The role of large scale energy storage systems in the electricity grid ...

University of Groningen
CIO, Center for Isotope Research
IVEM, Center for Energy and Environmental Studies
Master Programme Energy and Environmental Sciences
The role of large scale energy storage
systems in the electricity grid of the
Netherlands in 2050
Martin Velthuis
EES 2012-136 T

Training report of Martin Velthuis
Supervised by: Dr. R.M.J. Benders (IVEM)
Prof.dr. F.A. de Bruijn (ESRIG)
University of Groningen
CIO, Center for Isotope Research
IVEM, Center for Energy and Environmental Studies
Nijenborgh 4
9747 AG Groningen
The Netherlands
http://www.rug.nl/fmns-research/cio
http://www.rug.nl/fmns-research/ivem

TABLE OF CONTENTS
Samenvatting ................................................................................................................... 3
Summary .......................................................................................................................... 5
1 Introduction ............................................................................................................... 7
1.1 Problem definition .......................................................................................................... 7
1.2 Research aim .................................................................................................................. 8
1.3 Main research question ................................................................................................... 8
1.4 Sub questions .................................................................................................................. 8
1.5 Methodology................................................................................................................... 8
2 Potential renewable resources ................................................................................ 11
2.1 Wind energy ................................................................................................................. 12
2.2 Solar photovoltaic ......................................................................................................... 14
2.3 Biomass ........................................................................................................................ 15
3 Variability ................................................................................................................ 17
3.1 Wind energy ................................................................................................................. 17
3.2 Solar photovoltaic ......................................................................................................... 18
3.3 Demand ........................................................................................................................ 18
4 Future electricity mix .............................................................................................. 21
5 Large scale energy storage ..................................................................................... 23
5.1 Pumped Hydro Storage or Energy Island ..................................................................... 23
5.2 Compressed Air Energy Storage .................................................................................. 25
5.3 Flow Battery Energy Storage (FBES) .......................................................................... 26
6 GoldSim Model ........................................................................................................ 29
7 GoldSim Results ...................................................................................................... 33
7.1 Storage demand ............................................................................................................ 33
7.2 Scenarios....................................................................................................................... 34
8 Conclusion, discussion and Further Research ...................................................... 39
8.1 Conclusion .................................................................................................................... 39
8.2 Discussion..................................................................................................................... 40
8.3 Final conclusion............................................................................................................ 41
8.4 Further research ............................................................................................................ 41
Literature ....................................................................................................................... 43
Appendix 1 – Powerplan scenarios .............................................................................. 47
Appendix 2 – Other Energy Storage Technologies .................................................... 55
Appendix 3 – ESS model .............................................................................................. 57
Appendix 4 – Storage demand ..................................................................................... 59
Appendix 5 – ESS scenarios ......................................................................................... 63

SAMENVATTING
De verbranding van fossiele brandstoffen voor elektriciteitsproductie heeft een wereldwijde impact op
het milieu. Ook zullen de fossiele brandstoffen in deze of volgende eeuw opraken. Dit is de reden
voor het toenemende gebruik van hernieuwbare energiebronnen. Het kan verwacht worden dat dit
doorzet in de toekomst, vanwege de Europese doelstelling die gesteld is om bijna 100% hernieuwbare
energie in de elektriciteitsproductie te hebben in 2050.
Het probleem met de elektriciteitsproductie van hernieuwbare energiebronnen is het verschil
tussen vraag en aanbod. Het waait niet altijd op een windpark en de zon schijnt niet elke dag de hele
dag op zonnepanelen. Dit kan variëren van minuten tot seizoenen.
Eén van de mogelijkheden om met dit probleem om te gaan is het (in)direct opslaan van de
elektriciteit in een energieopslagvoorziening wanneer de elektriciteitsproductie hoger is dan de vraag.
Wanneer de productie lager ligt dan de vraag, dan kan de opgeslagen energie gebruikt worden voor
het leveren van elektriciteit.
De hoofdvraag in dit onderzoek is:
In hoeverre kunnen grootschalige energieopslagsystemen een rol spelen in het Nederlandse elektriciteitsnet
om het verschil in de elektriciteitsvraag en elektriciteitsproductie van hernieuwbare bronnen
op te vangen om zo de Europese doelstellingen te halen in 2050?
Uit literatuuronderzoek blijkt dat in grotere mate wind op land en op zee en in mindere mate zon fotovoltaïsch
en biomassa de meest potentiële hernieuwbare bronnen zijn voor elektriciteitsproductie in
Nederland. Een patroon van de elektriciteitsproductie van wind en van de elektriciteitsvraag met
chronologische tijd intervallen van 1 uur over een heel jaar zijn gebruikt in het simulatieprogramma
PowerPlan. PowerPlan is gebruikt om de Nederlandse elektriciteitsvraag en –aanbod tot 2050 te genereren,
waarin de Europese doelstelling wordt gehaald.
De chronologische uurpatronen van de elektriciteitsvraag en –aanbod in 2050 zijn gebruikt als
input voor een model die gemaakt is met GoldSim. In dit model worden de elektriciteitsoverschotten
en tekorten berekend en wordt er gekeken in hoeverre opslagsystemen deze onbalans kunnen opvangen.
Hiervoor zijn er vijf energieopslagsystemen gemodelleerd die met een literatuuronderzoek als
meest geschikt voor grootschalige toepassing in Nederland zijn bevonden. Dit zijn: Energie Eiland
(een valmeer in de Noordzee), gecomprimeerde lucht (CAES, Crompressed Air Energy Storage) en
drie soorten vloeistofaccu’s.
Uit de resultaten blijkt dat de totale elektriciteitstekort over 2050 6,4 TWh is. Om dit op te
vangen is een opslagcapaciteit van 1,2 TWh nodig. Het vermogen dat de opslagsystemen nodig hebben
zijn voor het opladen 10,3 GW en voor het ontladen 8,5 GW.
Om een technisch betrouwbaar elektriciteitsnet te hebben in 2050, zijn er 40 Energie Eilanden,
140 CAES systemen of 10.000 vloeistofaccu’s nodig. Deze scenario’s zijn niet praktisch vanwege
de benodigde ruimte en locaties. Een meer praktische scenario is een combinatie van 2 Energie
Eilanden, 20 CAES systemen en 100 van elk type vloeistofaccu, maar dit scenario is dan niet technisch
betrouwbaar. De enige economisch aantrekkelijke scenario’s zijn de technisch betrouwbare
scenario met 140 CAES systemen en het praktische scenario zonder vloeistofaccu’s. Maar deze zijn
respectievelijk niet praktisch of technisch betrouwbaar.
De hoofdconclusies van dit onderzoek zijn:
Grootschalige energieopslagsystemen op het Nederlandse elektriciteitsnet kunnen technisch het verschil
tussen elektriciteitsvraag en elektriciteitsproductie van hernieuwbare bronnen voor 100% opvangen
om de Europese doelstelling te halen in 2050, maar dit is niet praktisch door de benodigde ruimte
en onder andere daardoor ook niet economisch aantrekkelijk.
Uit de resultaten blijkt ook dat met 150 GWh opslagcapaciteit (12,5% van de 1,2 TWh dat
nodig is) al de helft van het elektriciteitstekort opgevangen kan worden. Dit kan gedaan worden met 1
Energie Eiland en 20 CAES systemen. Voor de andere helft is dus nog 1,05 TWh meer nodig. Deze
zou opgevangen kunnen worden met andere alternatieven. Zoals het inzetten van gascentrales. Dit is
economisch aantrekkelijk, maar dan wordt de Europese doelstelling voor 2050 niet gehaald. Een ander
alternatief is gebruik maken van een Europees elektriciteitsnetwerk.
3

SUMMARY
The burning of the fossil fuels for electricity generation has an environmental impact on a global
scale. Also, the world is going to be running out of the fossil fuels before or within the next century.
This is the reason why renewable energy sources are used more often. The growth of renewable energy
can be expected to continue, because of the European targets which are set for future share of renewable
energy of almost 100% in 2050.
The problem with the electricity production from renewable sources is the mismatch between
demand and supply. Wind is not always available at a wind park and the sun does not always shine all
day and every day on solar panels. This can vary from minutes to seasons.
One of the potential possibilities to cope with this problem is to store the electricity directly or
indirectly in an energy storage facility during the time when the electricity production is higher than
the electricity demand. When the electricity production is lower than the electricity demand, the
stored electricity is supplied to the electricity grid.
The main research question in this research is:
To which extend can be the role of large scale energy storage systems in the Dutch electricity grid to
intercept the mismatch between the electricity demand and the electricity production from renewable
sources to meet the European targets in 2050?
Literature research shows that wind onshore and offshore, and fewer solar photovoltaic and biomass,
are the most potential renewable energy sources for electricity production in the Netherlands. Data
patterns of the wind electricity production and electricity demand with chronological time intervals of
1 hour over a whole year are used in the simulation program PowerPlan. PowerPlan is used to generate
the Dutch electricity demand and production till 2050, where the European target is met.
The chronological hourly patterns of the total electricity demand and production in 2050 are
used as input for the model made with GoldSim. This model is used to calculate the electricity surplus
and shortage and to see to which extend energy storage systems can dissolve the mismatch. For this,
five energy storage systems are included, which are considered from a literature study as the best storage
systems for large scale use. These are: an energy island (inverted pumped hydro storage on the
North Sea), Compressed Air Energy Storage (CAES) and three kinds of Flow Battery Energy Storage
(FBES).
The results show that the total electricity shortage over 2050 is 6.4 TWh. An energy capacity
of 1.2 TWh from the storage systems is needed to dissolve this electricity shortage. The needed power
capacity of the storage systems is 10.3 GW for charging and 8.5 GW for discharging.
To have a technical reliable Dutch electricity grid in 2050, 40 Energy Islands, 140 CAES systems
or 10,000 PSB systems are needed. These scenarios are not very practical, because of the required
space and locations. A more practical scenario is a combination of 2 Energy Islands, 20 CAES
systems and 100 of each type Flow Battery Energy Storage, but this scenario is not technical reliable.
The only economical attractive scenarios are the technical reliable scenario with140 CAES systems
and the practical scenario without FBES systems, but these are respectively not practical and not
technical reliable.
The main conclusion of this research is:
Large scale energy storage systems in the Dutch electricity grid can technically intercept the mismatch
between the electricity demand and the electricity production from renewable sources for 100%
to meet the European targets in 2050, but this is not practical through the needed space and not economical
attractive.
The results also show that 150 GWh storage capacity (12.5% of the 1.2 TWh needed storage
capacity) dissolves 50% of the electricity shortage. This can be done by 1 Energy Island and 20 CAES
systems. For the other 50%, 1.05 TWh more capacity is needed. This could be dissolved with the use
of other alternatives, for example the installation of gas turbines. This is economical attractive, but
then the European target for 2050 is not met. Another alternative is the use of an European electricity
grid.
5

