversion of Organic Waste. IEA Bioenergy and AEA Technology
Environment, Oxfordshire, UK. 32 p.
Al Seadi, T.; D. Rutz; H. Prassl; M. Köttner; T. Finsterwalder; S. Volk and R. Janssen. (2008).
Biogas Handbook. University of Southern Denmark Esbjerg, NielsBohrsVej 9-10, DK6700 Esbjerg, Denmark. 126 p.
Amours, L. D. and P. Savoie. (2005). Density Profile of Corn Silage in Bunker Silos. J. of
Canad. Biosys. Eng., 47 (2): 21 - 28.
An, B. X. and T. R. Preston. (1999). Gas Production from Pig Manure Fed at Different
Loading Rates to Polyethylene Tubular Bio-digesters. The Inter. J. for Res. Into.
Sustain. Dev. world agri., 11 (1): 53 - 60.
Anaerobic Digester. (2003). Plug Flow Digesters. [online] Available at:
<http://www.anaerobicdigester.com/ /> [Accessed 9 August 2012].
Anaerobic Digestion. (2010). Biogas Yields. [online] Available at: <http://www.biogasinfo.co.uk/index.php/biogas-yields-agri.html#topofpage> [Accessed 17 July 2012].
Anaerobic Granular Sludge Bed Reactor Technology. (2003). What is a UASB?. [online]
Available at: < http://www.uasb.org/discover/agsb.htm#uasb> [Accessed 11 August
2012].
Arora, K. and M. Licht. (2004). Calibrating Slurry Tank Manure Applicators. [online]
Available at:
<http://www.extension.iastate.edu/Pages/communications/EPC/Fall03/slurrytank.
html> [Accessed 26 June 2012].
Aworanti, O. A.; S. E. Agarry; A. O. Arinkoola and V. Adeniyi. (2011). Mathematical
Modeling for the Conversion of Animal Waste to Methane in Batch Bio-reactor.
Inter. J. of Eng. Sci. and Techno. (IJEST), 3 (1): 573 - 581.
Babaee, A. and J. Shayegan. (2011). Effect of Organic Loading Rates (OLR) on Production of
Methane from Anaerobic Digestion of Vegetables Waste. in: (Sharif University of
Technology, Tehran, Iran), World Renewable Energy Congress 2011 - Sweden.
Linköping, Sweden 8th - 13th of May 2011. Linköping: Sweden.
151
References
Balasubramaniyam, U.; L. S. Zisengwe; N. Meriggi and E. Buysman. (2008). Biogas
Production in Climates with Long Cold Winters. [pdf] Wageningen: Wageningen
University, Netherlands. Available at:
<http://www.susana.org/docs_ccbk/susana_download/2-1502biogascoldclimatesweb-wecf0608.pdf> [Accessed 19 July 2012].
Baldwin, S.; A. Lau and M. Wang. (2009). Development of a Calculator for the Technoeconomic Assessment of Anaerobic Digestion Systems. [pdf] Vancouver: Chemical
and Biological Engineering University of British Columbia. Available at:
<http://www.biomass.ubc.ca/IBSAL/AD%20Calculator%20Project%20%20Final%20Report.pdf> [Accessed 2 July 2012].
Balliette, J. (1998). Alfalfa for Beef Cows. [pdf] Nevada: Cooperative Extension service,
University of Nevada. Available at:
<http://www.unce.unr.edu/publications/files/ag/other/fs9323.pdf> [Accessed 26
November 2012].
Banks, C. (2009). Optimizing Anaerobic Digestion. [pdf] Southampton: University of
Southampton. Available at:
<http://www.forestry.gov.uk/pdf/rrps_AD250309_optimising_anaerobic_digestion.
pdf/$FILE/rrps_AD250309_optimising_anaerobic_digestion.pdf> [Accessed 12 July
2012].
Barnett, J. & J. Russell. (2010). Energy Use on Dairy Farms. Environmental issues at dairy
farm level. [pdf] Brussels: International Dairy Federation. Available at:
<http://www.idf-lca-guide.org/Files/media/PDF/443-2010.pdf> [Accessed 5
September 2012].
Batstone, D. J.; J. Keller; I. Angelidaki; S. V. Kalyuzhnyi; S.G. Pavlostathis; A. Rozzi; W. T. M.
Sanders; H. Siegrist and V.A. Vavilin. (2002). The IWA Anaerobic Digestion Model
No 1 (ADM1). Water Sci. & Techno. ( WST), 45 (10): 65 - 73.
Belloin, J. C. (1988). Milk and dairy products: production and processing costs. [Online]
Available at: <http://www.fao.org/docrep/003/x6931e/X6931E00.htm#TOC>
[Accessed 21 November 2012].
Bio Fuel Cells Concepts for Local Energy. (2000). Anaerobic Digestion Applications - The Use
of Pig Slurry. [online] Available at:
<http://www.esru.strath.ac.uk/EandE/Web_sites/9900/bio_fuel_cells/groupproject/library/applications/pageframe.htm> [Accessed 19
July 2012].
Biogas a Renewable Biofuel. (2011). Feedstocks for Biogas Production. [online] Available at:
<http://biogas.ifas.ufl.edu/feedstocks.asp> [Accessed 27 June 2012].
Biogas Process for Sustainable Development. (1992). Chapter Seven: Anaerobic Processes,
Plant Design and Control. [online] Available at:
<http://www.fao.org/docrep/T0541E/T0541E09.htm> [Accessed 18 July 2012].
152
References
Biogas Technologies. (2012). Building a Biogas Plant. [online] Available at:
<http://www.fluid-biogas.com/?page_id=137&lang=en> [Accessed 2 July 2012].
Biogas Training Center. (2011). Design of Biogas Plant. [pdf] Sichuan: Biogas Training
Center. Available at: <http://www.lgedrein.org/archive_file/publications_Design%20Biogas%20Plant.pdf> [Accessed 26
June 2012].
Biomass Energy Center. (2011). Animal slurry and farmyard manure. [online] Available at:
<http://www.biomassenergycentre.org.uk/portal/page?_pageid=75,17978&_dad=p
ortal&_schema=PORTAL> [Accessed 27 June 2012].
