Degree Project in Energy Technology,
Second Cycle 30 Credits
Techno-economic analysis of
Energy Storage as a Service
business models for prosumers in
France
ALICE LACROIX
Stockholm, Sweden 2023
Master of Science Thesis
Department of Energy Technology
KTH 2023
Techno-economic analysis of Energy Storage as a
Service business models for prosumers in France
TRITA: TRITA-ITM-EX 2023:40
Approved
Examiner
Hatef MADANI LARIJANI
Supervisor
Hatef MADANI LARIJANI
Industrial Supervisor
Contact person
IDEX
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Acknowledgments
I would like to thank the IDEX Low-Carbon Buildings department for welcoming me in their
team during this six month internship. I especially thank Edouard Aubin, my internship
supervisor, and Timothée Schmutz, business developer, for their support in setting up this study.
I would like to thank Hatef Madani Larijani for having followed me as a supervisor at KTH.
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Abstract
One of the current challenges for developed countries is the transformation of the entire
electricity system. Ambitious objectives of renewable energy penetration in the electricity mix
are established to reduce the energy sector’s greenhouse gas emissions rate and reach
sustainability goals. These objectives mean both a higher share of electricity in the energy mix,
and a higher share of electricity from renewable sources. This new electricity mix is generating
transformations for the electricity grid and causes the need for flexibilities to compensate for
the intermittency of solar and wind energies which make up most of the renewable electricity
additions. One of the vectors of remodeling of the electricity system is the local on-site
production of electricity consumed, which makes it possible to reduce the needs for additional
transmission capacity. Thanks to the decrease of photovoltaic costs, self-consumption solar
projects have become profitable and have developed a lot in Europe in the last years. Batteries
will likely follow the PV trend a few years later and are also becoming affordable. Several
companies now offer solar energy packs combining roof-top solar panels with a small battery
for the residential sector. Larger consumers in the commercial, industrial or tertiary sectors can
also benefit from locally produced and cheap energy in the face of rising electricity costs. This
study focuses on France where electricity prices were affordable but the question of the
profitability of a battery for a greater local consumption is now raised due to rising and volatile
prices. We try to develop an Energy as a Service business model profitable for both the provider
and the consumer to overcome the barrier of high investment costs and technical complexity of
batteries. The use cases of the battery investigated are increasing self-consumption and load
shifting. They are compared to establish the profitability of a photovoltaic plus storage project
for a tertiary consumer in France. It is found that the addition of a battery to a solar selfconsumption project decreases slightly the annual net savings on the electricity bill for the
consumer. However, it increases the self-sufficiency rate between 2% and 8%. Another
conclusion is that the retail price of electricity is the most important element in the profitability
of batteries. Thus, the profitability of behind-the-meter storage projects under current policies
relies on unstable and high electricity prices.
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Sammanfattning
En av de nuvarande utmaningarna för de utvecklade länderna är omvandlingen av hela
elsystemet. Ambitiösa mål för hur mycket förnybar energi som ska ingå i elmixen har fastställts
för att minska energisektorns utsläpp av växthusgaser och nå hållbarhetsmålen. Dessa mål
innebär både en högre andel el i energimixen och en högre andel el från förnybara källor. Denna
nya elmix skapar förändringar i elnätet och medför ett behov av flexibilitet för att kompensera
för den intermittenta karaktären hos sol- och vindkraft, som utgör den största delen av tillskottet
av förnybar el. En av de faktorer som bidrar till att bygga om elsystemet är den lokala
produktionen på plats av den el som förbrukas, vilket gör det möjligt att minska behovet av
ytterligare överföringskapacitet. Tack vare att kostnaderna för solceller har sjunkit har
solcellsprojekt för egen konsumtion blivit lönsamma och har utvecklats mycket i Europa under
de senaste åren. Batterier kommer troligen att följa solcellstrenden några år senare och håller
också på att bli prisvärda. Flera företag erbjuder nu solenergipaket som kombinerar solpaneler
på taket med ett litet batteri för bostadssektorn. Större konsumenter inom handel, industri eller
tertiär sektor kan också dra nytta av lokalt producerad och billig energi i samband med stigande
elkostnader. Den här studien är inriktad på Frankrike där elpriserna var överkomliga, men där
frågan om lönsamheten av ett batteri för en större lokal förbrukning nu väcks på grund av
stigande och volatila priser. Vi försöker utveckla en affärsmodell för energi som tjänst som är
lönsam för både leverantören och konsumenten för att övervinna hindret med höga
investeringskostnader och batteriernas tekniska komplexitet. De användningsområden för
batteriet som undersöks är ökad självförbrukning och lastväxling. De jämförs för att fastställa
lönsamheten för ett projekt med solceller och lagring för en tertiär konsument i Frankrike. Det
visar sig att tillägget av ett batteri till ett solcellsprojekt för självförbrukning minskar den årliga
nettobesparingen på elräkningen för konsumenten något. Däremot ökar självförsörjningsgraden
med mellan 2 och 8 %. En annan slutsats är att detaljhandelspriset på el är den viktigaste faktorn
för batteriers lönsamhet. Lönsamheten för lagringsprojekt bakom mätaren med nuvarande
politik är således beroende av instabila och höga elpriser.
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Acronyms
BESS .......................................................................................... Battery Energy Storage System
BTM ................................................................................................................. Behind-the-meter
CRE .............................................................................................. Energy Regulatory Comission
EaaS .............................................................................................................. Energy as a Service
FCR .......................................................................................... Frequency Containment Reserve
PV ............................................................................................................................ Photovoltaic
RTE ........................................................................................ Réseaux de Transport d’électricité
TSO ............................................................................................. Transmission System Operator
TURPE ......................................................................... Tariff for the Use of Public Power Grids
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Table of Contents
Abstract .......................................................................................................................................................................... 3
Sammanfattning ............................................................................................................................................................ 5
Acronyms ....................................................................................................................................................................... 6
1
2
3
Introduction........................................................................................................................................................ 10
1.1
Renewable energy development ........................................................................................................... 10
1.2
Flexibility needs for grid support ......................................................................................................... 11
1.3
Distributed PV and self-consumption ................................................................................................. 12
1.4
Behind-the-meter battery storage ......................................................................................................... 13
1.5
Revenue streams for behind-the-meter batteries ............................................................................... 14
1.5.1
End user applications ....................................................................................... 14
1.5.2
Grid Services .................................................................................................... 16
1.5.3
Revenue stream stacking.................................................................................. 17
Objective and Methodology.............................................................................................................................18
2.1
Objective of the study ............................................................................................................................18
2.2
Methodology ............................................................................................................................................ 18
2.2.1
Energy-as-a-Service Business Model .............................................................. 18
2.2.2
Case study methodology .................................................................................. 19
2.2.3
Battery dispatch model .................................................................................... 20
2.3
Input data ................................................................................................................................................. 22
2.4
Key Performance Indicators ................................................................................................................. 23
2.4.1
Technical indicators ......................................................................................... 23
2.4.2
Economic indicators......................................................................................... 25
Technology description .................................................................................................................................... 27
3.1
Battery energy storage system ............................................................................................................... 27
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3.2
4
5
6
PV and battery characteristics ............................................................................................................... 29
3.2.1
Battery life ....................................................................................................... 29
3.2.2
Round trip efficiency ....................................................................................... 29
3.2.3
Battery degradation .......................................................................................... 30
3.2.4
Self-discharge .................................................................................................. 30
3.2.5
Battery costs ..................................................................................................... 31
3.2.6
Photovoltaic parameters ................................................................................... 32
Geographic focus on France............................................................................................................................33
4.1
The role of distributed PV and battery storage in the future French energy mix ........................ 33
4.2
The French electricity market ............................................................................................................... 34
4.3
Policy review for self-consumption ..................................................................................................... 35
4.4
Analysis of revenue streams in the case of France ............................................................................ 36
4.4.1
End-user applications ....................................................................................... 36
4.4.2
Grid services .................................................................................................... 37
Results and Discussion ..................................................................................................................................... 38
5.1
PV and battery sizing method ............................................................................................................... 38
5.2
Comparison of two use cases ................................................................................................................ 39
5.3
Values of battery storage for the consumer ........................................................................................ 41
5.4
Sustainability of batteries ....................................................................................................................... 41
5.5
Sensitivity Analysis .................................................................................................................................. 43
5.6
Conclusion ............................................................................................................................................... 45
Limitations and future work ............................................................................................................................45
Bibliography ................................................................................................................................................................. 47
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Table of Figures
Figure 1 European Union Renewable energy targets (European Commission, 2022b) .......... 10
Figure 2 Battery storage costs reduction(Mauler et al., 2021) ................................................. 12
Figure 3 Behind-the-meter PV battery production .................................................................. 13
Figure 4 Energy as a Service Business Model ......................................................................... 19
Figure 5 Techno-economic analysis model flowchart ............................................................. 20
Figure 6 Flowchart of battery dispatch strategy for self-consumption increase ...................... 21
Figure 7 Battery state of charge on an average week according to photovoltaic generation curve
.................................................................................................................................................. 22
Figure 8 Self-consumption load and photovoltaic production mismatch during one day. ...... 25
Figure 9 Battery Energy Storage System Architecture ............................................................ 28
Figure 10 Schematic diagram of BTM PV battery plant(Rezaeimozafar et al., 2022) ............ 29
Figure 11 Degradation of lithium-ion batteries as a function of cycling (Preger et al., 2020) 30
Figure 12 Electricity spot prices In France since 2018(tradingeconomics.com, 2022) ........... 34
Figure 13 Results of sizing simulation. Self-consumption, self-sufficiency, equivalent solar
tariff and equivalent full cycle for battery storage size from 0kWh to 400kWh and PV from
300kWp to 800kWp ................................................................................................................. 38
Figure 14 Self-sufficiency and total economies performance as a function of PV size and battery
size in the case of self-consumption increase and time of use tariff optimization revenue
stacking .................................................................................................................................... 40
Figure 15 Self-sufficiency and total economies performance as a function of PV size and battery
size in the case of self consumption increase with additional revenues from self-consumption
call for tenders.......................................................................................................................... 40
Figure 16 Carbon emissions reduction estimates for battery cells manufacturing .................. 42
Figure 17 Sensitivity analysis on project lifetime economies for the use case self-consumption
increase with self-consumption premium ................................................................................ 43
Figure 18 Sensitivity analysis on project lifetime economies for the use case self-consumption
increase + load shifting ............................................................................................................ 44
Figure 19 Net cashflow for the consumer during the lifetime of the project ........................... 45
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1 Introduction
1.1 Renewable energy development
The rapid deployment of renewable energies has become a fundamental concern for Europe.
