is it profitable to develop a large-scale pv plant without

Is it profitable to develop a large-scale PV plant

without subsidies? Business Plan Analysis for locations

in Spain, Portugal and United Kingdom

Master Thesis

Krzysztof Marek Działo

Escola Tècnica Superior d'Enginyeria Industrial de Barcelona

Universitat Politècnica de Catalunya

Barcelona 2018

Is it profitable to develope a large scale PV project without subsidies?

Business Plan Analysis for locations in Spain, Portugal and United Kingdom

Programme: InnoEnergy Master SELECT Environomical Pathways for Sustainable Energy Systems

Conducted at:

KTH Royal Institute of Technology, Stockholm

UPC Universitat Politècnica de Catalunya, Barcelona

Master Thesis:

Is it profitable to develop a large-scale PV plant without subsidies?

Business Plan Analysis for locations in Spain, Portugal and United

Kingdom

Supervisors:

Lucas Philippe Van Wunnik – First UPC Supervisor

Fredric Horta – Second UPC Supervisor

Cooperation: João Garrido – Independent Renewable Energy Advisor

Solar Data: Solargis s.r.o.

Mýtna 48

81107 Bratislava, Slovakia

Convocation: October 2018



ABSTRACT

A constantly increased amount of the renewable sources of energy has led to growth of its cost

competitiveness on the global energy market. It is supported by the fact that related

technological and infrastructural costs have been decreasing in the recent years leading to the

solar grid and market parity, that have been already achieved in the south regions of the

European Union. Thus, several market movements can be currently observed: phasing out of

the governmental support mechanisms such e.g. Feed-in-Tariffs; investments in the subsidy-free

solar PV projects across the Europe; further movement towards alternative forms of energy

contracts e.g. Power Purchase Agreements (PPAs). The lastly mentioned PPAs can also be present

in the corporate form that can be beneficial for companies aiming for fast decarbonization of

their electricity consumption.

The following work will try to answer the question whether it is possible and profitable to develop

a 50 MW large-scale PV project without any form of the governmental support. Three different

locations: Alcala de Guadaira in Andalusia, Spain, Evora in Alentejo, Portugal and Milton Keynes

in the South East England, United Kingdom have been chosen for the analysis. The selection of

the regions with similar markets and solar conditions (Spain and Portugal) will enables to examine

the non-climate factors influencing the profitability of the PV project, while the United Kingdom

case will show the importance of the proper solar conditions. The technical analysis has been

conducted in order to estimate the yearly energy production while the economic analysis will try

to answer the major research question about the PV project profitability. The profitability of the

has been determined by comparison of the calculated internal rates of return with the return

rates expected by the investors. Eventually, the sensitivity analysis has been accomplished in

order to identify the external factors that influences on the system’s profitability. The impact of

various irradiation levels, different CAPEX and OPEX costs, electricity prices and debt-to-equity

ratio has been checked.

The performed analysis confirmed that the development of the large-scale PV plant without

governmental support is possible in Spain and Portugal. The best economic performance has

been noticed in case of Portugal due to more favourable policy towards renewable sources of

energy. Regarding the United Kingdom, the poor irradiation conditions are the major obstacle for

the profitability target. However, the performed sensitivity analysis indicates that if solar PV costs

continue its decreasing trends, the mentioned profitability can be also expected in the countries

with lower irradiation levels in the nearest future. The ongoing solar markets actions confirms

that the obtained results are credible and that the aforementioned transition towards

unsubsidized solar PV projects is possible.



LIST OF CONTENT

1. INTRODUCTION ................................................................................................................... 10

1.1. BACKGROUND OF THE PROJECT .................................................................................. 10

1.2. OBJECTIVE OF THE PROJECT ........................................................................................ 13

1.3. WHY WITHOUT SUBSIDIES? ......................................................................................... 13

1.4. SCOPE OF THE PROJECT ............................................................................................... 15

2. ADDITIONAL INFORMATION ................................................................................................ 17

2.1. EUROPEAN ENERGY SITUATION .................................................................................. 17

2.2. ELECTRICITY MARKET ................................................................................................... 18

2.2.1. POWER PURCHASE AGREEMENTS ....................................................................... 19

2.2.2. PRICES ON THE WHOLESALE MARKET ................................................................. 20

2.3. SOLAR PHOTOVOLTAICS .............................................................................................. 21

2.3.1. SOLAR PV STATISTICS ........................................................................................... 21

2.3.2. LARGE SCALE PV – TECHNICAL DESCRIPTION ...................................................... 23

2.3.3. STORAGE IMPLEMENTATION ............................................................................... 25

3. LITERATURE REVIEW ............................................................................................................ 26

4. FRAMEWORK ....................................................................................................................... 28

4.1. TECHNICAL ANALYSIS ................................................................................................... 28

4.1.1. LOCATION AND CLIMATE DATA ........................................................................... 29

4.1.2. SOFTWARE DESCRIPTION .................................................................................... 29

4.1.3. COMPONENT SELECTION ..................................................................................... 30

4.1.4. PLANT MODELLING .............................................................................................. 31

4.2. ECONOMIC ANALYSIS .................................................................................................. 35

4.2.1. FINANCIAL TOOLS ................................................................................................ 35

4.2.2. MAJOR ASSUMPTIONS ......................................................................................... 37

4.2.3. CASE STUDIES ...................................................................................................... 41

4.2.4. FINANCIAL MODELLING ....................................................................................... 42

4.2.5. SENSITIVITY ANALYSIS .......................................................................................... 43

5. RESULTS ............................................................................................................................... 44

5.1. TECHNICAL RESULTS .................................................................................................... 44

5.2. ECONOMIC RESULTS .................................................................................................... 48

5.2.1. BASE CASE RESULTS ............................................................................................. 48

5.2.2. SENSITIVITY RESULTS ........................................................................................... 53

6. CONCLUSIONS ..................................................................................................................... 59



7. BIBLIOGRAPHY ..................................................................................................................... 61

APPENDIX I ................................................................................................................................... 67

APPENDIX: II ................................................................................................................................. 70

APPENDIX: III ................................................................................................................................ 70

APPENDIX: IV ............................................................................................................................... 71



LIST OF FIGURES

Figure 1: Solar Pv competitiveness [7]. ........................................................................................ 12

Figure 2: PCR users and members [25] ........................................................................................ 19

Figure 3: PV Price Development considering the Economies of Scale Effect [37] ....................... 22

Figure 4: General layout of a utility-scale PV plant [13] ............................................................... 24

Figure 5: JinkoSolar JKM 370M-72 Specifications [50]................................................................. 30

Figure 6: Orientation of the PV modules ..................................................................................... 32

Figure 7: Module degradation over project lifetime.................................................................... 34

Figure 8: CAPEX division .............................................................................................................. 40

Figure 9: Conversion process ....................................................................................................... 45

Figure 10: Selected inverter topology [13] .................................................................................. 47

Figure 11: Cumulative FCFF for all the examined locations ......................................................... 49

Figure 12: The cost division during the lifetime of the project .................................................... 50

Figure 13: Revenues vs Expenditures in all the examined locations ............................................ 51

Figure 14: Cumulative FCFE for all the examined locations ......................................................... 52

Figure 15: Price Sensitivity Analysis – post-tax IRR and payback time ......................................... 57

Figure 16: Sensitivity Analysis – Debt-to-Equity Ratio ................................................................. 58



LIST OF TABLES

Table 1:Framework of the Analysis .............................................................................................. 28

Table 2: Climate and location data .............................................................................................. 29

Table 3: Major Project Settings [54] ............................................................................................ 31

Table 4: Losses Description .......................................................................................................... 32

Table 5: OPEX Components ......................................................................................................... 38

Table 6: Detailed case studies assumptions – base case scenario ............................................... 41

Table 7: Sensitivity Analysis Components .................................................................................... 43

Table 8: Results of the simulation: Generated Electricity and Plant Performance Indicators...... 46

Table 9: Solar PV plant parameters ............................................................................................. 47

Table 10: Free cashflow to firm - Results ..................................................................................... 48

Table 11: Free cashflow to equity - Results ................................................................................. 52

Table 12: Location comparison .................................................................................................... 53

Table 13: CAPEX & OPEX Sensitivity Analysis – post tax IRR ........................................................ 55

Table 14: CAPEX & OPEX Sensitivity Analysis – payback time ...................................................... 56



LIST OF ACRONYMS

ACER – Agency for the Cooperation of Energy Regulators

ASP – Average Selling Price

BDEW – Bundesverband der Energie

BoS – Balance of the System

CAPEX – Capital Expenditures

CEER – Council of European Energy Regulators

CfD – Contract for Difference

CF – Capacity Factor

DC/AC – Direct/Alternate Current

DIF – Diffuse Horizontal Irradiation

EBITDA – Earnings Before Interests, Tax and Depreciation

EBIT – Earnings Before Interests and Tax

EBT – Earnings Before Tax

EES – Electrical Energy Storage

ENTSOE – European Networks for Transmission System Operators

EPC – Engineering, Procurement and Construction

FCFE – Free Cashflow to Equity

FCFF – Free Cashflow to the Firm

Fit – Feed-in-Tariff

GHI – Global Horizontal Irradiation

IFRS – International Financial Reporting Standards

IPP – Independent Power Producer

IRR – Internal Rate of Return

LCoE – Levelized Cost of Electricity

MCO – Market Coupling Operator

NPV – Net Present Value

NRA – National Regulatory Authority

OPEX – Operational Expenditures

O&M – Operation and Maintenance

PCR – Price Coupling Regions



PPA – Power Purchas Agreement

PR – Performance Ratio

PTC/ITC – Production/Investment Tax Credits

RPS – Renewable Portfolio Standards

STC – Standard Thermal Conditions

TMY – Typical Meteorological Year

WACC – Weighted Average Cost of Capital

XBID – Intraday Cross Border Solution



1. INTRODUCTION

The major purpose of the introduction chapter is to familiarize readers with all the necessary

information about the given dissertation. This chapter has been divided into four major parts.