Bond, T. and M. R. Templeton. (2011). History and Future of Domestic Biogas Plants in the
Developing World. Elsevier Inc., 15 (2): 347 - 354.
British Biogen. (2000). Anaerobic Digestion of Farm and Food Processing Residues - Good
Practice Guidelines. [pdf] London: British Biogen. Available at:
<http://www.mrec.org/biogas/adgpg.pdf> [Accessed 11 July 2012].
BSRIA. (2010). Making CHP ‘do-able’. *online+ Available at:
<http://blogs.bsria.co.uk/category/chp/> [Accessed 18 August 2012].
Budhijanto, W.; C. W. Purnomo and N. C. Siregar. (2012). Simplified Mathematical Model for
Quantitative Analysis of Biogas Production Rate in a Continuous Digester. Eng. J., 16 (5):
165 - 176.
Bulletin of the International Dairy Federation. (2010).A common Carbon Footprint
Approach for Dairy. The IDF Guide to Standard Lifecycle Assessment Methodology
for Dairy Sector. [pdf] Brussels: International Dairy Federation. Available at:
<http://www.idf-lca-guide.org/Files/media/Documents/445-2010-A-commoncarbon-footprint-approach-for-dairy.pdf> [Accessed 5 September 2012].
Buxton, B. (2010). Using Biogas Technology to Solve Pit Latrine Waste Disposal Problems.
[pdf] Warwickshire: The Schumacher Centre for Technology and Development.
Available at: <http://practicalaction.org/using-biogas-technology-to-solve-pitlatrine-waste-disposal> [Accessed 3 August 2012].
Campiotti, C.; C. Bibbiani; F. Dondi; M. Scoccianti and C. Viola. (2011). Energy Efficiency
and Photovoltaic Solar for Greenhouse Agriculture. J. of sustainable energy, 2 (1): 51
- 56.
Campiotti, C.; C. Viola; G. Alonzo; C. Bibbiani; G. Giagnacovo; M. Scoccianti and G.
Tumminelli. (2012). Sustainable Greenhouse Horticulture in Europe. J. of
sustainable energy, 3 (3): 728 - 732.
Centre, A. and G. Redman. (2010). A Detailed Economic Assessment of Anaerobic Digestion
Technology and Its Suitability to UK Farming and Waste Systems. 2nd ed. NNFCC,
Leicestershire, UK. 135 p.
Centre for Energy Studies Institute of Engineering. (2001). Advanced Course in Biogas
Technology. [pdf] Lalitpur: Centre for Energy Studies Institute of Engineering, Nepal.
153
References
Available at:
<http://www.snvworld.org/sites/www.snvworld.org/files/publications/advanced_c
ourse_in_biogas_technology_nepal_2001.pdf > [Accessed 3 August 2012].
Ciborowski, P. (2001). Anaerobic Digestion of Livestock Manure for Pollution Control and
Energy Production: A Feasibility Assessment. [pdf] Minnesota: Minnesota Pollution
Control Agency. Available at:
<http://www.pca.state.mn.us/index.php/component/option,com_docman/task,doc
_view/gid,9244> [Accessed 18 July 2012].
Cioabla, A. E.; I. Ionel; G. A. Dumitrel and F. Popescu. (2012). Comparative Study on Factors
Affecting Anaerobic Digestion of Agricultural Aegetal Residues. J. of Biotec. for
Biofu., 5 (39).
Commercial Energy Advisor. (2008). Managing Energy Costs in Dairy Farm Facilities. [pdf]
Providence: Companies LLC. Available at:
<http://www.esource.com/BEA/demo/PDF/CEA_10_DairyFarms.pdf> [Accessed 13
December 2012].
Covered Lagoon. (2003). Covered Lagoon. [online] Available at:
<http://www.coveredlagoon.com/> [Accessed 9 August 2012].
Crolla, A. and C. Kinsley. (2011). Background on Anaerobic Digestion at the Farm. [pdf]
Ontario: Ontario Rural Wastewater Centre, Université de Guelph-Campus d’Alfred.
Available at:
<http://www.orwc.uoguelph.ca/Research/documents/InfoSheet_AD%20Basics.pdf>
[Accessed 2 July 2012].
CRPA. (2011). Zootecnia. [online] Available at:
<http://www.crpa.it/nqcontent.cfm?a_id=2558&tt=crpa_www> [Accessed 25
August 2012].
Delaval Global. (2012). Types of Manure. [online] Available at:
<http://www.delaval.com/en/-/Product-Information1/Manure/Manuresolutions/Types-of-manure/> [Accessed 27 June 2012].
Dennis, A. and P.E. Burke. (2001). Dairy Waste Anaerobic Digestion Handbook.
Environmental Energy Company, 6007 Hill St., Olympia, WA 98516, USA. 57 p.
Department of Environmental Protection. (2009). Field Workshop at Dairy Farm. [online]
Available at: <http://www.ct.gov/dep/cwp/view.asp?A=2720&Q=450230>
[Accessed 6 August 2012].
Department of Primary Industries. (2010). Feeding cattle. [online] Available at:
<http://www.dpi.vic.gov.au/agriculture/farming-management/fire-flood-otheremergencies/drought-information/drought-a-guide-for-farmers/chapter-5>
[Accessed 7 November 2012].
Dewil, R.; J. Lauwers; L. Appels; G. Gins; J. Degrève and J. V. Impe. (2011). Anaerobic
Digestion of Biomass and Waste: Current Trends in Mathematical Modeling. In:
154
References
(Preprints of the 18th IFAC World Congress), August 28th - September 2th. Milano:
Italy.
Dimpl, E. and M. Blunck. (2011). Reality Check: Biomass as a Fuel for Small-Scale Electricity
Supply in Developing Countries. In: (Technische Universität Berlin), Micro
Perspectives for Decentralized Energy Supply. Berlin, Germany 7th - 8th of April 2011.
Berlin: Germany.
DIRECTINDUSTRY. (2012). Dual fuel diesel / biogas engine. [online] Available at:
<http://www.directindustry.com/prod/guascor-power/dual-fuel-diesel-biogasengines-23116-435030.html> [Accessed 17 August 2012].
