EXPLORING MARKET FORCES FOR TRANSMISSION EXPANSION AND GRID STORAGE INTEGRATION

EXPLORING MARKET FORCES FOR TRANSMISSION EXPANSION AND GRID STORAGE INTEGRATION
EXPLORING MARKET FORCES FOR
TRANSMISSION EXPANSION AND
GRID STORAGE INTEGRATION
A technical-economic thesis about variation moderators for intermittent
renewable power generation in the developed country of Sweden and the
developing country of China
ERIKSSON, PERNILLA
SUNDELL, MARTIN
The School of Business, Society and Engineering
Course: Degree Project in Industrial Engineering
and Management
Course Code: FOA402
Subject: Industrial Engineering and Management
Credits: 30.0 credits
Program: Master of Science – Industrial
Engineering and Management
Supervisor: Cecilia Lindh
Examiner: Anette Hallin
Company Supervisor: Stefan Thorburn, ABB
Date: 2015-06-05
E-mail: [email protected]
[email protected]
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ABSTRACT Intermittent renewable power generation increases globally. In Sweden, installed wind power
capacity has increased most of all electricity sources the last few years and China is today the
world’s largest wind power producer. This on-going development increases the demand of
flexible regulating measures to reduce wind curtailment and secure a reliable electricity
supply. Two technical solutions that can provide such flexibility is transmission expansion
and integration of grid battery storage. The transmission grid can transmit energy
geographically, while grid storages have the potential to store energy over time to provide
energy output when necessary.
This master thesis examines market forces for transmission and grid storage development as
variation moderators in a power system containing an increasing share of intermittent
renewable power generation. Two countries with diverse market conditions are studied; a
developed country as Sweden and a developing country as China. Since the market for grid
battery storage is emerging, potential market entry barriers are investigated. A cost-benefit
model has been created to examine which alternative of transmission expansion and lithiumion battery storage integration is the most cost-effective in a system perspective. Several cases
have been studied in the model, including cost reductions of lithium-ion batteries and the
impact of wind curtailment.
Based on the results from the cost-benefit model and the market analysis, it can be concluded
that cost reductions of lithium-ion batteries are crucial for grid storage market penetration.
Another important driving force for future development of grid storage is establishment of a
regulatory framework. Furthermore, grid storage is found to be most suitable for peak shaving
and transmission deferral applications due to its flexibility. The fact that storage facilities can
be realized in a shorter timeframe compared to transmission grid expansion is also an
advantage for grid storage development, since problems related to congestion can be reduced
earlier. However, uncertainties related to the low market experience of grid battery storage
technologies can be in favour for transmission expansion in future investment decisions.
Keywords: Grid storage, energy storage, lithium-ion battery, transmission grid expansion,
variation moderator, variation management, regulating powers, intermittent power
generation, market analysis, market entry barriers, cost-benefit model, cost-benefit analysis,
driving forces, market drivers, China, Sweden, emerging technology, wind curtailment,
congestion.
i
ACKNOWLEDGMENTS
This thesis is a result of the final examination moment for our degree in Master of Science in
Industrial Engineering and Management at Malardalen University in Vasteras, Sweden. The
field of research has been conducted on behalf of ABB Corporate Research in Vasteras,
Sweden, during spring 2015. To further increase the international aspect of the thesis work,
half of the project time was spent at North China Electric Power University in Beijing, China.
We would like to thank all the people who has been involved in this research work and to
some extent contributed to its execution. A special thanks is devoted to the following persons:
PhD. Stefan Thorburn, ABB Corporate Research
Prof. Erik Dahlquist, Malardalen University
PhD. Cecilia Lindh, Malardalen University
PhD. Qiang Lu, North China Electric Power University
Martin Sundell
Vasteras, 2015-06-05
Pernilla Eriksson
Vasteras, 2015-06-05
Figure 1: Martin Sundell and Pernilla Eriksson at North China Electric Power University in Beijing, China
ii
CONTENTS
Introduction ....................................................................................................................... 1
1.1 Background .................................................................................................................. 1
1.1.1
Wind Power Growth............................................................................................. 2
1.1.2
Intermittent Power Generation Challenges .......................................................... 3
1.1.3
Variation Moderators ........................................................................................... 3
1.1.3.1
1.1.3.2
1.2
1.3
1.4
Transmission ............................................................................................................................ 4
Energy Storage ......................................................................................................................... 4
Purpose ........................................................................................................................ 6
Research Questions ..................................................................................................... 6
Expected Contributions ............................................................................................... 7
Methodology ...................................................................................................................... 9
2.1 Research Design and Approach .................................................................................. 9
2.2 Data Collection.......................................................................................................... 10
2.3 Research Approach Quality....................................................................................... 10
2.3.1
Validity and Reliability ...................................................................................... 11
2.4 Cost-Benefit Analysis ................................................................................................. 12
2.4.1.1
Annualized Cost-Benefit Analysis ......................................................................................... 15
Market Conditions .......................................................................................................... 17
3.1 The Swedish Electricity Market ................................................................................. 17
3.1.1
Electricity Generation ........................................................................................ 21
3.1.2
A Competitive Market ........................................................................................ 21
3.1.3
Upcoming Challenges ........................................................................................ 22
3.1.4
Future Scenarios ................................................................................................. 23
3.2 The Chinese Electricity Market ................................................................................. 25
3.2.1
Electricity Generation ........................................................................................ 26
3.2.2
A Controlled Market .......................................................................................... 26
3.2.3
Upcoming Challenges ........................................................................................ 27
3.2.4
Emerging Market................................................................................................ 30
Market Analysis Variation Moderators........................................................................ 33
4.1 Grid Storage .............................................................................................................. 33
4.1.1
Market Entry Barriers......................................................................................... 33
4.1.1.1
4.1.1.2
4.1.1.3
4.1.1.4
4.1.1.5
4.1.1.6
4.1.1.7
4.1.1.8
4.1.1.9
4.1.2
4.1.2.1
4.1.2.2
4.1.2.3
4.1.2.4
4.1.2.5
Ownership Uncertainties ........................................................................................................ 33
Operation Uncertainties .......................................................................................................... 34
Government Policies .............................................................................................................. 35
Product Diversity .................................................................................................................... 36
Competition ............................................................................................................................ 37
Capital Requirements ............................................................................................................. 38
Market Experience.................................................................................................................. 38
Technical Performance ........................................................................................................... 38
Changing Market Conditions.................................................................................................. 39
Market Forces ..................................................................................................... 39
Technology Development ...................................................................................................... 39
Congestion and Security ......................................................................................................... 41
Wind Curtailment ................................................................................................................... 42
Economic Incitements ............................................................................................................ 43
Energy Targets ....................................................................................................................... 44
iii
4.2 Transmission.............................................................................................................. 45
4.2.1
Market Forces Sweden ....................................................................................... 45
4.2.2
Market Forces China .......................................................................................... 47
Cost-Benefit Model ......................................................................................................... 51
5.1 Case Descriptions ...................................................................................................... 51
5.2 Cost Descriptions ...................................................................................................... 52
5.2.1
Investment Cost Transmission ........................................................................... 52
5.2.2
Investment Cost Grid Storage ............................................................................ 53
5.2.3
Reinvestment Costs ............................................................................................ 54
5.2.4
Operation and Maintenance Costs...................................................................... 54
5.2.5
Planning and Construction Cost ......................................................................... 55
5.2.6
Residual Value ................................................................................................... 55
5.3 Benefit Descriptions .................................................................................................. 55
5.3.1
Renewable Energy Time Shifting ...................................................................... 56
5.3.2
Renewable Load Following ............................................................................... 56
5.3.3
Electric Service Reliability................................................................................. 57
5.4 Capacity Constraints ................................................................................................. 57
5.5 Distance Constraints ................................................................................................. 58
5.6 Input Data Sweden..................................................................................................... 59
5.7 Input Data China ....................................................................................................... 62
5.8 Objective Function .................................................................................................... 64
5.9 Constraints................................................................................................................. 64
5.10 Variables .................................................................................................................... 65
5.11 Equations ................................................................................................................... 65
5.12 Results ........................................................................................................................ 66
5.12.1 Sweden ............................................................................................................... 66
5.12.1.1
5.12.1.2
5.12.1.3
5.12.1.4
5.12.1.5
5.12.1.6
5.12.1.7
5.12.1.8
5.12.2
5.12.2.1
5.12.2.2
5.12.2.3
5.12.2.4
5.12.2.5
5.12.2.6
5.12.2.7
5.12.2.8
Case 1 ..................................................................................................................................... 66
Case 2 ..................................................................................................................................... 66
Case 3 ..................................................................................................................................... 67
Case 4 ..................................................................................................................................... 67
Case 5 ..................................................................................................................................... 67
Case 6 ..................................................................................................................................... 67
Case 7 ..................................................................................................................................... 68
Case 8 ..................................................................................................................................... 68
China .................................................................................................................. 68
Case 1 ..................................................................................................................................... 68
Case 2 ..................................................................................................................................... 68
Case 3 ..................................................................................................................................... 69
Case 4 ..................................................................................................................................... 69
Case 5 ..................................................................................................................................... 69
Case 6 ..................................................................................................................................... 69
Case 7 ..................................................................................................................................... 70
Case 8 ..................................................................................................................................... 70
Discussion......................................................................................................................... 72
6.1 Market Conditions ..................................................................................................... 72
6.1.1
Sweden ............................................................................................................... 72
6.1.2
China .................................................................................................................. 73
6.1.3
Market Contrasts ................................................................................................ 74
iv
6.2 Driving Forces ........................................................................................................... 74
6.2.1
Grid Storage ....................................................................................................... 74
6.2.2
Transmission ...................................................................................................... 75
6.3 Cost-Benefit Model .................................................................................................... 77
6.3.1
The Impact of Li-ion Battery Cost Development............................................... 77
6.3.2
The Impact of Residual Value ............................................................................ 77
6.3.3
The Impact of Wind Curtailment ....................................................................... 77
6.3.4
The Impact of Benefits ....................................................................................... 78
6.3.5
Source of Errors ................................................................................................. 79
Conclusions ...................................................................................................................... 81
Future Research .............................................................................................................. 84
APPENDIX
APPENDIX I – CODE COST-BENEFIT MODEL SWEDEN
APPENDIX II – INPUT DATA SWEDEN
APPENDIX III – CODE COST-BENEFIT MODEL CHINA
APPENDIX IV – INPUT DATA CHINA
v
LIST OF FIGURES
Figure 1: Martin Sundell and Pernilla Eriksson at North China Electric Power University in
Beijing, China .............................................................................................................. ii
Figure 2: Installed Wind Capacity in the World, Source: (Global Wind Energy Council, 2014)
...................................................................................................................................... 2
Figure 3: Installed Wind Power top 10 countries 2013 [MW], Source: (Global Wind Energy
Council, 2014) .............................................................................................................. 2
Figure 4: Installed Wind Power Capacity, Source: (The Wind Power, 2013a) ......................... 2
Figure 5: Share of Wind Power Generation Capacity, Source: (U.S. Energy Information
Agency, 2012a) (The Wind Power, 2013b) (The Wind Power, 2013)
(Energimyndigheten, 2014) ......................................................................................... 2
Figure 6: Impacts of wind power on power systems, displayed by time and spatial scales,
Source: (Holttinen, et al., 2011, p. 180) ....................................................................... 4
Figure 7: Predicted cost trends for full automotive Li-ion battery packs. Source: (Climate
Spectator, 2014) ........................................................................................................... 6
Figure 8: Three layers of factors generated by infrastructure project, Source: (THINK, 2013)
.................................................................................................................................... 13
Figure 9: Comprehensive list of effects, Source: (THINK, 2013) ........................................... 14
Figure 10: Reduced effect mapping, Source: (THINK, 2013) ................................................. 15
Figure 11: Social costs of non-competitive pricing, Source: (Posner, 1975) ........................... 18
Figure 12: Electricity areas in the Nordic countries, Source: (Svenska Kraftnät, 2013b, p. 16)
.................................................................................................................................... 19
Figure 13: Swedish Power Grid, Source: (Svenska Kraftnät, 2014a) ...................................... 20
Figure 14: Sweden’s Electricity Generation 2012, Source: (U.S. Energy Information Agency, 2012a)......................................................................................................................... 21
Figure 15: Expected wind capacity 2017, Source: (Global Wind Energy Council, 2014) ...... 23
Figure 16: Demand of variation moderators with increased amount of wind power, Source:
(Svenska Kraftnät, 2013a).......................................................................................... 24
Figure 17: China’s Electricity Generation 2012, Source: (U.S. Energy Information Agency, 2012a)......................................................................................................................... 26
Figure 18: Feed-in-tariffs for onshore wind power, Source: (Hu, et al., 2013) ....................... 27
Figure 19: Locations of wind farms and electricity demand centres, Source: (Li, et al., 2012)
.................................................................................................................................... 28
Figure 20: Percentage of curtailed wind generation by province in 2011, Source: (Clavenna,
2012) .......................................................................................................................... 29
Figure 21: Historical cost of Li-ion battery packs, Source: (Nykvist & Nilsson, 2015) .......... 40
Figure 22: Transmission Deferral, Source: (THINK, 2013) .................................................... 41
Figure 23: Wind curtailment as a function of wind energy penetration, with and without a 500
MW storage device. Source: (Silva-Monroy & Watson, 2014) ................................. 43
Figure 24: Energy storage projects in China. Source: (Littlewood, 2013) .............................. 45
Figure 25: Supply and demand side bid representation ........................................................... 46
Figure 26: Age of 400 kV and 220 kV grids in the Swedish national grid, Source: (Svenska
Kraftnät, 2013b, p. 90) ............................................................................................... 47
Figure 27: Ratio of accumulated investment in power grid and power generation since 1978,
Source: (Li, et al., 2012) ............................................................................................ 49
Figure 28: Cost trend AC, Source: (Performance Curve Database, 2008) .............................. 53
vi
Figure 29: Main sections of EES systems and energy losses, Source (Zakeri & Syri, 2014) .. 54
Figure 30: St. Clair Curve, Source: (Hao & Xu, 2008) ............................................................ 58
Figure 31: Case 1 Sweden ........................................................................................................ 66
Figure 32: Case 2 Sweden ........................................................................................................ 66
Figure 33: Case 3 Sweden ........................................................................................................ 67
Figure 34: Case 4 Sweden ........................................................................................................ 67
Figure 35: Case 5 Sweden ........................................................................................................ 67
Figure 36: Case 6 Sweden ........................................................................................................ 67
Figure 37: Case 7 Sweden ........................................................................................................ 68
Figure 38: Case 8 Sweden ........................................................................................................ 68
Figure 39: Case 1 China ........................................................................................................... 68
Figure 40: Case 2 China ........................................................................................................... 68
Figure 41: Case 3 China ........................................................................................................... 69
Figure 42: Case 4 China ........................................................................................................... 69
Figure 43: Case 5 China ........................................................................................................... 69
Figure 44: Case 6 China ........................................................................................................... 69
Figure 45: Case 7 China ........................................................................................................... 70
Figure 46: Case 8 China ........................................................................................................... 70
Figure 47: Acknowledged Driving Forces - Grid Storage ....................................................... 75
Figure 48: Acknowledged Driving Forces – Transmission in Sweden .................................... 76
Figure 49: Acknowledged Driving Forces – Transmission in China ....................................... 76
Figure 50: Conclusions............................................................................................................. 82
vii
LIST OF TABLES
Table 1: Abbreviations .............................................................................................................. ix
Table 2 Advantages and disadvantages of storage technologies, Source: (Insight_E, 2014)
(Evans, et al., 2012) ..................................................................................................... 5
Table 3: Electric Service Reliability Validation ...................................................................... 57
Table 4: General Input Data Model, Sweden ........................................................................... 59
Table 5: Input Data Grid Storage Model, Sweden ................................................................... 60
Table 6: Input Data Transmission Model, Sweden .................................................................. 61
Table 7: General Input Data Model, China .............................................................................. 62
Table 8: Input Data Grid Storage Model, China ...................................................................... 63
Table 9: Input Data Transmission Model, China ..................................................................... 64
viii
ABBREVIATIONS
Table 1: Abbreviations
ALCC
ACBA
CAES
CBA
CHP
CNY
CO2
CS
CSG
DSM
DSO
EU
GW
GWh
h
Hz
ICT
km
kW
kWh
Li-ion
MW
MWh
Na-S
NDRC
NEA
O&M
OECD
PHS
RI
SEK
SERC
SGCC
SMES
SPC
SS
TSO
TW
TWh
U.S.
UK
Annualized Life Cycle Cost
Annualized Cost-Benefit Analysis
Compressed Air Energy Storage
Cost-Benefit Analysis
Combined Heat and Power
Chinese Yuan
Carbon dioxide
Consumer Surplus
China Southern Power Grid
Demand Side Management
Distribution System Operator
European Union
Gigawatt
Gigawatt hours
Hours
Hertz
Information & Communication Technology
Kilometer
Kilowatt
Kilowatt hours
Lithium-ion
Megawatt
Megawatt hours
Sodium-sulphur
National Development and Planning Commission
National Energy Administration
Operation & Maintenance
Organisation for Economic Co-operation and Development
Pumped hydro systems
Reinvestment
Swedish Krona
State Electricity Power Regulatory Commission
State Grid Corporation of China
Superconduction Magnetic Energy Storage
State Power Corporation
Supplier Surplus
Transmission System Operator
Terawatt
Terawatt hours
United States
United Kingdom
ix
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x
1. INTRODUCTION
INTRODUCTION
This chapter intends to give an introduction to the subject of this master thesis. Firstly, a wide
background presentation to this thesis is provided. This includes underlying challenges that
lays the foundation to this thesis. Thereafter the purpose is clarified, along with research
questions and expected contributions of this study.
1.1 Background
Renewable energy sources continue to increase worldwide. Cost-competitiveness is
improving as renewable energy sources are promoted by energy policies. Ambitions to
intensify low-carbon energy technologies are increasing, both in developed and developing
countries. (International Energy Agency, 2014) This leads to challenges in global and
country-specific energy markets.
A challenge on the global energy market is the declining nuclear capacity. This trend is
acknowledged by the International Energy Agency (2014) as several nuclear plants are ageing
or are non-profitable in OECD countries. The International Energy Agency (2014) predicts
insufficient global nuclear capacity in 2025, where new reactors are providing a modest
capacity increase.
In Sweden, power capacity from the three oldest nuclear power plants must be replaced by
other energy sources. Svenska Kraftnät (2014c) does not expect these aging plants to be
substituted by new nuclear power plants, resulting in less nuclear power in a near future. This
might lead to future power shortage in the Swedish electricity mix, involving congestion and
impaired power balance in some regions (Svenska Kraftnät, 2014c).
In order to cover the gap from nuclear power, and at the same time achieve energy and
climate targets set by Sweden and the European Union (EU), the share of renewable energy
sources in the power system is expected to increase (Svenska Kraftnät, 2014c). The European
Commission (2015) includes a target of minimum of 27 percent share of renewable energy
consumption by 2030. Sweden alone has set the energy target to 49 percent share of
renewable energy already by 2020. This includes a target of reaching 30 TWh from wind
power generation by 2020, corresponding to approximately 20 percent of Sweden’s total electricity generation. (Swedish Energy Agency, 2011)
Similarly to Sweden, China also faces major challenges regarding the national electricity
generation. High level of air pollution, particularly in large cities as Beijing, has led to
regulated targets to reduce air pollutions in the fast growing country. (Reuters, 2014). A
reduction of fossil fuel combustion together with enlarged public environmental awareness is
expected to promote generation from renewable energy sources. China has agreed to reach its
peak in carbon dioxide (CO2) emissions in 2030 and by then have a 20 percent share of
1
1. INTRODUCTION
renewable energy. In order to reach this target, an amount of 1 000 GW non-carbon emitting
power such as nuclear, solar and wind power must be installed. (Scientific American, 2014)
1.1.1 Wind Power Growth
Wind power has increased most of all electricity sources in Sweden the last few years and
China is the world’s largest wind power producer, as seen in Figure 3. The wind industry is
promoted by governmental support systems in several countries all over the world, where
mass production and technology development has contributed to cheaper turbines. As seen in
Figure 2, the global installed wind capacity is increasing each year and has almost tripled the
last five years, from 120 000 MW in 2008 to 320 000 MW in 2013. (Global Wind Energy
Council, 2014)
Figure 2: Installed Wind Capacity in the World, Source: (Global
Wind Energy Council, 2014)
Figure 3: Installed Wind Power top 10 countries 2013 [MW],
Source: (Global Wind Energy Council, 2014)
The installed wind power capacity has increased in Sweden but especially in China as Figure
4 shows. The increasing installed wind power capacity in Sweden and China also yields a
higher share of wind power in the total generation capacity mix. Sweden had almost 10
percent wind power of total electricity production capacity year 2012 and China had more
than 5 percent wind power installed same year. The growth in share of wind power capacity
from 2005 to 2012 can be seen Figure 5 below.
Figure 5: Share of Wind Power Generation Capacity, Source:
(U.S. Energy Information Agency, 2012a) (The Wind Power,
2013b) (The Wind Power, 2013) (Energimyndigheten, 2014)
Figure 4: Installed Wind Power Capacity, Source: (The Wind
Power, 2013a)
2
1. INTRODUCTION
1.1.2 Intermittent Power Generation Challenges
Even though wind power increases rapidly due to its environmental benefits, new challenges
arise in the power system. Wind power generation is more intermittent and unpredictable than
conventional energy sources due to weather conditions with seasonally and daily variations.
Seasonal variations are repeated annually and are hence relatively predictable. Unpredictable
variations are caused by weather changes, leading to forecast errors and generation
challenges. (The Boston Consulting Group, 2010)
Real-time balance between load and generation must be maintained. Output fluctuation from
renewable energy sources influences system operation of frequency control, which often is
accomplished by conventional thermal generators operated to adjust the frequency. (IEC,
2011) When generation from intermittent energy sources is high, load should increase or
output from conventional power generators should be reduced. If scheduling is uncoordinated
or if transmission capacity is limited, there is a risk that energy is curtailed. (Li, et al., 2015)
Wind energy curtailment occurs when wind is available but not utilized for electricity
generation in wind power plants. When generation exceeds demand on windy days, there is a
risk of extremely low electricity prices on the spot market. Surplus power generation can be
exported, provided that there is sufficient transmission capacity, or energy is curtailed. When
there is a large power demand and less wind, regulating measures and balancing power is
required. (IEC, 2011) Intermittent energy sources thereby require variation moderators to
reduce wind curtailment and meet demand.