1 INTRODUCTION
Since the middle of the 20 th century the consumption of the energy has increased intensely worldwide
from 3,813 million tones oil equivalent (toe) in 1965 to 11,164 million toe in 2009 (BP, 2010). That is
an increase of 293% in 44 years. This increase is predicted to continue in the future to 16,432 million
toe in 2030 (BP, 2011). Electricity has a share of 17.3% of the world’s final energy consumption
(21,6% in the OECD), distributed to consumers for lightning, running appliances, air conditioning,
heating, etc. This electricity is generated at different types of electrical power plants (McKinney et al.,
2007; OECD/IEA, 2011b).
In 2008, the Netherlands produced almost 108 TWh electricity, where 85.7% was generated
from fossil fuels (coal, oil and natural gas), 10.3 % from renewable sources (wind, solar PV, biomass,
waste and hydro), 3.8% from nuclear and 0.2% from other sources (OECD/IEA, 2011a).
Currently the fossil fuels (specifically natural gas and coal) are the primary sources of generating
electricity, because fossil fuels have been available in a plentiful supply that was easy to mine.
They provide a form of concentrated energy that can be easily stored, transported and combusted. The
burning of coal and natural gas have an impact on a global scale and causes global warming, acid rain,
air pollution, water pollution and damage to the surface of the land as a result of mining and drilling
activities (especially in the case of strip-mining for coal). Beside of these environmental impacts it is
also the case that the world is going to be running out of these fossil fuels before or within the next
century. (McKinney et al., 2007)
Because of the environmental impacts related to the burning and the limited stock of the fossil
fuels, renewable energy sources are used more often (McKinney et al., 2007). The growth of renewable
energy can be expected to continue, because of the European targets which are set for future share
of renewable energy of 20% in 2020 and almost 100% in 2050 (European Commission, 2011). The
target of the Dutch government is to have 14% renewable energy in 2020 (Ministerie van Economische
Zaken, Landbouw & Innovatie, 2011). There is no target set in the share of electricity from
renewable sources by the Dutch government and there are no targets set for 2050.
1.1 Problem definition
The problem with the electricity production from renewable sources is the mismatch between demand
and supply.
Demand-side:
The electricity demand is not always the same and can differ from hours to seasons. During the day
the electricity demand is higher than during the night and peaks in the winter due to the increased
lighting demand, heating demand and higher average economic activity (due to holidays in the summer)
(Hekkenberg et al., 2009).
Supply-side:
A problem with the renewable sources is that they cannot produce electricity on demand. The wind
will not always blow at a wind park, the sun does not always shine all day on solar panels (during
nights and cloudy days) and the intensity of sunlight varies over the year (McKinney et al., 2007). The
variability of the renewable sources occurs on different time scales from minutes to seasons (Beaudin
et al., 2010).
The variability of the electricity demand and the renewable sources causes the mismatch between
electricity demand and supply in the Dutch electricity grid. Currently this is managed by the
use of gas power plants (Ummels et al., 2008), but this will be problematic when electricity from renewable
sources have a larger share in the electricity mix (Ibrahim et al., 2008). Nuclear- and coal
power plants are power plants which have to run at full capacity or are highly inefficient at a lower
capacity and it is not possible to turn these power plants off and on in a short time (McKinney et al.,
2007). Because of these characteristics of these power plants, the electricity from renewable sources
will be dumped when the production of electricity is higher than the electricity demand
One of the potential possibilities to cope with this problem is to store the electricity directly or
indirectly in an energy storage facility during the time when the electricity production is higher than
7

the electricity demand. This energy can be discharged, when the electricity production is lower than
the electricity demand. (Beaudin et al., 2010; Chen et al., 2009)
1.2 Research aim
The aim of the research is to have a share of reliable electricity from renewable sources of almost
100% in 2050 in the Dutch electricity grid by using large scale energy storage systems. The European
targets are chosen as the research aim, because of the lack of clear targets by the Dutch government.
1.3 Main research question
The main research question for this research is:
What can the role of large scale energy storage systems be in the Dutch electricity grid to intercept
the mismatch between the electricity demand and the electricity production from renewable sources to
meet the European target in 2050?
1.4 Sub questions
To answer the main research question, six sub questions are formulated:
1. Which of the renewable sources have a certain potential in the Dutch electricity grid in 2050?
2. What is the variability of the renewable sources in the Netherlands?
3. How variable is the electricity demand in the Netherlands?
4. What will the electricity mix be in the Dutch electricity grid in 2050?
5. What is the storage demand in 2050 and which large scale energy storage systems are suitable
for the Netherlands to fulfill the storage demand?
6. What is the most economical, practical and technical reliable scenario for the Dutch electricity
grid with large scale energy storage systems installed?
1.5 Methodology
A schematic overview of the methodology is shown in
Figure 1.
For the first sub question, literature is used to determine which renewable sources are relevant
for the research. Results of this literature study are in chapter 2. In this way, the amount of renewable
sources to study for sub question two can be limited.
To answer sub question two and three, data is collected from literature about the hourly variability
of the determined renewable sources and hourly electricity demand (chapter 3).
For the fourth sub question the computer program PowerPlan is used (chapter 4). This is an
interactive simulation model that plans the electricity supply of a country for several decades. This
program calculates with patterns of hourly data of electricity production from renewable sources and
electricity demand. With this program several scenarios for the Netherlands till 2050 are generated:
Business as Usual (BaU), European target (95% RS), 95% RS +gas and five scenarios with different
shares of wind offshore.
With the results from sub questions two, three and four the hourly storage demand is determined.
In this way it is determined which large scale energy storage systems are suitable for the Netherlands
to cope with the mismatch between electricity demand and supply (chapter 5).
All the data from the first five sub questions are used to make a model of the Dutch electricity
grid in the computer program GoldSim (chapter 6). GoldSim is a simulation program for dynamically
modeling complex systems. With this model several scenarios for sub question six are generated
(chapter 7). A conclusion and an answer to the research question are done in chapter 8, with some
discussion points and recommendations for further research.
8

Potential Renewable Sources
Variability Renewable Sources PowerPlan
Variability Electricity Demand
Energy Storage Systems
Figure 1 - Schematic overview of methodology
GoldSim model
Economical, technical reliable and practical
scenarios
Electricity mix scenarios 2050
Electricity supply and demand patterns
9

2 POTENTIAL RENEWABLE RESOURCES
To determine the electricity production in the future, it is needed to know which potential renewable
resources are available in the Netherlands. Table 1 gives an overview of energy sources which are
considered as renewable and non-fossil in the Netherlands. The technologies to convert them into a
useful form are also included in this table. Nuclear power is also considered as non-renewable source.
Table 1 - Overview of the renewable sources in the Netherlands (NL Agency, 2010)
Renewable Resource Technology
Wind - Wind turbines*
Sun - Photovoltaic systems (solar cells)*
- Thermal systems (solar thermal systems, dry swimming pool
heating systems)
Hydropower - Hydropower stations*
Tides - Tidal energy power station*
Waves - Wave energy power stations*
Fresh/saltwater gradient - Fresh/saltwater gradient*
Geothermal - Geothermal installations*
Ground energy - Direct as heat/cold storage
- With a heat pump
Aerotherm (air) - Heat pumps
Biomass - Thermal conversion: combustion*, gasification*, pyrolysis
- Biological conversion: digestion
- Input as transport fuel
* Used or can be used for electricity generation.
This study is only focused on electricity production
from renewable sources and not on heat production. In
Table 1, the technologies which are or can be used for
electricity production are marked with ‘*’.
Figure 2 gives an impression of what the potential of
these renewable sources are. Wind, sun and biomass are
the most potential renewable resources for the Netherlands
and will be used in this study. The potential of the
other renewable resources, like geothermal, hydro, tide,
waves, fresh/saltwater gradient and solar thermal, are
too small or too uncertain and are not included in this
study. The potential of wind energy, solar photovoltaic
and biomass in 2020 and 2050 will be described separately
by a literature study in this chapter. The year
2020 is also chosen, because more literature for 2020 is
more available than for the year 2050.
Figure 2 - Mid-term potentials of electricity
from renewable energy sources in the Netherlands
(Commission of the European Communities, 2004)
11

2.1 Wind energy
Compared with other renewable energy sources, wind energy has the highest potential for large-scale
electricity production. The European Wind Energy Association (EWEA) predicts that wind energy
will have a share of 24% of the electricity consumption in the Netherlands in 2020 or 32.4 TWh in
electricity production (EWEA, 2011). The European Commission made a scenario with a wind energy
capacity of 9.7 GW in 2020 and 11.5 GW in 2030 (European Commission, 2010), but in this document
there is no distinction made between offshore and onshore wind energy. Offshore and onshore
wind farms have other characteristics, because there is a difference in the cost, the foundation, the
electrical networks and the works in construction and operation (Esteban et al., 2011). In this study,
offshore and onshore are researched separately.
2.1.1 Offshore
There are several reasons to generate electricity
from offshore wind turbines. One of the main reasons
is the availability of large continuous areas
which are suitable for large wind farms. Another
reason is that the wind speeds are higher in these
areas. These wind speeds increases with distance
from the shore (Figure 3). There is also less turbulence
on the sea, which reduces the fatigue loads on
the turbines, so they are able to produce the energy
more effectively. Compared with onshore wind
parks, offshore wind parks have fewer issues with
visual impact and noise. (Bilgili et al., 2011)
The main drawback of offshore wind energy is that
the costs are higher than onshore wind energy, because
of the more expensive marine foundations,
integration to the electrical network (increase in the
capacity of weak coastal grids are necessary in
some cases), installation procedures and restricted
access during construction due to weather conditions.
Another drawback is the limited access for
operations and maintenance during operation.
(Bilgili et al., 2011)
2020:
Several studies researched the potential of offshore wind energy. In a report of ECN (Energy research
Centre of the Netherlands) it is mentioned that the realizable potential of offshore wind energy is 6
GW installed capacity in 2020 (Noord, de et al., 2004). The EWEA sets a target of 14% (18.9 TWh)
of the total electricity consumption in 2020, produced by offshore wind farms with a total capacity of
almost 5.2 GW (EWEA, 2011). In Odenberger & Johnsson (2010) the potential and upper limit in the
Netherlands is 19.5 TWh in 2020. Junginger et al. (2004) gives predictions of potentials for electricity
from offshore wind energy in 2020 from different points of view, which are listed in
Table 2. The above literature shows that the potential of offshore wind energy in 2020 is in a range
from 2.6 GW to 6 GW installed capacity.
2050:
In the ECN report it is mentioned that the realistic potential of offshore wind energy is 6 to 30 GW in
2050 (Noord, de et al., 2004). In Odenberger & Johnsson (2010) the potential and upper limit in the
Netherlands is 28.6 TWh in 2050.
12
Figure 3 - Mean wind speed at a height of 90
meter in the Netherlands' Exclusive Economic
Zone (Donkers, Brand, & Eecen, 2011)

Table 2 - Potential of electricity from offshore wind in 2020 from the study of (Junginger et al., 2004)
Max. technical potential 10.000 – 56.000 MW
Economical potential > 4400 MW
Max. potential limited by production/installation capacity
and technological development until 2020
3250 – 4400 MW
Max. environmental sustainable potential 100 MW nearshore, 3000 MW offshore
‘Best guess’ 2600 MW
Range found in scenario studies for 2020 500 – 2600 MW
2.1.2 Onshore
The annual average wind speed in the Netherlands
is the highest in the coastal regions and around the
IJsselmeer (Figure 4). This is because the wind
encounters here the smallest friction from the
ground. Further inland the friction from the ground
increases by buildings and forested areas (KNMI,
2002).
2020:
The EWEA sets a target to 10% (13.5 TWh) of the
total electricity production in 2020, produced by
onshore wind farms with a total capacity of 6 GW
(EWEA, 2011). In Odenberger & Johnsson (2010)
the potential and upper limit in the Netherlands is
5.5 TWh in 2020. In the Energy Report of 2011
(Ministerie van Economische Zaken, Landbouw &
Innovatie, 2011) the Dutch government sets there
target to 6 GW of installed capacity of onshore
wind energy in 2020.
Junginger et al. (2004) studied the potential of
electricity from onshore wind energy in 2020
from different points of view, which are listed in
Table 3.
Figure 4 - Map of the Netherlands with average
wind speed at a height of 100 meters between
1981 and 2010 (KNMI, 2011)
Table 3 - Potential of electricity from onshore wind in 2020 from the study of (Junginger et al., 2004)
Max. technical potential 3000 – 6000 MW
Economical potential > 3000 MW
Max. potential limited by production/installation capacity
and technological development until 2020
> 6000 MW
Max. environmental sustainable potential 700 – 2500 MW
‘Best guess’ 2214 MW
Range found in scenario studies for 2020 700 – 3100 MW
2050:
In the ECN report it is mentioned that the realistic potential of onshore wind energy is 1.5 to 3.2 GW
in 2050 (Noord, de et al., 2004). In Odenberger & Johnsson (2010) the potential and upper limit in the
Netherlands is 17.2 TWh in 2050.
13