Dong, H.; J. Mangino; T. A. McAllister; J. L. Hatfield; D. E. Johnson; K. R. Lassey; M. A. Lima
and A. Romanovskaya. (2006). IPCC Guidelines for National Greenhouse Gas
Inventories. Vol. 4: Agriculture, Forestry and Other Land Use. Chapter 10: Emissions
from Livestock and Manure Management. [pdf] Geneva: IPCC. Available at:
<http://www.ipccnggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_10_Ch10_Livestock.pdf>
[Accessed 26 August 2012].
Donoso-Bravo, A; C. Retamal; M. Carballa; G. Ruiz-Filippi and R. Chamy. (2009). Influence
of Temperature on the Hydrolysis, Acidogenesis and Methanogenesis in Mesophilic
Anaerobic Digestion: Parameter Identification and Modeling Application. Water Sci.
& Techno. (WST), 60 (1): 9 - 17.
EC&M. (2002). Standard 1459-2000: A New Way to Measure Power. [online] Available at:
<http://ecmweb.com/power-quality-archive/standard-1459-2000-new-waymeasure-power> [Accessed 7 November 2012].
Ecochem. (2011). Manure is an Excellent Fertilizer. [online] Available at:
<http://www.ecochem.com/t_manure_fert.html> [Accessed 10 November 2012].
Electrigaz Technologies Inc. (2007). Feasibility Study – Anaerobic Digester and Gas
Processing Facility in the Fraser Valley, British Columbia. [pdf] British Columbia:
Electrigaz Technologies Inc. Available at:
<http://www.lifesciencesbc.ca/files/PDF/Fraser_Valley_feasibility_study_anaerobic.
pdf> [Accessed 6 August 2012].
ENEA. (2010). Renewable Energy Sources. [online] Available at:
<http://old.enea.it/com/ingl/New_ingl/research/energy/RenewableEnergySources.
html> [Accessed 1 August 2012].
Esfandiari, S.; R. Khosrokhavar and M. Sekhavat . (2011). Greenhouse Gas Emissions
Reduction through a Biogas Plant: A Case Study of Waste Management Systems at
FEKA Dairy Farm. J of IPCBEE, 6 (1): 445 - 448.
European Biomass Association. (2009). A Biogas Road Map for Europe. [pdf] Brussels:
European Biomass Association. Available at:
<http://www.aebiom.org/IMG/pdf/Brochure_BiogasRoadmap_WEB.pdf> [Accessed
11 July 2012].
155
References
European Parliament. (2002). Regulation (EC) No. 1774/2002 of the European Parliament
and of the Council of 3 October 2002 laying down health rules concerning animal
by-products not intended for human consumption.
European Waste Catalogue. (2009). Environment Agency. Secretary of State for
Environment, Food and Rural Affairs, Wales, UK.56 p.
Eurostat. (2012). Glossary: Livestock Unit. [online] Available at:
<http://epp.eurostat.ec.europa.eu/statistics_explained/index.php/Glossary:LSU>
[Accessed 6 November 2012].
Extension. (2011). Manure Production and Characteristics. [online] Available at:
<http://www.extension.org/pages/15375/manure-production-and-characteristics>
[Accessed 27 June 2012].
EXTENSION. (2012). Types of Anaerobic Digesters. [online] Available at:
<http://www.extension.org/pages/30307/types-of-anaerobic-digesters> [Accessed
11 August 2012].
FAO. (1996). Biogas Technology: A Training Manual for Extension. [pdf] Kathmandu: FAO.
Available at:
<http://www.sswm.info/sites/default/files/reference_attachments/FAO%201996%
20Biogas%20Technology%20A%20Training%20Manual%20for%20Extension.pdf>
[Accessed 3 August 2012].
Fiorese, G.; G. Guariso and A. Polimeni. (2008). Optimizing Production of Biogas: an
Application to an Italian Farming District. In: (International Congress on
Environmental Modeling and Software Integrating Sciences and Information
Technology for Environmental Assessment and Decision Making), 4th Biennial
Meeting of iEMSs 2008 - Spain. Barcelona, Catalonia 7th - 10th of July 2008.
Catalonia: Spain.
FLOTECH. (2010). Biogas Upgrading. [online] Available at:
<http://www.flotech.com/biogas.htm> [Accessed 19 August 2012].
Frandsen, T.; Q. Rodhe; L. Baky; A. Edström; M. Sipilä; I. K. Petersen and S.L. Tybirk.
(2011). Best Available Technologies for Big Manure Biogas Plants in the Baltic Sea
Region. Baltic Sea 2020, Stockholm. 159 p.
Für Mikrofonaufnahmetechnik und Tonstudiotechnik. (2002). Electric Current. [online]
Available at: < http://www.sengpielaudio.com/calculator-ohm.htm> [Accessed 7
November 2012].
Gaillard G.; P. Crettaz and J. Hausheer. (1997). Umweltinventar der landwirtschaftlichen
Inputs im Panzenbau. FAT 46 Schriftenreihe der Eidg. Forschungsanstalt für
Agrarwirtschaft und Landtechnik CH-8356 Tänikon TG.
Gas Turbines. (2008). What is Gas turbine?. [online] Available at:
<http://www.ustudy.in/node/1165> [Accessed 17 August 2012].
156
References
Genesis Projects Corp. (2007). Anaerobic Digestion: A Cost-effective and Environmentally
Safe Option for the Disposal of Livestock Waste Tissue. [pdf] Calgary: Genesis
Projects Corp. Available at:
<http://www.iafbc.ca/funding_available/programs/livestock/documents/LWTI11_Anaerobic%20Report.pdf> [Accessed 6 August 2012].
Gottstein, M. (2010). Sheep Farm Management Notes. [online] Available at:
<http://www.teagasc.ie/newsletters/farmingtips/2010/sheep-20100518.asp>
[Accessed 25 June 2012].
Grieg-Gran, M.; M. Chambwera; B. Kantor and T. Corral. (2009). Technology Reference
Manual. [pdf] Washington, DC: World Bank. Available at:
<http://siteresources.worldbank.org/INTCARBONFINANCE/Resources/Technology_
manual_cd.pdf> [Accessed 30 July 2012].