It is essential to find a cost-effective solution for regulating power in order to secure the
electricity supply. Power reserves systems currently available have either geographical or
financial downsides. For example, hydropower has geographical limitations and is often too
remote from potential wind sites. (Li, et al., 2012) To provide optimistic investment outlooks
for renewable energy technologies, energy policies are crucial. Cost-competitiveness is
improving in some countries, depending on market strategies. (International Energy Agency,
2014) The Boston Consulting Group (2010) has anticipated Europe to be the first area to face
variation problems from intermittent power generation. A compensating capacity of 100 GW
is expected to be required in 2025, due to increased amount of intermittent electricity
generation. (The Boston Consulting Group, 2010)
1.1.3 Variation Moderators
Increased share of intermittent wind power in the system requires enhanced variation
moderators to balance generation and varying demand at all times. Interconnections and
integration of generation, transmission planning and market are all aspects affected by this
change in the energy system. These aspects have different positions, time frames and impacts
on the system, as displayed in Figure 6. The system wide impacts have been divided into three
focus areas; balancing and adequacy of power and grid. Primary reserves are short-term
reserves that need to be activated in seconds, for example frequency regulation. Secondary
reserves are activated in 10 to 15 minutes, for example load following reserves. A higher
share of wind power entails extra investment costs. These costs arise from operational
balancing and grid reinforcement costs, such as large-scale energy storage and transmission
3
1. INTRODUCTION
investments. However, total operating costs and emissions can be reduced as wind replaces
fossil fuels. (Holttinen, et al., 2011)
Figure 6: Impacts of wind power on power systems, displayed by time and spatial scales, Source: (Holttinen, et al., 2011, p. 180)
There are several examples of variations moderators that can provide flexibility to an
intermittent power system. For example energy can be transferred through geographical
transmission or stored over time in an energy storage.
1.1.3.1 Transmission
The electric power transmission systems transmit electricity from electric generators, such as
hydro power plants, nuclear power plants or wind power plants, to electrical substations
located near load centres. To reduce losses over long distances, electricity is transmitted at
high voltages, 120 kV or above. (World Nuclear Association, 2015) Since transmission
infrastructure depends on country specific conditions, further details are explained in chapter
3 for the transmission infrastructure in Sweden and China. By having a well-developed
transmission grid, power generation from example wind farms can be transmitted to another
geographical location, provided that the transmission capacity is sufficient. Trustworthy
forecasts of weather and demand are advantageous to transmit a stable power supply (The
Boston Consulting Group, 2010).
1.1.3.2 Energy Storage
Another option to regulate power from intermittent generation is by storing energy over time.
There are numerous of research work that advocates integration of large-scale energy storage
4
1. INTRODUCTION
into the power system with the purpose to provide variation capacity in the intermittent power
system. Various energy storage technologies keep developing towards grid usage (Anuta, et
al., 2014) (Evans, et al., 2012) (The Boston Consulting Group, 2010) (Lund & Münster,
2003). To compensate for short and long term energy interruptions there is also a need for
different types of energy storages. Individual needs will be important in the choice of energy
storage systems, but incorporation of several energy storage systems will also be necessary as
large amount of energy is required (Evans, et al., 2012). However, integration of large-scale
energy storage technologies is associated with potential market entry barriers, since the
market for several storage technologies is not yet mature.
Energy can be stored in many different forms and can be divided into four different
categories; mechanical, electrical, thermal and chemical energy, each offering different
advantages and disadvantages. (Evans, et al., 2012) In Table 2, advantages and disadvantages
have been summarized for storage technologies appropriate for intermittent balancing.
Table 2 Advantages and disadvantages of storage technologies, Source: (Insight_E, 2014) (Evans, et al., 2012)
Technology
Mechanical strorage
PHS
Advantages
Disadvantages
Large scale, efficient, commercial
CAES
Cost efficient, large scale, scalable
Flywheel
High power density, efficient, scalable
Site dependent, low energy density, potential
environmental impact
Low energy density, large scale requires natural
storage cavity (can be limited)
Cost, energy density
Electrical storage
Capacitors
Long cycle life, high efficency
Low energy density
Supercapacitors
Power density, response time, efficient, cycle time
Low energy density, relatively high cost
SMES
Power density, response time, efficient
Low energy density, cost, commercialisation
Thermal storage
Steam accumulator
Relatively low cost, manufacturing
Low energy density
Hot water accumulator High heat density, high energy density, long life cycle
Chemical storage
Lead-acid battery
Wide availability, reasonable low cost
Na-S battery
Long life cycle, high energy density, mature
Li-ion battery
High energy and power density, scalable, high
efficiency, no memory effect, low self-discharge, other
applications drives cost down
High energy and power density, large scale
Flow battery
Slow charge and discharge rate
Low specific energy and power, short life time,
high maintenance, temperature sensitive,
High cost, high self-discharge, temperature
sensitive
High cost, material safety concerns
Commercialisation, high cost, corrosion issues
As Table 2 shows, there are many different technologies for storing energy. One of them are
lithium-ion (Li-ion) batteries which is a fast developing technology. It has high energy to
weight ratio, high efficiency, high energy and power density. No memory effect and low selfdischarge are also some advantages with Li-ion batteries. The cost is currently high and it has
some safety concerns regarding the materials in the batteries, which require sophisticated
battery management. (Evans, et al., 2012) However, costs are expected to decrease as other
industries drive the technology development forward (Insight_E, 2014) (Eyer & Corey, 2010).
This can also be seen in Figure 7 below. Several references from the industry believe that Li5
1. INTRODUCTION
ion batteries will be a market leading technology for grid storage applications (Climate
Spectator, 2014) (Nykvist & Nilsson, 2015). Considering this development, Li-ion battery
storage technology becomes interesting to further examine in this thesis.
Figure 7: Predicted cost trends for full automotive Li-ion battery packs. Source: (Climate Spectator, 2014)
1.2 Purpose
This master thesis consists of two parts. The initial purpose is to explore market forces for
transmission and grid storage development as variation moderators for intermittent power
generation. Since battery grid storage is an emerging technology, market entry barriers for
integrating storage into the grid aims to be identified.
The second part of the thesis aims to investigate the most beneficial combination of grid
storage integration and transmission expansion in the future power system, in a system
perspective.
1.3 Research Questions
In order to fulfil the purpose of the study, the following research questions have been
addressed:
RQ1: What are the market entry barriers for integrating energy storage into the grid and
what drives the development of grid storage and transmission, respectively?
RQ2: How do these market forces affect the choice of variation moderators in the future
energy infrastructure?
6
1. INTRODUCTION
1.4 Expected Contributions
Several technical solutions are today available providing flexibility in the future power
system. According to the International Energy Agency (2014), the main question is not how
to bring flexibility to the power system, but which alternative is the most lucrative. This
master thesis is expected to investigate the most lucrative combination of grid storage
integration and transmission expansion by introducing a cost-benefit model.
Previous work within the area partly includes regional integration with separate plans of
variation management. Göransson (2014) examines power system containing a large share of
wind power and emphasis that intermittent energy sources will play an important role in the
future. However, what kind of technologies complementing these intermittent energy sources
is yet uncertain. (Göransson, 2014) Variation moderators such as transmission and storage,
which this master thesis will focus on, can provide regulation of intermittent wind power.
Previous research work indicates a lack of research within the area. According to Göransson
(2014) an important subject in future work is to:
“…find a balance between centralized (e.g., transmission investments and
trade with hydropower-rich Nordic countries) and decentralized (e.g., regional
storage and DSM) efforts to manage variations.”
This master thesis will cover two potential solutions to manage variations from intermittent
energy sources. The thesis is expected to contribute to a greater basis of research within the
area and provide market indications for future investment decisions when planning Sweden’s and China’s power systems. By increased knowledge about driving forces, potential barriers,
costs and benefits that influence the market conditions for these variation moderators, this
master thesis imply material for decision making on the future power market.
The thesis is also expected to contribute to a general system perspective of introducing grid
storage on the global power market. However, since grid infrastructure is country specific, a
comparison is performed between transmission and storage in two diverse market conditions.
Craig & Douglas (2005) support the international viewpoint and emphasize the importance of
performing research with a global perspective, as markets constantly change and businesses
are becoming more global.
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METHODOLOGY
This chapter covers the methodology of this research work. Firstly, the research design and
approach is explained. This is followed by describing the data collection method and research
approach quality. Lastly, the method of the Cost-Benefit Analysis is further clarified.
2.1 Research Design and Approach
This master thesis has been conducted by an inductive approach. Data gathered has led to
increased knowledge within the field of study. Thereafter, scientific theories have been used
to further increase knowledge about the findings. This has also laid a foundation to the first
version of the cost-benefit model. Then, additional reading within the field of study was
conducted and the model was developed further. This process was made in several steps,
thereby with an inductive approach. Although this approach could be time-consuming,
according to Bryman & Bell (2011) and Blomkvist & Hallin (2014), it was still chosen due its
advantage for exploratory studies, such as this thesis work.
Based on this study’s research questions and its purpose, it can be concluded that this study is of an interpretivist nature. According to Bryman & Bell (2011), interpretivism is a term for
research that focuses on social phenomena rather than natural sciences. This kind of study
requires a different research approach that respects the differences between people and the
objects of the natural science. An interpretivistic approach does not focus on quantitative data
but rather on qualitative data where the research is conducted in close interaction with what is
being researched. (Bryman & Bell, 2011)
In order to answer the research questions, a case study research design has been chosen. This
kind of research method is suitable for previous unexplored areas according to Bryman & Bell
(2011) and Blomkvist & Hallin (2014), such as this research area. Data has been gathered by
a qualitative approach and developed towards two different cases; one for a developed
market, Sweden, and one for a developing market, China. A cost-benefit model has been
constructed by data gathered and thereafter a Cost-Benefit Analysis (CBA) was made with the
purpose to study the cases for each country. The CBA and the cost-benefit model is further
examined in section 2.4 and in chapter 5.
The actual research procedure consisted firstly of building an understanding of the issue with
a high share of intermittent power generation in the power system. Grid storage and
transmission was chosen to be the two technologies in focus and further investigated in this
research. Then an understanding for the emerging technology energy storage’s market entry
barriers, further development and future potential in the energy infrastructure had to be
conducted. This applied also for transmission, but since transmission is a mature technology
in the energy infrastructure, this part had a different approach with focus on its current driving
forces. To create this understanding, an extensive literature survey within the field of study
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2. METHODOLOGY
was made. Further, this continuously increased understanding has been connected with
scientific theories, such as market entry and market conditions, during the process.
Furthermore, a cost-benefit model for the two different countries was conducted with data
gathered in the literature survey as its foundation, together with country specific data for grid
storage and transmission. The model has been constructed and developed simultaneously as
knowledge from the literature survey has increased during the work. This inductive approach
applies for both technologies and also for the market analysis.
2.2 Data Collection
The literature survey in this research is essential to understand the context of the problem and
find information available in the field of study. Previous research in the area laid a foundation
to this thesis, together with information from different governmental and industry
organizations and consulting reports. Statistics about electricity generation and consumption
in respectively country has been gathered through the Global Wind Energy Council, the U.S.
Energy Information Agency and Svenska Kraftnät. Information about the electricity markets,
together with information about energy storage and transmission, has been found through
multiple sources including academic journals, consultant reports and governmental
organizations.
The material is retrieved from the Internet and databases for scientific research, including
Google Scholar, Discovery, Diva and IEEE Xplore. Information have also been found at
different Swedish governmental organizations, like The Swedish Energy Agency
(Energimyndigheten), The Swedish Transmission System Operator (TSO), Svenska Kraftnät
and industry organizations such as Svensk Energi and Svensk Vindenergi. They present
information about the current electricity market and the transmission grid as well as future
plans of expansion. There are also a few consultant reports, from companies such as Sweco,
Ramböll, The Boston Consulting Group and Lazard, which are relevant for the study.
Information gathered from these consultant reports includes potential future scenarios.
Available information about China was limited, in particular from governmental
organizations. Most of the collected information comes from previous academic research in
the field of study and different news releases from websites.
2.3 Research Approach Quality
Bryman & Bell (2011) argues that reliability and validity are important criteria’s to consider when establishing and assessing the quality of a qualitative research. However, some
researchers’ claims that validity has less relevance in qualitative research since measurements
are not a major preoccupation among qualitative researchers. This would mean that validity
has little influence on such studies. (Bryman & Bell, 2011)
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2.3.1 Validity and Reliability
Validity refers to whether or not the purpose is met and research questions are answered.
Validity is achieved by confirming that the literature survey and theory is connected to the
purpose and the research questions. (Blomkvist & Hallin, 2014, p. 50) (Bryman & Bell, 2011)
The validity in this research has been achieved by reconstructing the research questions to fit
the context in the study, since the study has developed during the process and slightly
changed direction. Increased knowledge in the field of study has led to interesting findings
that have affected the research focus area. However, comparing grid storage and transmission
as variation moderators for intermittent power generation is an emerging field, which yields
that validity cannot be guaranteed completely. Further, there is a lot of previous research of
the variation moderators separately, as well as research on how to enter a new market and
differences between developed and developing countries. This enhances the validity in this
study. Moreover, Craig & Douglas (2005) acknowledge the challenges of collecting
comparative data and analyse results for diverse market environments. Several factors can
cause difficulties in achieving comparable results between developed and developing
countries. It is generally easier to use the same research approach for similar market
environments. (Craig & Douglas, 2005) Nevertheless, Craig & Douglas (2005) argue that the
research work can increase validity and support decision making if these challenges are
addressed in a reasonable way.
Reliability refers to the consistency of a concept measure; to what extent the results of the
study would differ if another researcher repeated the research. (Bryman & Bell, 2011) The
limitation of adequate accessible market data affects the reliability of the study. Battery grid
storage is an emerging technology and few market studies have been performed where the
market conditions for storage is compared with another variation moderator, such as
transmission. This makes this thesis a pioneer in the field of study, but it also creates some
uncertainties regarding its reliability. Since it is a high topic subject and there is a lot of ongoing development within the field of study the market conditions changes all the time, which
affects the reliability of the results in the study. The market analysis and the conclusions are
based on information available at present time. It is most likely that new information will be
available for another researcher in the future.
Further, evaluating costs for energy storage is challenging, as there is limited information
about economic performance of the few sites existing today. This research work considers
market entry of an emerging technology at an early stage. According to Craig & Douglas
(2005), the work should therefore be observed in a long-term perspective and aim to initiate
further research within the area. Since many markets move quickly, trends need to be
identified at an early stage. Also a long-term perspective is important when perceiving market
potential (Craig & Douglas, 2005). Craig & Douglas (2005) also acknowledge the importance
of entering a market at an early stage of the market development to avoid competition from
other actors. Diverse approaches and methods for cost calculations and estimations are used in
the literature. Furthermore, Zakeri & Syri (2014) claims that data for expenses cannot be
appropriately scaled for larger or smaller storage sizes. This has been an issue during the
design of the model that of course affects the reliability of the results. This has also been the
case for data about current transmission projects. Since there have not been many
transmission projects in the recent years of the appropriate size in Sweden, data from only one
projects has been used. This affects the reliability of the results. In China, there are on-going
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2. METHODOLOGY
projects in present time in appropriate size but due to China’s restrictions of sharing
information limited data was available. However, since an extensive data collection has been
performed and no more up-to-date data could be found, reliability can be considered to be
achieved. The thesis work was also performed under a limited time frame. The CBA and
market analysis could have been performed in more detail with extended time frame.
The aim has also been to create a reasonable and general cost-benefit model including the
most relevant benefits for integrating battery grid storage in the current energy infrastructure.
The model itself is considered as general, but country-specific costs have been included for
Sweden and China, respectively. Due to country-specific conditions, some data are hard to
compare but must be included separately for the two countries. Two countries are included to
increase quality to the model and understand how diverse market conditions can change the
barriers and opportunities for grid storage integration and transmission expansion.
2.4 Cost-Benefit Analysis
The research work investigates two different markets, a developed economy and a developing
economy represented by Sweden and China, respectively. Transmission expansion is
considered for market specific conditions in these countries, where the focus area is to analyse
the market situation from a wide infrastructure perspective. By means of the socioeconomic
CBA and market analysis, potential investment decisions can be considered for infrastructure
development. However, not all existing benefits for grid storage integration are included in
the CBA. Grid storage can be used for several applications when utilizing different properties.
The properties chosen for this thesis are applicable for regulating purposes of intermittent
renewable power generation.
A CBA can be viewed as a method to determine whether an investment should be realized or
not. It is also useful in comparing different projects to see which project that is more
beneficial to realize. In a CBA, costs and benefits from a project is considered and expressed
in a monetary value. (Layard & Glaister, 1994) Information about a monetary value does not
often exist, but must be based on reasonable estimations. It is important to consider the most
relevant factors of the project. Regarding infrastructure projects, the project has multiple
factors such as impacts within the power system, external effects and macroeconomic effects
as presented in Figure 8.
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Figure 8: Three layers of factors generated by infrastructure project, Source: (THINK, 2013)
Within the power system, costs and benefits can be considered. Costs can involve
infrastructure investment costs over the lifetime and also production cost savings,
corresponding to more efficient use of ancillary and balancing reserves. Gross consumer
surplus and other market benefits can also be considered within the power system, such as
benefits from improved system reliability or price fluctuations on the spot market. (THINK,
2013)
Externalities refer to external effects that the project has on its environment. For instance, it
can affect CO2 emission costs depending on type of energy source used for generation.
Another external effect is amount of renewable energy curtailment. Local environmental and
social cost should also be considered, for example the impact that the project has on landscape
or noise to the surrounding. Early deployment is also important to consider, as the project can
lead to increased knowledge about certain types of technologies, such as grid storage. These
potential effects are presented in Figure 9. (THINK, 2013)
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Figure 9: Comprehensive list of effects, Source: (THINK, 2013)
However, some of these effects are not relevant in all projects or overlap with effects already
considered. For example, benefits from CO2 emission reductions can be included in
production cost savings, due to the decreased cost for CO2 emissions. Likewise, benefits from
renewable integration can be included in production cost savings. Local and environmental
costs can be included in infrastructure costs. For example, costs to meet the current directive
regarding local fauna and flora, material assets and cultural heritage can therefore be included
in infrastructure costs. This also applies to early deployment costs. Macroeconomic impacts
are relatively similar for most projects and can therefore be considered as less important when
comparing different projects. (THINK, 2013)
The most important effects on a project can be summed up to infrastructure costs, production
cost savings and gross consumer surplus. These reduced effects on a project are presented in
Figure 10 below. However, applicability of the CBA relies on consistency and quality of the
data wind curtailment that underlines the parameters. (THINK, 2013)
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2. METHODOLOGY
Figure 10: Reduced effect mapping, Source: (THINK, 2013)
All costs and benefits during the project’s lifetime are usually included in the CBA and discounted at the same point in time. Thereafter, they are summed up to a net present value
(NPV). (Layard & Glaister, 1994) The equations used in the model are showed in section
5.11.
NPV =
(
)
𝑛 = Year
𝐵 = Sum of costs for year 𝑛
𝑖 = Interest rate
L = Financial life time in years
2.4.1 Annualized Cost-Benefit Analysis
To compare two investments without income and different life time the annuity for the
alternatives can be calculated to make a trustworthy comparison of the costs. The Annualized
Cost-Benefit Analysis (ACBA) of an investment in grid storage and transmission is obtained
by multiplying the present value with the life annuity of the object.
𝐴 = 𝑁𝑃𝑉 ∗ 𝐹 = 𝑁𝑃𝑉 ∗
(
)
𝐹 = Annuity factor
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3. MARKET CONDITIONS
MARKET CONDITIONS
This chapter aims to give a further understanding of the conditions for variation moderators
on two diverse markets. The first part of this chapter describes the Swedish electricity market,
where upcoming challenges are identified and future scenarios presented. The second part
describes market conditions on the Chinese electricity market, together with upcoming
challenges and the influence of an emerging market.
3.1 The Swedish Electricity Market
The Swedish electricity market consists of hundreds of actors. However, the market is
dominated by a few actors; Vattenfall, Fortum and E.ON, who together have a substantial
market share of electricity generation and wholesale. Green & Newbery (1992) claims that it
would be more efficient if the market consisted of several actors with smaller market shares in
order to avoid deadweight losses. Deadweight losses means the loss a buyer suffer when
buying something to a higher price than the competitive level (L in Figure 11) or the loss the
buyer suffer when not choosing to buy at all (D in Figure 11) (Posner, 1975). Even though the
market in Sweden could be seen as an oligopoly (Brander & Lewis, 1986) the electricity is
traded on a joint Nordic market, Nord Pool Spot, which consist of several major actors and
hundreds of smaller actors. According to Fridolfsson & Tangerås (2009), this results in a
competitive market and no single actor has a dominating share of the market.
The Swedish national grid is controlled by a state monopoly. According to Bushnell (1999),
transmission right owners can take advantage of their monopoly position and reduce
transmission capacity during hours in which there would otherwise be no congestion. This
will lead to social costs, see Figure 11, but not necessarily a loss for the TSO, it could even be
beneficial. (Bushnell, 1999) (Posner, 1975)
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3. MARKET CONDITIONS
Figure 11: Social costs of non-competitive pricing, Source: (Posner, 1975)
The Swedish national grid is owned by the Swedish government and managed by the Swedish
TSO, Svenska Kraftnät. The Swedish TSO is responsible for ensuring that Sweden has a safe,
environmentally sound and cost-effective electricity supply. In short term this is achieved by
monitoring the electrical system around the clock and in the long term by plan and construct
new transmission lines to meet future demand. (Svenska Kraftnät, 2015b) The Swedish
national grid consist of 15 000 km high voltage lines with the current of 400 or 220 kV,
presented in Figure 13, where the connections to its neighbouring countries also can be seen.
(Svensk Energi, 2012d) Large wind plants over 100 MW are connected to the national grid.