Through the European Green Deal, the Union claims its ambition to become the first climate
neutral continent by 2050 by reducing carbon emissions by 55% by 2030 compared to 1990
levels. A large effort is needed to reduce the use of carbon intensive energy production from
fossil fuels since the energy sector is responsible for 75% of greenhouse gas emissions in
Europe. This heavy reduction will be partly addressed by energy efficiency measures. On the
other hand, it will be necessary to increase the share of renewable energy in the remaining
consumption. To achieve this, Europe has set renewable energy targets. After reaching its
objective of 20% renewable energy in 2020, the Union continues to set more ambitious targets
for 2030. The last one of 45% comes from the REPower EU Plan, published in 2022 as a
response to the urgent need to reduce Europe’s dependence on Russian fossil fuels.
Figure 1 European Union Renewable energy targets (European Commission, 2022b)
One of the main renewable energy sources relied on to reach these targets is Solar photovoltaics.
It is the technology in which Europe puts its hopes to reach its ambitious REPower EU
objectives, for which 1236 GW of renewable generation capacity is needed, including 600GW
of PV. This is also a global trend. PV has become the mean of electricity generation with the
lowest cost, attracting increasing investments. In the renewables 2022 report of the IEA, solar
PV is set to surpass coal and all other technologies in terms of cumulative installed capacity in
2027, reaching 28%. (IEA, 2022c) However, this will not be fast enough under current policies
to reach the IEA Net Zero Scenario target of 7400 TWh of solar PV generation in 2030, a large
increase compared to the 1000 TWh in 2021. (IEA, 2022d)
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1.2 Flexibility needs for grid support
The integration of renewable intermittent energies, such as solar PV, in the electric mix involves
a heavy need for flexibility on different scales. First, the current electricity demand does not
match the production profile of wind and solar energies, both on an annual and on a daily scale.
In 2015, the electricity mix of California was already made of 20% of solar energy. Its grid
operator stresses the need for flexibility improvements to overcome the 13GW ramp at the end
of the afternoon as the sun sets. This is because of the so-called duck-curve created by a high
penetration of solar energy. When the sun sets, a large capacity of production is suddenly lost
and needs to be rapidly replaced by other generation means. But not all conventional power
plants have the capability to operate such a fast ramp-up. (Martinot, 2016)
Another issue with intermittent renewable energies is the unpredictability of supply. This
increases the volatility of the supply and demand balance and requires more intelligent energy
management strategies and accurate and fast response flexibility capacities. Indeed, flexibility
is key for the electric grid to maintain an exact balance between supply and demand.
Historically, balance was achieved by adjusting supply to the demand. The output of base load
technologies, such as conventional power plants, nuclear power plants, or dams, can be adjusted
hour to hour and peak generation technologies such as gas turbines provide minute to minute
flexibility. New technologies, such as battery storage, can now provide second to second
services which were historically provided by fuel-based electricity generation. (Mohler and
Sowder, 2017) Storage and demand-side response are expected to be fundamental in the energy
transition and reach 400 GW of global capacity by 2040. (Claudia Pavarini, 2019)
These storage technologies are segmented into 5 categories, mechanical storage such as pumped
hydro or compressed air energy storage (CAES), thermal storage by transforming electricity
into heat, chemical storage, i.e. power-to-gas technologies, electrical storage with
supercapacitors, and finally electrochemical storage with batteries. In 2020, over 90% of the
storage capacity installed worldwide was pumped hydropower, the most mature technology.
(IEA, 2020b) Today, batteries are also becoming increasingly popular for flexibility services
throughout the day or over a few hours but also at a very small scale for frequency regulation.
Different chemistries of batteries exit, including lithium-ion, lead-acid, flow batteries, nickelbased, and high temperature. Lithium-ion batteries were first introduced on the market in 1991
by Sony. Because of its high energy and low costs, they have become the most mature and
dominant technology for stationary storage on all levels from grid-scale to residential
storage.(IEA, 2022b) Flexibility from the battery is both on the supply side, when it is coupled
with a renewable production plant to manage power output, and on the demand-side, when
behind-the-meter storage allows consumers to alter their withdrawal from the grid.
Like photovoltaic electricity generation, the deployment of battery storage is enabled by the
cost reduction for lithium-ion batteries. Mauler et. al show in Figure 2 that battery investment
costs have decreases by almost two thirds since 2010 and some studied still expect these costs
to decrease.
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Figure 2 Battery storage costs reduction(Mauler et al., 2021)
1.3 Distributed PV and self-consumption
One of the growth drivers for installed PV capacity is distributed PV. The concept of distributed
photovoltaic generation is the deployment of solar panels close to consumers, on small
structures on roofs or parking canopies. This distributed production is opposed to centralized
electricity production methods such as utility scale solar fields connected to the electricity
transmission network. These facilities typically have a capacity of less than 1MWp, although
they can be higher for some energy-intensive large sites. Often, the “prosumers” produce their
own electricity on-site from solar panels on rooftops or parking canopies and consume this
electricity simultaneously. This relieves the grid both from injection and withdrawal. Selfconsumption can be either complete, with no grid connection and the excess generation
curtailed by the inverter, or partial when the excess generation is injected into the distribution
grid.
In 2021, the utility power plants represented over half of the PV capacity additions worldwide.
The commercial and industrial segment still dominates the distributed PV and is responsible for
about 25% of global capacity additions. (IEA, 2020a) The International Energy Agency
forecasts the commercial and industrial segment to be the fastest growing for solar PV capacity
with additions from 150 GW in 2018 to 377 GW in 2024. Although China still dominates the
global market, a significant growth is expected in the European Union with the sustained
deployment in Germany but also accelerated growth in other countries such as France thanks
to incentivizing policies.(IEA, 2019) The reduction of PV panels prices over the past years
enabled many countries to reach grid parity, which is when the production price of selfconsumed electricity is lower than retail prices. In this case, self-consumed energy is cheaper
than bought electricity from the grid. This economic benefit of self-consumption can be a major
argument for consumers to become prosumers. Therefore, self-consumption photovoltaic
projects are more favorable in a context where subsidies such as feed-in-tariffs do not make the
sale of electricity more profitable than its consumption.
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1.4 Behind-the-meter battery storage
In the same way, distributed battery storage can help meet the increased need for flexibility.
This concept refers to small-scale storage systems installed on a consumption site, which is
used to help integrate a renewable energy production plant, to improve the quality of power
supply, or other use case which will be studied below. These battery systems are defined as
behind-the-meter (BTM) because the storage system is connected behind the electric meter of
the industrial or commercial site. The storage facility is managed by the consumer, but the
distribution system operator can in some cases remunerate the consumer for grid services,
which will be described more thoroughly later. Behind-the-meter storage systems are opposed
to front-the meter (FTM) batteries, which are connected to the transmission or distribution
network and provide services for the system operators, optimize the sale of renewable energies
like solar fields, or can be used for energy arbitrage.
Figure 3 shows a functional diagram of the installation in the case of behind-the-meter battery
and photovoltaic systems. The solar generation can provide for the load, be used to charge the
battery, or be injected into the grid, and the battery can discharge to provide for the load and
charge with energy from the photovoltaic panels or from the grid. In some cases, the battery
can also inject energy back into the grid and therefore be used for energy arbitrage or ancillary
services. All these power flows happen behind the electric meter of the site. This type of
installation allows flexibility for the consumer on site. But one of the major barriers for this
type of system is the high investment cost.