Hall, J. B.; W. William and S. M. Baker. (2009). Nutrition and Feeding of the Cow-Calf Herd:
Production Cycle Nutrition and Nutrient Requirements of Cows, Pregnant Heifers
and Bulls. [Online] Available at: <http://pubs.ext.vt.edu/400/400-012/400012.html> [Accessed 25 November 2012].
Harris, B. (1997). Nutrient Requirements of Dairy Cattle. [pdf] Florida: Institute of Food and
Agricultural Sciences, University of Florida. Available at:
<http://mysrf.org/pdf/pdf_dairy/cow_handbook/dc16.pdf > [Accessed 7 November
2012].
HAZEN AND SAWYER. (2012). Digester Gas Usage Optimization: The Moores Creek WWTP.
[online] Available at: <http://www.hazenandsawyer.com/work/projects/LFGmoores-creek-wwtp/> [Accessed 18 August 2012].
Hollis, G. (2012). PorkNet Ask an Expert. [online] Available at:
<http://www.livestocktrail.illinois.edu/porknet/questionDisplay.cfm?ContentID=52
01> [Accessed 25 June 2012].
Hopwood, L. (2011). Farm-Scale Anaerobic Digestion Plant Efficiency. [pdf] York: NNFCC.
Available at: <http://www.swarmhub.co.uk/downloads/pdf/Farm_Scale_AD.pdf>
[Accessed 25 June 2012].
Hörndahl, T. (2008). Energy Use in Farm Buildings. Swedish University of Agricultural
Sciences, Stockholm, Sweden. 59 p.
Huhnke, R. L. (1990). Bunker Silo Sizing and Management. [pdf] Oklahoma: Oklahoma
Cooperative Extension Service. Available at:
<http://pods.dasnr.okstate.edu/docushare/dsweb/Get/Document-2266/BAE1011web.pdf> [Accessed 11 November 2012].
Huisman, H.; F. Marree and M. Nijboer. (2007). Biogas: Viable or Not?. [pdf] Utrecht:
University of Utrecht. Available at:
<http://www.snvworld.org/sites/www.snvworld.org/files/publications/biogas_viabl
e_or_not_feasibility_study_tanzania_2007.pdf> [Accessed 30 July 2012].
157
References
Hyper Physics. (2000). Specific Heat. [online] Available at: <http://hyperphysics.phyastr.gsu.edu/hbase/thermo/spht.html> [Accessed 7 November 2012].
Institut für Energetik und Umwelt gMmbH, Bundesforschunungsanstalt für Landwirtschaft
& Kuratorium für Technik und Bauwesen in der Landwirtschaft e. V. (2006).
Handreichung – Biogasgewinnung und – nutzung. 3., überarbeitete Auflage. Gülzow,
Germany. 235 p.
Irish Farmers Journal. (2011). Germany Paying Farmers to De-gas Slurry. [online] Available
at: <http://www.farmersjournal.ie/site/farming-Germany-paying-farmers-to-degas-slurry-14339.html> [Accessed 17 July 2012].
ITABIA. (2009). La bioenergia. [online] Available at: <http://www.itabia.it/bioenergia.php>
[Accessed 20 August 2012].
Jacobs, J. (2002). Feeding Dairy Cows. 3nd Ed. Department of Natural Resources and
Environment, Victoria, USA. 264 p.
Kaiser, A. G.; J. W. Piltz; H. M. Burns and N. W. Griffiths. (2004). Successful Silage. 2nd ed.
Dairy Australia and New South Wales Department of Primary Industries, New South
Wales, Australia. 468 p.
Karellas, S.; L. Boukis and G. Kontopoulos. (2010). Development of an Investment Decision
Tool for Biogas Production from Agricultural Waste. Elsevier Ltd., 14 (10): 1273–
1282.
Kirchmeyr, F.; E. Rose; H. Hahn; B. Kulisic and D. Rutz. (2009). Capacity Building for
Administrative bodies Regarding the Implementation of Biogas Projects. [pdf]
Brussels: European Biogas Association. Available at:
<http://www.biogasin.org/files/pdf/WP3/D.3.3_EBA_EN.pdf> [Accessed 6 August
2012].
Knitter, T.; B. Caslin and J. Finnan. (2010). Anaerobic Digestion. [pdf]. Carlow: TEAGASC.
Available at:
<http://www.teagasc.ie/publications/2010/867/867_AnaerobicDigestion.pdf>
[Accessed 25 June 2012].
Kossmann, W.; U. Pönitz; S. Habermehl; T. Hoerz; P. Krämer; B. Klingler; C. Kellner; T.
Wittur; F. v. Klopotek; A. Krieg and H. Euler. (1999). Biogas Digest. Volume I and II.
German Agency for Technical Cooperation (GTZ), Germany.
Kramer, J. M. (2004). Agricultural Biogas Casebook. Resource Strategies, Inc. Wisconsin,
USA. 69 p.
KWS. (2012). Forage Maize - Silage Quality. [online] Available at: <http://www.kwsuk.com/aw/KWS/united_kingdom/Information1/Product_Development/Sugar_Bee
t/~cqti/Silage_Quality/> [Accessed 27 June 2012].
Lampinen, A. (2005). Bioenergy Technology Evaluation and Potential in Costa Rica. Research
Reports in Biological and Environmental Sciences, no. 81. University of Jyväskylä
Printing House. Jyväskylä, Finland. 92 p.
158
References
Landry, H.; C. Laguë; M. Roberge and M. T. Alam. (2002). Physical and Flow Properties of
Solid and Semi-solid Manure as Related to the Design of Handling and Land
Application Equipment. [pdf]. Mansonville: CSAE/SCGR. Available at:
<http://www.engr.usask.ca/societies/csae/PapersAIC2002/CSAE02-214.pdf>
[Accessed 26 June 2012].
Lehtomäki, A. (2006). Biogas Production from Energy Crops and Crop Residues. [pdf]
JYVÄSKYLÄ: University of JYVÄSKYLÄ . Available at:
<https://jyx.jyu.fi/dspace/bitstream/handle/123456789/13152/9513925595.pdf?se
quence> [Accessed 28 June 2012].