Firstly, the background information will try to introduce the reader into the selected topic. Then,

the objective of the project will be formulated, following by the discussion about the research

topic. Eventually, the scope of the project, including the justification of all the major decisions will

be described.

1.1. BACKGROUND OF THE PROJECT

Due to international agreements and general movement towards sustainable solutions,

renewable sources of the energy have always been helped by different forms of the governmental

incentives, usually described in the literature as subsidies or support mechanisms. According to

the information presented in [1] six major support mechanisms can be distinguished:

• Direct payments to developers for supplying renewable electricity to the grid in the form

of Feed-in Tariffs or payments of the difference between previously decided strike price

and present wholesale market price – Contracts for Difference.

• Reverse Auctions and Tenders – usually for independent power producers that bid

competitively for the possibility to construct the project according to previously

determined conditions. The conditions are usually set by off-takers or policy makers

considering the specific energy needs and the winner is the developer that presents the

lowest tariff bid.

• Market-based instruments – quantity-based mechanisms such as: Renewable Portfolio

Standards or Quota Obligations that required from the utility that a certain amount

electricity will be coming from the renewable sources of energy. The quantities are

usually confirmed in forms of renewable certificates or carbon certificates.

• Tax incentives – mechanisms that incentivise the investment in renewables by special

tax reductions. As an example: Production or Investment Tax Credits.

• Soft Loans – loans with a special rate conditions, usually much more attractive that the

majority offered by the market. These mechanisms are mostly used in the early stage of

a technology deployment.

• Capital Grants – grants coming from public sources, that help to decrease the up-front

financial costs. This option was mostly used in the earliest stages of the PV development.

All of the mechanisms aimed to both, help developers to improve their cashflows and for the

entrepreneurs to competitively enter the market. The introduction of subsidies helped to

increase the share of renewables in the European power mix and consequently enabled the

renewable technologies to mature [2]. It was correctly believed that through development of the

industries, production and supply chains, the overall cost of the technology will decrease in the



future. Described process can be assign to the “Learning Curve1” and “Economies of scale2”

concept that may eventually result in withdrawal of the subsidy policies.

Despite huge increment in renewable generation and further steps towards sustainable

development, the path of managing and organising subsidies was far away from being perfect. In

Spain, limiting the previously negotiated subsidy contracts has led to many difficulties for projects

development influencing disadvantages for all the related business such solar PV factories and

shops. Additionally, common rush in order to receive higher levels of subsidies has led to the

emergence of many falsely registered installations that are currently being investigated on the

suspicion of financial frauds [3]. Nowadays Spanish government has to face many arbitration

processes over cuts to the renewable energy subsidies that may yield in millions of Euros of

compensation to the developer companies [4]. As it can be noticed, the support mechanisms

have brought many advantages to the solar industry, however, the way of its implementation

resulted also in many disadvantages. Thus, it is believed, that there is a still need for new solutions

regarding market mechanisms that may improve present situation.

Currently, the moment of transition in the renewable energy industry can be observed. It is

especially visible in the solar and wind energy technologies. Constantly increased amount of the

renewable sources of energy has led to increment of their cost competitiveness versus

conventional energy sources. This phenomenon can be widely observed across the world and

influences many specialists and scientists. During a webinar regarding the solar market parity in

Europe [5], Mr. Tomas Garcia, claimed that the Southern countries such as: Spain, Portugal or

Italy has already reached the solar market parity. Market parity can be defined as the moment,

when generation costs expressed in the form of LCoE3, considering the wholesale market prices,

can be competitive with the conventional energy sources such as coal or gas power plants.

Additionally, in 2016 BayWa r.e. financed study about grid parity understood as, when the PV

electricity cost is equal to the electricity price from the grid [6]. The study was performed by the

Becquerel Institute in Brussel. The results show that in places such as: Cadiz in Spain or Ragusa in

Italy the grid parity has already been reached [7]. The grid and market parity phenomena are

believed to spread across the entire European continent, also considering other renewable

energy technologies. The results of this studies have been presented in the Figure 1:

1 Learning Curve - is a process where people develop a skill by learning from their mistakes. A steep learning curve

involves learning very quickly [75] . The PV learning curve displays the relationship between the average selling price of a PV module and the cumulative global shipments of PV modules. 2 Economies of Scale – reduced costs per unit that arise from increased total output of a product [78]. 3 LCoE – levelised cost of electricity - measures lifetime costs divided by energy production, thus it calculates present

value of the total cost of building and operating a power plant over an assumed lifetime. It is a tool that allows on the comparison of different energy technologies (e.g., wind, solar, natural gas)..



Figure 1: Solar Pv competitiveness [7].

Solar grid parity is additionally supported by the report presented during Aurora Spring Forum

2018 [8]. It claims that, if solar continues its historical trend of cost decrease, solar grid parity

might be also reached in countries with significantly lower values of solar irradiation such as Great

Britain. That information creates a huge opportunity for development and deployment of the new

subsidy-free PV projects. Aurora Energy Research in its report [9] has estimated, including the

cannibalization effect, that almost 40% of all the planned renewable projects could be deployed

as a subsidy-free by 2030. This percentage corresponds to around 60 GW that could be installed

in North-West Europe countries. Almost half of this value is represented by the new solar PV

projects.

The introduced market and grid parity concepts will allow developers on building PV plants

without relying on support mechanisms, because they will be able to compete on the wholesale

markets or sell energy directly to large consumers through commercial power purchase

agreements [10]. This topic is currently widely discussed by many specialists and business

developers during many different meetings and events [11], [12]. The general outcome from the

events was very positive regarding further development of the unsubsidized solar PV projects. It

might be an opportunity to introduce changes to the current power markets such as: further

cost`s reduction or increment in the number of investors and new PV business models.

As it can be seen, the changing situation in the PV industry attracts many scientists and solar

developers as well as implies positively on their willingness towards further changes. It is believed

that the subsidy-free renewable energy models may play an important role in the further

development and shaping of the European Energy System, thus more detailed analysis of this

issue is very interesting and might be very useful in the future. It is believed that this work will

serve as a useful, approximate tool to assess the profitability of the utility scale PV projects,

considering different technical, economical and geographical factors.



1.2. OBJECTIVE OF THE PROJECT

The following work will try to answer the question whether it is possible and profitable, as for

year 2018, to develop a large-scale PV project (50 MW), without subsidies. As well as what are

the major factors that influences the profitability of the project. The term ‘without subsidies’

means deployment without any forms of government-mandated support that have been mention

previously. The analysis will be performed using particular locations in Spain, Portugal and UK.

The obtained results will be used to compare the profitability of the large-scale PV project

between Spain, Portugal and UK.

1.3. WHY WITHOUT SUBSIDIES?

Since the concept of subsidy-free projects is reasonably young, there is a huge debate among

specialists whether such model has a right to succeed and positively influence on the market of

renewables and their further development. Similar to the subsidized installations, the new

models will have to face with the challenges related to:

• Technology and Grid Integration

• Finance

• Legal Framework

Concerns regarding technology and grid integration might be expressed by the question whether

grid can maintain stability with constantly increased number of renewables. Moreover, there are

opinions questioning the quality and execution of the new projects under further cost pressure.

As an example: leaving cables on the ground instead of burying them or using the worse quality

materials that may result in more frequent failures.

One of the major questions related to the financial aspect is: Considering the constant increment

of the production efficiency, is it possible that costs of renewable technologies will be constantly

decreasing? It is believed that due to the increase of the renewables share, the overall price of

electricity might become more dependent on additional factors such as weather conditions. That

may influence and handicap precise price estimation [2]. Moreover, there is an important issue

whether investors can manage the merchant risk4? Another concern is related to the

‘cannibalization effect’, that describes the situation when more solar PV is injected to the grid

during the central hours of the day. It increases the electricity supply, resulting in the wholesale

price reduction that influences the developer’s income and profitability of the project. Eventually,

there is a group believing that nowadays it is impossible to deliver a large-scale project that has

been left completely without any form of support [8]. Since the costs of providing constant and

stable electricity 24h/7 through the whole year are always spread between consumers, suppliers

and government, thus being precise there always exist a form of support.

4 Merchant Risk – the risk related to thee fact that the developers can earn only what the wholesale market will pay

rather than having secured earnings by the governmental contract [2].



In terms of legal objections, there are comments whether national governments together with

the European Organisations will be able to provide appropriate legal framework that will enable

and ease further development and functioning of the project without supporting schemes.

On the contrary, the issues addressed to the technological challenges and integration of

renewables to the grid, will emerge despite the fact whether the new renewable projects are

being subsidized or not. Increased share of renewables forced further development of new

technologies being able to improve and support the major concerns of grid stability such as

frequency and voltage control. Already existing wind and solar power plants are being forced to

follow the requirements described as by grid codes thus the subsequent technological

improvement, including storage technologies, will be unavoidable [13]. Additionally, it may foster

further development of new concepts such as flexible smart grids or business model such as

provision of an ancillary services.