(Energimyndigheten, 2013b)
Since November 1, 2011 Sweden is divided into four different price bidding areas, as
displayed in Figure 12 below. This breakdown is made to show where the grid requires an
increase in capacity. The borders are placed where the limitations in capacity are. In general,
there is a surplus of generation in north compared to the demand. The opposite occurs in the
south where the transmission capacity is not enough during peak hours. This congestion affect
market pricing; price decreases in one area and increases in the other area. The decision to
split the Swedish market in four areas is also a part of EU’s goal of one united electricity market in Europe. (Svenska Kraftnät, 2013b, p. 16)
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3. MARKET CONDITIONS
Figure 12: Electricity areas in the Nordic countries, Source: (Svenska Kraftnät, 2013b, p. 16)
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3. MARKET CONDITIONS
Figure 13: Swedish Power Grid, Source: (Svenska Kraftnät, 2014a)
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3. MARKET CONDITIONS
3.1.1 Electricity Generation
Sweden has an electricity generation that consist of low CO2 emitting fuels. The amount of
renewables and waste consist of 60 percent of Sweden’s total electricity generation, as seen in Figure 14. 38 percent of the generation comes from nuclear which is not renewable but still a
low CO2 emitter. Only two percent comes from fossil fuels and they are mostly used as
reserve capacity in peak hours. (Svensk Energi, 2012a)
Figure 14: Sweden’s Electricity Generation 2012, Source: (U.S. Energy Information Agency, 2012a)
The nuclear power generation is the base load in Sweden’s electricity system and consist of ten nuclear power plants on three locations different location in southern half of Sweden
(SE3). Hydro power generation is Sweden’s largest energy source and like nuclear it acts as a
base load. Furthermore, it also acts as a regulating reserve due to its good ability to handle
seasonal variation and also variation in shorter intervals. This ability to regulate the electricity
generation is very valuable for Sweden’s electricity system. The share of wind energy is
increasing in Sweden and with this weather dependent production there is a need for
regulating reserves. (Svensk Energi, 2012a) However, hydro power as regulating reserve
might not be enough in the future. Hydro energy in Sweden is already used near its maximum
potential. (Svenska Kraftnät, 2008)
3.1.2 A Competitive Market
Historically the trading in Sweden was controlled by a state monopoly and consumers were
forced to buy electricity for a set price. In January 1996 the first step was taken towards a
competitive electricity market. The market was partly deregulated and free competition was
created in trade and production of electricity. The major step towards a competitive market
was made in 1999. The new rules that were applied made it possible for consumer to buy
electricity from any electricity trading company on the market. This new competitive market,
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3. MARKET CONDITIONS
connected consumers and producers, with the basic principle of demand and supply. (Svensk
Energi, 2012c)
Nord Pool Spot market is today the leading power market in Europe and 90 percent of
Sweden’s electricity generation is traded there. Nord Pool Spot is owned by the TSOs in
Sweden, Norway, Finland and Denmark. (Svensk Energi, 2012b) Nord Pool is divided in two
physical parts, Elspot and Elbas.
Elspot is a day-ahead auction market for the Nordic and Baltic region. It is the main market
place and the traded power applies for delivery during the next day. The price is set by supply
and demand, where a buyer sets the demand and price for the following day. A seller, for
example an owner of a wind farm, sets the amount that can be delivered hour by hour and to
what price. Each actor uses a strategy to maximize their outcome of the deal. (Nord Pool
Spot, 2015a) (Engelbrecht-Wiggans, 1980)
Elbas is an intraday market which is traded on Nord Pool Spot. Elbas is covering the Nordic,
Baltic region and Germany. Trading takes place every day until one hour before delivery. Its
purpose is to set balance to the market if unexpected events occur, such as higher wind power
generation than planned. The price is set by a first come, first served principle. The best prices
is prioritized, highest buy price is matched to lowest sell price. (Nord Pool Spot, 2015b)
3.1.3 Upcoming Challenges
According to Global Wind Energy Council (2014) future constructions will be concentrated to
northern parts of Sweden where larger wind farms are more feasible, as seen in Figure 15.
These problems are most likely to occur in the most southern area (SE4) where transmission
capacity from north and regulation is limited. The regulation of intermittent generation could
be solved in a better way by investing in transmission capacity towards neighbouring
countries as well as domestically between the different bidding areas. However, these kinds of
grid investments are very costly. The process of constructing a new transmission line also
requires far ahead planning. Constructing a new transmission line, from planning to
commissioning, takes about five to ten years (Svenska Kraftnät, 2015). A challenge of
geographical transmission is also the monitoring of wind generation and wind forecasts. The
forecasts need to be constantly updated to facilitate planning of large wind power generation
and balancing power with long start-up time. The actual wind generation can also be used to
validate the forecast towards the outcome. (Svenska Kraftnät, 2013b)
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3. MARKET CONDITIONS
Figure 15: Expected wind capacity 2017, Source: (Global Wind Energy Council, 2014)
The Swedish TSO has received applications for connecting wind power of 20 000 MW,
which represents about 75 percent of Sweden’s maximum power demand. The expansion of
wind power expects to depend on the future design of the electricity certificate system. Slow
authorization processes can influence when wind power growth can be realized. Locations of
the wind power plants have big impact on the capacity of the transmission grid. Nevertheless,
increased transmission capacity in the national grid will be required, no matter of location of
the increased wind power generation. If expansions occur in the southern parts, hydro power
from the northern parts of the country is expected to balance the grid, requiring enhanced
transmission capacity. If expansion occur in the northern parts, improved transmission
capacity is also necessary to transmit the power to the rest of the country. (Svenska Kraftnät,
2013b)
3.1.4 Future Scenarios
The system electricity price should increase due to increased marginal costs. This is
concluded by both Ramböll (2014) and Sweco (2014). The consultant company Ramböll has
evaluated Sweden’s future electricity generation where two possible scenarios have been studied. The first scenario, scenario C, consists of 6 nuclear power plants instead of Sweden’s 10 plants today. It also consist of 33 TWh wind power per year and to meet peak load, 1 500
MW gas power needs to be installed. In the second scenario, scenario D, nuclear power has
been completely phased out and replaced with 82 TWh wind energy per year. Furthermore,
4 700 MW gas power has been installed to meet peak load. Both scenarios involve an increase
in the system price to 0.46 SEK/kWh ($0.055/kWh) and 0.53 SEK/kWh ($0.064/kWh),
respectively. This can be compared to today’s level of 0.30-0.35 SEK/kWh ($0.036/kWh$0.042/kWh) at Nord Pool Spot market. (Ramböll, 2014) Another consultant company,
Sweco, also expects the electricity prices to rise. A scenario analysis for 2030 has been
performed to study European Power Market Scenarios with different approaches. A scenario
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3. MARKET CONDITIONS
with high economic growth involves higher electricity demand and greater focus on the
environment. Consequently, the generation capacity increases and larger investments are
necessary for interconnections on the continent. (Sweco, 2014)
High focus on climate change and increased renewable power generation is also expected to
lead to volatility prices. Intermittent generation, and consequently volatile prices, is expected
to increase in all European countries. As a result of this, Sweco (2014) acknowledges that
increased transmission capacity is necessary. By expanding the market integration with
continental Europe, the Nordic countries are expected to increase exportation of surplus
power. (Sweco, 2014)
More wind power capacity in the future electricity mix can result in increased spill of energy.
According to Ramböll (2014), an increased amount of wind energy in the electricity mix will
result in an energy surplus, wind curtailment, of 5 percent and 26 percent of the hours of the
year. Two scenarios have been studied C and D, respectively. The excess generation will
yield a very low system price these hours. (Ramböll, 2014)
Increased demand of regulation in
percentage of installed wind power
The Swedish TSO has analysed a scenario for 2025, with a wind power capacity of 7 000
MW in Sweden. They expects an increase of variation moderators to integrate the expansion
of wind power. There is two scenarios shown in Figure 16. Scenario A has the assumptions of
an ideal market with continuous plans and forecasts, and with corrected trade on Elbas.
Scenario B is the opposite where all trade is made on Elspot and there are no updates of plans
and forecasts. However, to decrease the number of variation moderators needed and to
increase availability of the existing ones, a few measures have been identified. Two measures
are intensified monitoring and increased costs of imbalances. (Svenska Kraftnät, 2013a)
Scenario B
Scenario A
Forecast based on current situation
SC
Installed Wind Power [MW]
Figure 16: Demand of variation moderators with increased amount of wind power, Source: (Svenska Kraftnät, 2013a)
The Swedish TSO assesses that expansion of wind power in Sweden will not require an
adjustment of the present market model in a near future. Thereby, the Swedish TSO does not
currently intend to expand their responsibility of balancing the power system, partly because
European directives set guidelines for future developments of the market model. (Svenska
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3. MARKET CONDITIONS
Kraftnät, 2013a) However, Aigner (2013) acknowledges that an integrated intraday market in
Northern Europe would have major effect on production. This could result in reducing the
activation of balancing reserves by about 70 percent in 2020 and $361 million in annual
savings. (Aigner, 2013)
One main energy target on the Swedish energy market is to increase the share of renewable
energy sources to at least 50 percent by 2020. The Swedish TSO has therefore developed a
planning framework ten to fifteen years ahead, including increased wind power generation. In
the framework, the Swedish TSO recognizes a few concerns about the future energy market.
For instance, planning of the grid is a challenge due to uncertainties regarding future energy
sources. Grid expansions are time consuming, which can hold back integration of wind power
on the Swedish power market. A big share of wind energy is expected to result in increased
value of variation moderators. (Svenska Kraftnät, 2013b)
3.2 The Chinese Electricity Market
In 2002 the state owned State Power Corporation (SPC) monopoly on the power market
ended (Posner, 1975). SPC’s share of 46 percent of the country’s electrical generation and 90 percent of the transmission and distribution were divided into several companies. Two
national grid companies were created, State Grid Corporation of China (SGCC) and China
Southern Power Grid (CSG). Furthermore, five generation companies were created, each with
less than 20 percent market share, along with four power service companies that provides
ancillary services. The purpose with the restructuring of SPC was to create a competitive
market. (Gee, et al., 2007) This coincide with Green & Newbery (1992), who claims that it
would be more efficient if the market consisted of several actors with smaller market shares in
order to avoid deadweight losses. However, the market structure can still be viewed as an
oligopoly (Brander & Lewis, 1986).
Earlier, private investors have been lured into the Chinese power market with very beneficial
agreements, due to China’s lack of sufficient power generation during the late 80’s and 90’s. After the reconstruction in 2002, these private owned generator companies started to compete
for market shares under a “single buyer” system and the previous lucrative agreements were
dissolved. As a consequence of the power market reform, private actors sold most of their
business due to lack of returns. (Gee, et al., 2007)
State Electricity Power Regulatory Commission (SERC) was created in 2003 to work as a
regulatory agency under the State Council. However, the agency does not have the same
authority that similarly agencies in other countries have. SERC is in charge of overseeing
market reforms, for example tariff model proposals and competitive bidding rules, and of
protecting fair competition. SERC share the authority of tariff settings with the much larger
and more authoritatively, National Development and Planning Commission (NDRC), who is
in charge of central planning. NDRC opposed the market reform since it now has to compete
with the more recently created SERC. (Gee, et al., 2007) However, China plans to restructure
the National Energy Administration (NEA), which is under the jurisdiction of NRDC, and
incorporate the functions of the SERC that is to be dissolved. The reason for this is the
overlapping of functions and responsibilities between the NEA and the SERC.
(English.news.cn, 2013)
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3. MARKET CONDITIONS
This new oligopoly situation on the Chinese power market has moved the sector toward
structural unbundling and corporatization. However, pricing is still not truly set by an open
market and controlled by political and societal goals. (Gee, et al., 2007) (Brander & Lewis,
1986) (Posner, 1975) Mou (2014) also claims that the electricity market is still regulated by
the government. Furthermore, to create a united electricity market is more effective than the
current regional and provincial market. (Mou, 2014)
3.2.1 Electricity Generation
China is the largest global energy consumer and their electricity generation comes mainly
from fossil fuels where coal is dominating with 77 percent, as seen in Figure 17. China’s rapidly growing economy together with being the world’s most populous country drives the
urge to secure energy resources. In 2013, new leadership emerged in China and the new
administration has a more long-term and sustainable focus.
Figure 17: China’s Electricity Generation 2012, Source: (U.S. Energy Information Agency, 2012a)
3.2.2 A Controlled Market
In comparison to Sweden’s current competitive electricity market, the electricity market in China is controlled by the State Council. The State Council has ultimate control over the
power sector and its development and operation. NDRC, who is under the control of the State
Council, reviews and approves electricity tariff settings and adjustments. Regarding new
power projects, the tariff is often proposed by the provincial government, reviewed by SERC
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3. MARKET CONDITIONS
and approved by NDRC. New power projects also needs approval from NDRC before being
established. (Ma, 2011)
In 2009, a four category fixed feed-in tariff for new onshore wind power projects was
announced by NDRC. This was implemented to benefit the wind power industry and abolish
the earlier complex and time consuming tariff setting process. The new feed-in tariff has been
divided into four categories to reflect the wind resources in the different areas. The regions
with most beneficial wind conditions in north and west has been given a tariff of 0.51
RMB/kWh ($0.082/kWh). The regions with less beneficial wind conditions have been given
tariffs of 0.54 RMB/kWh ($0.086/kWh) and 0.58 RMB/kWh ($0.093/kWh), respectively.
Regions with even less wind resources have been given a tariff of 0.61 RMB/kWh
($0.098/kWh). Figure 18 shows the different tariff regions. These new feed-in tariffs are the
minimal on-grid tariffs in each region. The developer of each project has the possibility to
negotiate with the grid company for a better tariff. However, it is unlikely that the grid
companies will offer higher tariffs than minimal tariff defined. (Ma, 2011)
Figure 18: Feed-in-tariffs for onshore wind power, Source: (Hu, et al., 2013)
3.2.3 Upcoming Challenges
China’s ambitious renewable energy goals will continue to bring challenges to the grid. The
country aims to reach 200 GW of installed wind capacity and 50 GW installed solar capacity
by 2020. (The Electrical Energy Storage Magazine, 2014) The rapidly growing wind power in
China over the last decade, and especially after the first Renewable Energy Law was issued in
2006, had already brought substantial challenges for the county’s grid infrastructure. The
majority of wind farms in China are built in northern or north-western parts of the country due
27
3. MARKET CONDITIONS
to suitable weather conditions. The demand of electricity however, is mostly situated in the
eastern parts of the country. This means that electricity has to be transmitted through large
distances to reach the demand centres, as seen in Figure 19. For example, the distance from
Xinjiang province to Central China Grid is 2 500 km and to Eastern China Grid the distance is
4 000 km. (Li, et al., 2012)
Figure 19: Locations of wind farms and electricity demand centres, Source: (Li, et al., 2012)
The geographic disparity between power demand and the geographic distribution of installed
wind power capacity put pressure on grid connectivity. Demand centres are far away from the
large wind resources in the northern parts of the country, where grids are fairly weak with
insufficient capacity or technology to feed in the wind power. Grid balance can be disrupted
by low-quality generation, resulting in further wind capacity surplus. Given that technology
remains unchanged, the allowable grid-connected wind power capacity will be limited to a
relatively low level, otherwise the grid cannot work. Wind power generation exceeding
allowable grid-connected capacity will therefore be curtailed, even though wind power has
access priority to the grid. (Wu, et al., 2014)
Wind power curtailment along with the lack of transmission capacity from wind power plants
is a large problem in China. As seen in Figure 20, the curtailment for some provinces is
28
3. MARKET CONDITIONS
substantial. The total wind curtailment in China reached 12.3 TWh in 2011, representing 16
percent of China’s total generation from wind power. This result in an economic loss of over 1 billion US dollars, leading to 7.6 million tons of carbon emissions from coal power plants
that could have been saved. (Clavenna, 2012)
Figure 20: Percentage of curtailed wind generation by province in 2011, Source: (Clavenna, 2012)
A few factors represent the major challenges in the country and contribute to wind
curtailment. Infrastructure is influenced by a weak transmission grid, long distances between
wind resources and load centres, coal-fired power plants and insufficient market mechanisms.
According to Li et al. (2015) feed-in tariffs are unfavourable and dispatch priorities are
unreasonable. In addition, wind power grid integration is insufficient. (Li, et al., 2015) Also
Wu et al. (2014) recognizes that present policies hinder improvement of wind power
integration technology. Wind power integration can be developed by increasing wind power
generation quality (by stabilizing the output) and by improving grid technology. However,
wind power companies have no incentive to invest in solutions to increase generation quality
(including system control, dispatch and transmission), since the area pricing of wind power is
based on fixed benchmark prices unrelated to generation quality. The income depends on
wind power capacity, which technological enhancement cannot increase in a short time
perspective. (Wu, et al., 2014)
Moreover, Chinese power grid companies have no incentives to improve wind power
connection technology. The companies pay a fixed price for wind power, regardless whether
grid technology is improved or not. Low-quality wind power generation can be curtailed to
ensure system security, since there is no obligation to connect wind power into the grid if the
grid connection requirements are not satisfied. Thereby, instability from low-quality wind
power generation can require large investment costs for grid companies to improve
29
3. MARKET CONDITIONS
infrastructure and regulating technology. In addition, wind power has higher price than
traditional energy sources and increases consumer costs. Thereby, electricity demand
decreases following an income reduction for power grid companies. Consequently, power
grid companies do not profit from improving wind power integration technology. (Wu, et al.,
2014)
Chinese wind power policies has created reverse wind power incentives for generators and
transmitters. Consequently, the ability to manage wind power is currently far behind
installation development. Wu et al. (2014) suggest a reformation of the wind power pricing
system in order to remove imbalanced benefit distribution and encourage coordination on the
wind power market. Also, economic incentives and regulations for wind plants could result in
that grid connection requirements can be reached. By introducing risk-sharing instruments,
stakeholders can become aware of and carry out required obligations, such as system balance.
By policy and instrument improvements wind surplus can be reduced, wind power
development promoted and the environment protected. (Wu, et al., 2014)
3.2.4 Emerging Market
China is a developing country with an emerging market. This is supported by MSCI (2015),
which classifies China as an emerging market. This classification is set by several criteria’s such as; economic development, size and liquidity requirements and the market accessibility
(MSCI, 2014).
Many emerging markets have larger instability and stronger regulations compared to
developed markets. Lou (2003) state that the growth rate in emerging markets is fast and
instable, with many businesses existing at growing stages. Businesses in rapid growing
industries are more likely to challenge unpredictable market fluctuations than in slowgrowing industries. (Luo, 2003) Moreover, Wang et al. (2014) recognize that China is
influenced by fast urbanization, which tend to increase energy consumption and carbon
emissions. The energy sector, containing a large share of water-intensive coal production, put
large constraints on water resources (International Energy Agency, 2012). To become a lowcarbon economy, Wang et al. (2014) stress the importance to increase renewable energy
technologies and develop energy policies.
Renewable energy technologies are today expanding in developing countries. According to
the International Energy Agency (2014), global energy trends indicate that several developing
economies have intensified ambitions to become frontrunners in the development of lowcarbon energy technologies. As an example, more than half of the world’s solar PV installations were located in Asia in 2013. Furthermore, China’s electrification of the transportation sector has increased in order to reduce carbon emissions and improve air
quality. (International Energy Agency, 2014)
Technology development has also advanced over the last decade, to reach economic and
climate targets. The International Energy Agency (2015) recognizes that China aims to gain
economic advantage from implementing more sustainable energy policies and technology
reforms. This could accelerate innovation of low-carbon technologies and promote additional
climate goals. While expanding infrastructure, developing economies can be early movers in
applying a system transition to low-carbon technologies. Dynamic power systems require
30
3. MARKET CONDITIONS
major investments or have a major increase of demand. In such power system, a complete
system transition can be beneficial to balance demand and response more efficiently. In a
more stable power system, such transition would result in higher economic pressure.
(International Energy Agency, 2015)
As developed economies become more devoted to decrease carbon emissions, national
climate targets promote increased share of intermittent power generation. Further, to reach
targets of reducing global emissions climate actions in emerging economies will be critical.
Thereby, the International Energy Agency (2015) recognizes that developed economies’ market and energy policy experience can support energy actions in developing countries. By
transferring knowledge and technology support to developing economies, research and
strategies for technology advantages can be designed and air pollution reduced.
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4. MARKET ANALYSIS OF VARIATION MODERATORS
MARKET ANALYSIS OF VARIATION MODERATORS
This chapter investigates the market for grid battery storage and transmission as variation
moderators for intermittent renewable power generation. Since grid battery storage is an
emerging technology without an established market, potential market entry barriers are first
considered. Thereafter, market driving forces that influence and drive the development of grid
storage integration, are identified and analysed. This is followed by an analysis of market
driving forces for transmission expansion. These forces depend on country-specific conditions
and are thereby analysed for Sweden and China separately.
4.1 Grid Storage
Battery storage can change the power system and become one of the market leading storage
technologies for grid applications. This is supported by The Boston Consulting Group (2010)
and Insight_E (2014). Insight_E (2014) expects Li-ion batteries to be a foremost battery
storage technology in the future. The technology development is driven forward by increasing
demand of electric vehicles and home storage batteries. Today there is also an increased
interest in Li-ion battery technology for large-scale grid applications. (Insight_E, 2014)
Further use of storage is expected to make prices and efficiencies more favourable and
therefore more economical. (The Boston Consulting Group, 2010) Because of the recent
appearance of large-scale Li-ion battery storage, there are still limited data available and
substantial market entry barriers to overcome.
4.1.1 Market Entry Barriers
Implementation of grid storage in the electrical power system is associated with several
market entry barriers. The most significant have been identified as ownership and operation
uncertainties, recognition by policy makers, product diversity, competition, capital
requirements, market experience, technical performance and changing market conditions.
4.1.1.1 Ownership Uncertainties
One barrier of entry for grid storage establishment is to clarify which market actors that
should own and operate the storage. Since the national grid in both Sweden and China is
owned and operated by the government in respectively countries it puts constraints on the
ownership question for grid storage.
Current monopoly situation can hinder grid storage integration. The transmission grid in
Sweden is owned and operated by a state-owned monopoly that decide whether to invest in
new technology or not. Similarly, China's transmission grid is owned by two state-owned
companies, creating an oligopoly. Grid operators would benefit from grid storage, but the
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4. MARKET ANALYSIS OF VARIATION MODERATORS
technology would also bring high investment costs. Anuta et al. (2014) argue that grid
operators can cover the high capital cost associated with grid storage integration better than
other potential market actors. The storage system could provide continuous power regulation
and be owned and operated by grid operators, as a part of the transmission system.
Transmission grids that receive intermittent power is suggested to consider energy storage in
accordance with established regulation. (Anuta, et al., 2014)
Potential owners involve market actors from the energy sector, which have the right
knowledge to make an impact on the market situation. This is supported by The Boston
Consulting Group (2010) that has identified power producers as possible third party owners of
grid storage facilities. It is however uncertain whether these actors will be allowed into the
current energy infrastructure or not, since the transmission grid is controlled by monopolies.