Figure 3 Behind-the-meter PV battery production
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1.5 Revenue streams for behind-the-meter batteries
It is necessary to find sources of revenue to make the ever-increasing investment costs of
batteries profitable. A lot of literature has been published in recent years examining the
profitability of behind the meter battery storage for the residential sector. With falling battery
costs and growing retail electricity price for households, the levelized cost of electricity of
coupled PV and battery solutions have become price competitive in some regions, for example
in Germany since 2016, due to an average retail price around 20c€/kWh. (Pwc, 2020)
Batteries are flexible and have many different technical characteristics which allows them to
have many uses. The revenue streams of battery storage can be separated into two main
sections: end user applications and utility grid services.
1.5.1 End user applications
Self-consumption increase
Photovoltaic self-consumption leads to
economic revenues in cases where the
levelized cost of electricity from the
photovoltaic power plant is lower than the
electricity retail price of the consumer. In some
cases, photovoltaic production does not
coincide with the load curve, which may
encourage a smaller sizing of the plant during
the design phase or the sale of excess
generation to the grid. The profitability of the
latter option depends on policies in the region.
In some cases, the feed-in-tariff is low enough that it would be more profitable to consume this
excess generation, even considering the losses due to storage. Indeed, battery storage can store
excess solar production to be used at a later time when the sun is not shining or during on-peak
hours. The sizes of the battery storage and the photovoltaic plant determine the rate of selfconsumed energy in total consumption, which can in theory reach 100%, although this would
imply great infrastructure as well as demand-side management. This is however the case in
microgrids. Most literature studies residential size battery systems which generally the increase
of self-consumed energy by 20 percentage points. (Luthander et al., 2015)
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Time of use (Load shifting)
Some professionals have a time of use
electricity contract, where they pay
different rates depending on predetermined
periods of time. In that case the battery can
be used for load shifting. Electricity bill
savings come from consuming low-rate
electricity stored in the battery during onpeak hours when rates are higher.
Peak-shaving
Peak shaving consists in the smoothing
of the load curve of an electricity
consumer to reduce the rate of
consumption at certain peak times.
Billing for commercial and industrial
users sometimes includes demand
charges. At some point in time, they
will be charged for the rate at which
they are consuming electricity. Two
users who consume the same volume of
energy in kWh will not have the same
bill depending on the power called on
the grid. Darghouth et al. assesses the reduction of demand charges with behind the meter PV
generation and battery storage for different demand charge schemes and consumer types.
(Darghouth et al., 2020)
Backup power
Battery can also provide electricity consumers with back-up power in case of national grid
outages. Although grids are now resilient, crisis like has been known in France during the winter
2022 could happen more often in the next few years due to the transition to a high penetration
of renewable energy in the mix and the increase in demand with electrification. Some industrial
and commercial sites need to have a reliable power for sensitive equipment and a battery can
provide short term backup while diesel generators are started in the case of longer outages.
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1.5.2 Grid Services
One of the missions of the Transmission System Operator is to ensure the balance between
electricity supply and demand. This means being able to meet demand at all times and
maintaining the network from a physical standpoint. This task is becoming important and
complex due to the transformation of uses and the electricity mix. Batteries can provide several
types of support to the grid, at the utility scale, but also behind the meter. Thus, market designs
and subsidies exist to allow batteries to be compensated for these different services. At the BTM
battery scale, grid services are most often provided through a capacity aggregator. The methods
of remuneration differ from country to country.
Spinning reserve
The grid needs to be able to support the loss of the biggest generator capacity. The country
needs to have available capacity to supply the load and readjust the frequency. Reserve can
come in two forms, production capacity, and demand-side response capacity. Battery storage
behind the meter can be aggregated to provide either one of them.
Frequency regulation
The frequency of the power transmission grid must be kept at 50 Hz or 60 Hz depending on the
region. It is directly linked to the equilibrium between supply and demand. The inertia of
synchronous generators like gas and steam turbines keep the frequency stable when there are
small deviations from the balance. Wind and solar generators do not provide this service so new
technologies are needed to make small adjustments on a second-to-second basis.
Voltage support
The voltage level is another key metric which must be stabilized for a stable power flow. The
voltage level of the grid is regulated by controlling the reactance of the power grid. Generators
are able to provide reactive power to manage this, but some consumers still experience voltage
drops in a centralized electricity generation system because voltage can be regulated only on
short distances. Battery storage has the ability to regulate the reactive power it transmits to the
grid and therefore offer voltage regulation on a smaller scale.
Network investment deferral
The electrical network is today dimensioned to convey centralized production from
conventional generators to consumption centers such as cities. Today, renewable energies are
responsible for the decentralization of production. Moreover, the electrification of uses is at the
heart of the energy transition and will be responsible for a strong increase in electricity
consumption despite energy efficiency efforts. Thus, the transmission network must be adapted,
and the investment costs are significant. Diffuse power generation can reduce the need for
increased grid capacity if it is well integrated in the planning. Behind-the-meter battery storage
is an asset for better management of peak hours and can help further reduce network investment.
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Transmission congestion relief
On a more local scale, some power lines are too small to meet the transmission needs at certain
times of the day. In this case, there is no other way than to reduce the demand. Here, batteries
can participate in the demand-side management.
1.5.3 Revenue stream stacking
Even if the prices of batteries have decreased greatly, they remain a heavy investment that
requires important and stable revenues throughout its lifetime. More recent literature proposes
optimizing the use of batteries to combine multiple revenue streams. The multi-use of batteries
can allow investors to avoid the need for government support. In England, William Seward et
al. finds the most profitable combination of revenues for BTM battery on a school property in
the UK to be electricity arbitrage and dynamic containment, which is a mechanism in which
the battery provides fast frequency response after a significant deviation. (William Seward,
Meysam Qadrdan, and Nick Jenkins, 2022) Rancilio et al. also finds that combining revenues
from frequency reserve and replacement reserve in Italy improves investment’s rate of return.
(Rancilio, Bovera and Merlo, 2022) A case study on Germany by Englberger et al. investigates
the dynamic stacking of both end-user and grid services revenues and concludes that multi-use
can significantly improves the techno-economic performance of a project, with a result NPV
per euro invested of 1.24 when combining peak shaving and FCR with arbitrage trading on
intraday market. (Englberger, Jossen and Hesse, 2020)
In addition to providing an increase in revenue for the system, revenue stacking allows the longterm profitability of the asset to be freed from market volatility. Indeed, some mechanisms like
FCR require a limited amount of capacity. An increase in the installed capacity of batteries that
participate in the reserve will most likely lead to a rapid drop in the revenues of this mechanism.
Electricity arbitrage also depends on the price spread reached on the electricity market between
off-peak and peak hours. The majority of these revenues are thus based on market values and
the combination of these makes it possible to stabilize and secure revenues in the future.
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2 Objective and Methodology
2.1 Objective of the study
As seen in the previous chapter, battery storage is a key technology in reaching the flexibility
needed for the future energy mix in the world and more specifically in Europe. Utility storage
investments are increasing all over the world and the research on behind-the-meter applications
of battery storage has focused on the residential sector. Not much literature tackles the
profitability of coupled PV and battery systems for commercial and industrial sites. However,
these have a more important consumption than households, and a greater incentive for low price
and low carbon electricity. Although these solutions have developed in the recent years in
neighboring countries like the UK and Germany, France still has little referenced projects of
the sort. But interest is growing because of the recent soaring electricity prices. This report aims
at answering the two research questions below:
-
What are the revenue streams for behind-the-meter battery storage in France?
What is the value of battery storage addition to self-consumption photovoltaic projects for
commercial and industrial sites in France?
2.2 Methodology
To tackle these questions, a literature review is the first step to allow us to understand the
components of a battery energy storage systems (BESS) and their technical characteristics.
Then, a focus on France will shed light on the revenue streams that can be used in this country
considering the needs of the consumers, the regulations, and the electricity billing schemes.
Finally, a strategy for sizing the project is proposed through the modelling of the photovoltaic
and battery performance, considering both economic and non-economic value benefits,
followed by a sensitivity analysis of a few key input parameters.
2.2.1 Energy-as-a-Service Business Model
The financing scheme is based on an energy-as-a-service business model, where a third-party
solution provider invests in the project. Third party investment is allowed by the Energy Code
in France, when it is not in other countries. The investor is not considered a self-producer.
Instead of investing in year one in the production plant, the consumer rents the plant each year
to have access to all its production. From the point of view of the French law, the consumer is
still an individual prosumer and can benefit from the subsidies and tax exemptions.