Lfu. (2007). Biogashandbuch Bayern. Materialband. Bayerisches Landesamt für Umwelt,
Augsburg, Germany. 90 p.
Lindmark, J. (2005). The Biogas Optimization Project. School of Sustainable Development of
Society and Technology. Mälardalen University, Västerås, Sweden. 75 p.
Lovrenčec, L (2010). Highlights of Socio-economic Impacts from Biogas in 28 Target Regions.
[pdf] Brussels: Razvojna Agencija Sinergija Development Agency. Available at:
<http://www.biogasin.org/files/pdf/Highlights_of_socio-economic%20issues.pdf >
[Accessed 24 December 2012].
Lukehurst, C. T.; P. Frost and T. AL SEADI. (2010). Utilization of Digestate from Biogas Plants
as Biofertiliser. [Task 37]. [pdf] Paris: IEA Bioenergy. Available at: <http://www.ieabiogas.net/_download/Digestate_Brochure_Revised_12-2010.pdf> [Accessed 30
July 2012].
Massart, N.; J. Doyle; J. Jenkins; J. Rowan and C. Wallis-Lage. (2008). Anaerobic Digestion –
Improving Energy Efficiency with Mixing. [pdf] Missouri: Water Environment
Federation. Available at: <http://progresse.com/NewTech/BV_ImprovedEnergyEfficiencyWithMixingWEFTEC_08.pdf>
[Accessed 18 July 2012].
Mickan, F. (2006).How Much Silage in My Stack?. [pdf]. Victoria: Top Fodder Silage.
Available at:
<http://hayday.biz/silage_info/how_much_silage_in_stack_hb_comments200605.p
df> [Accessed 25 June 2012].
Miller, S. J. (2007). An Introduction to Linear Programming. [pdf] Providence: Mathematics
Department, Brown University. Available at:
<http://web.williams.edu/Mathematics/sjmiller/public_html/416/currentnotes/Lin
earProgramming.pdf> [Accessed 1 November 2012].
Miner, W. H.; C. S. Ballard; E. D. Thomas; K. W. Cotanch; J. W. Darrah and S. Kramer.
(2005). The Use of Bio-augmentation to Reduce Odor and Liquefy Solids in Stored
Dairy Manure. [pdf] Chazy: Agricultural Research Institute. Available at:
<http://www.whminer.com/Research/WHM-05-2.pdf > [Accessed 26 June 2012].
MLA. (2012). Nutrition. [online] Available at: < http://www.wpowerproducts.com/electricalpower-calculator.php> [Accessed 7 November 2012].
159
References
Monnet, F. (2003). An Introduction to Anaerobic Digestion of Organic Wastes. [pdf]
Scotland: Remade Scotland. Available at:
<http://www.biogasmax.co.uk/media/introanaerobicdigestion__073323000_1011_
24042007.pdf> [Accessed 26 June 2012].
Moran, J. (2005). Tropical Dairy Farming. Feeding management for small holder dairy farms
in humid tropics. Landlinks Press, Sydney, Australia. Pp: 51-59.
Nagamani, B. and K. Ramasamy. (1999). Biogas Production Technology: an Indian
Perspective. [online] Available at:
<http://www.iisc.ernet.in/currsci/jul10/articles13.htm> [Accessed 28 June 2012].
Ndegwa, P. M.; D. W. Hamilton; J. A. Lalman and H. J. Cumba. (2005). Optimization of
Anaerobic Sequencing Batch Reactors Treating Dilute Swine Slurries. Trans. of the
ASAE, 48 (4): 1575 - 1583.
Nels. (2011). Anaerobic Digesters. [online] Available at:
<http://www.nelsonelson.com/wiki/index.php?title=Anaerobic_Digesters>
[Accessed 18 July 2012].
NNFCC. (2010). Anaerobic Digestion. [pdf] York: NNFCC. Available at:
<http://large.stanford.edu/courses/2010/ph240/cook2/docs/hopwood.pdf>
[Accessed 25 June 2012].
Nordic Folkecenter. (2010). Farm Biogas Digester. [online] Available at:
<http://www.folkecenter.net/gb/tech-trans/technologies/farm-biogas/> [Accessed
13 August 2012].
Normak, A.; J. Suurpere; K. Orupõld; E. Jõgi and E. Kokin. (2012). Simulation of Anaerobic
Digestion of Cattle Manure. Agro. Res. Biosys. Eng. (special Issue), 1: 167 - 174.
NSW Government. (2010). Heating Greenhouses. [online] Available at:
<http://www.dpi.nsw.gov.au/agriculture/horticulture/greenhouse/structures/heati
ng> [Accessed 1 October 2012].
Ohio State University Extension. (2006). Ohio Livestock Manure Management Guide. [pdf]
Ohio: Ohio State University Extension. Available at:
<http://ohioline.osu.edu/b604/pdf/b604.pdf> [Accessed 26 June 2012].
Ontario. (2011). Biogas Production - Lessons Learned from Europe. [online] Available at:
<http://www.omafra.gov.on.ca/english/livestock/beef/news/vbn1006a1.htm >
[Accessed 12 August 2012].
Patel, H. A. (2006). Anaerobic Digestion - A Renewable Energy Resource. [pdf]
Leicestershire: Leicestershire Country Council. Available at:
<http://www.leics.gov.uk/supplementary_ad_report-2.pdf> [Accessed 11 July
2012].
Philip, R. (2005). Anaerobic Digester Systems for Mid-Sized Dairy Farms. [pdf] Minnesota:
The Minnesota Project. Available at:
160
References
<http://permitools.wikispaces.com/file/view/Anaerobic+Digester+Systems+for+Mid
-Sized+Dairy+Farms.pdf> [Accessed 3 August 2012].
Plöchl, M. and M. Heiermann. (2006). Biogas Farming in Central and Northern Europe: A
Strategy for Developing Countries?. Agri. Eng. Inter.: the CIGR Ejournal. Invited
Overview, No. 8. Vol. VIII.
Purdue Dairy Page. (2012). Purdue Dairy Facilities. [online] Available at:
<http://www.extension.purdue.edu/dairy/facility/facility.htm> [Accessed 6 August
2012].