2.2 Solar photovoltaic
The average annual duration of sunshine and amount of global radiation in the Netherlands is the
highest in the coastal regions and the islands in the Waddenzee and the lowest in the eastern part of
the Netherlands (Figure 5 and Figure 6). Due to convection, more clouds originate further inlands
(KNMI, 2002).
Figure 5 - Map of the Netherlands with average
annual amount of global radiation between 1981
and 2010
In the coming decade the photovoltaic market will remain to be rooftop systems. In the further future
more interest is expected in building integrated PV and ground based PV.
2020:
The potentials for electricity from photovoltaic in 2020 studied in Junginger et al. (2004) are listed in
Table 4.
Table 4 - Potential of electricity from solar photovoltaic in 2020 (Junginger et al., 2004)
Max. technical potential 70.000 MWp
Economical potential 0 MWp
Max. potential limited by production/installation capacity
and technological development until 2020
1200 – 1800 MWp
Max. environmental sustainable potential 20.000 – 60.000 MWp
‘Best guess’ 580 MWp
Range found in scenario studies for 2020 16 – 2000 MWp
The European Commission has made a trend scenario with generation capacity of solar of 151 MW
2020 and 241 MW in 2030 (European Commission, 2010).
14
Figure 6 - Map of the Netherlands with average
annual duration of sunshine between 1981 and 2010

2050:
According to ECN (Noord, de et al., 2004) the realistic potential for the Netherlands is 600 km 2 ,
which will have a realizable potential of 49 (7 to 180) GW in 2050. The realizable potential is very
wide ranged, because the development in technology (especially in power density) and cost reduction
are very influencing uncertain factors.
2.3 Biomass
Biomass can be processed in many ways for energy use. Thermo chemical and biochemical processes
are the main technologies for electricity production. Technologies for thermo chemical conversion are
direct and indirect co-firing coal plant, indirect co-firing gas-fired plant, combustion, pyrolysis and
gasification. The technology for biochemical conversion is digestion (Noord, de et al., 2004). The
main advantage of biomass compared to fossil fuels is the shorter carbon cycle. The growth of new
biomass absorbs the carbon dioxide from the combustion of the old biomass (McKinney et al., 2007).
2020:
The Dutch government has set the goal to get 33-50 PJ from biomass in 2020 (Ministerie van Economische
Zaken, Landbouw & Innovatie, 2011). In the ECN report (Noord, de et al., 2004) they estimate
the potential of biomass in the range 87 to 146 PJ from energy crops, biomass residues and biomass
waste.
Junginger et al. (2004) studied the domestic biomass and organic waste potentials (Table 5) and the
potential of co-firing capacity of electrical power plants (Table 6) for renewable electricity in 2020.
Table 5 - Domestic biomass and organic waste potentials for the Netherlands in 2020 (Junginger et al.,
2004)
Max. technical potential 146 PJth
Economical potential 142 PJth
Max. potential limited by production/installation
capacity and technological development until
2020
142 PJth
Max. environmental sustainable potential 40 PJth
‘Best guess’ 65 – 75 PJth
Range found in scenario studies for 2020 44 – 166 PJth
Table 6 - Electrical (co-firing) capacity of power plants for the Netherlands in 2020 (Junginger et al., 2004)
Max. technical potential > 5300 MW
Economical potential 1080 MW
Max. potential limited by production/installation 5300 MW (Based on a maximum co-firing ca-
capacity and technological development until pacity of 20% for all existing coal-fired and gas-
2020
fired electricity plants, and a maximum of
3200MW new standalone capacity of (B)IG/CC
plants.)
Max. environmental sustainable potential Minimal emissions, high efficiency.
‘Best guess’ 750 MW
Range found in scenario studies for 2020 329 – 2270 MW
2050
No estimations for the year 2050 are found in the used literature. In the ECN report an estimation is
made for the global biomass potential: 100-1250 EJ/year. There are many factors to estimate to which
extend the Netherlands can participate to this potential. The most important factor is the demand of
biomass from other countries (Noord, de et al., 2004).
15

3 VARIABILITY
The produced electricity from wind turbines and solar panels is different every hour. This is because
the wind speeds and sunshine vary on a location. The amount of wind and solar power capacity is
growing in the Netherlands, which means that the variability of these sources will have a bigger impact
on the Dutch electricity grid. The produced electricity from biomass is not directly dependent on
weather conditions and is controllable (McKinney et al., 2007).
3.1 Wind energy
The variability of wind power production is measured by hourly wind speed data from different locations.
In the study of (Wijk, van et al., 1990), eleven meteorological stations were selected. Hourly
wind speed data at a height of 10m is used from each station from 1971 to 1980 to model the hourly
wind power production. To scale the wind speed with height, (Wijk, van et al., 1990) used the Monin-
Obukhov similarity theory, which takes into account the roughness length and stability effects. These
wind speed data are combined with the power curves for the wind turbines, to calculate the hourly
wind power produced by 1000 MW wind turbine capacity in the Netherlands. Figure 7 shows the
hourly wind power produced by 1000 MW installed capacity of onshore wind turbines for a typical
January. In this figure, the wind power fluctuates from almost 0 to over 80% of the installed capacity
in a few days.
Figure 7 - Hourly wind power produced by 1000 MW wind turbine capacity for a typical January (Wijk,
van et al., 1990)
With this hourly wind speed data for a perdiod of ten years, the mean capacity factor is determined to
be 22% (the annual capacity factor varies from 19% to 26%). This indicates the electricity production
over a certain period of time, divided by the nominal wind turbine capacity, times the number of hours
in that period. The mean capacity factor reaches its minimum in the summer period (15%) and his
maximum in the months of November and December (30%). In the ten year period the wind power
production never have varied by more than 40% of the nominal wind turbine capacity. Four times in
this period, the variations reached 30% to 40% of nominal wind turbine capacity (Wijk, van et al.,
1990). This pattern will be used for the simulation of the Dutch future electricity mix in the simulation
program PowerPlan. For onshore wind power, the pattern is modified to a capacity factor of 25% over
a year. For offshore wind power, the pattern is modified to a capacity factor of 45% over a year.
17

3.2 Solar photovoltaic
The hourly pattern for solar PV is provided by Dr. R.M.J. Benders of the faculty of Mathematics and
Natural Sciences at the University of Groningen. The electricity power from solar PV is dependent on
sunshine. There are peaks during the day and during the night the electricity production is zero. This
figure also shows that the solar radiation differs every day. The peaks are higher at clear days and
lower at cloudy days. Figure 8 shows the electricity production of every month in a year. The electricity
production is the highest in the summer and the lowest in the winter, due to the position of the
earth surface to the sun. The used capacity factor in this study for solar PV is 16%.
Figure 8 - Monthly electricity production of 1000 MW installed photovoltaic panels
3.3 Demand
The hourly pattern for electricity demand used in this study is also provided by Dr. R.M.J. Benders of
the faculty of Mathematics and Natural Sciences at the University of Groningen. The used pattern is
based on the year 2009. The electricity demand in the Netherland is not the same over time, because
appliances connected to the grid are switched on or off at different times of the day, week, month and
year. About half of the maximum demand, there is a continuous demand for electricity (Figure 10).
This is also called as the base load, which is caused by industries and appliances in the commercial
and residential sector during the night. Like refrigerators, freezers, standby televisions and appliances
with timers. Figure 9 shows peaks in the electricity demand in the morning and in the evening. The
difference between working days and weekend is also recognizable in the figure. (Benders, 1996)
18

Figure 9 – PowerPlan simulation of the hourly electricity demand in January 2050
Figure 10 shows the seasonal fluctuation over a year. The electricity demand is the highest in the winter
and the lowest in the summer holidays. The peak in the summer can be the result of the use of fans
and air conditioners (Hekkenberg et al., 2009).
Figure 10 – PowerPlan simulation of the demand pattern over the year 2050
19

4 FUTURE ELECTRICITY MIX
PowerPlan is used in this study to design scenarios of the installed power capacity of power plants till
2050. The target of the EU is used for the design of the future electricity mix, because of the lag of
clear targets to 2050 of the Dutch government. Figure 11 shows a scenario where the European target
of almost 100% electricity from renewable sources in 2050 is met. This scenario is called the 95% RS
scenario. The EU energy trends to 2030 provided by the European Commission are used for the electricity
mix till 2030 (European Commission, 2010). The period 2030-2050 is designed by estimated
assumptions to meet the European target.
Figure 11 - Installed power capacity of power plants in the 95% RS scenario till 2050.
The results of the electricity mix in 2050 in the 95% RS scenario are given in Table 7.
Table 7 - Electricity mix 95% RS scenario in 2050.
Power plant Generated Electricity Installed Power Capacity Installed Power Capacity
(TWh)
(MW)
(%)
Import 4.6 700 2%
Wind onshore 9.8 4720 13%
Wind offshore 59.2 14,350 40%
Sun PV 10.2 4090 12%
Nuclear 0.0 0 0%
CHP 5.4 979 3%
Distr. heating 6.9 1188 3%
Pub. waste 3.2 510 1%
Coal 0.0 0 0%
Biomass 22.0 3825 11%
Comb. cycle 5.0 1400 4%
Biogas 9.9 3705 10%
Oil/Gas 0.0 0 0%
Gas turbine 0.0 0 0%
Total 136.2 35,467 100%
21

The black line in Figure 11 is the demand curve and the red line is the required capacity to meet the
demand. The capacity demand in 2050 is 20,189 MW and the required capacity is 52,400 MW. The
required capacity increases faster in time than the demand, because the share of variable and limited
predictable solar and wind energy increases in the electricity mix. Electricity production from solar
and wind energy does not meet the electricity demand, because wind energy is dependent on weather
conditions and have lower capacity factors. In PowerPlan the patterns with time intervals of one hour
for wind energy production and electricity demand are used. These patterns are described in chapter 3.
Beside the 95% RS scenario, there are seven other scenarios simulated in PowerPlan:
• Business as Usual scenario (BaU);
• 95% RS + gas scenario: This is the same scenario as the 95% RS -scenario. The only difference
is the addition of combined cycle gas turbines (CCGT) to meet the required capacity.
• 35% Wind Offshore (35% WO): Compared to the 95% RS scenario 5% less Wind Offshore
and 5 % more CCGT in 2050.
• 30% Wind Offshore (30% WO): Compared to the 95% RS scenario 10% less Wind Offshore
and 10 % more CCGT in 2050.
• 25% Wind Offshore (25% WO): Compared to the 95% RS scenario 15% less Wind Offshore
and 15 % more CCGT in 2050.
• 20% Wind Offshore (20% WO): Compared to the 95% RS scenario 20% less Wind Offshore
and 20 % more CCGT in 2050.
• 15% Wind Offshore (20% WO): Compared to the 95% RS scenario 25% less Wind Offshore,
21 % more CCGT and 4% more coal in 2050.
Figure 12 shows the electricity mix in first year of the simulation, which is the same in every scenario,
and in 2050. The complete simulation figures and tables of the scenarios can be found in Appendix 1.
Figure 12 - Eight scenarios of the Dutch electricity mix in 2050. The starting year is 2008 and is the same
for every scenario.
PowerPlan generated the total electricity production and demand for every hour of the year (8760
hours in total). These sets of data are used in the GoldSim model, which will be presented in chapter
6. The gap between the installed capacity and required capacity in the 95% RS scenario can be dissolved
with the use of large scale energy storage systems.
22

5 LARGE SCALE ENERGY STORAGE
A literature study is done of different types of large scale energy storage systems. Table 8 gives an
overview of the results of the literature study.
Table 8 - Comparison of the energy storage systems
Energy storage
system
Storage
capacity
(MWh)
Discharge
time
(hours)
Efficiency
(%)
Technical
lifetime
(years)
Energy density
(kWh/m 3 )
Capital cost
(€-2010/kW) 1
PHS/Energy
Island
30,000+ 24+ 70-87 30-80 0.5 - 1.5 416 - 1387
CAES 10,000+ 24+ 70-89 20-40 3 - 6 277 – 555
Lead acid 40 8 65-90 5-15 50 - 80 208 – 416
NiCd 6.75 8 60-83 10-20 60 - 150 347 – 1040
NaS 245 8 75-92 5-15 150 - 250 693 – 2080
Litium-ion - 2+ 85-100 5-15 200 - 500 832 – 2773
VRB 30 10 75-85 10 16 - 33 416 – 1040
PSB 150 10 75 15 - 485 – 1733
ZnBr 20 10 75 10 30 - 60 485 – 1733
Hydrogen - 24+ 35 5-20 500 - 3000 6933+
Metal-Air