Considering the financial aspect, vision of the energy market that is fully independent from the

policy and government decisions but instead is driven only by the pure market powers might

attract investors. Even though the merchant risk still might be an issue, the risk related to the

retroactive revision of already approved projects disappears thus investors may feel more

comfortable about their investments. Lack of the binding agreements with the government might

incentivise investors to generate electricity when it is mostly needed in order to increase their

incomes [2]. Moreover, the higher income can be also achieved by decreasing capital and

operational expenditures of the PV installations across the whole Europe. Financial costs related

to the investment in the PV projects are also decreasing due to higher investors’ attention

towards solar photovoltaics, that increases the competitiveness on the market [5]. Many experts

additionally believe that long term contracts – power purchase agreements - between suppliers

and large scale industrial or commercial consumers could be a solution to the decrease in the risk

related with estimation of the wholesale market prices. Development of PPAs is not only

beneficial for the project developers but also for the large-scale consumers (e.g. Google or Apple),

aiming in fast decarbonisation of their electricity consumption. The confirmation, that they are

purchasing a green energy will accelerate fulfilling their sustainability targets. According to the

information presented in the report [9], development of the unsubsidized renewable energy

projects will contribute to the positive influence on the environment by further decreasing of the

carbon intensity.

Regarding the financial support it is believed that overall trend towards energy transition will

influence on national governments towards development of legal frameworks favouring and

facilitating appearance of further non-subsidy projects. Since the beginning of the renewables in

Europe we can observe many different political mechanisms that have been trying to adapt the

new technology to the market. Projects without subsidies model can be considered as a new step

forward. It is believed that unsubsidized models will help to re-create the energy market and

additionally enables entering new business models.

Despite negative opinions and concerns, both from the scientific and business environments,

many investors see the reasons to push ahead with unsubsidized models, even though, at

present, they are going beyond pure financial considerations. They believed that it might be



a valuable investment for securing future businesses, or for accessing and booking the most

favourable locations or grid connection points, that considering current renewables development

might be an issue in the future. The number of approved or waiting in the pipeline projects can

be taken as a confirmation to this statement [14]. According to Mr Pietro Radoia [15], the amount

of subsidy-free PV projects that have been built or are currently under construction, only within

European Union, is around 676 MW. This number shows the potential behind the new subsidy-

free projects.

1.4. SCOPE OF THE PROJECT

In order to fulfil the objective that has been set for this work, a separate framework will be

developed. The proposed structure will include all the necessary steps and tools that will be used

for the analysis. The major parts of the framework will represent a technical analysis followed by

an economic evaluation and sensitivity analysis. Considering the function of this sub-chapter, it

will serve as the justification of the most important decisions taken during the project

development.

Development of the large-scale PV project is a very complex process that involves many specialists

from different fields. According to the document [16] every solar PV project can be described by

three major variables: application segment, financing scheme and financial business model.

Regarding the first variable, project has to be defined according to one of the following

application segments:

• Single Family

• Multifamily Residential

• Commercial/Public/Industrial Buildings

• Solar Farms

The same large, utility-scale solar PV farm will be analysed for every location. According to the

article [17], it is difficult to define the exact size from which the PV plant can be named large-

scale, however all the research institutes agree that it has to be a megawatt-scale project.

Additionally, the utility-scale plants are selling the produced electricity to the wholesale utility

buyers, usually by signing the different forms of power purchase agreement [18]. The size of the

plant – 50 MW has been selected based on the real-life project information that have been

provided by Global PV Consulting Company. The project is being used as a source of comparison

for the obtained results.

Secondly, the project has to be financed using one or combination of different financing schemes.

Considering this analysis, the project will be financed by the combination of debt in the form of

bank loan and equity, where the investors have a stake in the project or ownership of the assets.

These two financial schemes are often combined together. It is mainly due to better risk

management and funds allocation during the project lifetime. Since the equity investors,

expecting huge returns, can tolerate higher risk operations, they will be more involved in the

initial phase of the project, where the risk of project failure is higher because of uncertainties.

The debt funding will occur during later phases of the project that provides stable returns from



the investment [16]. For the simplicity reasons, in this work, both financial schemes will be

allocated equally during the construction and operations phases of the project.

Considering the last variable, the financing scheme, operating strategy and all the involved parties

have to be connected by the particular financial business models e.g. self-consumptions, selling

electricity on the whole-sale market or power purchase agreement. The wholesale long-term

power purchase contract with a stable floor price will be used in this work. This decision has been

made due to ongoing popularity of the PPA in solar PV projects as well as difficulties in estimation

of the future whole-sale electricity prices.

Once the three major variables have been decided the project can proceed to the development

stage. It is a very complex process that involves many specialists from different fields. It can be

divided into the following phases [1]:

• Concept and site selection

• Prefeasibility study

• Feasibility study

• Financing and contracts

• Engineering, construction and commercial operation

• Decommissioning

The more advanced phase of the project, the more detailed technical and financial assessment

needs to be performed, thus it is necessary to use information from already achieved steps for

further actions. This dissertation will be mostly focused on the concept analysis, supported by

prefeasibility and feasibility study that includes technical and financial evaluation of the preferred

option.

To properly examine the objective question, three different locations have been chosen for the

analysis: Alcala de Guadaira in Andalusia, Spain, Evora in Alentejo, Portugal and Milton Keynes in

the South East England, United Kingdom. The selection of the exact locations can be justified

based on the currently existing solar projects that have been commissioned or are presently

under construction. Most recently, the renewable energy company BayWa r.e. and the

Norwegian energy supplier Statkraft has signed the a 15-years Power purchase agreement for a

subsidy-free, 170MW solar plant that will be placed near to Alcala de Guadaira [7]. In Portugal,

the 28.8 MW solar facility is being planned next to Evora city based on the 10-years PPA with local

power distributor Axpo Iberia [19]. Lastly, there is already existing Anesco 10 MW – first fully

subsidy-free project in Great Britain located near to the Milton Keynes town [20]. By choosing

places with already confirmed plans or existing installations, there is a certainty that these venues

have been previously checked in terms of solar conditions as well as restrictions related to the

land availability and grid connection.

Most recently Spain, Portugal and UK have presented high activity in terms of signing new

subsidy-free PV contracts thus analysis of these particular energy markets seems to be the most

reasonable [15]. Introduction of 2 different locations with similar irradiation levels (Alcala de

Guadaira and Evora enables identification of key non-climate factors while the United Kingdom

case will show the importance of proper level of insolation.



2. ADDITIONAL INFORMATION

This chapter will provide the most up to date information related to the topic of this dissertation.

The chapter is divided into three main sections. First two sections focus on the European

electricity situation including introduced policies and power market description. Third section

will describe the current status of the Solar Energy and PV technologies.

2.1. EUROPEAN ENERGY SITUATION

The European Union is putting a lot of efforts to make energy more secure, affordable and

sustainable for all its inhabitants. New legislation and rules enable energy transition on many

different layers: implementation of new technologies and renewed infrastructure, free flow of

energy across the borders by implementation of a fully integrated energy market, energy

efficiency or decarbonising the economy. All the ongoing changes related to every layer follow

the general strategy framework that describes the long-term goals for the nearest decades.

Three energy packages have already been introduced in 1990s, 2003 and 2009 containing

legislative proposals for renewable energy generation, energy efficiency, energy performance in

buildings and electricity market design including electricity regulations, electricity directive and

risk preparation. The Third Package from 2009 had a huge impact on the electricity market

operation. As stated in [21], it included the following aspects:

• Separation of the energy supply and generation from the operation of transmission

networks – unbundling

• Strengthening the independence of regulators from industry interests and government.

Additionally, the regulators from different European countries should collaborate in

order to promote the further opening of the internal European market

• Increasing the transparency on the retail markets favouring energy consumers and

securing their rights

• Creation of the European Networks for Transmission System Operators (ENTSOE) and

Agency for the Cooperation of Energy Regulators (ACER)

The establishment of the both ENTSOE and ACER aims to improve and smooth the further

transition towards single, unify, European electricity market. ACER as a fully independent agency

should control and guide in operation such as: cross-border electricity regulations, review of the

network development plans, coordination of the National Regulatory Authorities, monitoring the

functioning of the internal markets and protection of the consumer rights. ACER is additionally

supported by the non-for-profit agency: Council of European Energy Regulators. Both agencies

sharing common targets thus their work is complementary, CEER is more responsible for sharing

the experience and information with similar agencies around the globe. While the mentioned

agencies are mostly focused on the regulatory and legislative parts, the major task for the ENTSOE

is to check and control all of the planned changes regarding the technical and practical aspect

[21]. The major task are as follows: standard and network codes development, monitoring and

inspection of the new network investments and new transmission capabilities.



On the 30 of November 2016, the European Commission presented the newest package of

measures – “The Winter Package” [22]. The framework covers all the aforementioned issues,

however, in a more detailed and regulated version. The package adapts to the current status of

the energy transition, considering the level of development in all of the EU member countries.

The ACER position has been strengthened and new targets for the energy efficiencies and

renewable sources penetration have been set. The package has not yet been implemented,

presently it is discussed and consulted by the European Parliament and Council of the European

Union.

2.2. ELECTRICITY MARKET

Power plants generate its revenues by selling power. The way of selling this power depends on

both the power sector structure and the regulations that govern certain electricity market.