The ‘As a Service’ business model is developing in many product sectors. The customer
switches roles from owner to user benefiting from a service without owning the product. Energy
as a Service (EaaS) contracts can be divided into two broad categories, performance contracts
on the demand-side, and supply contracts. The first service-based models to see the light were
energy efficiency solutions. Energy efficiency enables savings in the long-term but has long
known the barrier of the high initial costs. With an energy as a service model, the provider
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invests in energy efficiency measures, such as building retrofit, and generates revenue from the
savings thus generated for the consumer. Later this model was also a success in overcoming the
investment cost barrier for distributed photovoltaics for residential customers and communities.
Through a solar lease or a power purchase agreement, the investor builds and maintains a solar
plant that benefits the consumer without him having to make an upfront investment.
In an energy as a service contract, there are three main stakeholders: the provider of the solution,
the investor, and the customer. In some cases, the EaaS provider can also act as investor. This
will be the case in this study. The customer receives a turn-key service in exchange for which
he pays a monthly or yearly subscription. This model is particularly attractive for the customer
for two main reasons. An integrated system has value for the customer because energy storage
is a technically complex system which requires many different components from battery
container to an adequate energy management system. Third-party investment raises the second
barrier to implementing battery storage on a commercial or industrial site, which is the high
capital investment cost of the product.
Figure 4 Energy as a Service Business Model
2.2.2 Case study methodology
For this study, a techno-economic model was developed using Google Sheets and Apps Script.
The first step is the yearly simulation of battery energy flows. Then, the results from this
dispatch are fed to the financial model for the third-party investor to determine the yearly fee
for the consumer. This rent is calculated using a financial model for the company with an
objective IRR of 10.5%. Finally, revenues can be calculated for the client each year and be
compared to his annual fee to assess profitability of the solution. Other indicators are evaluated
to characterize non-economic benefits of battery storage. Self-consumption and self-sufficiency
rates translate the energy service for the client and the equivalent full cycles (EFC) measures
the relevance of the battery addition to the project.
-19-
Figure 5 Techno-economic analysis model flowchart
2.2.3 Battery dispatch model
We are studying the profitability of a storage project coupled with PV panels. The goal being
to decarbonize the building, the increase of self-consumption to provide a larger part of the
site's electricity consumption from low-carbon and local production will be the use case that
will take priority over the others in the case study. The case study will be a time of use tariff
because it is the most spread out in France, where all day hours are peak. Therefore, all the
electricity production from solar panels will reduce consumption from the grid on highest
supply prices, so there is no need to optimize the dispatch of the battery during the day. The
added value of the battery will be to avoid curtailment of solar energy and increase selfconsumption.
For all the above reasons, the dispatch strategy is an algorithm that stores surplus electricity
until the battery is full and then discharges it when part of the consumption is no longer provided
by the photovoltaic. In order to further optimize the consumer’s bill, the battery is also
instructed not to discharge during off-peak hours. Thus, if it is not empty at 10 pm, it will wait
6 am to be discharged again. This strategy is described in Figure 6. During the days when there
is no excess PV generation, the use of the battery will be chosen between load shifting, ancillary
services, and other use cases which will be discussed.
Figure 7 shows the battery state of charge in the case of self-consumption increase on an average
week. Battery charging and discharging correspond respectively to the start and end phase of
photovoltaic excess generation. Because this graph shows a weekly average of the annual
dispatch of the battery, charging and discharging overlap.
-20-
Figure 6 Flowchart of battery dispatch strategy for self-consumption increase
-21-
Consumption
Solar production
300
250
kW
200
150
100
50
0
Sunday
Monday
Tuesday
Battery charging
Days of the week
Wednesday
Thursday
Battery discharging
Friday
Saturday
Battery State of Charge
200
80
150
60
100
40
50
20
0
0
Week days
Sunday
Monday
Tuesday
Wednesday
State of charge (kWh)
Charge and discharge (kW)
100
Thursday
Friday
Saturday
Figure 7 Battery state of charge on an average week according to photovoltaic generation curve
2.3 Input data
The technical model works as a power plant controller dispatching the energy in the system
made of the site consumption, the PV production, the battery, and the grid. To study a typical
commercial and industrial site, the load curves were taken from Enedis open data platform.
(ENEDIS, 2022) The latter provides consumption average profiles by sector and by grid
connection power capacity. The consumption profile used is the average in Île de France for
professionals in the tertiary sector. The grid connection considered go from 250kVA to 1000
kVA, since these are the most frequent customers for self-consumption. The annual electricity
consumption equals 1.3 GWh.
Next, a production curve is needed. The photovoltaic production is generated using the System
Advisory Model (SAM) developed by NREL to facilitate the techno-economic analysis of
renewable energy projects. The PV Watts model was chosen with no financial model. The PV
production is not the cornerstone of this project, and the point of this generation is to assess the
advantages of adding battery storage to a photovoltaic production. Therefore, a standard
-22-
500kWdc system was designed with a 1.2 AC to DC ratio. A simple and efficient system design
was chosen with a 20° tilt and a 180° azimuth. The meteorological data from Île de France
comes from the Photovoltaic Geographical Information System (PVGIS) tool from the
European Union Joint research center.
Finally, reference retail electricity prices are needed to compute electricity bill savings. We
study the case of a time-of-use electricity billing. The 8760 of the year into five categories, peak
hours, on-peak high season, off-peak high season, on-peak low season, and off-peak low season.
The definition of each category depends on the distribution operator and the supplier. Generally,
high season is from November to March and Low season from April to October; Off-peak hours
correspond to 8 hours a day between, which are taken between 22:00 and 06:00 for this study,
and on-peak hours are from 06:00 to 22:00. Peak hours depend on the contract, and can be
either fixed or mobile, in which case they are only on certain days decided by the transmission
system operator. Therefore, they will not be accounted for in the following study because they
are unpredictable. The retail electricity price used come from the reference estimates of the
CRE for 2023 rates for small and middle-size companies. These prices include the TURPE and
only the CSPE needs to be added for economies estimate. CSPE is rate is 22.5€/MWh.
Table 1 Retail electricity price estimates for French companies (CRE, 2022b)
Peak hour
On-Peak High
Season
Off-Peak High
Season
On-Peak Low
Season
Off-Peak Low
Season
650 €/MWh
453 €/MWh
186 €/MWh
176 €/MWh
123 €/MWh
2.4 Key Performance Indicators
2.4.1 Technical indicators
Self-consumption and Self-sufficiency (%)
Many metrics exist to characterize self-consumption profiles. The ones investigated in this
thesis are self-consumption and self-sufficiency. The time resolution of the load and production
curve have a great impact on self-consumption metrics and studies have shown that sub-hourly
data should be used to reflect the mismatch between demand and production peaks.(Luthander
et al., 2015) They will be calculated on a 30-minute to follow the load profiles provided by
Enedis. Self-consumption is the ratio between the self-consumed energy and the total PV
production over the year. This is a good indicator of the optimal sizing of the PV plant. The
higher the self-consumption, the less PV energy is lost. In some cases where the energy which
is not consumed can be sold to the grid at a feed-in tariff, the self-consumption is not necessarily
correlated with the economic profitability of the system. Self-sufficiency represents the part of
the load which will be covered by the local production during the year. It measures the
-23-
independence of the site from the grid. It is defined as the ratio between self-consumed energy
and the total consumption over the year.
Figure 8 shows the typical load and PV production profiles for one day. A and B represent the
energy consumed by the load. A is provided by the grid while B is provided by the solar
production on site. In this case, there is excess PV production, C.
The annual self-consumed energy can be calculated, in the case of an hourly time-step as:
'()*
𝐸!" = # min'𝑃#$# (𝑡), 𝑃%& (𝑡)+,-
In the case of a storage on site,
'()*
𝐸!" = # min'𝑃. (𝑡), 𝑃%& (𝑡) + 𝑃/0!! (𝑡)+,-
Where 𝑃. is the load, 𝑃%& is the PV production, and 𝑃/0!! is the relative storage power, i.e.
𝑃/0!! > 0 when the battery is discharging and 𝑃/0!! < 0 when the battery is charging. Now
we can define self-consumption and self-sufficiency.
𝑆𝐶 =
𝐸!" ∑'()*
+,- min'𝑃. (𝑡 ), 𝑃%& (𝑡 ) + 𝑃/0!! (𝑡 )=
𝐸%&
∑'()*
+,- P12 (𝑡)
𝑆𝑆 =
𝐸!" ∑'()*
+,- min'𝑃. (𝑡 ), 𝑃%& (𝑡 ) + 𝑃/0!! (𝑡 )=
𝐸.
∑'()*
+,- P3 (𝑡)
-24-
C
B
A
A
Figure 8 Self-consumption load and photovoltaic production mismatch during one day.
Equivalent Full Cycle (nb of cycles)
Looking at the number of charge/discharge cycles without regard to the charge rate does not
give information on the adequacy of the battery size. On the other hand, the average depth of
charge over all the battery cycles does not tell you if the battery is used enough days in the year.