Table 9 - Ways to store 100 GWh, assuming the generators have an efficiency of 90% (MacKay, 2009).
Drop from upper Working volume re-
reservoir quired (million m 3 Example size of reservoir
) (area x depth)
500 m 80 2 km 2 x 40 m
500 m 80 4 km 2 x 20 m
200 m 200 5 km 2 x 40 m
200 m 200 10 km 2 x 20 m
100 m 400 10 km 2 x 40 m
100 m 400 20 km 2 x 20 m
Normally, PHS systems are built in mountainous
areas, but the Netherlands is a flat country without
mountainous areas. KEMA, Lievense and
Rudolf Das have developed a new “Energy Island”
concept with an energy storage system
located in the North Sea off the Dutch coast. It
consists of a ring of dikes enclosing a 50 meters
deep dredged reservoir and the size of the internal
reservoir will be 60 km 2 (Figure 13). The water
level of the reservoir will vary between -30 and -
40 m. Dependent on the water level the energy
storage system will have a maximum generation
capacity between 2 and 2.5 GW (16 modules with
Figure 13 - Impression of the Energy Island (Boer et al., 2007)
a maximum of around 160 MW) and the storage
capacity will be 30 GWh. To prevent seawater
leakage into the reservoir, thick layers of clay (around 40 m) are needed to resist the ground water
pressure and bentonite walls till a depth of 60 m should prevent seawater from aside. (Boer et al.,
2007).
Discharge time
PHS systems can produce electricity for 1 hour to more than 24 hours (Beaudin et al., 2010; Chen et
al., 2009). The Energy Island can produce electricity for 12 hours at maximum capacity.
Efficiency
The cycle efficiency of a PHS is 70% to 87%, including the conversion and evaporation losses
(Beaudin et al., 2010; Chen et al., 2009; Hadjipaschalis et al., 2009). The cycle efficiency of an energy
island is 81%.
Lifetime
The lifetime of a PHS lies between 30 to 60 years (Beaudin et al., 2010; Chen et al., 2009; Denholm
& Kulcinski, 2004). The lead time of a PHS is around 10 years (Chen et al., 2009). The lifetime of an
Energy Island is around 80 years.
Space
For a PHS a specific site is needed for two large reservoirs at different heights (see
Table 9). The drawbacks of this requirement are the scarce availability of sufficient sites and often a
large amount of trees and vegetation has to be removed (Chen et al., 2009). This is different for the
case of the Energy Island which is located in the middle of the North Sea.
24

5.2 Compressed Air Energy Storage
A conventional natural gas power plant uses nearly two-thirds of the available power to compress the
combustion air. In a natural gas power plant with a Compressed Air Energy Storage (CAES), air is
compressed by the use of electrical power during off-peak hours and expanded in a combustion
chamber before it goes into the turbines (Chen et al., 2009). In a more advanced CAES the heat energy
is extracted and stored separately before the compressed air enters the cavern. The stored heat energy
and the compressed air are combined together and expanded through an air turbine when electricity
is needed (Figure 14).
Figure 14 - Schematic overview of a compressed air energy storage (Bullough et al., 2004).
Storage capacity
Currently there are two CAES plants in the world. The first CAES plant is in Huntorf, Germany, operating
since 1978 with a capacity of 290 MW for 2 hours (580 MWh). The second CAES plant is in
McIntosch, Alabama, USA operating since 1991 with a capacity of 110 MW for 26 hours (2.86
GWh). There are several CAES plants under construction or being planned over the world with power
capacities from 200 MW to 9 x 300 MW (Beaudin et al., 2010; Chen et al., 2009; Schoenung et al.,
1996). In Iowa, USA, a CAES will be built with a capacity of 269 MW for 50 hours (13.4 GWh)
(Beaudin et al., 2010).
Discharge time
Like the PHS, also a CAES can produce electricity for 1 hour to more than 24 hours (Beaudin et al.,
2010; Chen et al., 2009).
Efficiency
The cycle efficiency of a CAES is in the range of 70% to 89% (Beaudin et al., 2010; Chen et al.,
2009).
Lifetime
A CAES is able to operate for 20 to 40 years (Chen et al., 2009; Kaldellis et al., 2009).
Space
Similar to the PHS, a CAES is reliable to geographical conditions. There are different types of CAES
reservoirs. The best options are large caverns made of high-quality rock deep in the ground, underground
natural gas storage caves or ancient salt mines (Ibrahim et al., 2008).
The CAES in Germany has a cavern of approximately 310,000 m 3 , located around 600 m underground.
The CAES in the USA has a cavern of approximately 500,000 m 3 , located around 450 m
underground. (Beaudin et al., 2010; Chen et al., 2009)
25

There are three areas in the Netherlands with salt caverns today (Figure 15). In the future
these caverns can be used for CAES. Some of these caverns are already used for natural gas storage. It
is not known how many salt caverns there will be available for CAES in the future.
Figure 15 – Salt cavern locations in the Netherlands on January 1 st , 2011 (TNO, 2011)
5.3 Flow Battery Energy Storage (FBES)
The energy in a flow battery is stored and released by means of a reversible electrochemical reaction
between two liquid electrolyte solutions. The energy is externally stored in the electrolyte solutions in
reservoirs (Figure 16). In one cell of a flow battery, there are two compartments, one for each electrolyte,
separated by an ion-exchange membrane. The electrolyte is pumped through the power cell
where the electrochemical reaction takes place. One electrolyte is oxidized and the other is reduced to
produce current to an external circuit. Flow batteries are also known as redox (reduction-oxidation)
flow batteries. The main difference of flow batteries compared to the other batteries is that power and
energy ratings are independent from each other. The power rating is determined by the active area of
the cell stack and energy storage capacity is determined by the quantity of the electrolyte. Currently
there are three different electrolytes which are most applicable for large scale energy storage: Vanadium
redox (VRB), Polysulphide bromide (PSB) and Zinc bromine (ZnBr). (Baker, 2008; Chen et al.,
2009; Denholm & Kulcinski, 2004; Divya & Østergaard, 2009; Kaldellis et al., 2009; Nourai, 2002)
5.3.1 Vanadium redox (VRB)
Vanadium redox couples are employed to store energy in this kind of battery. V 2+ /V 3+ in the anode
reservoir and V 4+ /V 5+ in the cathode reservoir, both dissolved in mild sulphuric acid solution which is
26

the electrolyte. H + ions are exchanged between the two electrolyte reservoirs through the hydrogenion
permeable polymer membrane during the cycles of charging and discharging. (Beaudin et al.,
2010; Chen et al., 2009; Divya & Østergaard, 2009; Nourai, 2002)
Figure 16 - Schematic overview of a flow battery (Baker, 2008).
5.3.2 Polysulphide bromide (PSB)
This kind of battery is also known as Regeneyses. PSB provides its reversible electrochemical reaction
between two salt solution electrolytes of sodium bromide and sodium polysulphide. The polymer
membrane that separates the two electrolytes only allows the exchange of sodium ions between the
two electrolytes. (Chen et al., 2009; Divya & Østergaard, 2009; Nourai, 2002)
5.3.3 Zinc bromine (ZnBr)
In two compartments separated by a micro porous polyolefin membrane, two different electrolytes
flow past electrodes of carbon-plastic composite. During discharge, Zn and Br combine into zinc
bromide what will increase the Zn 2+ and Br - ion density in both electrolyte reservoirs. During charge,
on one side of the carbon-plastic composite electrode metallic zinc will be deposited as a thin film and
on the other side of the membrane bromine evolves as a dilute solution reacting with other agents to
make bromine oil. This oil sinks down to the bottom of the reservoir to a separate part of it. It is allowed
to mix it with the rest of the electrolyte during discharge only. (Chen et al., 2009; Divya &
Østergaard, 2009; Nourai, 2002)
Storage capacity
The largest FBES is a PSB battery in the UK, which has a storage capacity of 120 MWh (Divya &
Østergaard, 2009). The largest ZnBr battery and the largest VRB battery have a storage capacity of 4
MWh and 1.5 MWh respectively (Divya & Østergaard, 2009). The main advantage of a FBES is that
the storage capacity is only dependent on the amount of electrolytes (Divya & Østergaard, 2009). To
increase the storage capacity of a FBES, only larger reservoirs will be required.
Discharge time
The maximum discharge time of the three FBES systems is around 10-12 hours (Beaudin et al., 2010;
Chen et al., 2009).
Efficiency
The VRB has the best cycle efficiency of 75-85% and PSB and ZnBr batteries have both a cycle efficiency
of around 75% (Beaudin et al., 2010; Divya & Østergaard, 2009).
Lifetime
VRB and ZRB are able to operate for 10 years and PSB for 15 years (Chen et al., 2009).
Space
27

ZnBr has an energy density of 30-60 kWh/m 3 (Chen et al., 2009). The energy density of VRB is 16-33
kWh/m3 and will require 9-18.7 million m 3 of space (Chen et al., 2009). There is no literature found
about the energy density of PSB.
28

6 GOLDSIM MODEL
This chapter describes the design of the model, how it works and which data is used for the input.
At the start of the model (Figure 17) the hourly electricity production and electricity demand from
PowerPlan are used to calculate the power difference for every hour of the year 2050. As mentioned
in chapter 0, the electricity demand is the same in every scenario. Only the electricity production is
different in every PowerPlan scenario. From the power difference, the electricity surplus (overproduction)
and the electricity shortage for every hour is taken. Dependent on the available storage room, the
electricity surplus will be fully or partial stored in the energy storage systems (ESS). When the electricity
surplus is higher than the available storage capacity in the ESS, there will be a net electricity
surplus. This works the same for the electricity shortage. When the electricity shortage is higher than
the amount of electricity stored in the ESS, there will be a net electricity shortage. To have a reliable
electricity grid, the net electricity shortage has to be zero. Both net electricity surplus and shortage are
put together in the net power difference.
Hourly_Demand_Power
Hourly_Electricity_Production
Figure 17 - Basis of the model in GoldSim
There are five different kinds of ESS included in the model (Figure 18, see also chapter 5): Pumped
Hydro Storage (PHS), Compressed Air Energy Storage (CAES), PolySulphide Bromide battery
(PSB), Vanadium Redox Battery (VRB) and Zinc Bromine battery (ZnBr). The ESS are checked one
by one if they can store the electricity surplus or can supply the electricity shortage. PHS is checked
first for storing or supplying electricity. If there is still a surplus or a shortage then CAES is checked.
ZnBr is the last storage system to be checked.
X
ESS_Input
X
ESS_Output
PHS
PHS
Power_Difference
X
PHS_Surplus
X
PHS_Shortage
CAES
CAES
Figure 18 - Zoom in the model of the energy storage systems
X
Electricity_Surplus
X
Electricity_Shortage
X
CAES_Surplus
X
CAES_Shortage
PSB
PSB
ESS
ESS
X
PSB_Surplus
X
PSB_Shortage
VRB
VRB
X
Net_Electricity_Surplus
X
Net_Electricity_Shortage
X
VRB_Surplus
X
VRB_Shortage
ZnBr
ZBR
Net_Power_Difference
X
ZBR_Surplus
X
ZBR_Shortage
29

The modeling of every ESS is set up as in Figure 19. The input elements for the characteristics of the
storage system can be found in the top of the model, including:
30
• Power Capacity (MW);
• Energy Capacity (MWh);
• Efficiency (%);
• CO2e emissions during operation per
MWh-output;
• CO2e emissions during construction
per MWh installed;
The used data of the characteristics of the ESS can be found in Table 10.
• Energy density (m3/kWh);
• Storage height (to calculate the storage
area);
• Economic Lifetime (years);
• Costs per kW installed;
• Interest rate (%).
The reservoir of the storage system is in the middle of the model (PHS_Storage). The input calculations
are on the left of the reservoir and the output on the right. If there is an electricity surplus, then
the input function (PHS_Input, Equation 1) checks if there is enough storage capacity in the reservoir.
The possible remaining surplus is the net surplus of the storage system (PHS_Net_Surplus) and goes
to the next storage system as illustrated in Figure 18.
PHS_Input:
if PHS_Storage < PHS_Energy_Capacity,
then if ESS_Input < PHS_Energy_Capacity - PHS_Storage
else 0MW
then if ESS_Input < PHS_Power_Capacity
then ESS_Input
else PHS_Power_Capacity
else if PHS_Energy_Capacity - PHS_Storage < PHS_Power_Capacity
then PHS_Energy_Capacity - PHS_Storage
else PHS_Power_Capacity
Equation 1 - If-then-else formula of the PHS_Input function
When there is an electricity shortage, the withdrawal function (PHS_Withdrawal, Equation 2)
checks if there is enough energy stored in the reservoir. In this function the efficiency of the storage
system is included.
The output function (PHS_Output) is the actual delivered electricity. More energy is extracted
from the reservoir than it actually delivers, because of the efficiency. The possible remaining electricity
shortage is the net shortage of the storage system (PHS_Net_Shortage) and goes to the next storage
system as illustrated in Figure 18. The volume of the storage system is calculated by the energy density
(PHS_m3_kWh) multiplied by the size of the reservoir. When there is a determined height, the
used area (PHS_Area) of the storage system can be determined. The emissions during operation
(PHS_CO2e_variable) are the multiplication of the emissions per MWh and output. The emissions
during construction (PHS_CO2e_construction) are the multiplication of the emissions per MWh installed
and energy capacity.