Ownership by small power producers could involve investment issues because of high capital
costs and partnerships between market actors might be necessary. (The Boston Consulting
Group, 2010) In this manner, grid operators are more likely to carry the large investments
better than small power producers.
Conversely, European legislation can be a major barrier for storage ownership by grid
operators. This theory is supported by several research findings within the area. There is a risk
that storage can be classified as a generation tool that would intrude the market rules for
unbundling ownership, included in a directive created by the EU. If grid operators acted on
the generation market, the system wide responsibility could be hindered. Furthermore, neither
a clear definition of storage nor a framework is provided by the EU. However, the benefits of
deploying energy storage to the grid are recognized. (Insight_E, 2014) (The Boston
Consulting Group, 2010) The uncertainty about how to interpret EU’s unbundling directive
sets central barriers for grid storage integration and storage development in EU membership
countries. Vague ownership regulations constitute obstacles for grid operators and potential
stakeholders and hinder the development of power system enhancement.
Because of the unbundling directive, power producers might be the only possible owners of
grid storage in the EU today. Power producers can also benefit from grid storage facilities by
taking advantage of spot price fluctuations on the competitive market and increase income. In
addition, more energy can be utilized since less energy would be curtailed. It is however
uncertain whether these actors will be allowed into the current grid infrastructure or not, since
the grid is controlled by monopolies.
China’s controlled market does not bring power producers incentives to invest in grid storage
technologies, since no profit can be received from spot market fluctuations. Neither power
grid companies nor power producers, such as wind power companies, have economic
incentives to invest in regulating technologies like grid storage, as described in section 3.2.3.
There is no further profit to be received by improving wind power integration technology or
by increasing generation quality. Instead, wind power generation is curtailed to ensure system
security.
4.1.1.2 Operation Uncertainties
Uncertainties about storage ownership also involve challenges about how the grid storage
should be operated. There is a potential risk of conflicting interests between the owner and the
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4. MARKET ANALYSIS OF VARIATION MODERATORS
operator of a storage facility. Insight_E (2014) acknowledge that the owner would want to
take fully financial advantage of the storage by dispatching electricity according to market
data and price anticipations. Operators of the grid storage would on the other hand want to
dispatch electricity depending on grid requirements. (Insight_E, 2014) This potential conflict
could be reduced by introducing a clear regulated framework.
The risk of conflicting interests could also be limited if the same market player owns and
operates the grid storage. At an early stage of market entry, small power producers can be the
best possible operators of energy storage systems. In comparison to large established utilities,
small utilities can be more adjustable and open for new business opportunities that can
strengthen the market position. Small-scale community storages might be more convenient at
first, while large-scale energy storage systems might require partnerships between several
market actors. Once the market for energy storage is established, new actors can appear and
larger storage facilities integrated. This is supported by The Boston Consulting Group (2010),
which also expects regulators to increase power producers’ responsibility of balancing power at peak and off-peak hours. Furthermore, present PV suppliers already offer battery storage
solutions in small scale. Energy storage could also be provided in a large scale, and assist
power producers in providing balance regulation. (The Boston Consulting Group, 2010)
4.1.1.3 Government Policies
One of the largest barriers of successful market penetration is found to be absence of
recognition by policymakers. There is not a developed framework for energy storage for grid
use, which causes uncertainty for stakeholders that hold back potential investments in the
business. The lack of standards can cause stakeholders to invest in other areas where the
market is more mature. This is supported by Anuta et al. (2014), who point out that
technologies of renewable energy sources can benefit from inclusion within the renewable
energy targets and therefore be perceived as cheaper compared to grid storage. Inclusion of
energy storage into the renewable energy targets would however be problematic, since the
energy stored can originate from any kind of energy source. (Anuta, et al., 2014) Also the
Electric Power Research Institute (2013) recognizes challenges for regulators and policymakers to valuate energy storages, since comparison with other conventional solutions is
problematic. Operation can be viewed both for generation and for loading, but with limited
energy duration. There is also a lack of commercial track record of energy storage, which can
cause uncertainties about costs and performance related to energy storage utilization.
(Electric Power Research Institute, 2013) Because grid battery storage is an emerging
technology, government action is necessary to initiate the market development.
Government policies have large effect on market entry, where standards, regulations and
restrictions affects the barrier of entering a market. This is supported by Porter’s (1979)
theory about market entry barriers. There is an absence of business models and regulatory
framework for integrating grid storage in the present power system. The lack of standards and
measures of connecting, operating and maintaining grid storage is also recognised by previous
research (Anuta, et al., 2014) (Eyer & Corey, 2010). Governmental support can provide
economic incitements for energy storages and be of great importance in order to promote
improved balance in the energy infrastructure system.
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4. MARKET ANALYSIS OF VARIATION MODERATORS
Reasonable compensation set by authorities and regulators can be significant important to
further promote grid storage development, especially since energy storages do not yield
income that investors normally require. This is confirmed by Eyer & Corey (2010) and Anuta
et al. (2014), who recognize the importance of authorities and policymakers recognition of the
advantages that energy storage systems can carry. Subsidies could help reduce the large
capital cost to lure investors into this new business area with high risks and lack of clear
regulations. Compensation for energy storage can impede stakeholders’ current cautiousness
in taking high risks on new technologies because of large investment costs and conventional
regulations. (Anuta, et al., 2014), (The Boston Consulting Group, 2010) When a few actors
initiate market investments, the market development is driven forward. Recognition of the
value of grid storage by policymakers could thereby reduce the entry barriers for the
technology.
To implement an effective and robust business model is important for grid storage penetration
on the power market. In order to do so, governments should consider grid storages as
variation moderators and provide a regulated framework to reduce uncertainties in investment
decision making. Robust business models for integrating energy storage would drive and
increase the market potential of integration into the electricity grid. In consistency to Anuta et
al. (2014) findings, stable electricity markets and policies are driving forces which can
decrease capital costs by reducing uncertainty in energy storage investments and at the same
time stimulate the technology development. Anuta et al. (2014) identify the need for
modernisation of the current market structure, by establishing suitable regulation for grid
storage and policies to provide opportunities for stakeholders and third party owners of grid
storage systems to build sustainable business models. According to Anuta et al. (2014), the
design of applied business models should depend on grid location, regulations, ownership and
market structure, in order to implement grid storage successfully.
4.1.1.4 Product Diversity
A potential market barrier is the diverse types of energy storage technologies. There are many
potential technologies and applications for grid storage, but no single technology available
has the appropriate characteristics for all applications. This is confirmed by previous research
findings by Karlsson & Dahlqvist (2014). This can result in competition over funds for
research and development of several grid storage technologies. The development of different
types of energy storage technologies can be a potential barrier, since product differentiation
can form a source of market competition at the market entry stage. This is supported by Porter
(1979), who also claims that product differentiation can decline as the business mature and
then lower barriers of entry and increase buyer-power. (Porter, 1979) As one or a few grid
storage technologies establish the number of applicable grid storage technologies might
decrease.
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4. MARKET ANALYSIS OF VARIATION MODERATORS
4.1.1.5 Competition
Apart from the product diversity within energy storage technologies, there is also competition
from other technologies which also have the potential to provide flexibility on the energy
market. Competition is expected from flexible generation1, integration of demand response2
solutions, Smart Grids3, distributed generation4 and renewable technologies. (Eyer & Corey,
2010) (International Energy Agency, 2014) Adjustable wind generation and increased
transmission capacity are two other examples of competition. (Johnson, et al., 2014) These
competitive technologies and solutions compete for funding and a place in the future
electricity market (Eyer & Corey, 2010). The economical aspect, with high capital costs for
grid storage technologies, can hinder grid storage to compete with other, more cost-effective
technologies.
Previous research findings has compared the cost of expanding the transmission grid and the
cost of integrating grid storage, resulting in diverse conclusions. According to findings by
Döring et al. (2014), options like grid expansion can today be more cost-effective than energy
storage. This is however a controversial and depends how cost estimations are performed. As
the cost for grid storage technology decreases, storage can in some situations provide a more
flexible solution. According to the International Energy Agency (2014), the demand of energy
storage is expected to increase as intermittent power generation increases, due to the system
flexibility that energy storage can provide.
It is likely that energy storage will be a part of the infrastructure development, in combination
with other flexible technologies and solutions. Even though grid storage will not be the only
key technology in the future energy infrastructure, it can provide an important asset in a
system-wide development. Both the International Energy Agency (2014) and Anuta et al.
(2014) confirms this theory and recognize that energy storage can be combined with other
interconnecting and demand-response solutions. Research and development for grid storage
should therefore be integrated with the present infrastructure, in order to optimize investments
and management in the future electricity system. This is confirmed by the International
1
Generation that is easy to regulate, such as hydro power and gas power plants.
Federal Energy Regulatory Commission defines Demand Response as: “Changes in electric usage by end-use
customers from their normal consumption patterns in response to changes in the price of electricity over time, or
to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when
system reliability is jeopardized.” (Balijepalli, et al., 2011)
3
Smart Grids is an international concept of a future efficient electrical system. By using new technology the
current system can be developed to meet the demand of a sustainable energy supply in the most cost-effective
way possible. (Svenska Kraftnät, 2013b, p. 58) Communication, control and computer technologies are expected
to be important for reduced costs and increased reliability. Smart Grids is expected to enable efficiency and new
products, services and markets. (Eyer & Corey, 2010, p. XXVII)
4
Distributed generation refers to power generation that takes place close to the consumption. Generation occur
on- site which reduces the costs of transmission and distribution. Historically this kind of generation came from
combustion generator like diesel generators. Today, solar power has become a popular distribution generator.
(Bloom Energy, 2014)
2
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4. MARKET ANALYSIS OF VARIATION MODERATORS
Energy Agency (2014), which promotes a wide system thinking. Nevertheless, for energy
storage to compete with other options cost-effectiveness is a key aspect.
4.1.1.6 Capital Requirements
Large capital cost is a major financial barrier for market integration of grid storage. This
statement is supported by many sources, including Johnson et al. (2014), Hittinger et al.
(2012), Anuta et al. (2014), International Energy Agency (2014) and Eyer & Corey (2010).
Moreover, Porter (1979) identifies large capital requirements as a barrier of market entry. This
applies especially if the required capital is used for costs that cannot be recovered, such as for
Research and development (Porter, 1979). Such costs are likely to be required for market
integration of grid storage technologies that have not yet been introduced for large-scale
usage. This is confirmed by The Boston Consulting Group (2010), that recognize that the
technology for large-scale application of electricity storage is not fully formed and
inadequately operational tested, with the exception of hydro pump storage. Historically,
energy storage research has focused on improving performance. Improving the manufacturing
process to be able to decrease the capital cost will be far more valuable in the near term,
which is confirmed by Hittinger et al. (2012). The real costs and worth of energy storage can,
according to Anuta et al. (2014), change if the technology improves, investment costs
decrease and knowledge among users increase.
4.1.1.7 Market Experience
One market entry barrier for grid storage is the lack of market experience. According to Porter
(1979), market experience involves several advantages which stimulate cost reduction,
including economies of scale, capital-labour replacement and efficiency among workers. Eyer
& Corey (2010) acknowledge that limited understanding, knowledge and experience of
energy storage together with limited risk-reward sharing mechanisms are major challenges
which energy storage involve today.
However, as technology improves and the technology cost reduces, the entry barrier may no
longer exist. According to Porter (1979), new competitors can even experience a cost
advantage when exempted from large investment costs. In this matter, grid storage might
require less investment cost in the future after integration on the energy market. Although the
first market actors may experience high technology costs, the costs might decrease for
following actors entering the market. In this manner, the technology of Li-ion battery is
advantageous for market integration of grid use. As the battery technology is developed for
electric vehicles, the market experience increases.
4.1.1.8 Technical Performance
A key challenge for all electrical storage technologies is limitations in technical performance.
There is a loss of energy in all systems and the efficiency can be as low as 80 percent for
battery storage. The low efficiency can cause a disadvantageous business situation and entails
costs for the lost electricity. (The Boston Consulting Group, 2010) This, together with high
capital cost, can hinder grid battery storage to be economical profitable.
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4. MARKET ANALYSIS OF VARIATION MODERATORS
Technical performance can also hinder storage integration with large wind farms that require
large storage capacity. A technical limitation is the amount of energy that can be stored,
which Karlsson & Dahlqvist (2014) confirm. Li et al. (2012) claims that the energy storage
capacity for electrochemical energy storage systems cannot provide satisfactory support to
wind farms, with an installed capacity of 50 MW. This could, according to Li et al. (2012)
make electrochemical energy storage inappropriate in China, where the majority of wind
farms exceed 50 MW installed capacity and it could therefore be hard to find a suitable
reserve capacity system to obtain security of supply. (Li, et al., 2012) However, from a system
perspective as this thesis focus on, grid storages can be scaled by building numerous storage
units connected in the system to obtain desired power capacity.
4.1.1.9 Changing Market Conditions
The disability to look several years ahead can be a market entry barrier for an emerging
technology as grid battery storage. Today the electricity mix does not comprise a large share
of intermittent power sources, but the problems related to intermittent power generation is
expected to escalate as the share increases. The barriers of entry changes as market condition
changes (Porter, 1979). This is consistent with Craig & Douglas (2005), who identify change
as a market challenge. The fast movement of market conditions force research to adapt and
monitor financial, political and technological changes (Craig & Douglas, 2005).
The strong need for grid storage might not exist today or in a near-term future, but several
years ahead. According to Holttinen et al. (2011), the share of wind generation is crucial for a
cost efficient balancing of energy storage. Wind penetration levels of 10-20 percent of gross
demand is not enough for cost-effectiveness regarding grid storage (Holttinen, et al., 2011).
Göransson (2014) has found that sufficient variation management can be reached by load
shifting from daytime to night-time when 20 percent of the power demand originates from
wind power generation. When wind power generation cover 40 percent of the power demand,
load shifting will not be enough as variation management (Göransson, 2014). Holttinen et al.
(2011) claims that wind penetration levels exceeding 10-20 percent requires extra flexibility,
which energy storage can provide. As the share of wind energy grow, the demand for grid
storage increases. To recognize the future value of grid storage integration actions must be
taken in advance.
4.1.2 Market Forces
Following the market entry barriers for grid storage, several market forces can be concluded.
The development of energy storage is driven by several forces which can create opportunities
for integrating energy storage into the grid. This section will present the drivers on the market
for grid storage.
4.1.2.1 Technology Development
The ongoing technology development increases the potential of energy storage for grid
integration. Because of similar technical properties for battery technologies, other research
areas such as Smart Grids, electric vehicles and home batteries drive the technology
39
4. MARKET ANALYSIS OF VARIATION MODERATORS
development forward also for grid storages. These developments can have significant role for
implementing the storage technology in the energy infrastructure in a large scale. The
development for grid storage is also driven by economies of scale from increased use of
batteries. (Eyer & Corey, 2010) (Anuta, et al., 2014) (IEC, 2011) (Ny Teknik, 2015)
Li-ion batteries predict to decrease radically in price along with technological improvements
due to the electrification of the automotive industry. The growing market for electrical
vehicles and for electrical portable devices pushes the battery development forward and drives
the costs down (Eyer & Corey, 2010). As seen in Figure 21, large cost reductions have been
made in the last few years. The cost reductions can be expected to continue as technology
improves in the future. These factors are crucial for grid storage’s entry in the energy infrastructure market. As earlier stated, technical and economical restrictions still limits grid
storage ability for large scale impact. However, since these issues continuously reduce with
the on-going technological development, it could be believed that grid storage will have a
bright future in a future energy infrastructure system.
Figure 21: Historical cost of Li-ion battery packs, Source: (Nykvist & Nilsson, 2015)
Also the development of other flexible solutions in the power grid can provide opportunities
for grid storage. Energy storage is expected to be a balancing instrument in the future Smart
Grid (Anuta, et al., 2014), (IEC, 2011). Smart Grids involves distributed energy resources and
load aggregation, which contributes to increasing market demand for energy storage. (Eyer &
40
4. MARKET ANALYSIS OF VARIATION MODERATORS
Corey, 2010) This follows the growing need for improved electric service power quality and
reliability.
Furthermore, batteries for home applications are likely to contribute to a faster development
for grid storages as well. According to Ny Teknik (2015), Tesla5 has announced a battery for
home and office applications to expedite the transition to an efficient renewable energy
system. Tesla Motors (2015) claims that the price for this home battery of 7 kWh is $3000
which is approximately $430/kWh. This was announced during this study’s final moments
and it is another example of the fast development within the energy storage field.
4.1.2.2 Congestion and Security
Grid storage has also been recognized as an alternative to expand the current transmission
grid, or at least postpone the very costly investment of a new transmission lines, so called
transmission deferral. This is illustrated in Figure 22. This is verified by Zakeri & Syri (2014)
who states that transmission grids are oversized in order to handle temporary peak hours. If
the grid capacity needs to be increased, grid storage can be an alternative instead of
reinforcing the transmission grid. (Zakeri & Syri, 2014) Likewise, Insight_E (2014) claims
that one of the highest value of energy storage is received when investments in new
transmission grids can be postponed.
Figure 22: Transmission Deferral, Source: (THINK, 2013)
Problems related to congestion in the transmission grid can push the introduction of energy
storage into the grid, in order to improve reliability and security. According to Eyer & Corey
(2010), managing peak demand and reducing congestion on current transmission lines can
thereby drive the storage development. This coincide with transmission deferral, as mentioned
5
Tesla is an American company, founded in 2003, who designs and manufactures electric vehicles and electric
powertrains. (Tesla Motors, 2015)
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4. MARKET ANALYSIS OF VARIATION MODERATORS
above, since transmission upgrades also is a solution of the reliability and security issues
related to congestion. Postponing costly transmission upgrades by investing in grid storage
can reduce issues associated with congestion and contribute to increased economic benefit.
Zakeri & Syri (2014) claims that service costs for power supply reliability and grid
management can be reduced when implementing grid storage in the energy infrastructure.
Avoiding oversized transmission capacity can also lead to decreased losses in the grid
(Brakelmann, 2003) (Negra, et al., 2006).
Furthermore, grid storage can provide new opportunities for operating the transmission
system in case of incidents and major disturbances. Döring et al. (2014) claims that the
increase of intermittent renewable energy in Europe has decreased existing security margins.
Moreover, integration of grid storages can contribute to an even higher reliability than grid
reinforcements can. In addition, the economic cost associated with reliability cannot be
assigned by market instruments. The reliability and system security aspect has a social value
and belongs in a regulated framework for energy storage. (Döring, et al., 2014) The
development of grid storage would not only lead to improved system reliability and security,
but also reduce wind curtailment.
4.1.2.3 Wind Curtailment
Wind curtailment can be a future concern in Sweden and is already a major problem in China.
By operating grid storage for renewable time shifting, more wind power available can be used
and wind curtailment reduced. By utilizing more energy from the wind, wind farm
investments are used in an efficient manner. Thereby, storage can contribute to increased
economic benefit, which also coincides with an environmental friendly and sustainable
thinking. Figure 23 shows how grid storage can influence the amount of curtailed wind
energy based on a simulation modelled by Silva-Monroy & Watson (2014). The result of
integrating a 500 MW storage shows a clear reduction of spilled wind energy by about 2
percent. (Silva-Monroy & Watson, 2014)
42
4. MARKET ANALYSIS OF VARIATION MODERATORS
Figure 23: Wind curtailment as a function of wind energy penetration, with and without a 500 MW storage device. Source: (Silva-Monroy &
Watson, 2014)
However, other studies have shown that it might not be cost efficient to invest in grid storage
for only a few MWh of curtailed energy. Holttinen et al. (2011) claims that it can be
preferable to spill a few percent of the annual wind power generation due to economic
reasons. This is supported by Johnson et al. (2014), who claim that batteries available today
and in the near-term future are found to be too costly to reduce curtailment in an economical
viable way. Yet, the share of intermittent energy sources is increasing, meaning that curtailed
energy can increase. In a long term perspective, it is reasonable to believe that integration of
grid storage, with the purpose to reduce curtailed energy, will be more economically
reasonable.
Furthermore, problems related to spill could be solved by investing in flexible energy systems
as storage rather than investment in new transmission grids to export generation surplus. Lund
& Münster (2003) claims that investment costs for new transmission lines are significant
higher than costs related to avoid surplus generation. The recommendation is thereby to invest
in a flexible energy system, including heat pumps, regulation of CHP plants and heat storages
to limit surplus generation. The solution of a flexible energy system is found to be the best
option independently if the market price is high or low, but dependently on market reactions
on surplus generation. If the market reacts, substantial profits can be made. (Lund & Münster,
2003) These findings are of great interest for this master thesis, since it is found to be more
economical to avoid generation surplus, by for example including energy storage, than to
transmit excess energy to another areas.
4.1.2.4 Economic Incitements
Renewable time shifting can not only reduce wind curtailment and congestion problems but
also profit from the spot market. Since there are large gaps between peak and off-peak prices,
the storage unit can be charged when the electricity price is low and discharged when the
electricity price is high. The off-peak prices are most likely to occur when congestion occurs
43
4. MARKET ANALYSIS OF VARIATION MODERATORS
and there is an excess of energy in a certain bidding area. This is verified by Anuta et al.
(2014) who claims that high electricity prices as well as large gaps between peak and off-peak
prices are two driving forces for energy storage. Further, Zakeri & Syri (2014) also argues
that grid storage can be operated to receive higher electricity prices on open spot markets for
electricity trading. The profitability of energy storage can thereby increase due to deregulation
of electricity markets and price arbitrage. The level of economic benefit depends on how
much the spot prices fluctuate.
These increased revenues can be retrieved by price forecasting along with optimized
scheduling for charging and discharging time. This is also concluded by Zakeri & Syri (2014)
who claims that improved price forecasting and optimized scheduling for charging and
discharging energy will lead to increased revenue from energy storage systems. However, if
congestion is reduced due to increased integration of variation moderators such as grid
storage and transmission, also the incitement of spot market benefits reduces since the
fluctuation in prices would not be as high. In a long-term perspective, the electricity prices at
peak hours would decrease as there is no longer a lack of supply. Similarly, low dips in
electricity prices will be reduced as excess energy supply can be either stored or transferred to
another location where the demand is higher. This does not apply for the Chinese market
where they have a predetermined feed-in tariff. Furthermore, there are sources that claim that
the average electricity price in Sweden will increase in the future. (Ramböll, 2014) (Sweco,
2014)
High generation costs to stabilize intermittent power generation can be reduced. To adjust
frequency from instable generation thermal generators are normally used. As the share of
intermittent energy sources increases the output margin from thermal generators must
intensify, which reduces efficiency. If grid storage can alleviate output fluctuations from
intermittent power generation, the thermal generators can operate at a higher efficiency.