Instead, the equivalent full cycle is calculated to assess the purpose of the battery on site. It is
defined as the amount of total energy stored divided by the energy capacity of the battery.
𝐸𝐹𝐶 =
𝐸456789#
𝐸:6++97;
2.4.2 Economic indicators
Internal Rate of Return (%)
The Internal Rate of Return (IRR) assesses the economic profitability of a hybrid PV battery
system for the energy service company. IRR is a commonly used indicator by companies for
capital investments. The investment with the highest IRR will be considered the most profitable.
The IRR was chosen to assess the profitability of different system sizes for any company with
different financing mechanisms. It is defined as the discount rate that leads a Net Present Value
of 0€. Because of the risk of a battery storage project, the expected IRR should be high. For this
study the target IRR is 10.5%.
-25-
=<>9+<$9
𝐼%& + 𝐼/0!! +
#
+,-
𝐶%& + 𝐶/0!! − 𝑅:<== − 𝑆!"
=0
(1 + 𝐼𝑅𝑅)+
Equivalent solar price (€/MWh)
The consumer is paying an annual fee in exchange for the use of the energy from the solar
panels and the battery. In a self-consumption increase only scenario, the only service coming
from the system is a quantity of energy 𝐸?4 . To compare the cost of that energy to the retail
price of the consumer, it is common to calculate the equivalent solar price, defined as the annual
fee divided by the quantity of energy self-consumed. It translates the cost of solar energy in
current euros per MWh for the consumer. The first year of operation is taken as a reference to
compute this metric.
𝐸𝑆𝑃(€/𝑀𝑊ℎ) =
𝐴𝑛𝑛𝑢𝑎𝑙 𝑟𝑒𝑛𝑡 (€)
;𝐸?4
(𝑀𝑊ℎ)
Net Present Value (€)
The profitability of the project for the consumer should account for the quantity of energy
provided by the system, the annual cost of the project, the economies from all revenue streams,
and the degradation of the performance of the battery. The net present value of the battery
project will be computed to compare stacked revenues. The net present value measures the
profitability of an investment as the sum of the cash flows generated by this operation, each of
which is discounted so that its importance in this sum is diminished as it moves away in time.
Since there is no investment cost for the consumer in the energy as a service business model,
the formula of the NPV is limited to :
*+
𝑁𝑃𝑉 (€) = )
),-
𝑅!"## + 𝑅$%&'( − 𝑅𝑒𝑛𝑡
(1 + 𝑑 ) )
Where 𝑅!"## economies on the bill from self-consumed energy or load shifting, 𝑅$%&'( are the other
additional revenues, for example from feed-in-tariff or self-consumption premium, and 𝑅𝑒𝑛𝑡 is the
annual rent due to the energy company.
Since the risk for the consumer is low, the discount rate chosen is only 3%. However, since there is no
initial investment in the case studied, and the cash flow profile is similar for the different projects, the
discount rate chosen does not affect the comparison of the projects between them. It was verified that
the trends shown remain true for different discount rates.
-26-
3 Technology description
3.1 Battery energy storage system
Battery storage is the technology that best fits the requirements for C&I self-consumption
systems, thanks to a good scalability, fast response time, easy transportation, and installation.
Most batteries on the market are lithium-ion NMC or LFO chemistries, which is why they will
be investigated in this study.
A battery energy storage system consists of various components.
•
Battery Cabinet
Serial connection of cells adds up their voltages and parallel connection adds up the cells the
usable capacity. Lithium-ion cells are first connected to form modules of the desired voltage
and capacity. These modules are then assembled into packs, which can also be called tray or
rack in the literature. The battery system also contains a Battery Management System (BMS)
which ensures the safe operation of the cells and the optimization of their lifetime by controlling
key characteristics such as voltage, temperature, and current conditions. The BMS balances the
state of charge of all cells in a module to make sure all cells age at the same rate. It also monitors
and controls the state of charge (SOC) and the state of health (SOH) of the battery. The battery
cabinet or container also contains a cooling system, which can be air cooling or liquid cooling,
and security devices, the main disadvantage of lithium-ion batteries being thermal stability.
Chemical reactions that release oxygen when the cathode overheats may lead to the cells
catching fire. This overheating can be caused by external heat or charging or discharging
conditions.
•
Power Conversion System
The Power Conversion system consists of power electronics with two main objectives. The first
is to convert direct current voltage into alternative current voltage and vice versa through a
bidirectional AC/DC converter. The second part of the PCS is a control unit, sometimes called
power management system, which controls the charge and discharge state of the battery
according to the power command. It can receive control commands through communication.
The PCS also communicates with the BMS discussed previously to have information on status
of the battery pack.
The PCS is then connected to the grid through a transformer to adapt the output voltage to the
grid level.
•
Energy Management System
The Energy Management System (EMS) is a supervisory controller that dispatches energy and
optimizes scheduling. It aggregates data from the BMS as well as PV production, grid
-27-
availability, and load to optimize energy dispatching from the different sources. It allows the
coordination of numerous PCS and battery systems to manage operation at a site level. It
receives information from the PCS through a Supervisory Control and Data Acquisition
(SCADA) system. The EMS has a human interface which enables human scheduling of the
plant but can also implement many decision algorithms to operate the system according to input
data.
Figure 9 Battery Energy Storage System Architecture
When coupled to PV panels, the battery system can be connected either in DC or in AC. In the
DC-coupling case, the energy flows from the panels to the battery stay in DC and this limits
power conversion losses. AC-coupling allows for more flexibility, it can be retrofitted to an
existing PV system. Although DC-coupling offers higher efficiency, detailed comparison of
both technologies has not been found and AC-coupling is the favored solution by industrials.
In the case of DC-coupling, energy from the PV goes through a DC-DC converter to match the
link voltage and is then fed to the ESS through the DC-DC converter of the ESS or to the DCAC inverter to provide for the load. In this case the inverter is multimode, which is more
expensive than traditional ones. Moreover, the whole system relies on only one inverter, and
this limits the output power of the generation unit (PV+battery) to that of the multimode
inverter. In the case of AC coupling, both the PV and the battery can provide for the load at the
same time with the addition of both their inverter power. Another advantage of Ac-coupling is
the flexibility it offers since ESS can be added on an existing PV unit. (Rezaeimozafar et al.,
2022)
-28-
Figure 10 Schematic diagram of BTM PV battery plant(Rezaeimozafar et al., 2022)
3.2 PV and battery characteristics
3.2.1 Battery life
The life of a battery is both temporal and cyclical. Estimates of the cyclic life of lithium-ion
batteries vary widely in the literature and can range from 1000 to 10000 cycles.
(Rezaeimozafar et al., 2022) The cycle life for this study is the regular estimated life by
battery manufacturers of 6000 equivalent full cycles. The shelf life depends on the use of the
battery and estimates of shelf life go from 5 years to 20 years for lithium-ion batteries. The
estimate of 20 years is used. However, manufacturer warranties often cover 15 years so a
provision of 10% of the investment cost is taken to replace some pieces at year 15.
Temperatures have an important impact on battery life. An increase in temperature of about
10K can cause the reduction of calendar lifetime by 50% because unwanted reactions occur at
a higher rate under high temperatures. The best temperature range for Li-ion batteries are
between 20°C and 30°C, which is a temperature range often respected in a great part of
metropolitan France.(IRENA, 2017)
3.2.2 Round trip efficiency
The electricity going into the battery is lost in the conversion. The round-trip efficiency of a
battery refers to the ratio between the energy output of the battery and the energy input. The
efficiency is impacted by the state of charge, the charging and discharging power, the
temperature, but for simplicity a fixed efficiency value is taken. Lithium-ion batteries have the
highest round-trip efficiency of all storage technologies, making them most profitable for
renewable energy storage. The AC-to-AC round-trip efficiency accounts for the losses in the
power conversion system as well. The value for lithium-ion batteries is 86%. (Schmidt et al.,
2019)
-29-
3.2.3 Battery degradation
The charge capacity of batteries declines with time because of chemical reactions. Battery
suffers both from calendar degradation and cyclic degradation. Therefore, the annual
degradation of the system will depend on its uses. The main factors impacting the discharge
capacity of a Lithium-ion battery are temperature, depth of discharge (percentage of battery
capacity discharged each cycle), and C-rate (the speed at which the energy is discharged). The
chemistry with the least degradation rate is the LFP, which will be chosen for this study.
Figure 11 Degradation of lithium-ion batteries as a function of cycling (Preger et al., 2020)
An average value considering about one cycle per day during the year is calculated following
the methodology from (Schmidt et al., 2019)
-
(
𝐶𝑦𝑐#98 = 1 − 80% ";4!"#$
(
-
𝑇#98 = 1 − 80% B%&$!#
)
)
With cycle life 6000 and shelf life 20 years, the annual degradation considering 365 cycles per
year is 2.4%/year. This value is also aligned with Lazard’s estimate of 2.6%.