PHS_Withdrawal:
if ESS_Output > 0MW
then if ESS_Output > PHS_Storage
else 0MW
then if PHS_Storage > PHS_Power_Capacity / PHS_Efficiency
then PHS_Power_Capacity / PHS_Efficiency
else PHS_Storage
else if ESS_Output / PHS_Efficiency > PHS_Storage
then if PHS_Storage > PHS_Power_Capacity / PHS_Efficiency
then PHS_Power_Capacity / PHS_Efficiency
else PHS_Storage
else if ESS_Output > PHS_Power_Capacity
then PHS_Power_Capacity / PHS_Efficiency
else ESS_Output / PHS_Efficiency
Equation 2 - If-then-else formula of the PHS_Withdrawal function
PHS Data Input
3.14
16
PHS_height
X
PHS_Area
3.14
16
PHS_m3_kWh PHS_const_CO2e_MWh
X
PHS_Volume
3.14
16
X
PHS_CO2e_construction
X
PHS_Net_Surplus
3.14
16
PHS_Energy_Capacity
X
PHS_Input
3.14
16
PHS_Power_Capacity
PHS_Storage
Figure 19 - Zoom in the model of the Pumped Hydro Storage (Energy Island). A larger image of this figure
can be found in Appendix 3.
3.14
16
PHS_Efficiency
X
PHS_Withdrawal
3.14
16
PHS_var_CO2e_MWh
X
PHS_CO2e_variable
3.14
16
PHS_Cost_kW PHS_Economic_LifeTime PHS_interest_rate
X
PHS_Output
3.14
16
X
PHS_Capital_Cost_PowCap
PHS_Tot_En_Prod_accumulator
X
3.14
16
PHS_Net_Shortage
X
PHS_annuity_factor
X
PHS_Capital_Cost
X
PHS_Cost_kWh
PHS_Total_Energy_Production
31

The annual costs of the ESS are based on the fixed capital costs. In Equation 3, the annual capital
costs are calculated:
32
Equation 3
Where: ACi = Annual costs for ESS i (€) (PHS_Capital_Cost)
a = the annuity factor: r/[1 - (1 + r) -L ] (PHS_annuity_factor)
ICi = Investment Costs for ESS i (€/kW) (PHS_Cost_kW)
PC = Plant Capacity (kW) (PHS_Power_Capacity)
r = interest rate (PHS_interest_rate)
L = economic Life-time for ESS i (PHS_Economic_LifeTime)
In Equation 4, the costs per generated kWh are calculated for all the energy storage systems and power
plants together:
Where: ECT = Total Electricity Costs of all ESS and power plants (€/kWh)
ACT = Total Annual costs for all ESS and power plants (€)
EGT = Total Electricity Generated per year for all ESS and power plants (kWh)
Equation 4
Table 10 - Characteristics of the energy storage systems used in the GoldSim model. The values are for
one ESS unit.
PHS
CAES
PSB VRB ZnBr
(Energy Island) In salt caverns
Power capacity (MW) 2500 3
300 2
15 2
3 2
2 2
Energy capacity 30,000
(MWh)
3
7,200 2
150
(300 MW x 24 hr)
2
30 2
20 2
Efficiency (%) 81 3
89 2
75 2
85 2
75 2
m3/kWh 20 3
1/6 2
0.024 5
0.030 2
0.017 2
m2/kWh 2 3
- - - -
Height (m) 10 3
- - - -
CO2e/MWh storage
capacity (construction)
35.7 tonnes 4
19.4 tonnes 4
125.3 4
161.4 4
143 6
CO2e/GWh (during
operation)
1.8 tonnes 4
3 tonnes 4
4 4
3.3 4
3.7 6
€/kW installed 1511 3 416 1,2 1109 1,2 728 1,2 1109 1,2
Interest rate 7% 7% 7% 7% 7%
Economic Lifetime 30 20 10 5 5
1
= Converted from US dollars to Euro (www.ecb.int): (2008: €1 = $1.47) and from Euro(2008) to
Euro(2010): +1.909% (epp.eurostat.ec.europa.eu)
2
= (Chen et al., 2009). For €/kW installed: the middle of the range token.
3
= (Boer et al., 2007)
4
= (Denholm & Kulcinski, 2004)
5
= No data found. The assumption is the middle between the values of VRB and ZnBr.
6
= No data found. The assumption is the middle between the values of PSB and VRB.

7 GOLDSIM RESULTS
The results of the calculations from the model are presented in this chapter. First, the results of the
storage demand are described. Secondly, the results of the technical reliable, practical and economical
scenarios are presented.
7.1 Storage demand
The graph in Figure 20 shows how much cumulative hourly electricity surplus and electricity shortage
occurs at different amounts of energy storage capacity on the electricity grid in the 95% RS scenario
for the year 2050. The model ran 22 times with increasing steps of 50 GWh energy storage capacities
from 0 GWh to 1,200 GWh. The average efficiency of the storage systems for this graph is set to
81%. The power capacity (in GW) of the storage systems was set to unlimited, to know the maximum
demand of the power capacity.
Total electricity shortage and surplus (TWh)
12
10
8
6
4
2
0
0
95% RS Scenario 2050
50
100
150
200
250
300
350
400
450
500
550
600
650
700
750
800
850
900
950
1.000
1.050
1.100
1.150
1.200
Energy storage capacity (GWh)
Total surplus Total shortage Input power capacity Output power capacity
Figure 20 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
95% RS scenario and the input and output power capacity demand.
When there is no storage system installed, the total electricity shortage over 2050 is 6.4 TWh and the
total electricity surplus is 10 TWh. To dissolve all the electricity shortage 1.2 TWh of storage capacity
is needed. It would get more and more difficult to dissolve the whole electricity shortage. To dissolve
50% of the electricity shortage, an energy storage capacity of 150 GWh is needed. There is 1,050
GWh more energy capacity needed to dissolve the last 50% of the electricity shortage.
In the 35% wind offshore scenario, 950 GWh of storage capacity would be needed. In the 30% wind
offshore scenario, 700 GWh. In the 25% wind offshore scenario, 650 GWh. In the 20% wind offshore
scenario, 400 GWh and in the 15% wind offshore scenario, 100 GWh. The graph of the storage demand
of these scenarios are presented in Appendix 4.
The input and output power capacity that is needed is also shown in Figure 20. The needed input
power capacity is 10.3 GW. The needed output power capacity is 8.5 GW. The reason for the lower
power capacities at lower energy storage capacities is that the storage systems with this energy
12
10
8
6
4
2
0
Input and output power capacity (GW)
33

capacities will not be charging or dischargin at the hours when there is a higher electricty production
or demand, because the storage systems are already full or empty by then.
7.2 Scenarios
The technical reliable scenarios are scenarios with enough energy storage systems to have no electricity
shortage over the whole year 2050. The practical scenario is a scenario with more practical
amounts of energy storage systems. The costs of different scenarios are presented in the economical
scenarios. In Appendix 5, a list of more simulated scenarios are listed with their results.
7.2.1 Technical reliable scenarios
To have a technical reliable electricity grid in the Netherlands, the total electricity shortage over the
whole year has to be zero. To achieve this 40 energy islands, 140 CAES’s or 10,000 PSB’s are needed
(Table 11).
Table 11 - Technical reliable scenarios for the Dutch electricity grid in 2050
ESS Scenar- Power Capaci- Energy capacity Total sur- Total Size
ioty
(MW) (GWh)
plus shortage
No Storage 0 0 9,954,152 6,357,505 -
40 Energy
100,000 1,200 1,983,109 - 2,400 km
Islands
2 in the
North Sea
140 CAES's 42,000 1,008 2,687,477 - 140 Salt Caverns
10,000
150,000 1,500 1,291,662 - 7.2 km
PSB's
2 with 5m
height
For 40 energy islands a total area of 2,400 km 2 is needed in the North Sea. In comparison: the IJselmeer
and Markermeer cover an area of 1,800 km 2 together. For 140 CAES units, 140 salt caverns,
with a volume of 1.2 million m 3 each, will be needed. At this moment there are only 2 CAES units
operating in the world. A total land area of 7.2 km 2 with 5 meters of height is needed for 10,000 PSB
units. 10,000 PSB’s requires 250 times smaller area than 40 Energy Islands to have no electricity
shortage in the Dutch electricity grid.
7.2.2 Practical scenario
The technical reliable scenarios can be considered as not practical, due to the available locations of
the energy storage systems. A more practical scenario would be two energy islands (5000 MW, 60
GWh), 20 CAES (6000 MW, 144 GWh) and 100 of each FBES (2000 MW/ 20 GWh). The total capacity
of this scenario is 13,000 MW and 224 GWh. Figure 21 shows the hourly pattern of the electricity
production, electricity demand (which is inverted in the graph), power difference (without
storage) and net power difference (with storage) over the year 2050 in the 95% RS scenario with 2
Energy Islands, 20 CAES, 100 PSB, 100 VRB and 100 ZnBr. Beneath the purple line of the net power
difference is also the green line of the power difference. For a technical reliable electricity grid there
should be no purple line under the horizontal axis in the figure, because this represents the electricity
shortage. There are some periods in the practical scenario with electrcity shortage.
34

Figure 21 - Hourly pattern of the electricity production, electricity demand (inverted), power difference
and net power difference over the year 2050 in the 95% RS scenario with 2 Energy Islands, 20 CAES, 100
PSB, 100 VRB and 100 ZnBr.
Weeks 6 to 8 of the practical scenario is one of the periods with an electricity shortage, caused by the
lag of wind energy (Figure 22). In this period there is an electricity shortage of seven days. There is an
electricity net surplus in the first four days. This means that there is an electricity surplus and that the
energy storage systems are full. Then there is a period of three days (day 39 to 42) with electricity
shortage. During these days, the storage systems are able to supply enough electricity. After these
three days, the storage systems are empty and cannot supply electricity to the electricity grid. From
day 51 there is a period of electricity surplus and the storage systems are able to charge again.
Electricity (GW)
25
20
15
10
5
0
-5
-10
35
Weeks 6-8
95% RS scenario with 2 Energy Islands + 20 CAES's + 100 PSB's + 100 VRB's + 100 ZnBr's
36
37
38
39
40
41
42
43
Figure 22 - Weeks 6 to 8 of the practical scenario.
44
45
46
Day
Production Demand Power Difference Net Power Difference
47
48
49
50
51
52
53
54
55
56
35

Weeks 10 to 13 is a period of four weeks in the practical scenario when there is no electricity
shortage. The energy storage systems have enough capacity to supply electricity to the electricity grid.
Figure 23 - Weeks 10 to 13 in the practical scenario
Weeks 37 to 40 is also a period with eleven days of electricity shortage in the practical scenario.
Figure 24 - Weeks 37 to 40 in the practical scenario
36
Electricity (GW)
Electricity (GW)
25
20
15
10
5
0
-5
-10
25
20
15
10
5
0
-5
-10
Weeks 10-13
95% RS scenario with 2 Energy Islands + 20 CAES's + 100 PSB's + 100 VRB's + 100 ZnBr's
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
Day
Production Demand Power Difference Net Power Difference
Weeks 37-40
95% RS scenario with 2 Energy Islands + 20 CAES's + 100 PSB's + 100 VRB's + 100 ZnBr's
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
Day
Production Demand Power Difference Net Power Difference