European electricity market is a very complex and rapidly changing market. It has to manage

issues, related to different type of the customer, length of energy contracts and distances. In

order to provide electricity to its final destination, several market’s divisions have been

introduced. Regarding the type of customers the retail and wholesale energy markets can be

distinguished [23].

The retail energy market mostly caters local offers between suppliers and consumers. The

consumer has a right to choose between different suppliers while the supplier is invoicing the

customer for the provided electricity.

The wholesale electricity markets gather generators, electricity suppliers and large industrial

consumers. The transaction holding on the wholesale markets are on a much bigger scale and

have a strong influence on the price of electricity, maintaining the grid stability and risk

management.

Currently, wholesale markets are being integrated on the European level - market coupling. It is

a gradual evolution towards a single wholesale market with the wholesale prices getting more

similar in every region. It bases on the fact that the high price locations will try to import the

electricity from the low-price ones thus resulting in overall price reduction. This phenomenon is

strongly related to the transmission capacities, lack of cross border connections may influence

the price differences between different market regions leading to the market splitting [23]. Thus,

improvement of the interconnection between the member countries will significantly accelerate

the achievement of the common European electricity market.

The Market Coupling Operator Plan has been introduced by European Commission and accepted

by all the NRAs in order to develop a strategy for a smooth integration of all European day-ahed

and intraday markets [24]. The plan consists from the following resolutions:

• Adoption of the Price Coupling Regions solution as the base for coupling all European

day-ahed markets

• Adoption of the intraday cross-border solution as the base for coupling all European

Intraday markets



• The NEMO Committee will be controlling the implementation of the aforementioned

plans

On the Figure 2 current status of the PCR solution including all the participants has been

presented.

Figure 2: PCR users and members [25]

Due to difficulties with storing big amounts of electricity, it has to be produced at the moment

when it is needed. Thus, the transactions have to include the delivery of electricity at a certain

moment according to the rules described in contracts. The next subchapters present the

wholesale transactions considering different time periods. The following ones can be

distinguished: long-term contracts - PPAs, Day-ahead markets and Intraday markets.

2.2.1. POWER PURCHASE AGREEMENTS

According to the information presented in [1] power purchase agreement is a legally binding

agreement between a power seller, usually the owner of the facility, and a power purchaser (off-

taker). Depending on the power market structure, the off-taker can be: Power Company, power

trading company or an individual consumer. Properly constructed PPA should include all the

information related to the project financing such as: date of beginning of the operation, schedule

and volume of the delivered electricity, tariff, payment term, provision and related penalties for

breaking the contract. The PPA also specifies the capacity of the project and estimated annual

electricity production.



The PPA tariff can be set in various ways [16]:

• Fixed PPA price for the duration of the contract

• Tracker PPA that set discounts basing on the wholesale or retail electricity price situation

• PPA with more dynamic discounts, especially on the retail electricity price

Solar PV market is a good technology for the first way due to the fact that most of the PV system

costs are mostly at the beginning of the project. Compared to tracker PPAs, the fixed price

contract decreased the risk of sudden price drop to the investors.

Presently, due to transition towards distributed generation, where the power is sold directly to

the end user, emergence of new financial business models can be observed. Such models also

require purchasing agreements, usually named as commercial (corporate) PPAs that bind the off-

taker (either individual residence or a huge industrial facility) to purchase power for a previously

defined period [26]. The major advantages for off-takers are as follows: long-term cost

affordability and recognition in carbon emission (if the PPA concerns renewable sources), while

for the suppliers: easier bankability with secured revenues and business development. Huge

popularity of corporate PPAs is caused by the fact that organisations and companies are looking

for ways to reduce their carbon footprint and increase the energy efficiency resulting in fulfilling

their sustainability targets. Thus, they decide to purchase power from high quality renewables

suppliers as a part of their energy management strategy.

Only in 2017, the 5.5 GW of corporate PPA agreements have been signed worldwide, more than

half of this value is coming from the USA. However, new activity can be observed in sub-Saharan

countries or Mexico. Compared to the previous years, in Europe, the development of the PPA

activity remains on the same level - around 1 GW, mostly focusing on Nordic countries,

Netherlands and United Kingdom. It was mostly due to stable subsidy policy and integrated

energy market [27].

2.2.2. PRICES ON THE WHOLESALE MARKET

It is a very important type of market that is responsible for the for the delivery of the electricity

for the next day. The prices of the electricity are being set every day at noon for the following

24 hours. Market agents participate by proposing electricity transactions through presentation of

electricity sales and purchase bids. While talking about electricity, the auctioneer wants to

purchase electricity with the lowest possible price thus the participants try to offer the lowest

fare [28]. Once the market is closed, all the bids and sales are gathered together. Then,

considering the priorities between different sources of energy - merit order criterium, the general

curves of supply and demand are obtained. The intersection of the curves indicates the clearing

price – the most expensive price accepted by the demand, and the corresponding clearing volume

[29]. For all the European electricity markets, the EUPHEMIA algorithm has been adopted for this

task [30]. The algorithm has been programmed to optimise the overall income additionally

including the congestion charge. Once, the prices are being set, the process has to be also

checked in terms of physical feasibility. The algorithm results are being sent to the system

operators in order to check their technical viability, thus it can be assured that the market results



can be technically accomplished. The technical check can influence the initial market results;

however, it is necessary for the proper functioning of the whole system.

Once the results of the day-ahead market are being set, the market agents can again participate

in the power auctions on the intraday markets that deal with the sale and purchase of energy

during the day of delivery. This practise is used to adjust the generation schedules obtained from

the day-ahead market before the real time operations [29]. The auctions sessions are being

scheduled during the day. The principles of the market operation are the same as for the

wholesale market, however, the intraday market allows on readjusting the schedule of the market

agents more closely to the real time. It supports market agents and enables their smoother and

more flexible operation.

Historically speaking, vast majority of the PV projects relied on the power purchase agreements

[31]. However, the reduction of solar costs as well as constant technological advancement foster

the growth of the solar merchant power plants. These power plants can compete directly on the

whole-sale markets without any long-term agreement. It is becoming a popular practice

especially in the regions with high solar irradiation. Latin America countries such as Mexico and

Chile, due to low-cost utility PV systems, are the major players in the field of merchant market PV

plants. 14 out of 15 top merchant solar projects is located or planning to be located in those two

countries [31]. Regarding European market, countries like Spain, Portugal or Italy have also

announced ongoing merchant solar projects. Thus, it is believed that if the solar development

costs will continue to decline, in the next years transition towards merchant projects can be

observed.

2.3. SOLAR PHOTOVOLTAICS

According to the website [32], European Union aims to become the major actor in the field of

sustainable, low carbon and environmentally friendly economy that will be setting the standards

for renewable energy production, clean technologies and fight against global warming. The

development of solar PV technologies is a huge contributor to the overall success of this strategy.

The sub-chapters 2.3.1 - 2.3.3 will provide information regarding the current status of the

development of the photovoltaic industry as well as basic technical description.

2.3.1. SOLAR PV STATISTICS

Based on the information presented in the recent report about renewable sources of energy [33],

it can be noticed that solar photovoltaics is the fastest growing source of renewable energy. It is

represented as the average annual growth rate of world renewables supply. In the period

between 1990 and 2015 solar photovoltaics has noted annual growth of 45,5% which is almost

twice bigger than the second in line wind energy. Such increment is influenced by big investments

in the PV sector in EU, China and USA. In 2016, the total installed capacity of solar PV within the

European Union has exceeded 100 GW, that corresponds to more than 48 million of m2 of total

collector surface. Additionally, such capacity enables on more than 108 TWh of energy produced

in one year. Germany, United Kingdom and Italy together represent almost 70% of this value [34].



Rapid growth of the PV industry is strongly related with its increasing cost competitiveness on the

energy market. As it was mentioned in the introduction chapter, the LCOE of the PV application

can compete with conventional energy on some power markets. It is mostly due to the fact, that

in the last years, solar generation costs have decreased significantly, mostly driven by the huge

Chinese production of solar cells [35]. According to the document [36] China together with Japan

are accounted for almost 70% of the global module production between 2015 and 2016.

Currently the dominant module technology is Crystalline silicon accounted for 94% of total

production in 2016 with the average module efficiencies around 17-18%. However, recent

laboratory tests show that by 2024 the efficiencies of mass-produced Crystalline silicon modules

can rise up to 20-25%. The efficiency improvement together with increased usage of tracking

systems and deployment of the PV projects in regions with great solar conditions strongly

influence on the overall increment of the capacity factor of the PV project, that additionally

decrease the LCOE of the PV technologies.

Considering the economic aspect, in the period between 2010 and 2017, the solar PV module

prices have decreased by 83%. The price reduction was primarily driven by the economies of

scale, but most recently it is also connected with the improvements of the technological

processes and efficiency gains – learning curve [36]. PV price decrease due to the economies of

scale can be seen on the Figure 3. For every doubling of the cumulative PV delivery, there is an

approximate 22% of average sailing price reduction [37]. The recent PV prices, as for 2018,

achieved by almost all major PV manufacturers are around 0,32 USD/W and the further cost drop

is expected. It is predicted that the PV price might be around 0,25 USD/W in 2021. The costs of

other components are also going down, most recent central inverter costs are around

0,06 USD/W [38].