3.2.4 Self-discharge
An important aspect of electrochemical storage is the self-discharge. There are energy losses in
the charged battery when it is resting. However, in the case of batteries used for storing excess
solar power, the battery stays at rest for less than a day and there is usually more excess
production than what is stored, making it possible to keep on charging the battery to balance
-30-
out the energy loss. Moreover, lithium-ion batteries are found to have a discharge rate of
1%/day, which can therefore be neglected in our model. (Dulout, 2017)
3.2.5 Battery costs
Battery storage costs were expected to decrease due to growing production capacity for the
electric vehicles market. However, it is still a good estimate in 2023 to use 2017 costs for two
reasons. First, the range of estimates of battery costs in the literature is wide. The 2025
projection of stationary battery costs for residential and commercial use ranged from 200€/kWh
to 800€/kWh. Moreover, BNEF reported an increase in battery pack prices for the first time in
2022 due to inflation and increase in lithium and nickel prices. The prices for raw materials are
expected to stay high in the coming years and are very uncertain, influencing greatly the prices
of batteries.(BNEF, 2023, p. 10) Therefore, the cost estimations for battery systems will be
taken from a 2018 study whose analyses are a synthesis of values presented by several reputable
organizations such as the IEA. (Tsiropoulos, Tarvydas and Lebedeva, 2018) Stationary battery
system costs taken include battery packs and balance of system but also the power conversion
system and the engineering, procurement, and construction. Other developer costs such as grid
connection and transport are often excluded from analyses. The average costs for battery
stationary system costs in 2017 was 600€/kWh according to Tsiropoulos et. al. (2018).
The battery systems studied are rather small in size, which often allows for a simplified cabinet
containing all the components of the BESS. Maintenance is therefore generally low and is
estimated at only 0.5% of CAPEX.
Table 2 Battery techno-economic parameters
Shelf life
20 years
Cycle life
6000 cycles
AC to AC efficiency
86%
Battery Degradation
2,4%
Self-discharge
0%
CAPEX (€/kWh)
600 €/kWh
OPEX
0.5% CAPEX
-31-
3.2.6 Photovoltaic parameters
Photovoltaic panels have also known a great fall in prices in the past decades and are now more
stable, although their prices depend greatly on raw material costs. There is now more experience
on these types of facilities, and it is easier to predict costs and performance. Photovoltaic
modules are generally warrantied for 20 to 25 years, however there is no practical end of life.
The panels can continue to produce electricity after these 25 years, despite deterioration. Thus,
it is chosen in this case to estimate the life of the photovoltaic project at 30 years. During
operation, the panels suffer from a small annual degradation of efficiency, around 0,5%. The
techno-economic parameters are summarized in Table 3.
Table 3 Photovoltaic techno-economic parameters
CAPEX
1,15€/Wc
(photovoltaique.info,
2022)
OPEX
5€/kWc
Shelf life PV
30 years
(NREL, 2018)
Degradation
0,5%/y
(Jordan et al., 2016)
-32-
4 Geographic focus on France
4.1 The role of distributed PV and battery storage in the future
French energy mix
Since 2016, self-consumption is defined in the French law as the consumption of part of or all
the electricity generated on-site by a consumer, instantaneously or after a period of storage.
Battery storage makes sense from a national perspective. The French TSO RTE published in
2020 a study investigating different scenarios of the electricity mix until 2050 and their
implications on the electricity network. Six scenarios were studied, with electricity mix
assumptions ranging from 100% renewable models to high nuclear renewal ones. All scenarios
include a penetration of renewable energies of 50% at least. Solar and wind energy hold the
greatest share of renewables considered and their intermittent nature implies many
transformations of the electricity grid. Flexibility is needed to counter these implications on
many levels. Seasonal flexibility is important to overcome the high summer production of PV
and high winter consumption for heating, especially in France where the electricity demand is
very temperature sensitive, with an increase in 2.4GW of demand with the decrease of each
degree of mean temperature. In 2021, the storage fleet outside of pumped hydro reached 292
MW installed in France. (RTE, 2021b) One of the key findings of the French TSO’s “energy
pathways to 2050” report is the economic point for installing batteries to support solar power.
Most of the installed battery capacity is for now dedicated to providing ancillary services. In
the scenario which is based on the important development of distributed renewable energy
generation, 21 GW of battery deployment to sustain the self-consumption which is mostly
photovoltaic. (RTE, 2021a)
Behind-the-meter battery storage has recently started making sense for individuals as well.
Despite the decrease in solar panel prices, distributed PV deployment has been slower than
neighboring countries due to the low retail prices available thanks to the nuclear power plants.
In 2022, wholesale electricity prices reached a historic high of 1000€/MWh. Although this was
a punctual high, Figure 12 shows wholesale prices have increased from an average of 50/MWh
to an average of 400€/MWh with a volatility unknown before. The reasons for this record are
manifold. The first one is similar to other European countries who relied on Russian gas. The
merit order dispatch causes the electricity prices to be aligned with that of the peak power
generation, usually gas. The high price of gas induced high prices of electricity. Moreover,
France relies on 56 nuclear reactors, of which only 24 were operational in September 2022.
Electricité de France (EDF) had to stop many of them because of flaws which had been
discovered. This can also be deemed as punctual, but the nuclear park in France has an average
of 36 years old. Although their allowed lifetime will be extended over the initial 40 years limit,
they will need maintenance. Moreover, the construction time for new nuclear plants prevents
nuclear power from keeping up with electricity demand increase. Therefore, the future of
electricity retail prices is difficult to predict. As retail prices increase, battery storage becomes
-33-
economically profitable for companies, and the value of flexibility and higher self-sufficiency
rate becomes greater in the face of volatile prices.
Figure 12 Electricity spot prices In France since 2018(tradingeconomics.com, 2022)
4.2 The French electricity market
Since 2007, the French electricity retail market was opened to competition. Today a large
number of electricity suppliers offer market deals, while regulated tariffs still exist from EDF
for some categories of consumers.
The electricity bill of a commercial or industrial site in France is divided into three main
components. The first one is the supply charge of electricity, which depends on its supplier, the
second is the Tariff for the use of public power grids (TURPE), and the third one is made of
various taxes.
Supply charge of electricity
The supply charge of electricity depends on the quantity of energy in kWh consumed by the
site. In December 2010, a new law was voted to ensure the effective competition on the
electricity market, called the NOME law (New organization of electricity market). One measure
was to give access to alternative suppliers to the low-cost energy from nuclear power plants
EDF benefited from. This mechanism, called the Regulated Access to Incumbent Nuclear
Electricity (ARENH), allows suppliers to buy nuclear energy from EDF at a regulated price
which should be representative of the economic conditions of production. Since 2012, the price
has been set at 42€/MWh. The subscribed volumes are measured on forecasts of their
customers’ consumption and the volume of ARENH subscribed is 100 TWh, about 25% of the
incumbent nuclear generation. The ARENH right of consumers is calculated with their
consumption on off-peak hours (summer nights and days and mid-season nights)., so is usually
-34-
higher than 80%. Only a small share of the supply electricity comes from the wholesale market,
making retail prices low.
TURPE
The Tariff for the Use of Public Power Grids (TURPE) is regulated by the Energy Regulatory
Commission (CRE). It is used to finance the transmission and distribution grid. It covers both
the operational charges of the grid, energy to make up for losses on the grid, employee wages,
and others, as well as capital investments needed for grid improvement. The TURPE includes
one power charge based on the subscribed power, and one energy charge based on the
consumption. It does not depend on the location of the site and its distance to the grid.
In the case of self-consumption with no excess generation sent to the grid, the prosumer does
not pay extra TURPE for becoming a producer and does not pay the energy charge on the selfconsumed energy. The network tariff is fixed by the Energy regulatory Commission (CRE) for
average periods of four years.
Taxes
The main tax on electricity is the Contribution to the Public Service of Electricity (CSPE). The
revenue from this tax helps to finance the energy transition and the grids in zones not connected
to the national grid. Its value is of 22,5€/MWh since 2020.
4.3 Policy review for self-consumption
The first key driver of self-consumption in Europe is policy implementation by governments.
The French Energy Regulatory Commission (CRE) is an independent and impartial entity
created in 2000 to ensure the smooth running of the electricity and gas markets in France for
the benefit of end consumers and in application of energy policy objectives. It is therefore
responsible for managing the support mechanisms for renewable energies.
The main subsidies for self-consumption of photovoltaic energy are:
-
-
-
Tax exemption
In the case of PV capacity lower than 1MW, prosumers are exempted from paying the
main tax on electricity on all self-consumed energy, whether it is partial or total selfconsumption, as long as the annual production is under 240 million kWh. Above 1MW
capacity, the exemption is only for total self-consumption, with a zero-injection policy
to the grid. (photovoltaique.info, 2022)
Feed-in-tariff
Under 500 kWp capacity, a specific entity of EDF buys the excess electricity at a feedin-tariff which increases with inflation and is today at 110€/MWh. These contracts last
20 years.