7.2.3 Economic scenario
Table 12 shows the total annual costs of every scenario made in PowerPlan. These costs include the
annual depreciation, the fuel costs and the operation and maintenance costs. The storage costs are not
included.
Table 12 – Total annual costs and the costs per generated kWh of the PowerPlan scenarios
Scenario Total Annual Costs (€-
2010)
Costs (€-2010/kWh)
BaU € 13,852,917,400 € 0.1043
95% RS +gas € 19,041,912,000 € 0.1329
95% RS € 19,656,113,100 € 0.1443
35WO € 20,881,098,000 € 0.1554
30WO € 20,968,561,900 € 0.1573
25WO € 21,121,161,400 € 0.1591
20WO € 21,243,376,000 € 0.1604
15WO € 20,858,451,900 € 0.1573
The BaU scenario is the cheapest scenario. This is because of the higher capital cost of the renewable
sources in the other scenarios than the capital costs of the conventional power plants in the BaU scenario.
An overview of the total annual costs in the 95% RS scenario + the annual costs for different installed
energy storage systems is shown in Table 13.
Table 13 - Overview of the total annual costs of the power plants + the energy storage systems in the 95%
RS scenario
Storage Systems Storage Power Storage Energy Total Annual Total Costs
Capacity (GW) Capacity (GWh) Cost (€-2010) (€-2010/kWh)
No Storage 0 0 € 19,656,113,100 € 0.1443
2 Energy Islands 5 60 € 20,264,943,379 € 0.1471
20 CAES 6 144 € 19,891,717,843 € 0.1428
100 PSB +100 VRB +100 ZnBr 2 20 € 20,000,318,760 € 0.1464
2 Energy Islands + 20 CAES +
13 224 € 20,893,911,487 € 0.1495
100 PSB +100 VRB +100 ZnBr
2 Energy Islands + 20 CAES 11 204 € 20,500,548,121 € 0.1468
1 Energy Island + 20 CAES 8.5 174 € 20,196,132,982 € 0.1449
40 Energy Islands 100 1,200 € 31,832,718,670 € 0.2233
140 CAES 42 1,008 € 21,305,346,299 € 0.1494
10,000 PSB 150 1,500 € 43,340,610,680 € 0.3040
In Chapter 6, the calculations for the total annual costs of the energy storage systems are described. In
the fourth column of Table 13, the total annual cost are given. This is the annual costs of the power
plants in the 95% RS scenario plus the annual costs of the energy storage systems. In the fifth column
the results for the total costs per kWh are given. This is calculated by formula given in Equation 4.
The total installed capacity costs of the power plants and storage systems together are divided by the
total electricity production of the power plants an energy storage systems together.
37

8 CONCLUSION, DISCUSSION AND FURTHER RESEARCH
In this chapter, an answer will be given on the main research question. After the conclusion, the constraints
of the research will be discussed and some recommendations for further research are given.
8.1 Conclusion
The main research question in this research is:
To which extend can be the role of large scale energy storage systems in the Dutch electricity grid to
intercept the mismatch between the electricity demand and the electricity production from renewable
sources to meet the European targets in 2050?
Some steps are made to give an answer to this question. First a literature research is done to
the potential renewable sources in the Dutch electricity grid in 2050. The renewable sources with the
highest potential in the Netherlands are wind onshore, wind offshore, solar photovoltaic and biomass.
Then, a literature research is done to the variability of these renewable sources. Wind and solar energy
is directly dependent on the weather conditions and by this very variable and changes every hour.
Electricity from biomass is not directly dependent on the weather conditions, because it is first converted
into a useful form and works about the same as a coal or a gas power plant. Data patterns of the
wind electricity production and electricity demand with time intervals of 1 hour over a whole year are
used in the simulation program PowerPlan.
PowerPlan is used to simulate a scenario of the Dutch electricity mix till 2050, where the European
target of almost 100% electricity from renewable sources is met. This scenario shows that the
installed capacity does not meet the required capacity, because of the low capacity factors of wind and
solar energy. With PowerPlan, hourly patterns of the total electricity production and electricity demand
are generated for the year 2050. These patterns are used in the model made with GoldSim. In
this model, five energy storage systems are included which are considered as the best suitable storage
system for large scale use from a literature study. These are: an energy island (inverted pumped hydro
storage on the North Sea), Compressed Air Energy Storage (CAES) and three kinds of Flow Battery
Energy Storage (FBES).
With the model in GoldSim, the total electricity shortage, the total electricity surplus, the
energy storage capacity and storage power capacity over 2050 is determined. The total electricity
shortage over 2050 is 6.4 TWh and the total electricity surplus is 10 TWh. To dissolve 6.4 TWh electricity
shortage, an energy capacity of 1.2 TWh from the storage systems is needed. The needed power
capacity of the storage systems is 10.3GW for charging and 8.5 GW for discharging.
To dissolve 50% of the electricity shortage, the energy storage systems need an energy capacity
of 150 GWh. To dissolve all the electricity shortage, the energy storage systems would need an
energy capacity of 1,200 GWh. There is 1,050 GWh more energy capacity needed to dissolve the last
50% of the electricity shortage.
To have a technical reliable Dutch electricity grid in 2050, 40 Energy Islands, 140 CAES systems
or 10,000 PSB systems are needed. These scenarios are not very practical, because in the case of
40 Energy Islands, a total area of 2,400 km 2 would be needed in the North Sea. For 140 CAES systems,
140 depleted salt caverns are needed.
The Business as Usual scenario is the most economical attractive scenario of the different
electricity mixes, but the European target is not met in this scenario. This is the same for the 95% RS
+ gas scenario, which is second cheapest scenario.
CAES is the cheapest energy storage system to use. This is because of the use of salt caverns
which already exist. FBES systems are the most expensive storage systems to use. The main reason
for this is the shorter life time of these FBES, which is 5 to 15 years. In the 95% RS scenario, the
technical reliable and practical scenarios are not economical attractive. Except for 140 CAES systems
and the practical scenario without FBES systems. 140 CAES systems could be economical attractive,
but not practical. Probably, there will not be 140 salt caverns available for CAES. The scenarios without
FBES could be economical attractive, but is not technical reliable.
39

8.2 Discussion
These are points of discussion to the research.
8.2.1 Biomass
The main idea from the use of biomass is that the carbon cycle is much shorter compared to the use of
fossil fuels. But in reality forests are often harvested in an unsustainable way. When replacements are
not planted for all the burned biomass, the burning of biomass will still contribute to the increase of
global warming.
The use of energy crops has some other issues. One issue is the need of large areas of land
which could result in a decrease in food production. Also, energy crops are probably better for fuel
purposes for the transport sector instead for electricity generation.
Another problem with biomass is that there is not enough of it in the Netherlands. Biomass
has to be imported from countries with an overshoot of biomass. This results in the need for more
transport and land use in another country.
All these biomass issues are important for the results from this research, because it could
change the Dutch electricity mix as projected in chapter 4. This will result in different production
patterns. When the share of biomass is smaller, than the share of wind and solar should be larger.
8.2.2 Demand pattern
The demand pattern used in this research is based on the electricity demand patterns of today. Probably
this pattern will not be the same in the future. It could happen that people will use the electricity
more efficient. Also the increase of battery electric vehicles will have an influence on the electricity
demand, but it is uncertain how this will influence the demand pattern.
8.2.3 Wind pattern
The offshore and onshore wind patterns used in this research are base on a onshore wind pattern. The
weather conditions are different at sea and wind calms occurs lesser. The lulls in the offshore wind
pattern are probably not as low and long as in the onshore wind pattern
8.2.4 GoldSim model
In the GoldSim model, an arbitrary chosen order of energy storage systems is used. The energy storage
systems are charged and discharged one by one. The Energy Islands are charging first. When the
Energy Islands are full, then the CAES systems are charging, then the PSB systems followed by the
VRB and ZnBr systems. This works in the same way for discharging. There could be different results
from the model when there is no order in the storage systems and charged and discharged at the same
time. Also a different order can result in other results. These two alternatives are both not modeled
and tested, because of the time of the research. It is expected that this will have no influence on the
reliability of the systems to the electricity grid, but the costs per kWh could be higher or lower.
8.2.5 Practical scenario
The amount of energy storage systems in the practical scenario are arbitrary chosen. The practical
amount of energy storage systems is dependent on the available locations. A study to available locations
for energy storage systems is also recommended for further research in paragraph 8.3.
8.2.6 Costs
In the literature (Beaudin et al., 2010; Chen et al., 2009), the capital cost (€/kW) of the energy storage
systems are given in a very wide range. The capital costs for CAES is in the range of €277 to €555,
for VRB €416 to €1040 and PSB and ZnBr €485 to €1733. This range is wide, because these systems
are new technologies. In this study the average cost is used, but the total costs of the energy storage
systems can be much higher or lower.
The operation and maintenance costs (O&M), transmission and distribution costs (T&D), replacement
costs and disposal costs are not included in the capital costs. This will result in higher total
costs of the energy storage systems.
40

Another aspect which can have an influence in the costs, is the price of oil, gas and renewable
sources. In this research, the prices provided in PowerPlan are used. When the fossil fuel reserves get
more depleted and scarce, than the price of fossil fuels will increase. The renewable energy sources
can get more economical attractive by this event. The total costs in the Business as Usual scenario in
this research can be much higher and even get higher than the 95% RS scenario and other wind offshore
scenarios.
8.3 Final conclusion
Large scale energy storage systems in the Dutch electricity grid can technically intercept the mismatch
between the electricity demand and the electricity production from renewable sources for 100%
to meet the European targets in 2050, but this is not practical and not economical attractive.
With 150 GWh energy storage capacity in the 95% RS scenario, 50% of the electricity shortage
can be dissolved. An extra 1,050 GWh energy storage capacity would be needed to dissolve all
the electricity shortage.
Another economical and practical alternative is the 95% RS scenario + gas scenario. This is
the 95% RS scenario with the addition of combined cycle gas turbines to meet the required capacity.
But in this scenario the European target of almost 100% electricity from renewable source in 2050 is
not met.
It is recommended to the Netherlands that if they want to meet the European target, a scenario
as the 95% RS scenario as described in this study is needed. To intercept the mismatch between the
electricity supply and demand in the 95% RS scenario, it is recommended to install 150 GWh of energy
storage systems with a power capacity of 9 GW. In this case, 50% of the electricity shortage is
dissolved. This can be done by 1 Energy Island and 20 CAES systems. For the other 50% of the electricity
shortage (1,050 GWh), other alternatives are needed. For example with use of a European electricity
grid, where electricity from renewable sources or energy storage systems can be traded with
neighboring countries.
8.4 Further research
To have a better answer to the research question, the following recommendations are done for further
research.
8.4.1 PV pattern
The pattern for solar photovoltaic is not used in the PowerPlan modeling. In PowerPlan, Solar PV has
a share of 12% in the 95% RS scenario. This could change the hourly production pattern and power
difference, because of the hourly, daily and seasonal fluctuations of solar PV.
8.4.2 Offshore Wind pattern
The offshore wind pattern used in this study is based on the onshore wind pattern. Further research is
needed in collecting offshore wind speed data.
8.4.3 North Sea
One Energy Island requires an area of 60 km 2 of the North Sea with a 50 m deep dredged reservoir on
a 40 m thick layer of clay. A research would be needed to suitable locations for an Energy Island in
the North Sea.
8.4.4 Salt caverns
Further research would be needed to the amount of available salt caverns for CAES systems in the
Netherlands in the future.
8.4.5 Alternatives
A study to alternative options to cope with the electricity shortage in the 95% RS scenario is also recommended.
One of the alternatives is to work together with neighboring counties and other countries
in the EU. Connections with wind parks in countries like Scotland, Germany and Scotland. Solar PV
in countries like France, Spain and Italy.
41