(IEC, 2011) Thereby, high generation costs can be reduced and efficiency improved.
4.1.2.5 Energy Targets
The growing sustainable thinking in the world in recent years has made wind power to one the
most emerging energy sources on the planet. The EU has set certain energy targets for 2020
and 2030 where wind power plays an important role since the targets involves increasing the
share of renewable generation to decrease greenhouse gas emissions. (European Commission,
2015) Insight_E (2014) recognizes that energy storage can bring an important advantage for
the EU to reach these energy targets. This is assumed to be one of the most important driving
forces for grid storage success of entry in the future energy infrastructure. However, it
depends of course of a lot of other factors such as political, technical and economical
properties.
China faces major pollution issues along with a rapidly growing economy which also
contributes to wind power development. However, this leads to issues in the energy
infrastructure due to the intermittent electricity generation from wind power. Furthermore,
Littlewood (2013) claims that over 80 percent of applications for energy storage projects have
the purpose of integrating renewable energy in China. As displayed in Figure 24, Li-ion is the
foremost technology with over 100 MW installed capacity (Littlewood, 2013). Also globally,
44
4. MARKET ANALYSIS OF VARIATION MODERATORS
several targets are associated with a cumulative share of intermittent energy sources. The
growing amount of intermittent renewables that requires regulation gives opportunities for
energy storage (Eyer & Corey, 2010).
Figure 24: Energy storage projects in China. Source: (Littlewood, 2013)
4.2 Transmission
The increasing share of intermittent power generation yields that increased transmission
capacity is necessary in order to secure the supply and maintain a stable and suitable voltage
profile. Holttinen et al. (2011) claims that integration cost from transmission investments may
be required for handling larger power flows and maintaining a stable and adequate voltage
profile. It is also needed if congestion occur on the grid, due to new wind generation far from
load centres. However, grid reinforcements have other benefits to consumers and producers
such as reliability and/or increased trade. The level of investments needed is very dependent
on where the wind power plants are located relative to current grid infrastructure and load.
Furthermore, they are not continuous and can differ and be very high in some cases.
(Holttinen, et al., 2011) Holttinen et al. (2011) also claims that the amount of grid
reinforcements should be customized to final amount of wind power instead of investing in
several different phases. However, it is not efficient to invest in grid reinforcements to avoid
bottlenecks on the grid completely. It can be preferable to spill a few percent of the annual
wind power generation due to economic reasons. Furthermore, a system without bottlenecks
can be classed as over-sized and not economic optimal, of course should severe bottlenecks
be avoided. (Holttinen, et al., 2011)
4.2.1 Market Forces Sweden
Congestion is a major driving force for transmission expansion and leads to imperfect market
competition. According to Shrestha & Fonseka (2004), constraints or bottlenecks, in any
45
4. MARKET ANALYSIS OF VARIATION MODERATORS
form, will prevent perfect competition between market participants in the transmission grid.
The consequence of this is price hikes above the marginal costs. To maximize the social
welfare it is important that supplier surplus (SS) and consumer surplus (CS) is maximized.
The SS curve and CS curve, respectively, can be seen in Figure 25. Furthermore, to maximize
social welfare an effective transmission system operation and planning becomes important.
(Shrestha & Fonseka, 2004)
Figure 25: Supply and demand side bid representation
The development of transmission in the Nordic countries is driven by market factors such as
price differences in different bidding areas, due to congestion. According to Göransson
(2014), an increase in exchange capacity between the Nordic countries would make it possible
to transfer electricity from one trading partner with low marginal cost to another one with
higher marginal cost. Low marginal cost is attractive to electricity intensive industries and
other electricity consumers, but is less attractive to the power industry. However, large
investments in transmission create marginal costs corresponding to marginal costs during
low-load hours in the United Kingdom and Germany. Thereby, it is possible to take advantage
of importing at a low price and exporting at a high price. (Göransson, 2014) This could create
economic incentive for the power market in the Nordics to invest in further transmission
expansion.
Furthermore, spot price fluctuations on the market also create an incitement to invest in
increased capacity. Electricity can be bought at a low price and sold at a higher price.
However, this incitement might be reduced over time, as installed capacity of variation
moderators increases, and the price differences between peak and off-peak hours reduce. This
also applies for increased grid storage integration, as discussed earlier in section 4.1.2.4.
Also at European level, transmission development is driven by removal of bottlenecks.
Internal grid expansion in Sweden and other countries in Europe is necessary to stabilize the
generation in Sweden. Removal of bottlenecks between European countries as well as
domestically yields stabilized generation patterns of conventional generators according to
Aigner (2013). This might lead to an overall price reduction of 5 percent and in some areas a
reduction of about 40 percent, in comparison to the case without grid expansion. A costoptimal grid expansion requires investments of $39.3 billion in 2030 but result in decreased
production costs of $20.1 billion. The resulting payback time is a period of about 6 years.
(Aigner, 2013) This highlights the importance of a favourable investment situation as a
condition for making large investments in the infrastructure.
46
4. MARKET ANALYSIS OF VARIATION MODERATORS
Another driver for transmissions development is EU’s target of a United European Electricity
Market. This target creates incentive to strengthen transmission capacities inside of Sweden
and to connect to the rest of Europe to increase reliability and security. To create a united
market in Europe it is necessary to develop the transmission grid. Some of the existing work
within this field promotes cross-national methods for a joint energy market in Europe in a
system with more large scale wind power. According to Aigner (2013), an energy market
without integration require more regulation power because of increased need to balance the
system. Costs can be reduced by exchanging regulating reserves in an integrated power
market in Northern Europe, involving grid expansion. (Aigner, 2013) This is seen as a strong
driver for transmission expansion.
National and international energy and climate politics drives reinvestments in Sweden’s aged
transmission grid. Grid constraints can otherwise hinder the societal development. A large
part of the Swedish national grid is more than 50 years old, as shown in Figure 26. According
to Svenska Kraftnät (2013b), reinvestments in the grid are necessary to reach energy targets to
increase the share of renewable energy. Reinvestments are necessary to replace aged parts in
the system to increase reliability and security. Benefits from this can be taking by investing in
new and more efficient equipment that will lead to an upgrade of installed capacity. Since
reinvestments generally are not as costly as building a completely new transmission line this
could be beneficial for transmission development.
Figure 26: Age of 400 kV and 220 kV grids in the Swedish national grid, Source: (Svenska Kraftnät, 2013b, p. 90)
4.2.2 Market Forces China
Energy targets to reduce the air pollution, relieve water constraints and the increase of
intermittent renewable energy generation drive the expansion of China’s transmission grid. However, the development of the transmission grid is also driven by congestion. China has
major issues in their transmission system, consisting of insufficient capacity in some areas.
China’s rapid growth in the country in recent year drives the development of transmission
grids in the country. China’s electricity infrastructure requires extensive improvements to 47
4. MARKET ANALYSIS OF VARIATION MODERATORS
avoid bottlenecks and maintain a security of energy supply, according to Li et al. (2012). The
existing power grid system is insufficient and cannot manage the increase of wind power
generation in recent years. The independently acting, but state owned, energy companies are
responsible for optimizing only their part of the system. This can hinder the target to build a
robust system and support renewable energy technologies, as it is important to consider the
entire system as a whole in order to reduce bottlenecks. (Li, et al., 2012) (Wu, et al., 2014)
The energy infrastructure is also challenged by a large amount of wind curtailment in the
northern parts of China, as earlier described in section 3.2.3. The lack of sufficient
transmission capacity is a result of the rapidly growing economy with fast expansion of
installed generation capacity in remote locations, far away from load centres. The need to
transmit large capacities over long distances puts high pressure on the transmission grid and
drives the grid expansion in the country. These forces, together with reliability and security
aspects, drive the development of long-distance transmission grids with high capacity to
decrease wind curtailment. This is also stated by Clavenna (2012) who claims that wind
capacity is expected to continue to increase in the northeast and west provinces. These
provinces are far away from China’s natural gas infrastructure, which can reduce curtailment by quickly responding to variations from wind power. Problems related to wind curtailment is
expected to remain the next few years. (Clavenna, 2012)
The high amount of wind curtailment is a result of China’s relatively low investment ratio in
the grid infrastructure, compared to investments in power generation. Li et al. (2012) claims
that the two state grid companies, SGCC and CSG have made heavy investments in the grid
construction, which corresponded to 48.94 percent of investments in the electricity sector in
2008. However, the accumulated investments in the power grid are still lower than the
investments in power generation. Figure 27 shows a comparison between investments in
power grids and power generation that has been made in U.S., Japan, UK and France since
1978. The accumulated investments in Chinese grid infrastructure corresponds to less than 40
percent, which can be compared to the other countries where the share is 50 percent or more.
(Li, et al., 2012) The increased need for investment in transmission is seen as a driver for its
future development. There is no need to invest in large generation capacities if the energy
generated cannot be transmitted to the consumers.
48
4. MARKET ANALYSIS OF VARIATION MODERATORS
Figure 27: Ratio of accumulated investment in power grid and power generation since 1978, Source: (Li, et al., 2012)
49
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50
5. COST-BENEFIT MODEL
COST-BENEFIT MODEL
In this chapter, the cost-benefit model is described. The cost-benefit model is created to find a
cost-effective balance between future investments in transmission expansion and grid storage
integration. The model is influenced by market forces and barriers identified in the previous
chapter. Initially, the case studies for Sweden and China are described followed by
clarifications of costs, benefits, constraints, input data and equations used in the model.
Thereafter, results from the cost-benefit model are presented for different cases in the model.
The Matlab code of the model is presented in Appendices.
5.1 Case Descriptions
The projected case for the model is based on the assumption that the share of intermittent
power generation increases. In Sweden, this is a probable consequence from closing down
three of the oldest nuclear plants situated in SE3. The replacing power generation from wind
power is expected to be transmitted from other parts of the country, most likely SE2 as
presented in section 3.1.3. This can cause problems due to uneven power supply to the grid.
As mentioned in section 3.2.3, wind curtailment is already a major problem in China. Large
capacity of wind power is installed but not fully utilized. Sweden might also experience
problem with curtailment, along with congestion, as power generation from wind increases, as
presented in section 3.1.3. When the power generation is higher than the demand in a certain
area, power can be transmitted to another area further away with higher demand. Another
option is to store energy to supply power to the grid when the supply is lower than the
demand in the current area.
Both of these options require high investment costs. If wind power generation in the northern
parts of Sweden is going to satisfy energy demand in the southern parts of the country, greater
transmission capacity is needed. This is also the case in China, where the wind power
generation in the north needs to be transferred to remote load centres in the eastern parts of
the country, as presented in section 3.2.3. Increased transmission capacity over long distances
involves large capital costs. These costs can possibly be reduced if grid storage is integrated.
Grid storage can also reduce the amount of wind curtailment and supply power to the grid
when there is a lack of supply from wind energy, but this alternative also involves high capital
costs. To consider both these alternatives when making an investment decision in order to
avoid wind curtailment, a cost-benefit model is created. In that way, transmission and grid
storage can be compared in a reasonable manner. The cost and benefits from grid storage
integration have been evaluated and considered in the model.
51
5. COST-BENEFIT MODEL
5.2 Cost Descriptions
A CBA for transmission and grid storage is estimated from costs of real projects. Both
investment costs and future costs, including maintenance, operation and replacement costs,
are taken into account.
5.2.1 Investment Cost Transmission
The investment cost for a power transmission line is based on actual investment cost of
projects in Sweden and China, respectively. In reality, the cost for building a new line is very
project specific and depends on many factors. According to Blomqvist & Gabrielsson (2014)
the cost for moving a transmission line of voltage level 400 kV is about $570,000 per
kilometre, while the cost for building a new line range between $950,000 and $5,695,000.
The large variation in cost depends on whether the line is overhead or underground, as well as
type of terrain. Type of terrain affects both scope and construction time. (Blomqvist &
Gabrielsson, 2014) An underground cable can be up to 5-15 times more expensive compared
to overhead lines with the same transmission capacity. However, underground cables are
more protected from weather variations and the costs of maintenance can be reduced
compared to overhead lines. (Svenska Kraftnät, 2014a) According to Blomqvist &
Gabrielsson (2014) economies of scale also affects the transmission cost, since the cost per
kilometre reduces as the distance increases.
The CBA is based on AC transmission lines, which in general are built stepwise in large
intervals. In Sweden, AC lines are the most common alternative, with a voltage of 400 kV
(Svenska Kraftnät, 2014a). The transmission investment cost for Sweden is based on a recent
transmission project with AC and DC lines combined. This combination is valuated as
relevant in Sweden, partly due to increased urbanization. According to Svenska Kraftnät
(2012), underground cables are applied in urban areas where DC is preferred due to fewer
losses. Also Khandelwal & Pachori (2013) acknowledge that underground cables are
preferred for situations where land is inhabited or has a high development potential, because
of less environmental impacts. For land with lower value, overhead lines are generally
preferred, because of less capital costs. (Khandelwal & Pachori, 2013) To simplify, the costbenefit model considers the entire investment to have AC properties.
To compare China and Sweden in a reasonable manner, 500 kV AC has been used in the
model for China since it is a more common current level than 400 kV (Global Energy
Network Institute, 2007). The cost from a recent long distance transmission project in China
was used as a base for transmission cost estimation for the Chinese case. The project only
contains AC lines, which is considered reasonable because of the longer distances of power
transmission in China and the common use of AC lines. The fact that DC lines generally are
more expensive than AC lines can however contribute to the large difference in transmission
investment cost for Sweden and China.
Cost development is considered to take the extensive lifetime into account. Cost trends for
both DC and AC transmission lines have been rather continuous for decades. Historical data
for cost per powered distance of AC lines is displayed in Figure 28, where significant
deviations have been excluded. All costs has been calculated to year 2005 $. The cost trend
for AC lines is fairly consistent during the last hundred years. DC lines indicate a slight cost
52
5. COST-BENEFIT MODEL
increase since 1960’s (Performance Curve Database, 2008). Based on the historical trends the
cost for power transmission can be presumed to remain on the same level as today. The losses
in the transmission grid have been considered by using a value for the efficiency of the grid.
Figure 28: Cost trend AC, Source: (Performance Curve Database, 2008)
5.2.2 Investment Cost Grid Storage
Large capital costs is the major challenge for storage technologies, but the cost development
for Li-ion batteries is expected to decrease drastically in upcoming years, as earlier presented
in Figure 7 and Figure 21. The main reason for the expected cost reduction is because of the
fast development of Li-ion batteries used in electric vehicles, driven by the transportation
sector. As technology improves and becomes more available costs are cut down. To take the
expected cost reductions into account, the model is simulated for four different battery cost;
25, 50, 75 and 100 percent of the present battery cost.
Regarding the grid storage system as a whole, the cost for the batteries is not the only cost
that has to be considered in the model, see Figure 29. The model includes cost for the energy
storage unit which means cost related to the batteries. The costs for the power conversion
system and balance of plant are also included in the model. Power conversion system contains
costs such as power interconnections and cabling. Balance of plant costs includes cost such as
project engineering, grid interconnection, system integration, building and foundation,
monitoring and control systems as well as shipment and installation costs. The losses have
been considered by using a value for the efficiency in the model.
53
5. COST-BENEFIT MODEL
Figure 29: Main sections of EES systems and energy losses, Source (Zakeri & Syri, 2014)
5.2.3 Reinvestment Costs
Transmission usually has a longer life time than grid storage. However, if reinvestments (RI)
are made in the grid storage system such as replacing the batteries, the projected lifetime can
be extended. In the analysis the batteries are assumed to dispatch every day for the projected
lifetime, which affects the battery durability. According to the Electric Power Research
Institute (2013) the replacement frequency of the batteries can be presumed to be every ten
years. Other parts of the grid storage facility can have longer life time, extending over the
entire projected lifetime of the storage system. Therefore, an annual reinvestment cost,
containing the expenses for replacing batteries, is included to increase the lifetime of the
entire storage system.
Transmission has also some parts in the system that requires reinvestment to obtain the
intended life time for the whole system. These costs are also included in the model. However,
sources of accurate data were limited and an approximate value was calculated. In Sweden,
data from the Swedish TSO was available for their whole system (RITotalSwe). This value was
divided by the total length of transmission grid in Sweden and the power capacity during a
cold day in a normal winter. This resulted in a value with the unit [$/MW, km, year] which
could be used in the model. For China, see section 5.2.4.
𝑅𝐼 =
∗
RI cost transmission Sweden [$/MW, km, year]
5.2.4 Operation and Maintenance Costs
Operation and maintenance (O&M) cost is also included in the model. Regarding
transmission, sources of accurate data were limited and an approximate value was calculated
for both countries. In Sweden, data from the Swedish TSO was available for their whole
system (OMTotalSwe). This value was divided by the total length of transmission grid in
Sweden and the power capacity during a cold day in a normal winter. This resulted in a value
with the unit [$/MW, km, year] which could be used in the model.
54
5. COST-BENEFIT MODEL
𝑂𝑀 =
O&M cost transmission Sweden [$/MW, km, year]
∗
Data of O&M and RI costs in China were very limited. Estimations based on Sweden’s O&M
and RI cost had to be made. O&M and RI has been calculated as a percentage of installed
capacity in Sweden and then approximated to be the same for China.
𝑂𝑀𝑅𝐼 =
(
)
∗𝐿
O&M and RI cost transmission China [% of investment cost]
OM cost for grid storage included in the model is both fixed and variable annual costs. The
variable costs are increasing with increased use of the storage. There is always a minimum
cost that is represented by the fixed cost.
5.2.5 Planning and Construction Cost
The cost model includes additional costs for time of construction of energy storage and
transmission due to loss of income during planning and construction time. These estimations
are based on project length of real projects, from planning of the project to commissioning.
The purpose of including this, is to consider a cost associated with hours of curtailment. The
alternative that can be realized in shortest time can benefit from the avoided curtailment. The
market price for electricity has been multiplied with the yearly hours of wind curtailment
during the planning and construction time. For Sweden, the mean spot price has been applied
and for China, a feed-in tariff represents market price for electricity. For every year of
planning and construction, this cost appears.
5.2.6 Residual Value
Battery storage units have valuable metals that could be sold and reused in future batteries or
other products. This yields an income which is included in the model every time the batteries
have to be replaced during the total system life time. There are limited available data on
residual value of energy storage. Enerdel (2013), a manufacturer of Li-ion batteries, offers a
residual value of up to 25 percent. This applies to cost reduction of a replacing system and
brings a lower cost over the system lifetime. (Enerdel, 2013)
Transmission however, is assumed to have zero residual value. The cost for demolition is
assumed to be equal to the income from the valuable metals that could be obtained in the
transmission lines and then reused in other products.
5.3 Benefit Descriptions
There is a difficulty in performing a typical CBA of grid storage, since the benefits that can be
received involve several applications. To recognize the entire worth of grid storage, all the
benefits for different applications should be measured and included in the analysis (Insight_E,
2014). It is however challenging to determine an accurate value of all the benefits that grid
storage can provide. Thus, the benefits considered most relevant for grid storage in the model
are long duration benefits for renewable integration applications. There are other benefits,
55
5. COST-BENEFIT MODEL
being excluded in this model, which can be considered relevant in other applications of grid
storage.
There are several ways to employ energy storage systems with the purpose of regulating
intermittent power generation. By storing energy, wind curtailment can be reduced and
oversized construction of power capacity eliminated. In addition, wind power output can be
smothered by relieving variation suppression and support voltage control. (Zakeri & Syri,
2014) Evaluations of benefits associated with renewable integration applications of grid
storage has been performed in other research work and is not be the focus in this thesis.
Instead, the most relevant benefits already evaluated in a previous research work by Narula et
al. (2011) have been included in the cost-benefit model. It should be observed that some of
the benefits based on previous research are evaluated based on other market situations. In
most cases, the benefit value have been rounded down for the purpose of not exaggerating the
worth of the benefit. Furthermore, benefits included in the cost-benefit model are chosen
based on relevance when integrating grid storage. Other benefits that can be received both by
increasing transmission capacity and by implementing grid storage are excluded.
Consequently, no benefits for transmission are included, since these would also be included as
benefits for grid storage.
5.3.1 Renewable Energy Time Shifting
One advantage of grid storage integration in Sweden, is to benefit from electricity price
fluctuations on the spot market. Energy can be stored at excess supply, when the electricity
price is low, and discharged at excess demand, when the electricity price is high. The benefit
from renewable energy time shifting is applied in the model for Sweden only. In China this is
not applicable due to predetermined feed-in tariffs, as presented in section 3.2.2.
The benefit has been evaluated by calculating the difference between average daily maximum
spot price6 during the years 2013 and 2014 for SE3 and the average daily minimum spot
price7 during the years 2013 and 2014 for SE3 and then multiplied with days per year.
5.3.2 Renewable Load Following
Grid storage can provide load-following service that would otherwise be provided by power
generation. As discussed in section 4.1.2.4, thermal generation is today often used to stabilize
output fluctuation from intermittent energy sources. The benefit of load following is based on
market prices of generation costs, including costs for fuel, generation and emissions. These
costs can be reduced or avoided when grid storage is integrated. The demand of the added
6
7
(Nord Pool Spot, 2014)
Ibid.
56
5. COST-BENEFIT MODEL
generation capacity is highly market specific, depending on area and time. According to
Narula et al. (2011) the wind generation output variability involves changes that occur over
minutes to hours. The annual benefit from grid storage integration is estimated to
$54 600/MW (Narula, et al., 2011). This value have has been used as an approximate value
for both markets in the model. It should be noted that this value estimation differs from the
market situation in Sweden and China. Because of lack of information from these specific
markets, the values are assumed to be roughly the same.
5.3.3 Electric Service Reliability
Grid storage can provide backup for unexpected wind generation shortfalls that can cause
electric service outages. The value for avoiding electric service outages has been included as a
benefit for grid storage in the model. Narula et al. (2011) have evaluated the value to
$10/kWh. To validate this value, the loss of GDP in Sweden and China is calculated during 1
hour of power outage per year, see Table 3.
𝑆𝑅 =
∗
Table 3: Electric Service Reliability Validation
Sweden
GDP [$]
Approx. Working hours per year [h]
Average load [MW]
Benefit [$/kWh]
447 264 000 0008
2 500
18 37910
10
China
8 230 000 000 0009
2 500
544 29211
6
The validation shows that the value for electric service reliability is equivalent for Sweden but
a bit lower for China. The benefit value for China is therefore adjusted in the model.