Figure 3: PV Price Development considering the Economies of Scale Effect [37]



The overall module costs reduction could be observed almost on every market however with

different scale. The differences between regions are mostly caused by the market preferences

regarding the module type as well as the costs connected with the module import. The decreased

technology cost influences the overall total installed cost of the PV technologies, however

providing different values between regions. It can be explained by differences in the maturity

level of the local PV markets supported by experience of the investors and political situation. In

general, in the period of 2010-2017, many countries have experienced total cost reduction of

almost 70%. This decrease has additionally influenced on the significance of the Operational and

Maintenance cost, that now in some location can account for almost 25% of the total LCoE value

[36].

The decreased costs and increased capacity factors of the PV projects strongly influenced the

LCoE of the large-scale PV installations. It is estimated that, in the period between 2010 and 2017,

the LCoE value for the large-scale PV has decreased by 40-75% depending on the country. The

decrement is mostly driven by the technological improvement as well as the increased capacity

factors. The LCoE values are expecting to still decrease in the nearest future, thus making space

for development of new PV projects [36].

2.3.2. LARGE SCALE PV – TECHNICAL DESCRIPTION

The major task of the PV plant is to produce electricity out the incoming solar irradiation. This

process is done due to the use of the electrical components. According to [13] these devices have

three major tasks:

• Convert solar energy into electricity

• Connect large-scale PV plant to the grid

• Assure the proper performance of the PV plant

The typical large-scale PV plant is a very complex installation; however the following major

components can be distinguished as: PV module; inverter; mounting structure; connection and

distribution boxes; cabling, potential equalization and grounding; lightning protection system;

weather station, communication and monitoring; transformer station; infrastructure and

environmental influence; miscellaneous. Most recently, the storage implementation has become

a huge topic, while talking about the improvement of the PV plants performance, therefore the

usefulness of this components is being discussed in the next sub-chapter. In this sub-chapter the

major focus is put on the: PV panels, PV inverters and transformers as for their involvement in

the large-scale PV plant operation:

PV modules as the devices responsible for the energy conversion processes are the crucial

components of every power plant. Their efficiency is one of the most important aspect during

sizing phase of the project thus the efficiency strongly affects the occupied area. It additionally

influences all the secondary operations such as transportation, installation and maintenance.

Most recently, strong focus is being put on the manufacturing and future recycling of the PV

panels, the overall goal is to maximise the reduction of the related CO2 emission.



PV inverters as a device that converts the DC to AC power is a necessary step to connect the PV

plant to the grid. The inverters are responsible to cover all the electrical requirements set to the

PV plant such as: galvanic isolation to protect form the leakage current from the PV

interconnections; maximum power point tracker; power quality and operational characteristics

required by the particular country. Moreover the large-scale PV plants are asked to provide the

grid support issues e.g. voltage and frequency control.

Regarding the large-scale PV installations, two types of transformers are being installed. First one

that increase the voltage to the medium voltage values, and the second one that provides the

galvanic isolation from the grid and additionally increase the voltage to the high voltage values.

Once, the major components have been described, the connection between them can be

explained. Considering the large-scale installation, three different configurations can be

distinguished: central, string and multi-string. According to [13] for the large-scale installations,

the central configuration is preferable. It is mostly due to the low installation and maintenance

costs, that are the crucial factor during the decision process. The next step is selection of the most

appealing AC grid topology. The most popular are: radial, ring and star topologies. Due to its

cheapness and simplicity, the radial one is the most suitable for large-scale applications. Typical

large-scale installation has been presented on the Figure 4.

Figure 4: General layout of a utility-scale PV plant [13]



2.3.3. STORAGE IMPLEMENTATION

Solar PV project is an investment that lasts more than 25 years, thus it should include the

possibility of further development in order to remain competitive on the power market in the

nearest years. One of the possibilities to increase the flexibility of the system that will succeed in

higher credibility, is implementation of the electrical energy storage systems. Such modification

enables to store the generated electricity and inject it into the grid during the periods when

energy is mostly needed or when electricity cannot be generated due to poor weather conditions.

Deployment of EES increased the efficiency of the system due to higher amount of produced

energy, that directly contributes to increased revenues. Additionally, it supports the emission

reduction and lower the PV output curtailments.

Installed on a large scale, EES could also bring revenues by providing ancillary grid services such

as frequency and voltage control that will succeed in higher power quality. According to the article

[39] only in the US market, the economy loses from 15 to 24 billion of US dollars due to power

quality. This cost could be partially decreased by deployment of the storage technologies.

Currently, the EES are still expensive and not legally regulated thus their implementation to the

PV projects is small, however, many already existing installations consider future deployment of

the EES technologies [40]. They may serve as a perfect complement to the current projects that

will make them even more cost and quality competitive in the nearest future. For the sake of

simplicity during system modelling, storage technologies will not be included in this analysis.



3. LITERATURE REVIEW

Profitability assessment is a crucial issue while talking about new PV investments thus many

studies have been performed in order to examine different methods of assessing profitability of

a certain project as well as detailed factors that mostly influenced the obtained results. These

analyses have been performed considering both subsidized and unsubsidized PV projects

implemented to different European electricity markets. Moreover, since deployment of the PV

project is a very complex process that involves many different fields, there exist many works that

examine this issue.

As it was mentioned in the previous chapters, initially, deployment of the solar PV projects

expected very rapid growth, mostly caused by favourable policy. Thus, there exist many articles

that widely describes different national support schemes and ways of their implementation. In

the article [41] there is a wide description of French, German, Greek, Italian and British position

regarding development of PV systems including implementation of different supporting policies.

In order to estimate the impact of particular support schemes and predict future energy policies,

comparative profitability analysis based on major economic indexes such as net present value

and internal rate of return, is performed considering these five locations. Similar analysis was

performed by the same authors in [42], expending the level of research to all western European

Union countries, while information in the [43] provides some additional explanation to the

Spanish PV legal framework during the highest expansion of the Spanish PV sector.

Once the solar photovoltaic sector started questioning the policy towards renewable energy

subsidies, this issue has been also addressed in many researches. In article [44] there is a

discussion about the relevance of the feed-in tariffs in the near and post-grid parity world. It

examines the willingness for PV investments considering investors and business models

diversification. German, Italian and Swiss electricity markets are being analysed. The results show

the dependence of market trends on the policy and revenue-based risks. In [45] the negative

impact of the several cost-containment mechanisms on the profitability of Solar PV plants on the

Spanish market has been discussed. It is mostly focused on the governmental actions after huge

expansion of the photovoltaic installations in Spain.

Regarding unsubsidized projects, very broad profitability analysis of small-scale, residential PV

systems (3 kW, 6kW and 20 kW) in an Italian electricity market, additionally supported by

sensitivity analysis of critical variables such as: investment cost, electricity price, insolation level,

has been performed in the article [46]. The only difference to this work is, that the authors

additionally included revenues from self-consumption. The obtained NPV and discounted

payback time show that small-scale photovoltaic systems can adapt to the ongoing market

transition towards unsubsidized electricity market. Additionally, conducted environmental

analysis presents huge reduction of CO2 emission compared to conventional sources of energy.

Similar research, including the same economic indexes, however for bigger-scale PV power plants

(200 kW, 400 kW, 1 MW and 5 MW) has been performed by the same authors in [47]. The analysis

results show perspectives for investments in bigger-scale PV systems in the nearest future. Strong

impact is put on the gains from self-consumption, thus opportunities especially for the industrial



and commercial sector. Another feasibility study that checked the profitability of the large-scale

PV project (1MW) has been performed in the [48]. It is a very detailed investigation of the Cyprus

island, strongly focused on the legislative framework and sensitivity analysis of critical parameters

for the viability of the project. The results show the importance of capital expenditures while

talking about the unsubsidized.

Considering project development, the information contained in [1] provide a very consistent

guidelines for project developers about utility-scale solar photovoltaic power plants. It focuses on

the entire project life-time from site selection to final financial analysis, while [16] precisely

described different solar PV business models currently used within European Union. Technical

aspects of large-scale PV plants are being presented in [13]. This article deeply examines the

internal layout of the PV installation, including electrical components, plant configuration and

collection grid topologies in order to obtain the best design, operation and control of the PV

power plant.



4. FRAMEWORK

In this chapter, all the information regarding the methodology as well as used tools and

assumptions will be provided. The chosen framework will consist from two major parts. The

technical analysis, that will lead to estimation of the energy produced during lifetime of the

project. The economic analysis that will try to answer the research question whether it is

profitable to develop such a project in every of the chosen locations. The research will be closed

by sensitivity analysis that will indicate the key factors that influences the profitability of the large-

scale PV project. Table 1 presents all the framework components that will be included in this

analysis.

Table 1:Framework of the Analysis

Type of Analysis Components of the analysis

Technical

Research Data

Modelling Tool

Solar PV Plant Components

Plant Simulation

Economic

Financial Tools

General Assumptions

Case Studies

Financial Modelisation

Sensitivity Analysis:

• Energy dependence

• Cost/Price dependence

• Financial dependence

4.1. TECHNICAL ANALYSIS

With the use of the PVSyst software and solar irradiation data provided by the Solargis, the power

output from the 50 MW solar photovoltaic plant will be estimated for every of the selected

location. The analysis will include design of the plant layout together with selection of the major

components that will be used for the simulation.



4.1.1. LOCATION AND CLIMATE DATA

As it was mentioned in the sub-chapter 1.4, three different sites have been selected for the

analysis. Table 2 presents the chosen locations with all the related details that have been used

for the solar data collections.