LITERATURE
Baker, J. (2008). New technology and possible advances in energy storage. Energy Policy, 36(12),
4368-4373. doi:DOI: 10.1016/j.enpol.2008.09.040
Beaudin, M., Zareipour, H., Schellenberglabe, A., & Rosehart, W. (2010). Energy storage for mitigating
the variability of renewable electricity sources: An updated review. Energy for Sustainable
Development, 14(4), 302-314. doi:DOI: 10.1016/j.esd.2010.09.007
Benders, R. J. M. (1996). Interactive simulation of electricity demand and production. (Doctoral dissertation,
University of Groningen).
Bilgili, M., Yasar, A., & Simsek, E. (2011). Offshore wind power development in europe and its
comparison with onshore counterpart. Renewable and Sustainable Energy Reviews, 15(2),
905-915. doi:DOI: 10.1016/j.rser.2010.11.006
Boer, W. W. d., Verheij, F. J., Zwemmer, D., & Das, R. (2007). The energy island - an inverse pump
accumulation station. Unpublished manuscript.
BP. (2010). Statistical review of world energy 2010. Retrieved May 25, 2011, from
http://www.bp.com/liveassets/bp_internet/globalbp/globalbp_uk_english/reports_and_publicat
ions/statistical_energy_review_2008/STAGING/local_assets/2010_downloads/Statistical_Rev
iew_of_World_Energy_2010.xls
BP. (2011). BP energy outlook 2030. Retrieved May 25, 2011, from
http://www.bp.com/liveassets/bp_internet/globalbp/globalbp_uk_english/reports_and_publicat
ions/statistical_energy_review_2008/STAGING/local_assets/2010_downloads/BP-Energy-
Outlook-2030-summary-tables.xls
Bullough, C., Gatzen, C., Jakiel, C., Koller, M., Nowi, A., & Zunft, S. (2004). Advanced adiabatic
compressed air energy storage for the integration of wind energy. London.
Chen, H., Cong, T. N., Yang, W., Tan, C., Li, Y., & Ding, Y. (2009). Progress in electrical energy
storage system: A critical review. Progress in Natural Science, 19(3), 291-312. doi:DOI:
10.1016/j.pnsc.2008.07.014
Commission of the European Communities. (2004). The share of renewable energy in the EU - country
profiles - overview of renewable energy sources in the enlarged European Union.
Denholm, P., & Kulcinski, G. L. (2004). Life cycle energy requirements and greenhouse gas emissions
from large scale energy storage systems. Energy Conversion and Management, 45(13-
14), 2153-2172. doi:DOI: 10.1016/j.enconman.2003.10.014
Divya, K. C., & Østergaard, J. (2009). Battery energy storage technology for power systems—An
overview. Electric Power Systems Research, 79(4), 511-520. doi:DOI:
10.1016/j.epsr.2008.09.017
Donkers, J. A. J., Brand, A. J., & Eecen, P. J. (2011). Offshore wind atlas of the Dutch part of the
north sea. ECN.
Esteban, M. D., Diez, J. J., López, J. S., & Negro, V. (2011). Why offshore wind energy? Renewable
Energy, 36(2), 444-450. doi:DOI: 10.1016/j.renene.2010.07.009
43

European Commission. (2010). EU energy trends to 2030 — update 2009. Luxembourg: Publications
Office of the European Union. doi:10.2833/21664
European Commission. (2011). A roadmap for moving to a competitive low carbon economy in 2050.
Retrieved June 20, 2011, from
http://ec.europa.eu/clima/documentation/roadmap/docs/com_2011_112_en.pdf
EWEA. (2011). EU energy policy to 2050.
Hadjipaschalis, I., Poullikkas, A., & Efthimiou, V. (2009). Overview of current and future energy
storage technologies for electric power applications. Renewable and Sustainable Energy Reviews,
13(6-7), 1513-1522. doi:DOI: 10.1016/j.rser.2008.09.028
Hekkenberg, M., Benders, R. M. J., Moll, H. C., & Schoot Uiterkamp, A. J. M. (2009). Indications for
a changing electricity demand pattern: The temperature dependence of electricity demand in
the netherlands. Energy Policy, 37(4), 1542-1551. doi:10.1016/j.enpol.2008.12.030
Ibrahim, H., Ilinca, A., & Perron, J. (2008). Energy storage systems—Characteristics and comparisons.
Renewable and Sustainable Energy Reviews, 12(5), 1221-1250. doi:DOI:
10.1016/j.rser.2007.01.023
Junginger, M., Agterbosch, S., Faaij, A., & Turkenburg, W. (2004). Renewable electricity in the netherlands.
Energy Policy, 32(9), 1053-1073. doi:DOI: 10.1016/S0301-4215(03)00063-6
Kaldellis, J. K., Zafirakis, D., & Kavadias, K. (2009). Techno-economic comparison of energy storage
systems for island autonomous electrical networks. Renewable and Sustainable Energy Reviews,
13(2), 378-392. doi:DOI: 10.1016/j.rser.2007.11.002
KNMI. (2002). In Heijboer D., Nellestijn J. (Eds.), Klimaatatlas van nederland - de normaalperiode
1971-2000. Rijswijk: Uitgeverij Elmar B.V.
KNMI. (2011). Klimaatatlas - langjarige gemiddelden 1981-2010. Retrieved September 19, 2011,
from http://www.klimaatatlas.nl
MacKay, D. J. C. (2009). Fluctuations and storage. In Sustainable energy - without the hot air Cambridge:
UIT Cambridge Ltd.
McKinney, M. L., Schoch, R. M., & Yonavjak, L. (2007). Environmental science: System and solutions.
(4th ed.). Sudbury: Jones and Bartlett Publishers.
Ministerie van Economische Zaken, Landbouw & Innovatie. (2011). Energierapport 2011. Rijksoverheid,
NL Agency. (2010). Renewable energy monitoring protocol update 2010. ( No. 2DENB1014). Ministry
of Economic Affairs.
Noord, M. de, Beurkens, L.W.M., Vries, H.J. de,. (2004). Potentials and costs for renewable electricity
generation. ECN.
Nourai, A. (2002). Large-scale electricity storage technologies for energy management. Power Engineering
Society Summer Meeting, 2002 IEEE, , 1 310-315 vol.1.
44

Odenberger, M., & Johnsson, F. (2010). Pathways for the european electricity supply system to
2050—The role of CCS to meet stringent CO2 reduction targets. International Journal of
Greenhouse Gas Control, 4(2), 327-340. doi:DOI: 10.1016/j.ijggc.2009.09.005
OECD/IEA. (2011a). Electricity/Heat in netherlands in 2008. Retrieved May 30, 2011, from
http://www.iea.org/stats/electricitydata.asp?COUNTRY_CODE=NL
OECD/IEA. (2011b). Key world energy statistics. Paris: International Energy Agency (IEA).
Ribeiro, P. F., Johnson, B. K., Crow, M. L., Arsoy, A., & Liu, Y. (2001). Energy storage systems for
advanced power applications. Proceedings of the IEEE, 89(12), 1744-1756.
Schainker, R. B. (2004). Executive overview: Energy storage options for a sustainable energy future.
Power Engineering Society General Meeting, 2004. IEEE, 2309-2314 Vol.2.
Schoenung, S. M., Eyer, J. M., Iannucci, J. J., & Horgan, S. A. (1996). Energy Storage For A Competitive
Power Market. Annual Review of Energy and the Environment, 21(1), 347-370.
doi:10.1146/annurev.energy.21.1.347
TNO. (2011). Delftstoffen en aardwarmte in nederland - jaarverslag 2010. (Year report 2010). Den
Haag.
Ummels, B. C., Pelgrum, E., & Kling, W. L. (2008). Integration of large-scale wind power and use of
energy storage in the netherlands' electricity supply. Renewable Power Generation, IET, 2(1),
34-46.
Wijk, A. J. M. van, Coelingh, J. P., & Turkenburg, W. C. (1990). Modelling wind power production
in the netherlands. Wind Engineering, 14(2 , 1990), 122-140.
45

APPENDIX 1 – POWERPLAN SCENARIOS
Figure 25 - Business as Usual installed capacity till 2050
Table 14 - Electricity mix BaU scenario in 2050.
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 14%
Wind offshore 15.664 3800 11%
Sun PV 7.422 2973 9%
Nuclear 3.176 449 1%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 36.642 5200 15%
Biomass 11.550 1725 5%
Comb. cycle 28.245 10,525 30%
Biogas 0.211 1870 5%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 132.818 34,639 100%
47

Figure 26 - 95% RS + gas scenario installed capacity till 2050
Table 15 - Electricity mix 95% RS +gas scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 10%
Wind offshore 59.153 14,350 32%
Sun PV 10.211 4090 9%
Nuclear 0.000 0 0%
CHP 5.403 979 2%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 0.000 0 0%
Biomass 22.043 3825 8%
Comb. cycle 21.330 10,850 24%
Biogas 0.633 3705 8%
Oil/Gas 0.000 0 0%
Gasturbine 0.003 210 0%
Total 143.280 45,127 100%
48

Figure 27 - 35% wind offshore scenario installed capacity till 2050
Table 16 - Electricity mix 35% wind offshore scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 13%
Wind offshore 50.496 12,250 35%
Sun PV 10.211 4090 12%
Nuclear 0.000 0 0%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 0.000 0 0%
Biomass 23.328 3825 11%
Comb. cycle 12.245 3300 9%
Biogas 8.183 3705 11%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 134.370 35,267 100%
49

Figure 28 - 30% wind offshore scenario installed capacity till 2050
Table 17 - Electricity mix 30% wind offshore scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 13%
Wind offshore 43.076 10,450 30%
Sun PV 10.211 4090 12%
Nuclear 0.000 0 0%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 0.000 0 0%
Biomass 24.465 3825 11%
Comb. cycle 19.161 5000 14%
Biogas 6.483 3705 11%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 133.303 35,167 100%
50

Figure 29 - 25% wind offshore scenario installed capacity till 2050
Table 18 - Electricity mix 25% wind offshore scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 13%
Wind offshore 36.069 8750 25%
Sun PV 10.211 4090 12%
Nuclear 0.000 0 0%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 0.000 0 0%
Biomass 25.449 3825 11%
Comb. cycle 26.263 6700 19%
Biogas 4.855 3705 11%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 132.754 35,167 100%
51

Figure 30 - 20% wind offshore scenario installed capacity till 2050
Table 19 - Electricity mix 20% wind offshore scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 13%
Wind offshore 28.855 7000 20%
Sun PV 10.211 4090 12%
Nuclear 0.000 0 0%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 0.000 0 0%
Biomass 26.332 3825 11%
Comb. cycle 33.890 8450 24%
Biogas 3.246 3705 11%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 132.440 35,167 100%
52

Figure 31 - 15% wind offshore scenario installed capacity till 2050
Table 20 - Electricity mix 15% wind offshore scenario in 2050
Power plant
Generated Electricity
(TWh)
Installed Power Capacity
(MW)
Installed Power Capacity
(%)
Import 4.599 700 2%
Wind onshore 9.768 4720 13%
Wind offshore 21.641 5250 15%
Sun PV 10.211 4090 12%
Nuclear 0.000 0 0%
CHP 5.403 979 3%
Distr. heating 6.921 1188 3%
Pub. waste 3.217 510 1%
Coal 9.921 1400 4%
Biomass 26.460 3825 11%
Comb. cycle 32.715 8850 25%
Biogas 1.748 3705 11%
Oil/Gas 0.000 0 0%
Gasturbine 0.000 0 0%
Total 132.603 35,217 100%
53