Self-consumption calls for tenders
For capacities above 500 kWp, the CRE holds an annual call for tenders during which
projects are presented and bid for a self-consumption premium price. The rules promote
-35-
maximization of self-consumption by lowering the premium for a low self-consumption
rate under 50%. These contracts also ensure for the producer a guaranteed price of
50€/MWh for the excess generation. These contracts last only 10 years. The annual
subsidy for these projects is calculated with the following formula for plants which
benefit from CSPE exemption, with P the self-consumption premium, 𝐸!" the annual
self-consumed energy, 𝐸!C=# the annual sold energy, T is guaranteed price 50€/MWh
and 𝑀C the monthly calculated market price of electricity sold. The self-consumption
premium estimate in this study is 12€/MWh, the historic value. (CRE, 2022a)
𝑆𝑢𝑏𝑠𝑖𝑑𝑦; = 𝑃 ∗ 𝐸!" + (𝑇 − 𝑀C ) ∗ 𝐸?C=#
Although there are no specific subsidies for storage, both mechanisms allow self-consumers to
install a storage system with the photovoltaic panels. In fact, the energy is considered as selfconsumed whether it has been stored or not. However, in this case it is not allowed to take
electricity from the grid and store it. There is therefore a trade-off between the self-consumption
premium and the time of use optimization strategy.
4.4 Analysis of revenue streams in the case of France
4.4.1 End-user applications
The part of the electricity bill which is based on the energy use measured in kW peaked during
the month or the year, i.e. demand charge, exists in a French electricity bill only in the TUPRE.
Since the demand charge depends not on the maximum withdrawn power but on the subscribed
power for the period of time, very little value is found in peak-shaving. Indeed, subscriptions
tend to be overestimated to avoid any penalties for over exceeding power and reducing
theoretical maximum power withdrawal may not lead to a reduction of subscription value. The
risk of battery failure is another incentive not to reduce connection point power value.
Therefore, the peak-shaving case is not considered in this study for the case of France.
As previously mentioned, self-consumption is spreading in France and battery storage for selfconsumption increase is to be studied. Time-of-use tariffs are common for professionals and
make time-of-use optimization by load shifting a revenue stream to explore too. However, PV
plants which benefit from a feed-in tariff must prove that the electricity stored in the battery
only comes from solar generation. Therefore, it is impossible to combine load shifting, which
requires charging the battery from the grid at night, and self-consumption with feed-in-tariff for
excess generation. The two use cases for end-user application of battery identified in Table 4
will be studied.
Table 4 End-user applications use cases of the battery
SCI
Use case 1
Use case 2
LS
X
X
FIT and SC premium
X
X
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4.4.2 Grid services
The transmission system operator RTE must constantly ensure the balance between the
production and consumption of electricity. For this purpose, three balancing reserves exist and
are called frequency system services. The first reserve is activated in 15 to 30 seconds to
respond to an increase in consumption or a decrease in production. The backup to bring the
frequency back to 50 Hz is then taken over by the secondary reserve and the tertiary reserve
can be activated manually in case the secondary reserve is exhausted.
The primary reserve must respond to the loss of the two largest generating units in Europe, i.e.
3000MW. France contributes to this European reserve on the scale of 540MW. This reserve is
constituted by a daily call for tender where the producer commits to automatically modulate his
battery according to the frequency. The battery can be remunerated for participation in this
mechanism. However, the revenues are based on daily bids and might decrease fast with the
multiplication of battery storage capacities, since only 540MW are needed.
Secondly, behind-the-meter batteries can participate to grid services through the capacity
mechanism. Suppliers have an obligation to have production capacity available in proportion
to the consumption of their client portfolio during peak hours of the year. To attain this
objective, they buy capacity guarantees on a market where capacity certified by RTE are sold.
Capacities can be either for production or for demand-side response. This is a merchant
mechanism where these certified capacities are exchanged. In order to promote demand-side
response capacity, a call for tenders gives a complementary compensation for capacities, as a
€/kW/y. For a winner of this tender, the revenues from the capacity mechanism are guaranteed
for a duration going up to 10 years. To be a certified capacity, the battery needs to participate
in an adjustment mechanism for RTE for less than 25 days each year, mostly during winter, and
therefore only slightly impacts the other uses of the battery.
In conclusion, a battery can be remunerated by certain market mechanisms aimed at providing
the TSO with flexibility. These are mechanisms in which the battery can participate in addition
to the services provided to the consumer. If the participation in the FCR requires the battery to
be available for power orders by the TSO, the remuneration of the demand-side response call
for tenders can allow an additional annual income that will only affect the use of the battery for
25 days per year. Depending on site consumption and battery capacity, these additional revenue
streams can be further evaluated to establish cost effectiveness.
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5 Results and Discussion
5.1 PV and battery sizing method
A first study to size the PV + battery system is done studying only self-consumption increase
use of the battery because it is at the center of this study. Figure 13 shows results of the sizing
simulation for the tertiary building studied. PV size tested go from 300kWp, which is the
optimal size for a PV only setup, and 800 kWp, and storage size from 0kWh to 400kWh.
Figure 13 Results of sizing simulation. Self-consumption, self-sufficiency, equivalent solar tariff and equivalent full cycle for
battery storage size from 0kWh to 400kWh and PV from 300kWp to 800kWp
The graph representing the equivalent solar price shows that the minimum solar equivalent tariff
is obtained with minimum photovoltaic capacity and no batteries. In line with the literature on
battery storage, the application of the self-consumption increase alone does not make the battery
profitable. If a user is primarily looking for a cheap electricity supply, an installation with only
photovoltaics adapted to his consumption will surely be more attractive, but savings will still
be generated as long as the equivalent tariff remains below the retail price tariff.
There is no optimal PV or battery capacity that emerges from this modeling. However, these
results allow the consumer to have an overview of the different performances of the system and
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to choose an optimal system for each specific needs. A priority needs to be put on either one of
the four end-user KPIs calculated in the simulation. If the goal of the consumer is to minimize
its vulnerability in the face of volatile electricity prices, self-sufficiency will be the first KPI. A
look at the other three KPIs give additional information to avoid bad performance of the system
in one area. If the goal is to reach the highest possible self-consumption rate to waste less energy
while keeping a self-sufficiency higher than 20%, a 300kWp PV and 300 kWh battery could be
considered. But the information that the battery will only cycle about 80 times a year warns that
there could be more strategic alternatives.
The equivalent solar price of electricity is a common indicator to analyze a self-consumption
project, but it should be interpreted carefully. Battery storage increases this value but also the
quantity of energy consumed at this rate. Moreover, it does not account for the battery
degradation during its lifetime. Therefore, it is important to look also at the Net Present Value
of the project for the consumer.
5.2 Comparison of two use cases
End-user applications for bill savings of behind-the-meter battery storage are two-fold: selfconsumption increase, and load shifting. Since it has been shown that the two can only overlap
by suppressing the possibility of taking advantage of subsidies for self-consumption, the
comparison is made between the two revenue stacking schemes highlighted in Table 4:
•
•
increase of self-consumption without sale of excess generation and self-consumption bonus, but
with load shifting on days without surplus.
increase of self-consumption with the self-consumption premium and feed-in-tariff for excess
generation,
The two cases were compared regarding the two indicators which reflect the main values of the
battery for a consumer: self-sufficiency and Net Present Value.
Figure 14 shows that the larger the installed PV size, the less the battery negatively impacts the
profitability of the project. However, the mere presence of the battery significantly reduces the
savings generated by making it impossible to sell the excess generation.
In the case of self-consumption increase with self-consumption premium at 12€/MWh and the
feed-in-tariff at 50€/MWh for excess generation, Figure 15 shows that the battery harms the
profitability of the project regardless of the size of PV. However, the additional PV capacity
and the battery allow to reach a better self-sufficiency.
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Figure 14 Self-sufficiency and Net Present Value as a function of PV size and battery size in the case of self-consumption
increase and time of use tariff optimization revenue stacking
Figure 15 Self-sufficiency and Net Present Value as a function of PV size and battery size in the case of self consumption
increase with additional revenues from self-consumption call for tenders
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5.3 Values of battery storage for the consumer
The installation of a battery behind the meter in combination with a photovoltaic production
allows a consumer to make savings on his electricity bill. However, these savings will be lower
than in the case of a solar installation without battery. The other values of adding a battery are
however numerous. First, it allows for greater resiliency in the face of volatile electricity prices
and possible blackouts on the national grid. The battery also has other non-economic purposes,
such as increasing power quality and providing backup power for a few minutes before
alternative generators take over in the case of a load shedding producing an outage.
By increasing the share of solar self-consumption in his consumption by a few percent, the
consumer can also make his energy consumption more low carbon. This particular point is
discussed in the next section in the context of a low-carbon electricity mix thanks to nuclear
power plants in France and the controversial sustainability of lithium-ion battery
manufacturing.