Table 2: Climate and location data

Name Country Coordinates Elevation [m a.b.s]

Alcala de Guadaira Spain 37° 20’ 01’’N; 5° 50’ 25’’ W 56

Evora Portugal 38° 34’ 05’’N; 7° 54’ 22’’ W 278

Milton Keynes United Kingdom 52° 02’ 29’’N; 0° 45’ 20’’ W 116

The data has been obtained with the help of the Solargis and include the following information:

• Global horizontal irradiation [Wh/m2]

• Diffuse horizontal irradiation [Wh/m2]

• Sun elevation angle [°]

• Sun azimuth angle [°]

• Air temperature at 2m [°C]

All the given values are presented in the hourly form and delivered as the Typical Meteorological

Year (P50) for every location. The TMY contains compressed historical data series from the period

of 01.01.1994 – 31.12.2017 so that the obtained values represent best reflection of the actual

conditions presented in the chosen locations. The TMY has been created by choosing the most

representative months from the historical series following the criteria regarding the minimum

difference between statistical characteristics and the maximum similarity of monthly cumulative

distribution functions between TMY and time series. The term P50 describes the statistical level

of confidence suggesting that we expect to exceed the predicted energy yield 50% of time [49].

The TMY values have been imported to the PVSyst in order to perform further technical analysis

of the chosen system.

4.1.2. SOFTWARE DESCRIPTION

For the analysis, the trial PVSyst 6.73 version has been used. This particular tool has been selected

mostly due to trade-off between quality of the obtained results and software price. PVSyst is a

PC software that enables studying, sizing, simulation and data analysis of the complete

photovoltaic systems. For the analysis, the “Project Design” section of the program has been

used. It is the most developed part of the program that includes: choice of meteorological data,

system design, shading studies and losses determination. The Perez-Ineichen physical model has

been chosen for calculation of the incident radiation on a tilted plane. It is mostly due to more

accurate results achieved by this model.



4.1.3. COMPONENT SELECTION

PVSyst analysis enables on selection of two major components that will influence the

performance of the PV plant: PV module and Inverter, thus the major focus of this subchapter is

put in those two devices.

PV Module

Basing o the information presented during the webinar [50], the JinkoSolar monocrystalline JKM

370M-72 model has been selected. The Figure 5 presents the selected module in line with the

most important specifications.

Figure 5: JinkoSolar JKM 370M-72 Specifications [51]

This choice has been made basing on the several factors.

JinkoSolar is considered to be one of the major global players in the solar industry with an

integrated annual production and delivery capacity of 9 GW for solar modules [52]. Vertically-

integrated production chain with more than 10 years of experience, ensures top -class

components with quality guaranty along the whole manufacturing process.

Additionally, performance simulation of different JinkoSolar PV modules in the large-scale

50 MW PV plant has been made. The selected model has been analysed and compared with other

PV modules. Installation of more powerful 370W model in comparison with the most standard

Poly 320W modules shows higher energy output by 1,3% and higher performance ratio by 0,011.

These values transfer to overall decreased of LCOE by almost 3% and decreased PV area by almost

14%, that positively influenced on the general investment costs [52].

More detailed information regarding the selected PV module has been included in the

manufacturer sheet, that has been attached to this work as: APPENDIX I.



INVERTER

The inverter model has been selected basing on the discussion with [53]. The SMA Sunny Central

1000CP XT model with a 1 MW of nominal power has been chosen. The size of the inverter has

been chosen base on the optimal trade-off between the reliability of entire PV system and

number of inverters. It is a central type inverter for outdoor use with a maximum efficiency of

98,71% and maximum DC voltage of 1000V. At the temperature up to 25°C, the inverter can work

at 110% of its nominal power, while at temperatures 25-40°C, the AC power output decreases to

100% [54]. Additionally, the chosen model as well as all SMA inverters renown grid-integration

issues and PV power plants control. The selected model provides all necessary grid services to

fulfil the requirements specific for every country of installation [54]. Moreover, according to

standards presented in Germany - BDEW [13], all the utility-scale PV plants must provide grid

support functions. All the additional features of the selected model have been included in

APPENDIX I.

4.1.4. PLANT MODELLING

The aim of the modelling part is to obtain the energy output in the form of electricity that is

injected directly to the grid. Technical parameters of the PV plant have been set as identical for

all the locations in order to obtain the most similar plant design, thus the profitability comparison

between plant locations will be focused mostly on the economical and solar irradiation factors.

The same procedure, already implemented to the PVSyst software, has been used for every

location:

i. PV plant site has been determined and all the geographical and climate parameters

(paragraph 0 ) have been imported to the software.

ii. Major project settings have been defined. All the modified variables have been presented

in the Table 3, while other such as: reference temperatures and shading limitations have

been set as according to software recommendation and can be seen in the APPENDIX: II.

Table 3: Major Project Settings [55]

Name Description Assumed Value

Transposition

Model

Mathematical model that allows on calculation the

amount of energy received on a tilted plane. This

model has been selected due to more accurate and

detailed approach.

Perez-Ineichen

Albedo

Fraction of global incident radiation reflected by the

ground in front of the module plane. Assumed value

is typical for urban localities

0,20

Max. array voltage Maximum admissible array voltage defined

according to chosen inverter specifications 1000 V



iii. Due to easier maintenance and less space demand orientation of the PV panels has been

set due south with one-axis horizontal East-West tracking system. The range of tilt angle

is 10-80°. The geographical visualisation can be seen in the Figure 6.

Figure 6: Orientation of the PV modules

iv. The plant size has been defined as 50 MWp. Additionally, described in paragraph 4.1.3

models of PV modules and inverters have been selected. All the working parameters of

the selected devices have been imported automatically from the software database.

v. Major project losses have been determined. Assumed values together with the

description has been based on information presented in [55] and [1], are given in

Table 4:

Table 4: Losses Description

Type of Losses Description Assumed Value

Irradiance level

Conversion efficiency of a PV module decreases at low

light intensities that influences the module energy

output at STC. Calculated specifically for the chosen

collector model and climate data. Expressed as the ratio

to the STC power [56].

< 1,9%

Thermal

Decrement of the PV module efficiency due to increased

ambient temperatures (above STC). It is determined by

the thermal loss factor, that describes heat transfer

processes around the modules considering the type of

installation (free-standing, facades, roofing etc.)

U=29 W/m2K

Ohmic

Caused by ohmic resistance of the wiring circuit

between the power from PV module and the power at

the end of the array. Optimised as the percentage ratio

with respect to STC power.

< 1,5%

Module Quality

Represent the real module performance with respect to

the PV module manufacturer specifications. Defined as

the ratio to the STC power.

1,5%

LID

Light induced degradation losses that arise during the

first hours of exposition to the sun by respect to the flash

tests of STC. They are related to the quality of the wafer

manufacturing process. Similarly to the previous ones,

expressed as the ratio to the STC power.

1%



Module

mismatch

Due to different currents/voltage profiles of modules

that are connected to the same string. The lower value

drives the overall performance. Expressed as the ratio to

the STC power.

1,1%

Soiling

Describe the accumulation of dirt and its performance

on the system. Strongly dependent on the weather

conditions. Expressed as the ratio to the STC power.

3%

IAM

The incident angle losses account radiation reflected

from the front glass surface when the light beam is not

perpendicular. They are calculated basing on the used

PV panels and their glass surface type. PVSyst uses

ASHRAE method with bo parameter, that has been

provided by the manufacturer.

bo = 0,05

Auxiliaries

Define power necessary for proper operation of the

electrical equipment within PV plant such as: fans,

monitoring, lights etc. In this work expressed as the

constant value.

648000 W

vi. Project simulation has been performed and the yearly plant energy production has been

obtained.

Once the yearly amount of the electricity injected to the grid have been estimated, it was used

to calculate the amounts of electricity that will be injected to the grid during every of the 25 years

of the project lifetime. Calculations have been done using MS Excel and including the decreasing

performance of the PV panels over the lifetime of the project – module degradation.

According to [1] this phenomenon can be caused by:

• Pollution on the module surface

• Lamination defects

• Mechanical stress and humidity

• Cell contact breakdown

• Wiring degradation

In order to obtain the most realistic power performance, the linear performance warranty,

provided by the manufacturer has been used for the calculation, thus the initial energy output

has been multiplied by respective power performance. The graphical representation and used

linear trendline equation are being presented in the Figure 7:



Figure 7: Module degradation over project lifetime

Eventually, the plant performance indicators such as capacity factor and performance ratio have

been estimated.

Capacity factor is the ratio between the annual average electricity production to theorethical

maximum energy production of the given power plant throught a year [57]. It can be calculated

using the following equation:

𝐶𝐹 =𝐴𝑛𝑛𝑢𝑎𝑙 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 [𝑀𝑊ℎ]

𝑁𝑜𝑚𝑖𝑛𝑎𝑙 𝑃𝑜𝑤𝑒𝑟 [𝑀𝑊𝑝] 𝑥 8760 [ℎ𝑜𝑢𝑟𝑠]

Power performance ratio can be described as global system efficiency with respect to the nominal

installed power and incident solar energy. It is not dependent on the module efficiency and shows

the proportion of the energy that is actually available for export to the grid [58]. It can be

computed using the equation:

𝑃𝑅 =𝐴𝑛𝑛𝑢𝑎𝑙 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 [𝑀𝑊ℎ]

𝐼𝑟𝑟𝑎𝑑𝑖𝑎𝑡𝑖𝑜𝑛 [𝑘𝑊ℎ𝑚2 ] 𝑥 𝑁𝑜𝑚𝑖𝑛𝑎𝑙 𝑃𝑜𝑤𝑒𝑟 [𝑀𝑊𝑝]

Once all the necesary values have been calculated, the solar plant layout has been designed. The

proposed configuration together with obtained results will be presented in the

paragraph 5.1.

y = -0,0071x + 0,982R² = 1

75%

80%

85%

90%

95%

100%

0 5 10 15 20 25

Po

wer

Per

form

ance

[%]

Modules Lifetime [years]

Module Degradation



4.2. ECONOMIC ANALYSIS

Profitability of the system will be estimated using the post-tax internal rate of return, that will be

compared with set discount rates. In order to obtain IRR, the financial analysis focusing on

discounted cash-flows to firm and equity will be performed. Additionally, the net present value

and payback time of the project will be calculated. Eventually, the dependence of the estimated

IRR, NPV and payback time on external factors will be check by the sensitivity analysis.