APPENDIX 2 – OTHER ENERGY STORAGE TECHNOLOGIES
After the literature study, the following energy storage technologies are considered not to be suitable
for large scale use, but will be described shortly:
8.4.6 Hydrogen storage
In a hydrogen storage system, hydrogen and oxygen is produced from water by electrolyses. A hydrogen
fuel cell uses hydrogen and oxygen to produce water and electricity. Between these two processes
the hydrogen is stored (Beaudin et al., 2010). For large scale applications, the two most developed
storage technologies are the hydrogen pressurization and the hydrogen absorption in metal hydrides
(Hadjipaschalis et al., 2009). Simplest way to store the hydrogen is in pressurized tanks with a volume
anywhere between 0.01 and 10,000m 3 . It is possible to store the hydrogen at pressures up to 350 bars
(Ibrahim et al., 2008) and currently research is done to materials that are adequate for use at pressures
to 700 bars (Hadjipaschalis et al., 2009). The discharge time of hydrogen storage with pressurization
is dependent on the capacity of the fuel cell and can go up to more than 24 hours (Beaudin et al.,
2010). The electrolyzer has a cycle efficiency of 70% and the fuel cell 50%. So the hydrogen energy
storage has a cycle efficiency of around 35% (Ibrahim et al., 2008). This is the main disadvantage for
large scale use. The lifetime of a hydrogen energy storage lies between 5 and 20 years (Beaudin et al.,
2010; Kaldellis et al., 2009). The energy density of hydrogen storage is between 500 and 3,000
kWh/m 3 (Chen et al., 2009).
8.4.7 Lead acid Battery
In the charged state a lead acid battery consists of lead metal as anode electrode, lead oxide as cathode
electrode and sulphuric acid as the electrolyte. Both electrodes turn into lead sulphate and the electrolyte
loses its dissolved sulphuric acid and becomes primarily water in the discharged state. The reason
why the lead acid battery is not suitable for large scale applications is its short cycle life, low energy
density and poor low temperature performance. (Chen et al., 2009; Hadjipaschalis et al., 2009)
8.4.8 Nickel-cadmium (NiCd) Battery
A NiCd battery cell consists of cadmium hydroxide as anode electrode, nickel hydroxide as cathode
electrode and alkaline as electrolyte. The electrode plates are isolated from each other by a separator
and are rolled in a spiral shape inside a metal case. The disadvantages of NiCd batteries for large scale
use are: Cadmium is a toxic heavy metal, high cost and the memory effect (it will only take full
charge after a series of full discharges. (Chen et al., 2009)
8.4.9 Sodium-sulphur (NaS) Battery and ZEBRA (Na-NiCl2) Battery
A NaS battery cell consists of liquid sodium as anode electrode and liquid sulphur as cathode, separated
by a solid beta alumina ceramic electrolyte. A NaS battery operates at a temperature of 300-350
°C. Once the battery is running no external heat source is required, because the heat produced by
charging and discharging cycles is enough to maintain this temperature. The main disadvantage is that
the system uses its own stored energy as a heat source, what partially reduces the battery performance.
The difference between a ZEBRA battery and a NaS battery is that a ZEBRA battery uses nickel chloride
as cathode, but has a lower energy and power density. (Chen et al., 2009; Hadjipaschalis et al.,
2009).
8.4.10 Lithium-ion Battery
The anode of a lithium ion is made of graphite carbon with a layer structure, the cathode is a lithiated
metal oxide and the electrolyte is made up of lithium salts dissolved in organic carbonates. Lithiumion
are considered not suitable for large scale use, because of high cost short discharge time. (Chen et
al., 2009; Divya & Østergaard, 2009)
55

8.4.11 Metal-Air battery
A Metal-Air battery uses metal (like aluminum or zinc) as the fuel and air as the oxidant and can be
regarded as a special type of fuel cell. This type of storage is not sufficient for large scale energy storage,
because of the low efficiency and is difficult to be recharged. (Chen et al., 2009; Divya &
Østergaard, 2009)
8.4.12 Capacitor and supercapacitor
A capacitor consists of two metal plates separated by a molecule-thin layer of electrolyte as the dielectric.
Instead of a solid dielectric between the electrodes, a supercapacitor stores the energy by
means of an electrolyte solution between two solid conductors. The main disadvantage of this type of
storage is the low energy density. (Beaudin et al., 2010; Chen et al., 2009; Hadjipaschalis et al., 2009;
Ribeiro, Johnson, Crow, Arsoy, & Liu, 2001)
8.4.13 Flywheel energy storage
Flywheels store kinetic energy in the angular momentum of a spinning mass. The flywheel is operating
in a vacuum and the bearings are magnetic to reduce friction and heat losses. The low energy density,
high frictional loss, high self-discharge and short discharge time makes flywheel energy storage
not suitable for large scale application. (Chen et al., 2009; Ibrahim et al., 2008; Schainker, 2004)
8.4.14 Super conducting magnetic energy storage (SMES)
Superconducting magnetic energy storage (SMES) stores electrical energy in a magnetic field generated
by direct current flowing through a superconducting coil, which is often made of niobiumtitanium.
The inductor is immersed in liquid helium at 4.2 K or super fluid helium at 1.8 K contained
in a vacuum-insulated cryostat to maintain it in its superconducting state. SMES is not suitable for
large scale energy storage, because the discharge time of SMES is very short (in the range of seconds),
very high costs and environmental issues associated with strong magnetic fields. (Beaudin et
al., 2010; Chen et al., 2009)
56

57
APPENDIX 3 – ESS MODEL
PHS Data Input
3.14
16
PHS_height
X
PHS_Area
3.14
16
PHS_m3_kWh
X
PHS_Volume
3.14
16
PHS_const_CO2e_MWh
3.14
16
PHS_Energy_Capacity
Figure 32 - A larger image of the energy storage system in Figure 19
X
PHS_CO2e_construction
X
PHS_Net_Surplus
X
PHS_Input
3.14
16
PHS_Power_Capacity
PHS_Storage
3.14
16
PHS_Efficiency
X
PHS_Withdrawal
3.14
16
PHS_var_CO2e_MWh
X
PHS_CO2e_variable
X
PHS_Output
3.14
16
PHS_Cost_kW
X
PHS_Capital_Cost_PowCap
PHS_Tot_En_Prod_accumulator
X
3.14
16
PHS_Economic_LifeTime
PHS_Net_Shortage
3.14
16
PHS_interest_rate
X
PHS_annuity_factor
X
PHS_Capital_Cost
X
PHS_Cost_kWh
PHS_Total_Energy_Production

APPENDIX 4 – STORAGE DEMAND
Figure 33 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
35% wind offshore scenario and the input and output power capacity demand.
Figure 34 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
30% wind offshore scenario and the input and output power capacity demand.
59

Figure 35 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
25% wind offshore scenario and the input and output power capacity demand.
Figure 36 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
20% wind offshore scenario and the input and output power capacity demand.
60

Figure 37 - Total electricity shortage and surplus over 2050 at different amounts of storage capacity in the
15% wind offshore scenario and the input and output power capacity demand.
61

63
APPENDIX 5 – ESS SCENARIOS
ESS Scenario Power
Capacity
(MW)
Energy
capacity
(GWh)
Total surplus
(MWh)
Total
shortage
(MWh)
Annual capital
cost (€-2010)
Total
€ / kWh
(€-2010)
GHG emissions
during operation
(tonnes
CO2e)
GHG emissions
during construction
(tonnes CO2e)
Volume (m3)* Area
(km2)**
No Storage 0 0 9.954.152 6.357.505 0 0 0 0 0 0
1 Energy Island 2.500 30 8.553.073 5.210.481 € 304.415.139 1.340 1.071.000 600.000.000 60
2 Energy Islands 5.000 60 7.653.128 4.469.375 € 608.830.279 € 0.1471 2.823 2.142.000 1.200.000.000 120
3 Energy Islands 7.500 90 6.981.868 3.913.504 € 913.245.418 4.372 3.213.000 1.800.000.000 180
10 Energy Islands 25.000 300 4.684.165 1.967.315 € 3.044.151.393 7.902 10.710.000 6.000.000.000 600
40 Energy Islands 100.000 1.200 1.983.109 0 € 12.176.605.570 € 0.2233 11.444 42.840.000 24.000.000.000 2400
1 CAES 300 7,2 9.650.822 6.084.337 € 11.780.237 168 139.680 1.200.024
5 CAES's 1.500 36 8.608.262 5.143.642 € 58.901.186 1.351 698.400 6.000.120
10 CAES's 3.000 72 7.619.256 4.247.407 € 117.802.371 3.594 1.396.800 12.000.240
20 CAES's 6.000 144 6.278.573 3.022.159 € 235.604.743 € 0.1428 9.250 2.793.600 24.000.480
30 CAES's 9.000 216 5.458.367 2.260.136 € 353.407.114 12.292 4.190.400 36.000.720
140 CAES's 42.000 1.008 2.687.477 0 € 1.649.233.199 € 0.1494 19.073 19.555.200 168.003.360
1 PSB 15 0,15 9.944.243 6.350.017 € 2.368.450 7,9 18.795 3.600 0,00072
100 PSB's 1.500 15 9.111.544 5.719.923 € 236.844.976 1.338,3 1.879.500 360.000 0,072
1000 PSB's 15.000 150 5.970.661 3.313.636 € 2.368.449.758 12.175,5 18.795.000 3.600.000 0,72
10,000 PSB's 150.000 1.500 1.291.662 0 € 23.684.497.580 € 0.3040 25.430,0 187.950.000 36.000.000 7,20
1 VRB 3 0,03 9.952.212 6.355.842 € 532.657 1,3 4.842 900 0,00018
100 VRB's 300 3 9.767.283 6.197.390 € 53.265.728 160,1 484.200 90.000 0,018
1 ZnBr 2 0,02 9.952.826 6.356.502 € 540.950 1,0 2.860 340 0,000068
100 ZnBr's 200 2 9.825.269 6.260.092 € 54.094.956 107 286.000 34.000 0,0068
100 PSB's + 100 VRB's + 2.000 20 8.893.831 5.541.349 € 344.205.660 € 0.1464 1.527 2.649.700 484.000 0,0968
100 ZnBr's
1 E.I. + 5 CAES's 4.000 66 7.659.098 4.398.822 € 363.316.325 2.128 1.769.400 606.000.128 60
1 E.I. + 10 CAES's 5.500 102 6.911.850 3.717.751 € 422.217.511 3.577 2.467.800 612.000.240 60
1 E.I. + 20 CAES's 8.500 174 5.825.543 2.718.898 € 540.019.882 € 0.1449 8.473 3.864.600 624.000.480 60
2 E.I.'s + 5 CAES's 6.500 96 6.993.181 3.866.002 € 667.731.464 3.395 2.840.400 1.206.000.120 60
2 E.I.'s + 10 CAES's 8.000 132 6.395.413 3.317.968 € 726.632.650 4.423 3.538.800 1.212.000.240 120
2 E.I.'s + 20 CAES's 11.000 204 5.475.242 2.466.976 € 844.435.021 € 0.1468 8.488 4.935.600 1.224.000.480 120
2 E.I.'s + 20 CAES's +
100 PSB's + 100 VRB's +
100 ZnBr's
13.000 224 5.299.459 2.325.120 € 1.188.640.681 € 0.1495 8.708 7.585.300 1.224.484.480 120
2 E.I.'s + 20 CAES's +
1000 PSB's
26.000 354 4.409.404 1.611.348 € 3.212.884.779 11.910 23.730.600 1.227.600.480 120
3 E.I.'s + 30 CAES's 16.500 306 4.695.085 1.782.147 € 1.266.652.532 10.766 7.403.400 1.836.000.720 180

64
35% WO + 2 E.I.'s + 20
CAES's
30% WO + 2 E.I.'s + 20
CAES's
25% WO + 2 E.I.'s + 20
CAES's
20% WO + 2 E.I.'s + 20
CAES's
15% WO + 2 E.I.'s + 20
CAES's
35% WO + 2 E.I.'s + 20
CAES's + 1000 PSB's
30% WO + 2 E.I.'s + 20
CAES's + 1000 PSB's
25% WO + 2 E.I.'s + 20
CAES's + 1000 PSB's
20% WO + 2 E.I.'s + 20
CAES's + 1000 PSB's
11.000 204 2.433.289 1.106.102 € 844.435.021 6.089 4.935.600 1.224.000.480 120
11.000 204 872.823 380.222 € 801.989.016 3.986 4.935.600 1.224.000.480 120
11.000 204 213.051 148.135 € 590.283.323 1.659 4.935.600 1.224.000.480 120
11.000 204 0 55.214 € 457.382.436 460 4.935.600 1.215.935.335 120
11.000 204 0 0 € 200.765.946 76 4.935.600 1.214.179.951 120
26.000 354 1.842.681 606.896 - - 8.086 23.730.600 1.227.600.480 120
26.000 354 604.169 227.876 - - 4.595 23.730.600 1.227.600.480 120
26.000 354 63.051 91.885 - - 1.884 23.730.600 1.227.600.480 120
26.000 354 0 0 - - 680 23.730.600 1.217.735.335 120
* = In case of the energy island, this is the volume between the maximum and the minimum water level and not the volume of the whole reservoir.
** = In case of the CAES, there is no definition of a height. In case of the energy island the height difference between the maximum and minimum waterlevel
(10 meters). In case of the flow battery systems the assumption for height is 5 meters.