5.4 Sustainability of batteries
The deployment of electric cars worldwide as a vector of energy transition has put the lithiumion battery under the spotlight and criticism for its environmental footprint. Many studies
explore the lifecycle emissions of BEVs (battery electric vehicles) and show that the
manufacturing stage emits more carbon dioxide than ICEV (internal combustion engine
vehicles) because of the battery. (IEA, 2022a) Battery production is very material intensive and
the extraction and transformation of these materials is not always done in a sustainable way.
One example is the extraction of lithium from hard rock mines, which requires a great amount
of energy, still mainly provided by fossil fuels. Other sustainability issues arise from battery
production, such as the pollution of soil and water resources because the mining of lithium,
cobalt and nickel, require a lot of chemicals. These activities also consume great amounts of
water in regions where it is already scarce. Finally, 60% of cobalt production comes from the
Democratic Republic of Congo where forced and child labor is a verified fact. No regulations
in the EU regulate human rights violations in producing countries for now the forced labor or
the GHG accountability of products sold in the EU but produced elsewhere.(Transport &
Environment, no date)
-41-
Xu et al. estimate that the carbon footprint of cell manufacturing will decrease by 50% between
2020 and 2050. The main driver of the decarbonation is the low carbon electricity transition
which reduces the impact of cell manufacturing with a cleaner electricity. The investment of
battery producers in giga factories in Europe where carbon intensity of the mix is lower than in
China will help to reduce the emissions from the manufacturing step. The organization
Transport and Environment identified 22 planned giga factories in Europe. Production capacity
should rise from 460 GWh in 2025 to 730 GWh in 2030. The development of the field is mainly
due to the demand increase for electric vehicles, but also drives down carbon footprints of
stationary batteries. These automated giga factories drastically reduce emissions during the cell
and battery pack manufacturing phase, the CEA calculates emissions of 100kgCO2/kWhbatt.
The material extraction stage is now the main source of emissions and we can identify two
reduction levers: more energy efficient and renewable sourced processes and recycling of old
batteries. (Chengjian Xu et al., 2022)
Figure 16 Carbon emissions reduction estimates for battery cells manufacturing (Chengjian
Xu et al., 2022)
Only 10% of batteries are recycled today. However, the increase in demand for lithium-ion
batteries and the regulatory framework development will cause this industry to develop. While
the European Commission now compels to recycle only 50% of the weight of lithium-ion
batteries, it has agreed on new rules on batteries and battery waste to make them more
sustainable. The rules include strict recycling of materials, enabling better second-life of
batteries, better traceability with mandatory carbon footprint and rate of recycled materials
-42-
reporting, as well as stronger information requirements. The first key regulation affecting the
recycling is the requirement of recycling of end-of-life batteries, which is raised to 65% of total
weight in 2025 and 70% in 2030. Recovery rates for each material is also included, reaching
95% for nickel and cobalt and 70% for lithium in 2030. The second key regulation is the
mandatory declaration of recycled content in 2025, followed by specific required percentages
of recycled content per material in 2030. (European Commission, 2022a)
5.5 Sensitivity Analysis
A sensitivity analysis was conducted on key inputs of the model: the investment costs of both
battery and photovoltaics, which impact the annual cost of the system for the consumer, the
battery degradation rate, which impacts the performance of the system, and the selfconsumption premium and retail electricity price, which influence the profitability of each
MWh of self-consumed energy. The chosen set-up is 600kWp of solar panels with a 300kWh,
2-hour discharge battery.
The sensitivity analysis shows that the influence of the investment cost of the battery on Net
Present Value is weak compared to that of the investment cost of the photovoltaic. This is due
to the fact that the storage system is small compared to the PV system.
Another key output of this graph is that the self-consumption premium plays a small role in the
profitability of the system. However, it drives the equivalent cost of solar energy down and
helps the project to be profitable in the case of lower electricity retail price.
Figure 17 Sensitivity analysis on project lifetime economies for the use case self-consumption increase + load shifting
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Figure 18 Sensitivity analysis on NPV for the use case self-consumption increase with self-consumption premium
The sensitivity analysis shows that in both cases, the NPV of the project for the consumer is
highly sensitive to retail electricity price. Indeed, the incomes in the NPV formula mostly come
from bill economies, which are proportional to the retail electricity price with a ratio equal to
the total energy self-consumed. The sensitivity of Net Present Value to the price of electricity
is somewhat lower in the scenario with the self-consumption premium than in the scenario with
load shifting. This is due to the fact that the additional income in the former is not directly
dependent on the price of electricity, while that in the latter depends only on the price of
electricity. The self-consumption premium, which is decided through a call for tenders, may
vary year to year depending on average electricity prices. For example, if electricity prices so
low that it becomes more profitable to sell electricity to the grid than self-consume it, the selfconsumption premium may grow to help self-consumption projects become profitable.
However, the self-consumption premium is decided by project for a period of ten years, so will
not vary according to electricity prices in one specific project.
For a 15% decrease in electricity prices, the difference in Net Present Value between the two
scenarios is only 30 000€. This low figure is explained by the low revenue share of the selfconsumption premium or load shifting in these scenarios. As shown in Figure 19, the increase
in self-consumption is responsible for the majority of the savings, and the additional revenue is
only a small part given the low value of the self consumption premium.
-44-
Annual net revenues for the
consumer (€)
Self-consumption economies
Self-consumption premium revenue
Feed-in-tariff revenus
70000
60000
50000
40000
30000
20000
10000
0
1
2
3
4
5
6
7
8 9 10 11 12 13 14 15 16 17 18 19 20
Years of the project life
Figure 19 Net cashflow for the consumer during the lifetime of the project
5.6 Conclusion
This study seeks to evaluate the profitability of an energy storage system for a professional
consumer in France. Indeed, the high penetration of energy production from variable renewable
sources will be responsible for a strong need for flexibility on the network to maintain the
balance between supply and demand. Diffuse batteries could participate in filling this need.
A techno-economic analysis on a photovoltaic plus battery storage project is carried out for an
average tertiary consumer with a connection power between 250kVA and 1000kVA. The
results show that the battery increases the gross savings on the electricity bill, but not enough
to pay back the investment of this system and the net savings for the consumer are higher with
a PV system alone. The most profitable use for the battery is to increase self-consumption in
the current context of high electricity prices. However, this profitability decreases very quickly
with these prices. In addition to the economic profitability, the battery allows to increase the
share of energy consumed by the site from 2% to 8% while keeping an acceptable economic
profitability. This allows a consumer to protect himself against changes in the quality and
reliability of power on the network.
Batteries are more carbon-intensive than photovoltaic panels and therefore may not be a
sustainable solution in France’s low-carbon electricity mix. However, policies are
strengthening to promise a more sustainable future for lithium-ion batteries, reducing the carbon
footprint of such projects.
6 Limitations and future work
This study focuses on the benefits for the consumer when investing in a coupled PV battery
system. With a time-independent feed-in-tariff and a model which does not account for the
sensitivity of battery health to the charging power, the time at which the battery was charged
did not matter. From the grid point of view, an optimized charging schedule would be beneficial
by reducing the instantaneous power injected. Instead of charging all the excess generation until
-45-
the time when the battery is full and injecting for the rest of the time when there is excess
generation, battery charging would be spread out through all the hours during the day when
there is excess energy. This scheduling requires consumption and production forecasts. A costbenefit analysis could be done on this subject to compare the actual benefits for the grid
compared to the overhead costs of this optimization.
To assess further the profitability of end-user application, a more thorough study of peak hour
tariff influence on economies could be evaluated. A study on dynamic tariff scheme could also
be conducted. In the case of dynamic tariffs, the spread between lowest and highest electricity
prices during the day is much higher, therefore the flexibility of the battery has more value. In
that case, a linear program can be written to minimize the supply cost of electricity. For
commercial and industrial sites, it is not common in France to choose this possibility. The
ARENH mechanism also reduces the value of optimizing on spot prices because only a small
part of electricity will come from the wholesale market. Moreover, it leaves the consumer
vulnerable in the face of volatile electricity market when the battery capacity is not high enough
or the battery needs maintenance.
Grid services revenues have been discussed but not integrated in the use case even though they
can generate very important additional revenues. It is chosen here to provide services to the
consumer first, but it could be profitable to pay with frequency regulation on days when there
is no solar surplus, and the battery is not used. A study could be done to compare the revenues
of these services against the wear and tear that these additional cycles generate on the battery
and decrease the services to the consumer at the end of the battery's life.
The capacity mechanism would be a simpler way to earn income, as it only requires the battery
to be available for fewer than 25 days per year, as decided by the TSO, depending on the supply
stress. The laws in place in France promote the use of batteries in the capacity mechanism, with
the call for tenders for load shedding, in which batteries can participate. However, the
remuneration remains unstable. Since 2022, sites of less than 1MW can respond to the call for
tenders for a period of up to 10 years, which could improve the revenue forecast of a behindthe-meter storage asset. This leads to the added complexity of having to manage multiple
stakeholders in addition to the consumer.
-46-
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