4.2.1. FINANCIAL TOOLS

The major aim of this part of the document is to familiarize readers with the financial tools and

indicators that will be used in the following analysis. Similar to the [41], [42], [46] and [47] the

discounted cashflow analysis has been performed in order to determine the profitability of the

project. The profitability of the project will be confirmed if the calculated post-tax IRR will be

higher than the used discount rate. Regarding this work, two discounted cashflows have been

used: FCFF with the WACC discount rate and FCFE with cost of equity as discount rate.

Free cash flow for the firm

Free cash flow is one of the most important financial indicator of project value. It presents the

amount of cash flow from operations available for distribution considering depreciation

expenses, taxes, working capital, and investments. FCFF is essentially a measurement of a project

profitability after all expenses and reinvestments, it is a good representation of a project

operations and its performance [59].

A positive FCFF value indicates that the firm has cash remaining after expenses. A negative value

indicates that the firm has not generated enough revenue to cover its costs and investment

activities.

In this work, the FCFF has been calculating using the following formula:

𝐹𝐶𝐹𝐹 = 𝐸𝐵𝐼𝑇𝐷𝐴 ∙ (1 − 𝑇𝐶 ) + (𝐷𝑒𝑝. ∙ 𝑇𝐶 ) − 𝐿𝑜𝑛𝑔 𝑖𝑛𝑣. −𝑊𝐶

Where: EBITDA – earnings before interest, tax and depreciation, TC – corporate tax rate,

Dep. – depreciation, Long inv. – long term investments (devices), WC – investment in working

capital

Free cash flow to equity

FCFE is often used by analysts in an attempt to determine the value of a project. It is a measure

of how much cash is available to the equity shareholders of a project after all expenses,

reinvestment, and debt are paid. FCFE is a measure of equity capital usage. Can be used to

determine the project return that is going directly to the owners. Additionally, it checks the

project ability to pay dividends [60].



In this work, the FCFE has been calculating using the following formula:

𝐹𝐶𝐹𝐸 = 𝐹𝐶𝐹𝐹 − 𝑇𝑜𝑡. 𝐹. 𝐶𝑜𝑠𝑡 ∙ (1 − 𝑇𝐶) + 𝑁𝑒𝑡 𝐵𝑜𝑟𝑟𝑜𝑤𝑖𝑛𝑔

Where: FCFF – free cashflow for the firm, Tot. F. Cost – total financing costs (Interests, Cost of

raising Capital and Cost of issuing debt), TC – corporate tax rate, Net Borrowing – used to express

difference between New Debt and Debt Re-payment

Weighted average cost of capital

It is a way to calculate project cost of capital in which each category of capital is proportionately

weighted. In a broad sense, project can be financed either through debt or with equity. WACC is

the average of the costs of these types of financing, each of which is weighted by its proportionate

use in a given situation. Project WACC increases as the rate of return on equity increase, because

an increase in WACC denotes a decrease in valuation and an increase in risk. WACC is the overall

required return from a project, thus it is the discount rate that should be used to actualize cash

flows with risk that is similar to that of the project [61].

To calculate WACC, multiply the cost of each capital component by its proportional weight and

take the sum of the results. It can be done using the following equation:

𝑊𝐴𝐶𝐶 = 𝐸

𝑉 ∙ 𝐶𝐸 +

𝐷

𝑉 ∙ 𝐶𝐷 ∙ (1 − 𝑇𝐶)

Where:

CE = cost of equity – rate that express the expected investor’s return from the project. It has been

used as a discount rate for FCFE.

CD = cost of debt – credit interest rate used to calculate credit rates throughout the total credit

period.

E = value of used equity in the project, D = value of used debt in the project, V = E + D = total value

of project financing, E/V = percentage of financing that is equity, D/V = percentage of financing

that is debt, TC = corporate tax rate.

Based on the cashflow results the following financial indicators have been used in order to attest

the profitability of the analysed project:

Net Present Value

Net present value is the difference between the present value of cash inflows and the present

value of cash outflows over a period of time. NPV is used in capital budgeting to analyse the

profitability of a projected investment or project.

A positive net present value indicates that the projected earnings generated by a project or

investment (in present money) exceeds the anticipated costs (also in present money). Generally,

an investment with a positive NPV will be profitable, and an investment with a negative NPV will

result in a net loss. This concept is the basis for the Net Present Value Rule, which dictates that



the only investments that should be made are those with positive NPV values [62]. The NPV is

calculated using the following equation:

NPV = ∑𝐶𝑡

(1 + 𝑟)𝑡

𝑇

𝑡=1

−𝐶0

With: 𝐶𝑡 the net cash inflow during period t, 𝐶0 the total initial investment cost, 𝑟 the discount

rate, and 𝑡 the number of time periods.

Internal Rate of Return

Internal rate of return is a metric used in capital budgeting to estimate the profitability of

potential investments. Internal rate of return is a discount rate that makes the net present value

of all cash flows from a particular project equal to zero. IRR calculations rely on the same formula

as NPV.

To calculate IRR using the formula, one would set NPV equal to zero and solve for the discount

rate (r), which is the IRR. Because of the nature of the formula, however, IRR cannot be calculated

analytically and must instead be calculated either through trial-and-error or using software

programmed to calculate IRR [63].

Payback Time

The payback period is the length of time required to recover the cost of an investment. The

payback period of a given project is an important determinant of whether to undertake the

action. Longer payback periods are typically not desirable for investment action due to higher

possibility of risk occurring. The payback period ignores the time value of money, unlike other

methods of capital budgeting such as net present value or internal rate of return cash flow [64].

4.2.2. MAJOR ASSUMPTIONS

Every large-scale PV project is a unique enterprise that depends on many internal and external

factors, thus assumptions have to be taken in order to properly introduce the ongoing situation

as well as provide all the details that will be used during the modelisation process. The aim of this

part of the document is to introduce readers to the main assumptions that are equal for every of

the examined location.

General information

As it was mentioned in the sub-chapter 1.4 the large-scale 50 MWP PV plant with one-axis

horizontal East-West tracking system has been selected due to possibility of comparison with the

existing real-life PV project. Regarding the project lifetime similarly to the assumptions made in

works [1] and [2] it has been set as 25 years. It can be additionally supported by the 25 years

power guarantee for the chosen PV panels model, that is ensured by the manufacturer. The

power plant is owned by the independent power producer, while all the O&M activities will be

outsourced to a third-party company. Additionally, the dividends will be paid to the investors

basing on the net profit financial status of the project. Initially, all the profit will be collected until

the value of 3 million euros in order to finance the further investments (inverter or spare parts).



Once the value of 3 million euros will be collected, all the further profit will be distributed to the

investors.

Financial modelling has been performed considering the following decisions:

• The impact of inflation has not been included in the calculations

• The depreciation has been included for all the project hardware additionally including

the capitalisation of all the soft costs. The depreciation rate has been set basing on the

lifetime of the equipment: for all the components except inverter – 4% (25 years

lifetime), for inverter - 8% (12,5 years). Thus the inverter has to be replaced after 12

years of operation [54].

The balance sheet that specifies all the equity & liabilities together with assets has been prepared

in order to control correctness of the calculation. Balance sheets for every location can be seen

in the APPENDIX: IV.

Revenues

The project revenue is coming from selling electricity in a form of the long-term wholesale power

purchase contract between the power supplier and off-taker (e.g. power trading company). The

contracted price is being set as a floor price and is based on the average wholesale electricity

price from last ten years [65], [66]. Similar PPA prices are currently being negotiated in the market

[12] and [67]. The electricity price per MWh does not change during the project lifetime.

Additionally, the contract states that whole the produced electricity has to be purchased from

the off-taker. The yearly amounts of electricity injected to the grid have been estimated according

to the methodology presented in the sub-chapter 4.1.4.

OPEX

Operational expenditure for solar PV is significantly lower compering to other renewable sources

of energy. It is mostly due to simple engineering and less maintenance requirements. Regarding

the following analysis, the bottom-up approach has been used to estimate the total OPEX value.

The Table 5 presents all the OPEX components together with assumed values.

Table 5: OPEX Components

Type Cost

Operation & Maintenance 8,00 – 10,00 EUR/kWP per annum

Land rental 2,40 EUR/kWP per annum

Insurance 1,80 – 1,85 EUR/kWP per annum

Connection Fee 0,48 - 0,83 EUR/kWP per annum

Others 0,5 EUR/kWP per annum

Total 13,50 – 15,20 EUR/ kWP5 per annum

5 Different prices are being considered between Spain/Portugal and UK. This issue will be addressed in the following subchapter.