5.4 Capacity Limitations
Transmission power capacity is assumed to be installed in fixed large steps in the model. One
transmission line has a fixed value and the amount of transmission lines, in positive integers,
is calculated to obtain the optimal solution. This is to model the complexity in expansion of
new transmission lines because of the long planning and construction time. As presented in
section 4.2, transmission capacity should be customized to fit the final amount of wind energy
8
(Ekonomifakta, 2014)
(Trading Economics, 2013)
10
(U.S. Energy Information Agency, 2012b)
11
(U.S. Energy Information Agency, 2012c)
9
57
5. COST-BENEFIT MODEL
instead of making large investments in several stages. Therefore, a reasonable value of each
step of transmission capacity has been included in the model.
As validation for the value used in the model, the Swedish national grid has been studied.
Between SE1 and SE2, there is a transmission capacity of 4210 MW (Svenska Kraftnät,
2014c) divided on four 400 kV lines (Svenska Kraftnät, 2014a). This corresponds to a
capacity of approximately 1050 MW per line. However, these sections are about 300 km
which is shorter than the distance modelled. As can be seen in Figure 30 below, the
transmission capacity in an AC line decreases with length. Therefore, a lower capacity than
1050 MW, stated above, has been used in the model. A value of 700 MW has been estimated
for a line with the given distance for the case of Sweden.
Figure 30: St. Clair Curve, Source: (Hao & Xu, 2008)
For China, the input data is based on a project with 500 kV AC line which makes it possible
to transfer more power than in a 400 kV AC line. Thereby, the value has been estimated to
1000 MW for the case of China.
Grid storage however, is a more flexible system with shorter development times. “Grid storage” is referred to several storage units included in the total system and not a single unit.
Therefore, the power restrictions are assumed from low power demands (100 MW) and then
with the possibility to be scaled to higher power demands, no upper limit. Power efficiencies
for both technologies have been considered.
5.5 Distance Limitations
The length of transmission line is set to a constant value and is based on reasonable
assumptions and estimations of the distance between expected wind farms and demand
sources. Electricity is assumed to be transmitted over large distances, for example from
northern Sweden (SE2) to southern parts of the country (SE3) as presented in section 3.1.3.
This gives approximately a distance of 500 km which is used in the model. This length also
coincide with the project that the investment cost is based on, which is a project between
Sweden’s southern and central parts with a long distance of about 440 km (Svenska Kraftnät,
58
5. COST-BENEFIT MODEL
2013c). For China, the large geographical distance is a major challenge for power
transmission, as discussed in section 3.2.3. Because of the large distances and the
geographical disparity of wind power generation and power demand, the distance is doubled
compared to Sweden. The approximated distance used in the model is set to 1000 km.
5.6 Input Data Sweden
In Table 4, general input data for the model of Sweden is presented, followed by input data
for grid storage and transmission in Table 5 and Table 6, respectively.
Table 4: General Input Data Model, Sweden
Name
General Input Data Sweden
Short
Length of transmission
Average spot price Sweden SE3 benefits storage
Hours per year
Interest rate including inflation rate
Factor to convert SEK to U.S. Dollar
Factor to convert Euro to U.S. Dollar
Factor to convert CNY to U.S. Dollar
L
EP
t
ir
sd
ed
yd
12
See section 5.5.
(Nord Pool Spot, 2014)
14
(Zakeri & Syri, 2014) (Energimarknadsinspektionen, 2011)
15
(Microsoft, 2015)
16
Ibid.
17
Ibid.
13
59
Value
Unit
500
40.1
8760
5.5
12
106
16
km
$/MWh
h
%
%
%
%
Source
12
13
14
15
16
17
5. COST-BENEFIT MODEL
Table 5: Input Data Grid Storage Model, Sweden
Name
Input Data Grid Storage Sweden
Short
Value
Li-ion battery cost (100 %)
Power conversion systems cost
Balance of plant cost
Benefits from spot market
Benefits from load following
Benefits from electric service reliability
Fixed operation and maintenance cost
Life time
Variable operation and maintenance cost
Planning and construction time
Charge/discharge time
Efficiency
Residual value in percentage of initial battery cost
18
(Zakeri & Syri, 2014, p. 591)
Ibid.
20
Ibid.
21
See section 5.3.1.
22
(Narula, et al., 2011, pp. 8-7)
23
See section 5.3.3.
24
(Zakeri & Syri, 2014, p. 591)
25
See section 5.2.3.
26
(Zakeri & Syri, 2014, p. 591)
27
(Global Energy Storage Database, 2015a)
28
(Zakeri & Syri, 2014, p. 591)
29
(Zakeri & Syri, 2014, p. 580)
30
(Enerdel, 2013)
19
60
BC_GS
PCS_GS
BOP_GS
sp_GS
LF_GS
SR_GS
OMf_GS
y_GS
OMv_GS
t_PC_GS
t_dis
N_GS
RV_GS
795000
405980
84800
5475
54600
10000
7314
40
2.23
1
2
0.90
0.25
Unit
Source
$/MWh
$/MW
$/MW
$/MWh,year
$/MW,year
$/MW,year
$/MW,year
Years
$/MWh,year
Years
h
18
19
20
21
22
23
24
25
26
27
28
29
30
5. COST-BENEFIT MODEL
Table 6: Input Data Transmission Model, Sweden
Name
Input Data Transmission Sweden
Short
Value
Investment cost
Annual reinvestment cost per year in Sweden
Annual operation and maintenance cost
Power capacity Sweden, normal winter
Total length of transmission in Sweden
Power capacity for each line
Life time
Planning and construction time
Efficiency
IC_T
RI_T
OM_T
P_Swe
L_Swe
P_Ta
y_T
t_PC_T
N_T
31
(Svenska Kraftnät, 2013c)
(Svenska Kraftnät, 2015a)
33
(Svenska Kraftnät, 2014e, p. 62)
34
(Svenska Kraftnät, 2014d, p. 9)
35
(Svenska Kraftnät, 2014f)
36
See section 5.4.
37
(Energimarknadsinspektionen, 2010)
38
(Svenska Kraftnät, 2013c)
39
(Svenska Kraftnät, 2014e, p. 34)
32
61
850820
0.204
0.134
26200
15000
700
40
10
0.97
Unit
$/MW
$/MW,km,year
$/MW,km,year
MW
km
MW
Years
Years
Source
31
32
33
34
35
36
37
38
39
5. COST-BENEFIT MODEL
5.7 Input Data China
In Table 7, general input data for the model for China is presented, followed by input data for
grid storage and transmission in Table 8 and Table 9, respectively.
Table 7: General Input Data Model, China
Name
General Input Data China
Short
Value
Length of transmission
Wind Power feed-in tariff zone II
Hours per year
Interest rate including inflation rate
Factor to convert SEK to U.S. Dollar
Factor to convert Euro to U.S. Dollar
Factor to convert CNY to U.S. Dollar
L
EP
t
ir
sd
ed
yd
40
See section 5.5.
See section 3.2.2
42
(Zakeri & Syri, 2014) (Energimarknadsinspektionen, 2011)
43
(Microsoft, 2015)
44
Ibid.
45
Ibid.
41
62
1000
86.4
8760
5.5
12
106
16
Unit
Source
km
$/MWh
h
%
%
%
%
40
41
42
43
44
45
5. COST-BENEFIT MODEL
Table 8: Input Data Grid Storage Model, China
Name
Input Data Grid Storage China
Short
Value
Li-ion battery cost (100 %)
Power conversion systems cost
Balance of plant cost
Benefits from spot market
Benefits from load following
Benefits from electric service reliability
Fixed operation and maintenance cost
Life time
Variable operation and maintenance cost
Planning and construction time
Charge/discharge time
Efficiency
Residual value in percentage of initial battery cost
BC_GS
PCS_GS
BOP_GS
sp_GS
LF_GS
SR_GS
OMf_GS
y_GS
OMv_GS
t_PC_GS
t_dis
N_GS
RV_GS
46
(Zakeri & Syri, 2014, p. 591)
Ibid.
48
Ibid.
49
See section 5.3.1.
50
(Narula, et al., 2011, pp. 8-7)
51
See section 5.3.3.
52
(Zakeri & Syri, 2014, p. 591)
53
See section 5.2.3.
54
(Zakeri & Syri, 2014, p. 591)
55
(Global Energy Storage Database, 2015a)
56
(Zakeri & Syri, 2014, p. 591)
57
(Zakeri & Syri, 2014, p. 580)
58
(Enerdel, 2013)
47
63
795000
405980
84800
0
54600
6000
7314
40
2.23
1
2
0.90
0.25
Unit
Source
$/MWh
$/MW
$/MW
$/MWh,year
$/MW,year
$/MW,year
$/MW,year
Years
$/MWh,year
Years
h
46
47
48
49
50
51
52
53
54
55
56
57
58
5. COST-BENEFIT MODEL
Table 9: Input Data Transmission Model, China
Input Data Transmission China
Short
Value
Name
Investment cost
Annual RI and O&M cost
Power capacity for each line
Life time
Planning and construction time
Efficiency
IC_T
OMRI_T
P_Ta
y_T
t_PC_T
N_T
797
0.02
1000
40
7
0.97
Unit
Source
$/MW
%/year
MW
Years
Years
59
60
61
62
63
64
5.8 Objective Function
The cost model has the objective to minimize the cost for investing either transmission or grid
storage or a share of both technologies to avoid a certain amount of wind curtailment.
Therefore, the cost model minimizes the cost for each unit of wind curtailment.
Annualized Cost-Benefit Analysis [$/ year]
𝐴𝐶𝐵𝐴 = 𝑥 ∗
𝑥 ∗𝑃
∗ (𝐼𝐶
+ 𝑃𝐶𝐶 ) + 𝐴𝑉𝐶
+
∗ (𝐼𝐶 + 𝑃𝐶𝐶 − 𝑅 ∗ 𝑘𝑛 ) ∗ 𝑘𝑎 + 𝐴𝑉𝐶 + 𝐴𝐹𝐶 − 𝐴𝐵
5.9 Constraints
The constraints for the model are shown below.
𝑥 ∗
∗ 365 + 𝐴𝐹𝐶
+𝑥 ∗𝑃
∗𝑁 ≥ 𝑃
𝑥 ≥0
𝑥 ≥0
59
(Transmission & Distribution World, 2011)
See section 5.2.4.
61
See section 5.4.
62
(Energimarknadsinspektionen, 2010)
63
(Global Transmission Report, 2009)
64
(Svenska Kraftnät, 2014e, p. 34)
60
64
− 𝐴𝐵
−𝑅
+
5. COST-BENEFIT MODEL
5.10 Variables
𝑥
Energy stored in the grid storage [MWh]
𝑥
Amount of transmission lines [pcs]
5.11 Equations
𝑘𝑎
=
𝑘𝑎 =
𝑘𝑛
(
Annuity factor Grid Storage
)
(
Annuity factor Transmission
)
=(
)
𝑘𝑛 = (
Net present factor Grid Storage
Net present factor Transmission
)
𝑊𝐶 = 𝑃
∗𝑡
𝐼𝐶
∗𝑡
= 𝐵𝐶
Wind Curtailment per year [MWh/year]
+ 𝐵𝑂𝑃
+⋯
𝑃𝐶𝑆
Investment Cost Grid Storage [$/MW]
𝑅𝐼
= 𝐵𝐶
(
+
)
∗(
(
(
) ∗ 𝑘𝑎
)
𝐴𝐹𝐶
=
𝐴𝑉𝐶
= 𝑂𝑀𝑣
+⋯
)
+ 𝑅𝐼
Reinvestment Cost Grid Storage [$/MW]
∗ 𝑘𝑎
Annual Fixed Costs Grid Storage [$/MWh, year]
Annual Variable Costs Grid Storage [$/MWh, year]
𝐴𝐹𝐶 = (𝑂𝑀 + 𝑅𝐼 ) ∗ 𝐿
Annual Fixed Costs Transmission [$/MW, year]
𝐴𝑉𝐶 = 0
Annual Variable Costs Transmission [$/MW, year]
𝑃𝐶𝐶
= 𝐸𝑃 ∗ 𝑡
∗𝑡
𝑃𝐶𝐶 = 𝐸𝑃 ∗ 𝑡
𝑅
= 𝐵𝐶
∗ 𝑘𝑎
∗
∗𝑡
(
)
∗ 𝑅𝑉
=
𝐴𝐵 = 0
Planning & Construction Cost Transmission [$/MW]
+ 𝑅𝐼
…
Residual Value Grid Storage [$/MW]
𝑅 = 0
𝐴𝐵
Planning & Construction Cost Grid Storage [$/MW]
Residual Value Transmission [$/MW]
+ 𝑠𝑝
Annual Benefits Grid Storage [$/MWh, year]
Annual Benefits Transmission [$/MWh, year]
65
5. COST-BENEFIT MODEL
5.12 Results
This section shows the results from the cost-benefit model. The model has been adapted to the
two countries studied, Sweden and China, with country specific input data as presented in
section 5.6 and 5.7, respectively. Eight different cases have been studied for each country.
The cases were chosen based on the parameters importance and level of impact of the result.
The expected decrease of Li-ion battery cost, as presented earlier in 5.2, was considered as
relevant for further investigation in the model. Moreover, the upcoming challenges associated
with potential increase of wind curtailment, as presented in section 4.1.2.3, was also
considered as highly relevant in order to study the impact depending on choice of technology.
The model examines capacities installed from 100 MW to 3000 MW with steps of 100 MW.
Battery cost - 100 %, 75 %, 50 % and 25 % of current battery cost.
Wind curtailment - 100 hours and 1000 hours per year, respectively.
5.12.1 Sweden
In the following sections, the results from each different case with the country specific input
data for Sweden are presented. The x-axis shows the capacity demand, which means the total
capacity of variation moderators that needs to be installed. On the y-axis the actual installed
capacity of each technology is seen. This capacity is as minimum equal to the capacity
demand but it is possible with an overcapacity.
5.12.1.1
Case 1
5.12.1.2
Figure 31: Case 1 Sweden
Case 2
Figure 32: Case 2 Sweden
In Case 1 and 2, the battery cost represents an estimation of current market price at 100 and
1000 hours of curtailment per year, respectively. The results from Case 1 (Figure 31) shows
that transmission is generally the most beneficial alternative. Grid storage is suitable for small
capacities and as peak capacity, to avoid investments in overcapacity in some extent. This
result can be compared to Case 2 (Figure 32) where the increase in hours of wind curtailment
makes transmission more costly, which yields a result with larger share of storage in Case 2
compared to Case 1. However, it can be seen that it can be more optimal to invest in
overcapacity than in grid storage at some capacities. For example, for a capacity demand of
500 MW the result shows that it is more cost-effective to install 700 MW of transmission
capacity than to install 500 MW of storage capacity.
66
5. COST-BENEFIT MODEL
5.12.1.4
5.12.1.3
Case 4
Case 3
Figure 34: Case 4 Sweden
Figure 33: Case 3 Sweden
The results of Case 3 (Figure 33) shows that the battery cost reduction of 25 percent has
increased grid storage’s influence compared to Case 1. The amount of overcapacity in transmission becomes less in return for increased capacity of storage. Furthermore, in Case 4
(Figure 34) the increase in hours of wind curtailment makes transmission more costly, and
together with the cost reduction of batteries, it yields a result with larger share of storage in
Case 4 compared to Case 3. Investing in overcapacity gets less beneficial, but still occurs.
5.12.1.5
Case 5
5.12.1.6
Figure 35: Case 5 Sweden
Case 6
Figure 36: Case 6 Sweden
The result of Case 5 (
Figure 35) shows that a battery cost reduction of 50 percent of current battery cost has
increased grid storage’s influence even more, compared to Case 1 and 3. The amount of
overcapacity in transmission becomes less in return for increased capacity of storage, but still
occurs. Furthermore, in Case 6 (Figure 36) it can be seen that grid storage is more costeffective than transmission for all capacities included in the model, from 100 to 3000 MW.
The increase in hours of wind curtailment makes transmission more costly, and together with
the cost reduction of batteries, it yields a result where the break-even point can be found
somewhere between 25-50 percent battery cost decrease. This means that grid storage has
become more beneficial to invest in than transmission.
67
5. COST-BENEFIT MODEL
5.12.1.8
5.12.1.7
Case 8
Case 7
Figure 38: Case 8 Sweden
Figure 37: Case 7 Sweden
The results of Case 7 (Figure 37) shows that a battery cost decrease of 75 percent has led to
that grid storage is more cost-effective than transmission for all capacities included in the
model, from 100 to 3000 MW. Consequently, this means that somewhere between 50-75
percent battery cost decrease, the break-even point can be found for Case 7. The result of
Case 8 (Figure 38) shows the same result as Case 6 since the break-even point has already
been reached.
5.12.2 China
In following sections, the results from each different case with the country specific input data
for China are presented. The x-axis shows the capacity demand, which means the total
capacity of variation moderators that needs to be installed. On the y-axis the actual installed
capacity of each technology is seen. This capacity is as minimum equal to the capacity
demand but it is possible with an overcapacity.
5.12.2.1
Case 1
5.12.2.2
Figure 39: Case 1 China
Case 2
Figure 40: Case 2 China
In Case 1 and 2 the battery cost represent an estimation of current market price at 100 and
1000 hours of curtailment per year, respectively. The results from Case 1 (Figure 39) shows
that transmission is generally the most beneficial alternative. Grid storage is suitable for small
capacities and as peak capacity, to avoid investments in overcapacity in some extent. This
result can be compared to Case 2 (Figure 40), where increased hours of curtailment increase
the influence of storage. Furthermore, it can be concluded that it can be more optimal to
invest in overcapacity than in grid storage at some capacities. For example, for a capacity
demand of 400 MW the result shows that it is more cost-effective to install 700 MW of
transmission capacity than to install 400 MW of storage capacity. It can also be stated that the
time of wind curtailment have some effect on the results for these two cases.
68
5. COST-BENEFIT MODEL
5.12.2.4
5.12.2.3
Case 4
Case 3
Figure 42: Case 4 China
Figure 41: Case 3 China
The results of Case 3 (Figure 41) shows that the battery cost reduction of 25 percent has a
minor effect of storage’ penetration level compared to Case 1. This means that the battery cost
reduction of 25 percent makes it cost-effective to avoid some investments in transmission
overcapacity. Furthermore, in Case 4 (Figure 42) the increase in hours of wind curtailment
makes transmission more costly, and together with the cost reduction of batteries, it yields a
result with larger share of storage in Case 4, than in Case 3. Investing in overcapacity gets
less beneficial, even though it still occur.
5.12.2.5
Case 5
5.12.2.6
Figure 43: Case 5 China
Case 6
Figure 44: Case 6 China
The result of Case 5 (Figure 43) shows that a battery cost reduction of 50 percent of current
battery cost has increased grid storage’s influence even more, compared to Case 1 and 3. The amount of overcapacity in transmission becomes less in return for increased capacity of
storage, but still occurs. Furthermore, in Case 6 (Figure 44) the increase in hours of wind
curtailment makes transmission more costly, and together with the cost reduction of batteries,
it yields a result with larger share of storage in Case 6, than in Case 5. Investing in
overcapacity is no longer beneficial.
69
5. COST-BENEFIT MODEL
5.12.2.8
5.12.2.7
Case 8
Case 7
Figure 46: Case 8 China
Figure 45: Case 7 China
The results of Case 7 (Figure 45) and Case 8 (Figure 46) shows that a battery cost decrease of
75 percent has led to that grid storage is more cost-effective than transmission for all
capacities included in the model, from 100 to 3000 MW. Consequently, this means that
somewhere between 50-75 percent battery cost decrease grid storage gets more beneficial
than transmission, the break-even point has been reached.
70
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71
6. DISCUSSION
DISCUSSION
In this chapter the research findings together with the results from the cost-benefit model are
discussed. First, grid storage’s market potential for integration into the energy infrastructure
in Sweden and China is discussed. Furthermore, the outcome of the results from the costbenefit model is discussed together with potential sources of errors.
6.1 Market Conditions
The need for balancing measures in the energy infrastructure is increasing on both emerging
and developed markets. Both transmission expansion and grid energy storage integration are
becoming increasingly relevant to study as variation moderators. Stakeholders on the power
market can draw benefit from studies, such as this, when making future investment-decisions.
Moreover, policy-makers should also consider research of variation moderators in the energy
infrastructure to promote a sustainable energy infrastructure. At the same time as the
transmission grid needs to be expanded, energy storage systems are becoming increasingly
interesting in several areas of application. Development of Smart grids, electric vehicles and
home batteries drives the battery development forward and increases potential to cost
reductions. As technology is developed in one area of application, advantages can be gained
in other areas such as grid storage. Technology progress and research findings continue to
change the market conditions for variation moderators.
6.1.1 Sweden
The need for variation moderators highly depends on the future electricity market structure.
Future scenarios, addressed in section 3.1.4, indicate substantially higher demand of variation
moderators in the Nordic energy infrastructure. Despite these indications, the Swedish TSO
does not intend to increase responsibility of balancing the power system in a near future. It is
therefore doubtful that the grid operator considers investing in grid storages. However, a
regulating framework for storage systems could be an eye-opener for ownership potential.
Present ownership and operational uncertainties need to be clarified in EU regulations. The
future development of the market structure will be influenced by European directives, which
today hinder potential investments in the EU market for grid battery storages. Directives
about grid storages ownership can influence the market structure and increase the market
potential for storage devices in Sweden and in the rest of Europe. However, an integrated
intraday market in Northern Europe can influence the entire energy market and reduce the
need for balancing reserves. The demand of variation moderators is thereby dependent on
political decisions about the energy market structure, both in Sweden and neighbouring
countries.
72
6. DISCUSSION
Although problems related to intermittent power generation are not extensive in Sweden
today, a long-term perspective is necessary to be prepared for upcoming challenges. Potential
challenges in future scenarios presented in section 3.1.4 should be considered when planning
the future power system. Wind power integration can otherwise be hindered due to long
planning and construction time of the transmission grid. As wind power generation increases
in Sweden and other developed economies, grid storage integration can become a fast solution
to future challenges on the power market due to the short construction time.
High investment costs and low experience level are major barriers for market penetration of
grid storage in Sweden. It is therefore likely that Sweden will wait for a cost reduction of grid
battery storage before investing in the technology. Other countries already have several more
on-going battery storage projects than Sweden (Global Energy Storage Database, 2015b).