Ragazzoni, A. (2011). Biogas: normative e biomasse: le condizioni per fare reddito. Edizioni
L'informatore agrario, Verona, Italy. 144 p.
Rapport, J.; R. Zhang; B. M. Jenkins and R. B. Williams. (2008). Current Anaerobic Digestion
Technologies Used for Treatment of Municipal Organic Solid Waste. California
Environmental Protection Agency, California, USA. 90 p.
REHAU. (2010). Rehau Solutions for Anaerobic Digestion Plants. [pdf] London: REHAU.
Available at:
<http://www.rehau.co.uk/files/REHAU_Biogas_Sales_Brochure_UK.pdf> [Accessed
11 July 2012].
Rosenthal, R. E. (2012). GAMS - A User's Guide. GAMS Development Corporation,
Washington, DC, USA. 312 p.
Rosillo-Calle, F.; P. Groot; S. L. Hemstock and J. Woods. (2007). The Biomass Assessment
Handbook. Earthscan. London, UK. 276 p.
Ross, D. S. (2001). Planning and Building a Greenhouse. Fact Sheet 645 - University of
Maryland Cooperative Extension Service. [online] Available at:
<http://www.wvu.edu/~agexten/hortcult/greenhou/building.htm> [Accessed 1
October 2012].
Saev, M.; B. Koumanova and I. Simeonov. (2009). Anaerobic Co-digestion of Wasted
Tomatoes and Cattle Dung for Biogas Production. J. of the Univ. of Chemi. Techno.
and Metallurgy, 44 (1): 55 - 60.
Sasse, L . (1988). Biogas Plants. GTZ, Germany. 66 p.
SATTLER AG & Ceno Membrane Technology GmbH. (2010). Biogas storage tanks. [pdf]
Rudersdorf: SATTLER AG & Ceno Membrane Technology GmbH. Available at:
<http://www.sattler-ag.com/sattler-web/static/media/pdf/Broschuere_UT_EN.pdf>
[Accessed 15 August 2012].
Schulze, M. A. (1998). Linear Programming for Optimization. [pdf] Providence: Perceptive
Scientific Instruments, Inc. Available at:
<http://www.markschulze.net/LinearProgramming.pdf> [Accessed 12 November
2012].
161
References
Shokri, S. (2011). Biogas Technology, Applications, Perspectives and Implications. Inter. J. of
Agri. Sci. and Res., 2 (3): 53 - 60.
Spliethoff, H. and A. Schuster. (2006). The Organic Rankine Cycle – Power Production from
Low Temperature Heat. [pdf] Strasbourg: Technische Universiat Munchen. Available
at: <http://engine.brgm.fr/web-offlines/conferenceElectricity_generation_from_Enhanced_Geothermal_Systems__Strasbourg,_France,_Workshop5/other_contributions/40-slides-0-Spliethoff.pdf>
[Accessed 19 August 2012].
Steffen, R.; O. Szolar and R. Braun. (1998). Feedstock for Anaerobic Digestion. [pdf] Vienna:
Institute for Agro-bio-technology Tulln, University of Agricultural Sciences Vienna.
Available at: <http://www.adnett.org/dl_feedstocks.pdf> [Accessed 27 June 2012].
Stewart, P. G.; R. I. Jones and T. J. Dugmore. (2005). Practical Feeding of the Dairy Cow.
[Online] Available at:
<http://agriculture.kzntl.gov.za/portal/AgricPublications/ProductionGuidelines/Dair
yinginKwaZuluNatal/PracticalFeedingoftheDairyCow/tabid/250/Default.aspx>
[Accessed 21 November 2012].
Strohbehn, D. and D. Loy. (2007). Feeding Drought Corn Silage to Beef Cows. [pdf] Iowa:
Extension Livestock Specialists, Iowa State University. Available at:
<http://www.beefusa.org/CMDocs/BeefUSA/Resources/NC_Dec_07manFeedingDroughtC.pdf > [Accessed 26 November 2012].
Subramani, T. and M. Nallathamb. (2012). Mathematical Model for Commercial Production
of Biogas from Sewage Water and Kitchen Waste. Inter. J. of Mod. Eng. Res. (IJMER),
2 (4): 1588 - 1595.
TATEDO. (2009). Biogas Technology Construction, Utilization and Operation Manual. [pdf]
Dar Es Salaam: Tanzania Traditional Energy Development and Environment
Organization (TATEDO). Available at: <http://www.ease-web.org/wpcontent/uploads/2009/08/BIOGAS-MANUAL.pdf> [Accessed 11 November 2012].
The Dow Chemical Company. (2012). Silage Insights - Pre-wilting and How to Estimate Dry
Matter Content of Grass Silages. [online] Available at:
<http://www.dow.com/silage/resource/prewilting.htm> [Accessed 27 June 2012].
The Engineering Tool Box. (2010). Water - Thermal Properties. [online] Available at:
<http://www.engineeringtoolbox.com/water-thermal-properties-d_162.html>
[Accessed 7 November 2012].
The Merck Veterinary Manual. (2010). Nutritional Requirements. [online] Available at:
<http://www.merckvetmanual.com/mvm/index.jsp?cfile=htm/bc/182303.htm >
[Accessed 7 November 2012].
Timmerman, M. and W. Rulkens. (2010). Managing Phosphorus Cycling in Agriculture Pretreatment of Manure. [pdf] Wageningen: Dutch Ministry of Economic Affairs,
Agriculture and Innovation. Available at:
162
References
<http://www.mestverwerken.wur.nl/info/bibliotheek/pdf/BO-12.02-infoblad26.pdf> [Accessed 17 July 2012].
United States Department of Agriculture. (2007). An Analysis of Energy Production Costs
from Anaerobic Digestion Systems on U.S. Livestock Production Facilities. [pdf]
Washington: United States Department of Agriculture. Available at:
<http://faculty.apec.umn.edu/wlazarus/documents/TN_BIME_1_a.pdf > [Accessed
19 July 2012].
Vindis, P.; B. Mursec ; M. Janzekovic and F. Cus. (2009). The Impact of Mesophilic and
Thermophilic Aanaerobic Digestion on Biogas Production. J. of Achiev. in Mater.
and Manufact. Eng., 36 (2): 192 - 198.