Thereby, these countries have better opportunities to take the lead in the grid storage
development. As the market matures and cost reduces, market actors in Sweden might realise
the benefits of grid battery storage.
6.1.2 China
Due to large problems related to congestion, investments in transmission development can be
prioritized in China. The developing country already faces challenges due to transmission
limitations. Although grid storage integration can relive these concerns, it cannot completely
replace the need to invest in transmission expansion in order to reach the load centres.
Moreover, the experience level of building new transmission lines is high compared to the
uncertainties of investing in a new technology.
However, there are also aspects that indicate integration of grid storage. China has shown
efforts to become a leader in the development of technologies related to low-carbon energy,
which can suggest that China will be in the forefront of grid storage development. According
to The Electrical Energy Storage Magazine (2014) the energy storage industry in China has
grown rapidly, with 90 battery storage projects in operation, under construction or planned the
last two years.
Grid storage can reduce issues related to wind curtailment in a shorter time perspective than
transmission. Because of the short construction time, grid storage can be a fast solution to
China’s current wind curtailment problems. Today, wind curtailment causes financial losses
and brings major challenges to the grid. These challenges need to be solved fast as the amount
of installed intermittent energy sources keep increasing due to ambitious energy targets.
According to The Electrical Energy Storage Magazine (2014) several wind farms in China’s north-eastern areas have already been equipped with energy storages to reduce wind
curtailment caused by high wind penetration, high wind variability and limited transmission
capacity. Grid storages located close to the source of generation can reduce the need for
network expansion and also enable ownerships by power producers. As grid battery storages
becomes more available on the market, storage devices connected to wind farms can be
expected to increase.
73
6. DISCUSSION
6.1.3 Market Contrasts
China’s business climate with high constitutional control can be more advantageous for grid
battery storage. Short decision paths can speed up the decision making process and realize
grid storage projects in a shorter time frame compared to developed countries as Sweden,
where the decision processes are extensive. In addition, industries in developing countries can
challenge unpredictable market fluctuations than in slow-growing industries as discussed in
section 3.2.4. Furthermore, China has more than 100 Li-ion battery manufacturers, where
some are focusing on grid scale energy storages (The Electrical Energy Storage Magazine,
2014). This also indicates that China can take a forefront role of grid storage technology
development. With several manufacturers available, national battery prices can decrease and
grid storage systems can be integrated to the grid infrastructure.
6.2 Driving Forces
A number of market forces drive the development of variation moderators. For both
transmission and grid storage development, energy targets and congestion are two major
driving forces. Energy targets set by several nations drives the increase of intermittent
renewable energy sources, which create a need for variation moderators. Furthermore,
problems related to congestion can be relieved by both transmission expansion and grid
storage integration.
6.2.1 Grid Storage
Grid storage has many benefits as a variation moderator but also some downsides, as earlier
presented in chapter 4. The most important drivers acknowledged is presented in Figure 47
where their relation to each other has been tried to be clarified in a pedagogical way. Based on
market entry barriers and market forces recognized in chapter 4, the four most important
driving forces are Technology Development, Congestion, Recognition by Policymakers and
Energy Targets. From these driving forces, sub factors have been identified to clarify what
drives the development of grid storage.
74
6. DISCUSSION
Technology
Development
Congestion
Recognition by
Policymakers
Energy
Targets
Smart Grids
Reliability &
Security
Regulated
Framework
Renewable
Energy
Generation
Electric
Veichles
Wind
Curtailment
Economic
Incitements
Pollution
Home
batteries
Transmission
Deferral
Ownership
Regulations
Greenhouse
Gas Emissions
Renewable
Time Shifting
Robust
Business
Models
Figure 47: Acknowledged Driving Forces - Grid Storage
6.2.2 Transmission
Transmission has many benefits as a variation moderator and is also currently the most
common technology used for that purpose worldwide. The most important drivers
acknowledged for its continuous expansion in Sweden and China is presented in Figure 48
and Figure 49, respectively. Their relation to each other has been tried to be clarified in a
pedagogical way. Based on the market forces recognized in chapter 4, the three most
important driving forces in Sweden are Congestion, Politics and Energy Targets. In China,
Congestion, the Growing Economy and Energy Targets has been recognized as the three most
important driving forces. From these driving forces, sub factors have been identified to clarify
what drives the development of transmission in Sweden and China, respectively.
75
6. DISCUSSION
Congestion
Politics
Energy Targets
Price
Differences
United
European
Electricity
Market
Renewable
Energy
Generation
Reliability &
Security
Aged
Transmission
Grid
Greenhouse
Gas Emissions
Wind
Curtailment
Intermittent
Renewable
Generation
Spot Price
Fluctuations
Figure 48: Acknowledged Driving Forces – Transmission in Sweden
Congestion
Growing
Economy
Energy Targets
Wind
Curtailment
Long distances
Renewable
Energy
Generation
Reliability &
Security
Large Capacities
Pollutions
Intermittent
Renewable
Generation
Water
constraints
Figure 49: Acknowledged Driving Forces – Transmission in China
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6. DISCUSSION
6.3 Cost-Benefit Model
The results from the cost-benefit model have been presented in section 5.12 for both Sweden
and China. The factors affecting the outcome of the results is analysed and discussed further
in the sections below.
6.3.1 The Impact of Li-ion Battery Cost Development
From the result of the cost-benefit model, it can be seen that the cost reduction of batteries are
essential for its penetration on the power market. Grid storage influence increases with battery
cost reductions for both Sweden and China. Grid storage flexibility is valuable for small
capacities and as peak capacity. In that way, the results confirm that grid storage can
contribute to transmission deferral, meaning that it is possible to avoid costly upgrades and
investments of overcapacity of transmission as earlier discussed in section 4.1.2.2. By
integrating grid storage, costly investments in the transmission grid can be postponed.
In Case 6 to Case 8 for Sweden and Case 7 and Case 8 for China, the break-even point
between transmission and storage is passed. Storage is thereby a more advantageous
investment than transmission for all capacities. Forecasts by other researchers (Figure 7 and
Figure 21) have predicted this decrease to occur around year 2020 for Case 6 and around year
2030 for Case 7 and Case 8. As presented earlier in section 4.1.2.1 Tesla Motors has already
announced home battery prices close to the battery cost modelled in Case 5 and 6. The
announcement confirms the fast development and cost decrease of battery storages and shows
that storage has a high potential to be a beneficial alternative in the future energy
infrastructure. Even though it would not be possible to build grid storages exclusively,
transmission capacity can be decreased and the transmission grid can be used in a more
effective way by integrating storage technologies.
6.3.2 The Impact of Residual Value
Battery storage units have valuable metals that could be sold and reused in future batteries or
other products. This yields an income that is included in the model every time the batteries
have to be replaced during the total system life time. This value has large impact on the
results, since the battery investment cost is reduced. Without the residual value of the battery
investment, the influence of grid storage decreases in all cases for both Sweden and China.
The break-even point is then reached at a battery cost reduction of between 50-75 percent for
both Sweden and China.
Transmission is on the other hand assumed to have zero residual value. The cost for
demolition is assumed to be equal to the income from the valuable metals that could be
obtained from the transmission lines. If a residual value would be considered in the model,
transmission investments would be more beneficial.
6.3.3 The Impact of Wind Curtailment
From the cost-benefit model, it is clear that the amount of wind curtailment influences the
outcome of the results. For most capacities, the influence from grid storages increases as
77
6. DISCUSSION
hours of wind curtailment increase. The reason for this is the short construction time, from the
planning stage to operation, of grid storage in comparison to transmission. For every year of
construction for both storage and transmission, the loss of income due to wind curtailment is
added as a cost in the model. The shorter construction time of grid storage is one of the
benefits of integrating storage instead of expanding the transmission grid. Unnecessary spill
of available energy due to lack of transmission capacities can be avoided if investments in
grid storages are realised within a short timeframe. Previous research, included in section
4.1.2.3, has found that grid storage investments are not cost-effective enough to reduce wind
curtailment today. However, considering the risk of increased wind curtailment and the fact
that several economic benefits can be received from grid storage integration, investments can
become more cost efficient from a system perspective. The cost-benefit model is constructed
from a system perspective, where the results show the most beneficial alternative to invest in,
in order to reduce curtailment.
6.3.4 The Impact of Benefits
The benefits included in the model highly influence the outcome of the results. Benefits for
grid storage have been chosen from a system perspective. There are numbers of varied
benefits presented in previous research for different types of storage applications. Benefits
also differ depending on what market actor owns and operates the storage. Only a few
benefits are included in the model and have been evaluated to give the most realistic analysis
as possible. These are chosen from a system point of view and with the purpose of regulating
renewable intermittent energy supply.
In China’s controlled market it is not possible to benefit from renewable energy time shifting,
since a predetermined feed-in tariff is used for electricity from wind power plants. Thereby,
the benefit from renewable energy time shifting is only included for Sweden, where the price
is set on a competitive spot market. By this means, the profitability of grid storage is less in
China’s controlled market compared to Sweden’s competitive market. Furthermore, the cost
model is based on the current market structure and spot prices. Furthermore, the value of the
benefit can increase if the electricity price increases in Sweden. Also a larger share of
intermittent power generation can lead to more fluctuations on the spot market that can
increase the value of the benefit. If Sweden’s spot market changes and develop towards a power market, such as Elbas, the value of grid storage systems can be changed. The value of
the benefit highly depends on market structure.
The benefits from renewable load following is considered as the most valuable benefit in the
model with the largest impact on the results. The benefit is received by comparing storage to
other, more expensive, solutions to adjust the frequency such as thermal power generation.
However, the value of renewable load following is also highly market specific, depending of
area, time and other alternative solutions to load following.
Electric service reliability has also been included since storage can provide backup for
unexpected wind generation shortfalls that otherwise could cause electric service outages. A
reliable and secure electricity supply is important in the energy infrastructure and involves a
social value. Major power losses can lead to financial losses in the whole society, for instance
production losses in industries. The value of this benefit is smaller than for load following,
but do still have impact on the results.
78
6. DISCUSSION
6.3.5 Source of Errors
The outcome of the result depends on the accuracy of the cost data for grid storage and
transmission. There is however limited public information about specific project data, which
has led to that some data was estimated in the model. The cost-benefit model is based on data
and estimations of existing transmission projects in Sweden and China, providing recent
information about country specific conditions. Since these data are project specific, other
projects might have other specifications involving higher or lower costs. The results from the
model is also country specific, but the model can be applied for any country specific case,
where length, cost and capacity of the transmission line can be compared to the option of
integrating grid storage. Regarding grid storage cost data, no country specific data has been
used due to lack of available public information. The benefits included in the model are
country specific to some extent. Benefits from renewable load following has not been found
for the country specific conditions and is thereby based on previous literature, as presented in
section 5.3.2. Benefits from electric service reliability is also based on previous literature and
validated as presented in section 5.3.3. Previous literature includes several models and
theories developed and confirmed in the U.S. and Western Europe. It is unclear whether these
instruments can be applicable in other countries. However, since no sufficient data has been
available for the specific countries, the information has been applied for both market
conditions.
Accuracy of additional input data and the model design also influence the outcome of the
results. The model is created to suit properties for AC transmission lines, with stepwise
intervals for the installed capacity, which highly effects the structure of the model. The
additional input data also influence the result and involves interest rate, financial life time and
charging and discharging time of the storage unit. The value for the interest rate used in the
model is based on recommendations for energy infrastructure projects in Sweden and for grid
storage investments presented in other literature. This value has been applied as a general
input data, not country specific, which could be a source of error for the China cases. The
financial life time is also based on previous literature for both technologies and not country
specific. It is possible that this figure depend on country specific conditions, such as required
rate of return from investors. The charging and discharging time is a parameter that highly
influences the specification of the grid storage, since it determines the size of the storage unit
and thereby the size of benefits and investment cost. This parameter has a large impact of the
results in the model, since both the benefits and the investment cost is influenced.
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80
7. CONCLUSIONS
CONCLUSIONS
The purpose of this study was to investigate market forces for transmission and grid storage
development as variation moderators for intermittent power generation. Since battery grid
storage is an emerging technology, market entry barriers for integrating storage into the grid
was also identified. The most important market forces identified are presented and discussed
in chapter 6. The aim was also to investigate the most beneficial combination of grid storage
integration and transmission expansion in the future power system, in a system perspective.
Based on the case study research design, a cost-benefit model was created for two diverse
market conditions. The modelled results are presented in section 5.12, where the most
beneficial combination of grid storage integration and transmission expansion is investigated.
Due to the inductive approach and the fairly unexplored area, validity measurements are not
considered as a major concern. Although limited access to adequate and specific market data
influence the accuracy of the final results, the focus has been set on creating a research base in
the field of study. Few technical-economic studies have previously been performed where
market conditions for grid storage is compared to transmission expansion. The thesis is
thereby a forerunner in the research area and can be considered as a starting point for other
research work within the field of study to build upon. Based on the market analysis in chapter
4, identified driving forces in chapter 6, along with the cost-benefit analysis found in section
6.3, several interesting conclusions can be drawn from this thesis. These conclusions are
presented in Figure 50 below.
81
7. CONCLUSIONS
Battery cost reduction is crucial for grid storage market penetration
•The cost development of Li-ion batteries will highly influence the cost efficiency of grid storage and
decrease market entry barriers. In the long term, costs are expected to be reduced and investments in
grid storage will be more beneficial. The point where battery storage investments becomes more
beneficial than transmission investments for shaving is predicted to occur within a time frame of 10-15
years.
Grid storage can provide faster solutions for problems related to congestion
•Due to the faster construction time of grid storage, challenges related to congestion can be reduced in a
shorter time perspective compared to long project time of transmission grid development.
•Wind curtailment drives further reinforcements in the energy infrastructure. Grid storage can become a
fast solution to future challenges on the power market, particularly in China where the rate of wind
curtailment is high.
Grid storage is most suitable for peak shaving and transmission deferral applications
•Grid storage can bring flexibility to the transmission grid and is most suitable for small capacities. By
integrating grid storage it is possible to postpone costly investments of transmission upgrades, which
would lead to overcapacity.
Low grid storage market experience can be beneficial for transmission investments
•Uncertainties related to low market experience in building and operating grid storage is a barrier and can
hinder future investment decisions. For transmission projects, the experience level is high and can
therefore be favourable in investment decisions.
Regulatory framework is essential for grid storage integration into the energy infrastructure
•Introduction of a regulatory framework in the EU is necessary to stimulate the market for grid storage.
The potential of grid storage depend on market entry barriers, which is highly influenced by policy
decisions. Ownership uncertainties need to be clarified and EU's unbundling directive regarding storage
ownership is today a major barrier in the EU countries.
•China’s business climate with shorter decision paths can be advantageous for grid storage integration. A regulatory framework for market actors of grid storage projects can be realized in a shorter time frame
compared to market structures in developed countries with longer decision paths, such as Sweden.
Figure 50: Conclusions
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83
8. FUTURE RESEARCH
FUTURE RESEARCH
The market for battery storage is constantly changing. Future research work within the field
of study need to adapt as development in other market areas of storage applications affects the
grid storage potential. Cost reduction of battery storage can make grid storage a lucrative
investment option in the future power system. Economic viability of grid battery storage has
in this research been compared to transmission grid development. The true potential of grid
storage can be further investigated by comparing grid storage to other alternative solutions
that also can bring flexibility in the power system. One example is to evaluate grid storage
potential to demand response solutions as variation moderator.
Further progress of the research findings is to investigate appropriate location of grid storage
systems in the transmission grid. In this research, grid storage is viewed from a systemperspective as a part of the energy infrastructure, without consideration of where in the
system the grid storages are located. Location of the storage sites are however an important
aspect to be considered when planning the power system and can be further examined.
The cost-benefit model performed in this work can be viewed as a foundation for extended
research within the area. The model performance can be refined to increase rigorousness to
the research findings. The benefits included in the model are based on estimations and can be
further examined to increase model accuracy. Because of many potential grid storage
applications, benefits can be modified in further research. To increase research validity the
input data can also be tried in other model designs.
The two markets investigated in this thesis are Sweden and China. These countries have
different market conditions but are at the same time facing similar problems due to increased
amount of intermittent energy sources. Specific market situations and changes within the
countries can be further examined to find deeper understanding of national grid storage
potential and transmission expansion. A market perspective can be used to identify the most
feasible area for grid battery storage integration.
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Tesla Motors. (2015). POWERWALL - Tesla Home Battery. Retrieved May 12, 2015, from
http://www.teslamotors.com/powerwall
The Boston Consulting Group. (2010). Electricity Storage- Making Large-Scale Adaption of
Wind & Solar Energies a Reality. The Boston Consulting Group.
The Electrical Energy Storage Magazine. (2014, December 4). Energy Storage in China.
Retrieved May 14, 2015, from http://ees-magazine.com/energy-storage-in-china/
The Wind Power. (2013). Sweden. Retrieved May 18, 2015, from
http://www.thewindpower.net/country_en_17_sweden.php
91
REFERENCES
The Wind Power. (2013a). Country, General data, Production capacity. Retrieved 01 28,
2015, from http://www.thewindpower.net/
The Wind Power. (2013b). China. Retrieved May 18, 2015, from
http://www.thewindpower.net/country_en_9_china.php
THINK. (2013). Cost Benefit Analysis in the Context of the Energy Infrastructure Package.
European University Institute.
Trading Economics. (2013). China GDP. Retrieved April 22, 2015, from
http://www.tradingeconomics.com/china/gdp
Transmission & Distribution World. (2011). SGCC Jinping-Sunan ±800kV UHV DC
Transmission Project Progresses Smoothly. Retrieved April 18, 2015, from
http://tdworld.com/projects-progress/sgcc-jinping-sunan-800kv-uhv-dc-transmissionproject-progresses-smoothly
U.S. Energy Information Agency. (2012a). International Energy Statistics, Electricity,
Generation. Retrieved 01 28, 2015, from
http://www.eia.gov/cfapps/ipdbproject/IEDIndex3.cfm?tid=2&pid=2&aid=12
U.S. Energy Information Agency. (2012b). Total Electricity Net Generation Sweden.
Retrieved April 22, 2015, from
http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=12&cid=SW
,&syid=2008&eyid=2012&unit=BKWH
U.S. Energy Information Agency. (2012c). Total Electricity Net Generation China. Retrieved
April 22, 2015, from
http://www.eia.gov/cfapps/ipdbproject/iedindex3.cfm?tid=2&pid=2&aid=12&cid=CH
,&syid=2008&eyid=2012&unit=BKWH
Wang, S., Fang, C., Guan, X., Pang, B., & Ma, H. (2014). Urbanisation, energy consumption,
and carbon dioxide emissions in China: A panel data analysis of China’s provinces. Applied Energy, 136, 738–749.
World Nuclear Association. (2015). Electricity Transmission Systems. Retrieved May 19,
2015, from http://www.world-nuclear.org/info/Current-and-FutureGeneration/Electricity-Transmission-Grids/
Wu, Z., Sun, H., & Du, Y. (2014). A large amount of idle capacity under rapid expansion:
Policy analysis on the dilemma of wind power utilization in China. Renewable and
Sustainable Energy Reviews, 32, 271-277.
Zakeri, B., & Syri, S. (2014). Electrical energy storage systems: A comparative life cycle cost
analysis. Aalto : Department of Energy Technology, Aalto University.
92
Appendix I – Code Cost-Benefit Model Sweden
function [] = Sweden()
clc
clear all
close all
format bank
format compact
for t_WC=100:900:1000
m_new =1;
% Creates a loop for different battery costs
for j=0.25:0.25:1
m = m_new;
LB = 1;
UB = 30; % Sets amount of maximum capacity in 100 Watts.
dt = 1;
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
10
= LB*100;
= UB*100;
= UB*dt*100/10;
20
= LB*100*0;
= UB*100;
= UB*dt*100/10;
30
= LB*100*0;
= UB*100*(1+1/6);
= UB*dt*100/6;
% Creates a loop for different power to be installed
for n=LB:dt:UB
1
% Loads input data
load .\Model_v5.1\InputData_Sweden.mat
% Additional Input Data
P_lack = 100*n;
WC = P_lack*t_WC;
BC_GS = 795*10^3*ed*j;
% [MW]
% [MWh]
% [$/MWh]
% Total investment cost
IC_GS = BC_GS*t_dis+BOP_GS+PCS_GS;
RI_GS = BC_GS*((1/(1+ir)^10)+(1/(1+ir)^20)...
+(1/(1+ir)^30));
Lack of power
Wind curtailment per year
Storage section cost
% [$/MW]
% [$/MWh]
% Annual costs over time
AFC_GS = OMf_GS/t_dis+RI_GS*ka_GS;
AVC_GS = OMv_GS;
AFC_T = (OM_T+RI_T)*L;
AVC_T = 0;
%
%
%
%
[$/MWh,year]
[$/MWh,year]
[$/MW,year]
[$/MW,year]
Annual
Annual
Annual
Annual
fixed costs
variable costs
variable costs
fixed costs
% Costs for loss of income during planning and construction time
PCC_GS = EP*t_PC_GS*t_WC;
% [$/MW]
PCC_T = EP*t_PC_T*t_WC;
% [$/MW]
% Residual value
R_GS = RV_GS*(BC_GS*(1/(1+ir)^40)+RI_GS)*ka_GS;
R_T = 0;
% [$/MWh,year]
% [$/MW,year]
% Benefits
AB_GS = sp_GS+(LF_GS+SR_GS)/t_dis;
AB_T = 0;
% [$/MWh,year]
% [$/MWh,year]
Annual benefits storage
Annual benefits transmission
% CONSTRAINTS for minimization
% ----------------------------------------------------------------------% - EGS*N_GS/tload - P_T*A*N_T <= -P_lack
% - A <= 0
% -EGS <= 0
UB_GS = 10000;
% Upper boundary for grid storage
2
A =[-N_GS/t_dis -P_Ta*N_T;...
0 -1;...
-1 0];
b = [-P_lack;0;0];
% MINIMIZATION
% ----------------------------------------------------------------------% x(1) Energy storage
% x(2) Amount of transmission lines
%options = optimoptions(@fmincon,'Algorithm','active-set');
x0 = [100;0];
[x,out] = fmincon(@(x) myfun(x,IC_GS,t_dis,ka_GS,...
kn_GS,AVC_GS,t_WC,AFC_GS,PCC_GS,R_GS,AB_GS,P_Ta,...
IC_T,PCC_T,ka_T,kn_T,AVC_T,AFC_T,R_T,AB_T),x0,A,b);
% Start values for calculation
% The minimum is found for the objective function.