Vindiš, P.; D. Stajnko; P. Berk and M. Lakota. (2012). Evaluation of Energy Crops for Biogas
Production with a Combination of Simulation Modeling and Dex-i Multicriteria
Method. Pol. J. Environ. Stud., 21 (3): 763 - 770.
Vitali, G; G. Bazzani; C. Signorotti; S. Albertazzi; G. Baldoni; N. Cantore; M. Canavari; C.
Cardillo; M. D. Chiara and A. Trisorio. (in press). MAD. Bologna, Bologna University.
Vogelsang. (2012). Drehkolbenpumpen. [online] Available at:
<http://www.vogelsang.info/pumps/ > [Accessed 6 August 2012].
Wam India Private Limited. (2012). Screw Conveyors & Feeders. [online] Available at:
<http://2.imimg.com/data2/VV/VK/MY-291005/biomass-conveying-system.pdf >
[Accessed 7 August 2012].
Wand, C. and P. Doris. (2011). Managing Outdoor Confinement Areas and Livestock Yards.
[online] Available at: <http://www.omafra.gov.on.ca/english/engineer/facts/11007.htm> [Accessed 6 November 2012].
WBDC. (2012). Microturbines. [online] Available at:
<http://www.wbdg.org/resources/microturbines.php/> [Accessed 18 August 2012].
Wellinger, A. (1999). Process Design of Agricultural Digesters. [pdf] Ettenhausen: Nova
Energie GmbH. Available at:
<http://homepage2.nifty.com/biogas/cnt/refdoc/whrefdoc/d14prdgn.pdf>
[Accessed 14 July 2012].
Werner, U.; U. Stöhr and N. Hees. (1989). Biogas Plants in Animal Husbandry. GTZ,
Germany. 134 p.
Westerma, P.; M. Veal; J. Cheng and K. Zering. (2008). Biogas Anaerobic Digester
Considerations for Swine Farms in North Carolina. [pdf] North Carolina: North
Carolina Cooperative Extension. Available at:
<http://www.bae.ncsu.edu/programs/extension/manure/energy/digester.pdf>
[Accessed 19 July 2012].
What Size Digester Do I Need. (1996). The Biogas Calculation. [online] Available at:
<http://dspace.dial.pipex.com/town/terrace/ae198/Digestergoldsizeperformanc.ht
ml> [Accessed 18 July 2012].
163
References
Wilo Mixers. (2011). Submersible Mixers. [online] Available at: <http://www.wilousa.com/cps/rde/xbcr/us-en/Submersible_Mixers_Brochure_12-11.pdf> [Accessed
13 August 2012].
World Energy Outlook. (Anon. 2010). The International Energy Agency (IEA). IEA
Publications. Paris, France. 738 p.
Worldwide Power Products. (2008). Electrical Power Calculator. [online] Available at: <
http://www.wpowerproducts.com/electrical-power-calculator.php> [Accessed 7
November 2012].
WTERT. (2009). Anaerobic Digestion Process. [online] Available at:
<http://www.wtert.eu/default.asp?Menue=13&ShowDok=12> [Accessed 1 August
2012].
www.fueleconomy.gov. (2012). How Fuel Cells Work. [online] Available at:
<http://www.fueleconomy.gov/feg/fcv_PEM.shtml> [Accessed 18 August 2012].
Xie, S.; P.G. Lawlor; J.P. Frost; Z. Hu and X. Zhan. (2011). Effect of Pig Manure to Grass
Silage Ratio on Methane Production in Batch Anaerobic Co-digestion of
Concentrated Pig Manure and Grass Silage. Elsevier Ltd., 102 (10): 5728 - 5733.
Zaher, U; D. Cheong; B. Wu, and S. Chen. (2007). Producing Energy and Fertilizer from
Organic Municipal Solid Waste. [pdf] Washington DC: Department of Biological
Systems Engineering, Washington State University. Available at:
<https://fortress.wa.gov/ecy/publications/publications/0707024.pdf> [Accessed 12
July 2012].
ZORG. (2012). Dry Fermentation. [online] Available at: <http://zorg-biogas.com/biogasplants/dry_fermentation?lang=en> [Accessed 11 August 2012].
164
Appendices
8. APPENDICES
Table 8.1: Surface area required per livestock unit for different on-farm breeding and
production facilities (paved or concrete surface) (author elaboration cited in
Wand and Doris, 2011)
zo
27
28
27
aluzo (ha / lsu)
Dairy cattle
0.002
Non-dairy cattle
0.0012
Buffaloes
0.0012
Pigs
0.0005
28
Zoo index
Surface area required per livestock unit for different breeding and production facilities
165
Appendices
Table 8.2: Nutrition required for livestock unit in terms of diet nutrients (author elaboration
cited in Belloin, 1988; Stewart et al., 2005 and Hall et al., 2009)
Fdzzo,di
30
29
31
zo
(fu / lsu . year)
(cp / lsu . year)
Dairy cattle
3000
760
Non-dairy cattle
2000
420
Buffaloes
2000
420
Pigs
425
110
29
Nutrition required for livestock unit in terms of diet nutrients, based on dry matter content
fu = Forage unit, is a forage value of 1 kg of barley (unit)
31
cp = Crude protein (kg)
30
166
Appendices
Table 8.3: Available nutrition for livestock from on-farm production of forage crops (author
elaboration cited in Balliette, 1998 and Strohbehn and Loy, 2007)
fdscz,di
32
33
fu / ton
pr / ton
Alfalfa
210
175
Maize
150
90
Sorghum
220
83
cz
32
Nutrients content of forage crops available for animal feeding in terms of diet nutrients, based on dry matter
content
33
Forage crop index
167
Appendices
Table 8.4: Nutrition purchased for livestock from market (author elaboration cited in
Balliette, 1998 and Strohbehn and Loy, 2007)
34
fdmcm,di
cm
35
fu / ton
pr / ton
Alfalfa
210
175
Maize
150
90
Sorghum
220
83
34
Nutrients content of diet feedstock purchased from market for livestock feeding in terms of diet nutrients,
based on dry matter content
35
Market diet index
168
Appendices
Table 8.5: Thermal energy required for warming different greenhouse areas in Italy (author
elaboration cited in Campiotti et al., 2011)
36
Climate area
eth (kWhth / ha . year)
South
14375
Middle
21750
North
26250
West coast
10000
36
Thermal energy required for greenhouses warming
169
Appendices