% Creates an if statement to find best solution for <700MW capacities
if x(2) < 1 && n <= (P_Ta/100)
xnew(2)=1;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=1;
else
xnew(2) = 0;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 700MW < capacities <1400
if x(2) > 1 && x(2) < 2 && n > (P_Ta/100) && n < (2*P_Ta/100)
xnew(2)=2;
3
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=2;
else
xnew(2) = 1;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 1400MW < capacities <2100
if x(2) > 2 && x(2) < 3 && n >= (2*P_Ta/100) && n < (3*P_Ta/100)
xnew(2)=3;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=3;
else
xnew(2) = 2;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 2100MW < capacities <2800
if x(2) > 3 && x(2) < 4 && n >= (3*P_Ta/100) && n < (4*P_Ta/100)
xnew(2)=4;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=4;
4
else
xnew(2) = 3;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 280MW < capacities <3500
if x(2) > 4 && x(2) < 5 && n >= (4*P_Ta/100) && n < (5*P_Ta/100)
xnew(2)=5;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=5;
else
xnew(2) = 4;
% x values are rounded to integers to create step
wise
end
end
P_GS(n,m) = (x(1)/t_dis*N_GS+(x(2)-xnew(2))*P_Ta*N_T)/N_GS; %
%
if x(1) == UB_GS && xnew(2) == 0
%
upper boundary,
P_T(n,m) = P_Ta*round(P_lack/(P_Ta*N_T));
%
P_GS(n,m) = (P_lack-P_Ta*N_T)/N_GS;
else
P_T(n,m) = xnew(2)*P_Ta;
end
The amount of transmission power rounded is added
or subtracted from optimal storage power.
Creates a constraint that says if storage reaches
investment in transmission has to be done.
if P_GS(n,m) > UB_GS
exceeds upper boundary.
P_T(n,m) = P_Ta*round(P_lack/(P_Ta*N_T));
P_GS(n,m) = (P_lack-P_T(n,m)*N_T)/N_GS;
% Sets the optimal power's if optimum GS Power
if P_GS(n,m) > UB_GS
transmission power is rounded upwards.
% If storage power still exceeds upper boundary,
5
P_T(n,m) = P_Ta*ceil(P_lack/(P_Ta*N_T));
P_GS(n,m) = (P_lack-P_T(n,m)*N_T)/N_GS;
end
end
% Creates a constraint so storage can not be negative.
if P_GS(n,m) < 0
P_GS(n,m) = 0;
end
P_inst = P_GS(n,m) + P_T(n,m);
P_overcap(n,m) = P_GS(n,m)*N_GS+P_T(n,m)*N_T-P_lack;
Share_GS(n,m) = P_GS(n,m)/P_inst*100;
Share_T(n,m) = P_T(n,m)/P_inst*100;
if t_WC == 100
Share_tot_100(n,1) = Share_GS(n,m);
Share_tot_100(n,2) = Share_T(n,m);
else if t_WC == 1000
Share_tot_1000(n,1) = Share_GS(n,m);
Share_tot_1000(n,2) = Share_T(n,m);
end
end
end
m_new = m+1;
end
%--------------------------------------------------%--------------------Plotting----------------------%---------------------------------------------------
% Counter for looping battery cost.
if t_WC == 100
% Creates a matrix with shares of both technologies for case 100
for k=LB:dt:UB
Out_Power100(k,1) = P_T(k,1);
Out_Power100(k,2) = P_GS(k,1);
Out_Power100(k,3) = P_T(k,2);
Out_Power100(k,4) = P_GS(k,2);
Out_Power100(k,5) = P_T(k,3);
Out_Power100(k,6) = P_GS(k,3);
6
Out_Power100(k,7) = P_T(k,4);
Out_Power100(k,8) = P_GS(k,4);
end
end
if t_WC == 1000
% Creates a matrix with shares of both technologies for case 1000
for k=LB:dt:UB
Out_Power1000(k,1) = P_T(k,1);
Out_Power1000(k,2) = P_GS(k,1);
Out_Power1000(k,3) = P_T(k,2);
Out_Power1000(k,4) = P_GS(k,2);
Out_Power1000(k,5) = P_T(k,3);
Out_Power1000(k,6) = P_GS(k,3);
Out_Power1000(k,7) = P_T(k,4);
Out_Power1000(k,8) = P_GS(k,4);
end
end
end
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[1 2]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 25 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\7_25_100','tiff')
scrsz = get(0,'ScreenSize');
7
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[3 4]),'stacked');
C = ['c' 'k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 50 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\5_50_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[5 6]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 75 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\3_75_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
8
hold
P = bar(Out_Power100(:,[7 8]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 100 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\1_100_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[1 2]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 25 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\8_25_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
9
P = bar(Out_Power1000(:,[3 4]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 50 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\6_50_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[5 6]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 75 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\4_75_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[7 8]),'stacked');
10
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 100 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\Sweden\2_100_1000','tiff')
function out = myfun(x,IC_GS,t_dis,ka_GS,kn_GS,AVC_GS,...
t_WC,AFC_GS,PCC_GS,R_GS,AB_GS,P_Ta,IC_T,PCC_T,ka_T,kn_T,AVC_T,...
AFC_T,R_T,AB_T)
% Objective function - Annuity of investment with respect to previous
% spilled energy
% x(1) Energy storage [MWh]
% x(2) Amount of transmission lines [pcs]
out = [x(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+AVC_GS*365+AFC_GS...
-AB_GS-R_GS)+x(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T)]';
11
Appendix II – Input Data Sweden
clear all
clc
close all
% ----------------------------------------------------------------------% -----------------------------Input data-------------------------------% ----------------------------------------------------------------------% General Data
%--------------------------------------------------sd = 0.12;
% [.]
SEK to U.S. Dollar
yd = 0.16;
% [.]
CNY to U.S. Dollar
ed = 1.06;
% [.]
EURO to U.S. Dollar
EP = 334.5099*sd;
% [$/MWh]
Average spot price benefits storage
t = 8760;
% [h]
Hours per year
ir = 0.055;
% [.]
Interest rate
L = 500;
% [km]
Length of transmission
% Lithium-Ion Grid Storage Sweden
%--------------------------------------------------t_PC_GS = 1;
% [years]
OMf_GS = 6.9*10^3*ed;
% [$/MW,year]
OMv_GS = 2.1*ed;
% [$/MWh,year]
PCS_GS = 383*10^3*ed;
% [$/MW]
BOP_GS = 80*10^3*ed;
% [$/MW]
RV_GS = 0.25;
% [.]
N_GS = 0.9;
% [.]
y_GS = 40;
% [years]
ka_GS = ir/(1-(1+ir)^(-y_GS));
% [.]
kn_GS = 1/(1+ir)^y_GS;
% [.]
t_dis = 2;
% [h]
sp_GS = (379-254)*sd*365;
% [$/MWh,year]
LF_GS = 54600;
% [$/MW,year]
SR_GS = 10000;
% [$/MW,year]
outages/year)
Planning and construction time
Fixed Operation and Management cost
Variable Operation and Management cost
Power conversion systems cost
Balance of plant cost
Residual value in percantage of initial battery cost
Efficency, Source:
Payback time
Annuity factor
Net present factor
Discharging time, Source: LCC analysis- critical view.pdf
Income benefits from spot market
Benifits from Renewable Load Following
Benifits from Electric Service Reliability (1h power
% Transmission Input data (Sweden 180km HVAC + 250km HVDC 400 kV) Source:
% http://svk.se/Projekt/Utbyggnadsprojekt/Sydvastlanken/Information/
%---------------------------------------------------
1
IC_T = 7.3*10^9*sd/(1200*429)*L;
P_Ta = 700;
t_PC_T = 10;
L_Swe = 15000;
P_Swe = 26200;
OM_T = 440*10^6*sd/(P_Swe*L_Swe);
Sweden
RI_T = 667*10^6*sd/(P_Swe*L_Swe);
N_T = 0.97;
y_T = 40;
ka_T = ir/(1-(1+ir)^(-y_T));
kn_T = 1/(1+ir)^y_T;
%
%
%
%
%
%
[$/MW]
[MW]
[years]
[km]
[MW]
[$/MW,km,year]
Investment cost transmission
Power transmission
Planning and construction time
Total length of transmission in Sweden
Power capacity Sweden
Total fixed operation and maintenance cost per year in
%
%
%
%
%
[$/MW,km,year]
[.]
[years]
[.]
[.]
Total reinvestment cost per year in Sweden
Efficency
Payback time Transmission
Annuity factor
Net present factor
% ----------------------------------------------------------------------% -------------------------End of Input data----------------------------% ----------------------------------------------------------------------save .\Model_v5.1\InputData_Sweden.mat
2
Appendix III – Code Cost-Benefit Model China
function [] = China()
clc
clear all
close all
format bank
format compact
for t_WC=100:900:1000
m_new =1;
% Creates a loop for different battery costs
for j=0.25:0.25:1
m = m_new;
LB = 1;
UB = 30; % Sets amount of maximum capacity in 100 Watts.
dt = 1;
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
if UB ==
XPlot_LB
XPlot_UB
XPlot_dt
end
10
= LB*100;
= UB*100;
= UB*dt*100/10;
20
= LB*100*0;
= UB*100;
= UB*dt*100/10;
30
= LB*100*0;
= UB*100*(1+1/6);
= UB*dt*100/6;
% Creates a loop for different power to be installed
for n=LB:dt:UB
1
% Loads input data
load .\Model_v5.1\InputData_China.mat
% Additional Input Data
P_lack = 100*n;
WC = P_lack*t_WC;
BC_GS = 795*10^3*ed*j;
% [MW]
% [MWh]
% [$/MWh]
% Total investment cost
IC_GS = BC_GS*t_dis+BOP_GS+PCS_GS;
RI_GS = BC_GS*((1/(1+ir)^10)+(1/(1+ir)^20)...
+(1/(1+ir)^30));
Lack of power
Wind curtailment per year
Storage section cost
% [$/MW]
% [$/MWh]
% Annual costs over time
AFC_GS = OMf_GS/t_dis+RI_GS*ka_GS;
AVC_GS = OMv_GS;
AFC_T = (OM_T+RI_T)*L;
AVC_T = 0;
%
%
%
%
[$/MWh,year]
[$/MWh,year]
[$/MW,year]
[$/MW,year]
Annual
Annual
Annual
Annual
fixed costs
variable costs
variable costs
fixed costs
% Costs for loss of income during planning and construction time
PCC_GS = EP*t_PC_GS*t_WC;
% [$/MW]
PCC_T = EP*t_PC_T*t_WC;
% [$/MW]
% Residual value
R_GS = RV_GS*(BC_GS*(1/(1+ir)^40)+RI_GS)*ka_GS;
R_T = 0;
% [$/MWh,year]
% [$/MW,year]
% Benefits
AB_GS = sp_GS+(LF_GS+SR_GS)/t_dis;
AB_T = 0;
% [$/MWh,year]
% [$/MWh,year]
Annual benefits storage
Annual benefits transmission
% CONSTRAINTS for minimization
% ----------------------------------------------------------------------% - EGS*N_GS/tload - P_T*A*N_T <= -P_lack
% - A <= 0
% -EGS <= 0
UB_GS = 10000;
% Upper boundary for grid storage
2
A =[-N_GS/t_dis -P_Ta*N_T;...
0 -1;...
-1 0];
b = [-P_lack;0;0];
% MINIMIZATION
% ----------------------------------------------------------------------% x(1) Energy storage
% x(2) Amount of transmission lines
%options = optimoptions(@fmincon,'Algorithm','active-set');
x0 = [100;0];
[x,out] = fmincon(@(x) myfun(x,IC_GS,t_dis,ka_GS,...
kn_GS,AVC_GS,t_WC,AFC_GS,PCC_GS,R_GS,AB_GS,P_Ta,...
IC_T,PCC_T,ka_T,kn_T,AVC_T,AFC_T,R_T,AB_T),x0,A,b);
% Start values for calculation
% The minimum is found for the objective function.
% Creates an if statement to find best solution for <700MW capacities
if x(2) < 1 && n <= (P_Ta/100)
xnew(2)=1;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=1;
else
xnew(2) = 0;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 700MW < capacities <1400
if x(2) > 1 && x(2) < 2 && n > (P_Ta/100) && n < (2*P_Ta/100)
xnew(2)=2;
3
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=2;
else
xnew(2) = 1;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 1400MW < capacities <2100
if x(2) > 2 && x(2) < 3 && n >= (2*P_Ta/100) && n < (3*P_Ta/100)
xnew(2)=3;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=3;
else
xnew(2) = 2;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 2100MW < capacities <2800
if x(2) > 3 && x(2) < 4 && n >= (3*P_Ta/100) && n < (4*P_Ta/100)
xnew(2)=4;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=4;
4
else
xnew(2) = 3;
% x values are rounded to integers to create step
wise
end
end
% Creates an if statement to find best solution for 280MW < capacities <3500
if x(2) > 4 && x(2) < 5 && n >= (4*P_Ta/100) && n < (5*P_Ta/100)
xnew(2)=5;
xnew(1)=100*n*t_dis-(xnew(2)-1)*P_Ta*t_dis;
C_GS = xnew(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+...
AVC_GS*365+AFC_GS-AB_GS-R_GS)+(xnew(2)-1)*P_Ta*...
((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T);
C_T = xnew(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)...
*ka_T+AVC_T+AFC_T-AB_T);
if C_T < C_GS
xnew(2)=5;
else
xnew(2) = 4;
% x values are rounded to integers to create step
wise
end
end
P_GS(n,m) = (x(1)/t_dis*N_GS+(x(2)-xnew(2))*P_Ta*N_T)/N_GS; %
%
if x(1) == UB_GS && xnew(2) == 0
%
upper boundary,
P_T(n,m) = P_Ta*round(P_lack/(P_Ta*N_T));
%
P_GS(n,m) = (P_lack-P_Ta*N_T)/N_GS;
else
P_T(n,m) = xnew(2)*P_Ta;
end
The amount of transmission power rounded is added
or subtracted from optimal storage power.
Creates a constraint that says if storage reaches
investment in transmission has to be done.
if P_GS(n,m) > UB_GS
exceeds upper boundary.
P_T(n,m) = P_Ta*round(P_lack/(P_Ta*N_T));
P_GS(n,m) = (P_lack-P_T(n,m)*N_T)/N_GS;
% Sets the optimal power's if optimum GS Power
if P_GS(n,m) > UB_GS
transmission power is rounded upwards.
% If storage power still exceeds upper boundary,
5
P_T(n,m) = P_Ta*ceil(P_lack/(P_Ta*N_T));
P_GS(n,m) = (P_lack-P_T(n,m)*N_T)/N_GS;
end
end
% Creates a constraint so storage can not be negative.
if P_GS(n,m) < 0
P_GS(n,m) = 0;
end
P_inst = P_GS(n,m) + P_T(n,m);
P_overcap(n,m) = P_GS(n,m)*N_GS+P_T(n,m)*N_T-P_lack;
Share_GS(n,m) = P_GS(n,m)/P_inst*100;
Share_T(n,m) = P_T(n,m)/P_inst*100;
if t_WC == 100
Share_tot_100(n,1) = Share_GS(n,m);
Share_tot_100(n,2) = Share_T(n,m);
else if t_WC == 1000
Share_tot_1000(n,1) = Share_GS(n,m);
Share_tot_1000(n,2) = Share_T(n,m);
end
end
end
m_new = m+1;
end
%--------------------------------------------------%--------------------Plotting----------------------%---------------------------------------------------
% Counter for looping battery cost.
if t_WC == 100
% Creates a matrix with shares of both technologies for case 100
for k=LB:dt:UB
Out_Power100(k,1) = P_T(k,1);
Out_Power100(k,2) = P_GS(k,1);
Out_Power100(k,3) = P_T(k,2);
Out_Power100(k,4) = P_GS(k,2);
Out_Power100(k,5) = P_T(k,3);
Out_Power100(k,6) = P_GS(k,3);
6
Out_Power100(k,7) = P_T(k,4);
Out_Power100(k,8) = P_GS(k,4);
end
end
if t_WC == 1000
% Creates a matrix with shares of both technologies for case 1000
for k=LB:dt:UB
Out_Power1000(k,1) = P_T(k,1);
Out_Power1000(k,2) = P_GS(k,1);
Out_Power1000(k,3) = P_T(k,2);
Out_Power1000(k,4) = P_GS(k,2);
Out_Power1000(k,5) = P_T(k,3);
Out_Power1000(k,6) = P_GS(k,3);
Out_Power1000(k,7) = P_T(k,4);
Out_Power1000(k,8) = P_GS(k,4);
end
end
end
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[1 2]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 25 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\7_25_100','tiff')
scrsz = get(0,'ScreenSize');
7
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[3 4]),'stacked');
C = ['c' 'k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 50 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\5_50_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power100(:,[5 6]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 75 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\3_75_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/2 scrsz(3)/2 scrsz(4)/3])
8
hold
P = bar(Out_Power100(:,[7 8]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 100 %, 100 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\1_100_100','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[1 2]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 25 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\8_25_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
9
P = bar(Out_Power1000(:,[3 4]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 50 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\6_50_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[5 6]),'stacked');
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 75 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\4_75_1000','tiff')
scrsz = get(0,'ScreenSize');
figure ('Position',[800 scrsz(4)/16 scrsz(3)/2 scrsz(4)/3])
hold
P = bar(Out_Power1000(:,[7 8]),'stacked');
10
C = ['c','k'];
for n=1:2
set(P(n),'FaceColor',C(n));
end
title('Battery Cost 100 %, 1000 hours curtailment per year','FontSize',20)
xlabel('Capacity demand [MW]','FontSize',16);
range=(XPlot_LB:XPlot_dt:XPlot_UB);
set(gca,'XTickLabel',range)
ylabel('Capacity installed [MW]','FontSize',16);
xlim([0 31])
ylim([0 3500])
legend('Transmission','Grid Storage','Location','NorthWest')
set(gcf, 'PaperPositionMode', 'auto')
saveas(gcf,'.\Model_v5.1\Outputs\China\2_100_1000','tiff')
function out = myfun(x,IC_GS,t_dis,ka_GS,kn_GS,AVC_GS,...
t_WC,AFC_GS,PCC_GS,R_GS,AB_GS,P_Ta,IC_T,PCC_T,ka_T,kn_T,AVC_T,...
AFC_T,R_T,AB_T)
% Objective function - Annuity of investment with respect to previous
% spilled energy
% x(1) Energy storage [MWh]
% x(2) Amount of transmission lines [pcs]
out = [x(1)*(ka_GS/t_dis*(IC_GS+PCC_GS)+AVC_GS*365+AFC_GS...
-AB_GS-R_GS)+x(2)*P_Ta*((IC_T+PCC_T-R_T*kn_T)*ka_T+AVC_T+AFC_T-AB_T)]';
11
Appendix IV – Input Data China
clear all
clc
close all
% ----------------------------------------------------------------------% -----------------------------Input data-------------------------------% ----------------------------------------------------------------------sd = 0.12;
% [.]
SEK to U.S. Dollar
yd = 0.16;
% [.]
CNY to U.S. Dollar
ed = 1.06;
% [.]
EURO to U.S. Dollar
EP = 540*yd;
% [$/MWh]
Wind Power feed-in tariff II
t = 8760;
% [h]
Hours per year
ir = 0.055;
% [.]
Interest rate
L = 1000;
% [km]
Length of transmission
% Lithium-Ion Grid Storage China
%--------------------------------------------------t_PC_GS = 1;
% [years]
OMf_GS = 6.9*10^3*ed;
% [$/MW,year]
OMv_GS = 2.1*ed;
% [$/MWh,year]
PCS_GS = 383*10^3*ed;
% [$/MW]
BOP_GS = 80*10^3*ed;
% [$/MW]
RV_GS = 0.25;
% [.]
RI_GS = 369*ed*10^3/5;
% [$/MW,year]
N_GS = 0.9;
% [.]
y_GS = 40;
% [years]
ka_GS = ir/(1-(1+ir)^(-y_GS));
% [.]
kn_GS = 1/(1+ir)^y_GS;
% [.]
t_dis = 2;
% [h]
sp_GS = 0;
% [$/MWh,year]
LF_GS = 54600;
% [$/MW,year]
SR_GS = 6000;
% [$/MW,year]
outages/year)
Planning and construction time
Fixed Operation and Management cost
Variable Operation and Management cost
Power conversion systems cost
Balance of plant cost
Residual value in percantage of initial battery cost
Yearly reinvestment cost
Efficency, Source:
Payback time
Annuity factor
Net present factor
Discharging time, Source: LCC analysis- critical view.pdf
Income benefits from spot market
Benifits from Renewable Load Following
Benifits from Electric Service Reliability (1h power
% Transmission Input data (China 500 kV Ac total length 1634 km) Source:
% http://tdworld.com/projects-progress/sgcc-jinping-sunan-800kv-uhv-dc-transmission-project-progresses-smoothly
%--------------------------------------------------IC_T_Swe=7.3*10^9*sd/(1200*429)*L;% [$/MW]
Investment cost transmission
1
IC_T = 5.7*10^9/(1000*1634)*yd*L;
P_Ta = 1000;
t_PC_T = 7;
L_Swe = 15000;
P_Swe = 26200;
OM_T = 440*10^6*sd/(P_Swe*L_Swe);
Sweden
RI_T = 667*10^6*sd/(P_Swe*L_Swe);
OMRI_T = (OM_T+RI_T)/IC_T_Swe*L;
of investment per year
N_T = 0.97;
y_T = 40;
ka_T = ir/(1-(1+ir)^(-y_T));
kn_T = 1/(1+ir)^y_T;
% [$/MW]
% [MW]
% [years]
% [km]
% [MW]
% [$/MW,km,year]
Investment cost transmission
Power transmission
Planning and construction time
Total length of transmission in Sweden
Power capacity Sweden
Total fixed operation and maintenance cost per year in
% [$/MW,km,year]
% [1/year]
Total reinvestment cost per year in Sweden
Reinvestment, operation and maintenance cost in percantage
%
%
%
%
Efficency
Payback time Transmission
Annuity factor
Net present factor
[.]
[years]
[.]
[.]
% ----------------------------------------------------------------------% -------------------------End of Input data----------------------------% ----------------------------------------------------------------------save .\Model_v5.1\InputData_China.mat
2
Box 883, 721 23 Västerås Tfn: 021-10 13 00
Box 325, 631 05 Eskilstuna Tfn: 016-15 36 00
E-post: [email protected] Webb: www.mdh.se
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