Table 8.6: Thermal energy required for livestock unit (author elaboration cited in Hörndahl,
2008)
37
zo
etlzo (kWhth / lsu . year)
Dairy cattle
700
Non-dairy cattle
500
Buffaloes
500
Pigs
150
37
Thermal energy required for livestock unit
170
Appendices
Table 8.7: Electrical energy required for different greenhouse areas in Italy (author
elaboration cited in Campiotti et al., 2011)
38
climate area
eeh (kWhel / ha . year)
South
16000
Middle
11000
North
9000
West coast
26000
38
Electrical energy required for greenhouses
171
Appendices
Table 8.8: Electrical energy required for livestock unit (author elaboration cited in
Commercial Energy Advisor, 2008)
39
zo
eelzo (kWhel / lsu . year)
Dairy cattle
1000
Non-dairy cattle
550
Buffaloes
550
Pigs
95
39
Electrical energy required for livestock unit
172
Appendices
Table 8.9: Total number of workers required for operate on-farm biogas system (author
elaboration cited in Lovrenčec, 2010)
EET (kWhel / year)
6
2
40
41
40
lre (worker / kWhel)
41
-7
5
Total net productive capacity of electrical energy from on-farm CHP unit of biogas
Number of workers required for biogas system in terms of workers required for produced electrical energy
unit
173
Appendices
Table 8.10: Total mass of on-farm fresh silage available for livestock feeding and biogas
production (author elaboration cited in Kaiser et al., 2004 and Mickan, 2006)
cz
42
43
44
MSFcz (ton / ha. year)
ce
MSGce (ton / ha. year)
Alfalfa
50
Alfalfa
50
Maize
40
Maize
40
Sorghum
40
Sorghum
40
45
42
Silage crop index for livestock feeding
Mass of fresh silage from different on-farm crops available for livestock feeding
44
Energy crop index
45
Mass of fresh silage from different on-farm crops available for biogas production
43
174
Appendices
Table 8.11: Mass of on-farm manure slurry available for biogas production (author
elaboration cited in Dong et al., 2006)
46
47
46
zo
almzo (kg of lsu mass / lsu)
smezo (kg of manure slurry / kg of lsu mass . day)
Dairy cattle
600
0.106
Non-dairy cattle
450
0.106
Buffaloes
450
0.106
Pigs
150
0.08
47
Average live mass of livestock unit
Average specific mass of excrements
175
Appendices
Table 8.12: Mass of TS for air-dried silage and manure slurry (author elaboration cited in
Mickan, 2006 and Al Seadi et al., 2008)
48
49
3 48
3 49
ce
tssce (ton / m )
zo
tsmzo (ton / m )
Alfalfa
0.200
Dairy cattle
0.100
Maize
0.192
Non-dairy cattle
0.100
Sorghum
0.192
Buffaloes
0.100
Pigs
0.080
Mass of TS for air-dried silage
Mass of TS for manure slurry
176
Appendices
Table 8.13: Concentration of TS in unmixed substrate (air-dried silage or manure slurry only)
(author elaboration cited in Mickan, 2006 and Al Seadi et al., 2008)
Feedstock
Its (%)
50
Air-dried silage
Alfalfa
77
Maize
74
Sorghum
74
Manure slurry
50
Dairy cattle
10
Non-dairy cattle
10
Buffaloes
10
Pigs
8
Concentration of TS
177
Appendices
Table 8.14: Biogas yield generated, based on biogas yield per mass unit of fresh silage from
energy crops (author elaboration cited in NNFCC, 2009 and Hopwood, 2011)
51
3
ce
gycce (m / ton)
Alfalfa
185
Maize
220
Sorghum
200
51
Biogas yield generated from surface area unit of energy crops
178
Appendices
Table 8.15: Biogas yield generated, based on biogas yield per livestock unit (author
elaboration cited in NNFCC, 2010)
52
3
zo
gylzo (m / lsu . year)
Dairy cattle
580
Non-dairy cattle
435
Buffaloes
435
Pigs
110
52
Biogas yield generated from livestock unit
179
Appendices
Table 8.16: Thermal stages and typical hydraulic retention times (author elaboration cited in
Al Seadi et al., 2008)
sy
53
Psychrophilic
Mesophilic
Thermophilic
53
54
Process temperatures (°C)
hrtsy (day)
< 20
From 30 to 42
From 43 to 55
80
40
20
54
System index
Hydraulic retention time
180
Appendices
Table 8.17: Specific gas yield (author elaboration cited in Biogas Process for Sustainable
Development, 1992)
sy
Psychrophilic
Mesophilic
Thermophilic
55
3
3
sgy (m of biogas / m of total inner-volume of digester. day)
≤ 0.2
From 0.2 to 0.4
From 0.4 to 0.6
55
Specific gas yield
181
Acknowledgment
First I wish to thank my lord Jesus Christ for care, helping and allowing me
to complete this Ph.D. course.
I would like to express my deep thanks to Prof. Ing. Giovanni Molari, for
his sincere supervision, fruitful guidance and encouragement during the
different stages of this course.
Also, I would like to express my deep thanks to Prof. Dr. Giuliano Vitali,
for his sincere supervision, support and helpful advice during the different
stages of this course.
My deep appreciation to Prof. Ing. Adriano Guarnieri, for his precious
guidance, patience and support during this course.
My deep gratitude to Dr. Michele Mattetti, for his insight advice, valuable
time and helping me with Matlab programme.
My deep thanks to Dr. Maria Tancredi,
from D.G.C.S. - Office IIII,
Italian Ministry of Foreign Affairs, for her confidence, support and remove
many of the obstacles related to my scholarship grant.
Deep thanks for all members of Department of Agricultural and Food
Sciences and Technology (DISTAL), Faculty of Agriculture, University of
Bologna.
Last and not least, I would like to express my deepest appreciation and love to
my family, who has always been backing me with love and patience.
Was this manual useful for you? yes no
Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Download PDF

advertisement