The value for O&M and others (internet connection, administration, etc.) has been assumed

based on the recent information presented in [12]. Additionally, it is consistent with the values

presented in [1].

Considering the land issue, it has been assumed that the land will be rented, and the charge will

be paid every year. Land rental cost has been calculated using the price of 1200 EUR/ha [68]. The

needed area has been estimated considering that for 1 MWP of installed power 2ha are

necessary [1].

Insurance cost has been estimated as 0,3% of CAPEX paid every year. The rate value has been

provided by [68] and additionally confirmed by [1].

As for the grid connection costs, this include the charge for using the grid as well as the

expenditures necessary to maintain the electric substation that is responsible for the analysed

plant. The value of 0,5 EUR/MWh of produced electricity has been assumed using information

from [45].

CAPEX

Each project has different capital expenditure. It is due to the strong CAPEX dependence on the

selected site for the project, commissioning costs or moment of construction start. The final cost

is known once the EPC contract is signed. The EPC contract defines the project investment costs

and contractor responsibilities basing on the whole construction process starting from the

designing phase until final commissioning. According to [1], the EPC contractors’ scope of work

includes: management and supervision, labour, plant equipment, works and materials necessary

to complete the project. To the lastly mentioned can be listed: PV modules, inverters, mounting

structure, DC/AC cabling, transformers, grid connection facilities, security and monitoring, plant

commissioning and many others.

Considering this analysis, the CAPEX value after signing the EPC has been estimated as

600 EUR/kWP of installed power. The chosen value has been assumed based on the information

presented during the conferences [7] and [67]. The low CAPEX can be explained by constant

decrease of module prices as well as huge competition between project developers in order to

obtain permission to install the PV plant. Additionally, in the [47], the value of 700 EUR/kW for 5

MW PV plant has been used, thus considering the economies of scale phenomenon it can be said

that the value of 600 EUR/kWP is assumed correctly.

The Figure 8 presents distinguished CAPEX components that have been developed for the

purpose of the analysis.



Figure 8: CAPEX division

Presented division has been applied using the top-down approach and basing on the information

presented in [38] and [37]. The electrical balance of the system refers to all electrical equipment

necessary to connect the plant to the grid. It is assumed, that the substation and transmission

lines are already installed. The structural balance of the system is mostly composed of the

mounting structure for the collectors. Additionally, the land rental and the insurance costs have

also been added to the up-front costs as well as the wages for installation of the power plant. On

the graph they are presented as the soft costs.

Financing Schemes

According to the information in [16], there are many financing schemes that can be used for the

large-scale PV projects. As it was mentioned in the sub-chapter 1.4, this analysis considers the

combination of debt (bank loan) and equity. The ratio debt-to-equity has been set as: 60:40 of

the total investment cost. Basing on the information presented in [16] and [67] it is a widely used

share considering the solar photovoltaic projects.

The bank loan has been taken for a period of 20 years. The distribution of principal rates and

interests has been calculated using the French method. The already made Excel tool has been

used for this purpose. Additionally, cost of issuing debt has also been included with a 2% rate of

the overall debt value [69]. The interest rate is equal to the cost of debt.

The cost of debt has been assumed using the Excel tool provided by [70]. The values have been

calculated particularly for the European renewable energy sector and considering every of the

examined location. Differences between countries has been expressed by the economic ratings

of the chosen locations taken from [71]. Corporate tax rate has also been included in the

calculation.

The equity value has been estimated as a difference between the total investments’ costs and

the bank loan. The values have been chosen considering the mentioned debt-to-equity ratio.

Additionally, the cost of raising capital has been included with a 2% rate of the overall equity

value [69].

42%

9%13%

19%

1%16%

CAPEX Components

PV Modules

Inverters

Electrical BOS

Structural BOS

Monitoring &Security



Cost of equity is more difficult to estimate because it depends mostly on the investors approach

and attitude towards certain project. Thus, for this analysis, the interview with the PV field

specialist has been performed in order to obtain the cost of equity rates for every location [67]

and [12]. Additionally, the cost of equity has been used as a discount rate for the FCFE to calculate

the NPV value of the project.

Eventually, the value of the WACC has been calculated for every location using the equation that

has been introduced in the chapter 4.2.1. The obtain value has been used as a discount rate for

the FCFF to estimate the NPV of the project.

Taxes

Due to lack of data only two type of taxes have been included in the analysis. The corporate tax,

that is calculated for every year basing on the EBT value and the given tax rate [72] for every

location. The calculation additionally includes the tax credit which has been accumulated during

the previous period when the EBT value was negative.

Second tax considered in this work is the tax on the energy injected to the grid. The cost is

estimated by multiplying the given tax rate by the amount of electricity injected to the grid.

Different tax rates for every location will be presented in the chapter 4.2.3.

4.2.3. CASE STUDIES

Three different countries are being analysed to properly assess the research question. This part

of the document provides all the assumptions, that have been already described in the

sub-chapter 4.2.2, for every location. They have been summarized in Table 6. As it can be noticed,

there are several major differences.

Table 6: Detailed case studies assumptions – base case scenario

Parameters Spain Portugal UK

Capital Expenditures [EUR/kWP] 600,00 600,00 615,00

Operational Costs [EUR/kWP] 13,53 13,50 15,22

Price of PPA [EUR/MWh] 45,35 45,46 53,90

Cost of Equity [%] 8,00% 8,00% 7,00%

Cost of Debt [%] 5,56% 6,17% 4,12%

Equity to Debt Ration [%] 40,00% 40,00% 40,00%

WACC [%] 5,72% 6,14% 4,80%

Corporate Tax [%] 25% 21% 19%

Tax on the energy to the grid [%] 7% 0% 0%

The higher CAPEX value in UK might come from the higher module trnasportation costs as it was

already mentioned in the chapter 2.3.1. Regarding the higher OPEX, it can be explained by higher

labour costs.

As it was mention previously, the PPA price has been estimated on the yearly average wholesale

price (see APPENDIX: III). The price in Spain and Portugal is almost the same due to the significant



integration of the Iberian electricity market – OMIE. The higher average electricity prices in UK

can be explained by lower interconnection with the European continetnt that influences the

possibilities of cross-border trading and long-term supply contracts [73].

Regarding the financing schemes, the obtained WACC values are similar to the ones assumed in

[46], [47] and [48] as well as follow current market trends [12]. The lower WACC in UK can be a

result of a stronger, more secure economy. Similarly as for the equity rate, the lower rate for UK

can represents investors attitude towards PV projects.

Eventually, the 7% tax rate in Spain is a consequence of the previous policy towards renewable

sources of energy, described in [42] and [45]. Basing on the interviews [67] and [74], similar taxes

does not appear in United Kingdom and Portugal.

4.2.4. FINANCIAL MODELLING

This subchapter will focus on description of the financial modelisation that has been applied to

this work. The modelisation has been done using MS Excel and following the International

Financial Reporting Standards. The same modelling procedure has been used for every location:

i. Major project assumptions as well as found differences between locations (already

described in paragraph 4.2.2 and paragraph 4.2.3) have been defined.

ii. Profit and loss of the project that include total yearly revenues and yearly operational

costs have been calculated. Additionally, the cashflow of investment has been obtained.

iii. Basing on the obtained information and provided assumption, the indicators of project

financial performance such as: EBITDA, EBIT, EBT Net Profit6 and Retained Earingns7 have

been estimated.

iv. Balance sheet that specifies all the equity & liabilities together with assets has been

prepared. Fragment of the balance sheet for first years of project operation can be seen

in the APPENDIX: IV.

v. The final Free Cash Flow to the Firm has been calculated using equation presented in

paragraph 4.2.1.

vi. Basing on the FCFF the final value of FCFE using the equation presented in the

paragraph 4.2.1.

vii. Final values of post-tax IRR and NPV has been obtained using information from both FCFF

and FCFE. The NPV indicators have been calculated using the in-built MS Excel function

and considering the WACC as discount rate for FCFF and CE as discount rate for FCFE.

Similarly for the IRR indicator, the in-built MS Excel function has been used.

viii. Payback time has been estimated using the cumulative values of FCFF and FCFE

6 Net Profit – sales income less the total cost of sold goods [76] 7 Retained earnings - cumulative net earnings or profit of a firm after accounting for dividends [77]



4.2.5. SENSITIVITY ANALYSIS

The major purpose of the sensitivity analysis to check how the obtained post-tax IRR and payback

time values will be changing while manipulating the cashflow components. Additionally, the

analysis will serve as a test of model functionality. The Table 7 presents all the considered

components together with the assumed values.

Table 7: Sensitivity Analysis Components

Type Changing Component Changing Value

Technical Irradaition => Energy production Basing on the location

Economic CAPEX & OPEX

500 – 700 EUR/kWP

9 – 15 EUR/ kWP

Price of Electricity 35 – 65 EUR/MWh

Financial Debt - to - Equity Ratio Every 10%

The analysis will be performed for every location, so that there is a possibility to check the

influence of the certain parameter on the particular location. The in-built Excel tool will be used

for the calculations.



5. RESULTS

This chapter will describe all the obtain results during the simulation process. Firstly, the technical

viability of the project will be presented together with the proposed plant structure. Economic

evaluation of the project will be presented afterwards together with the discussion of the results.

5.1. TECHNICAL RESULTS

Following the general structure of this document, firstly all the calculated technical parameters

will be presented.

The graphical representation of the energy transformation process has been generated for the

first year of plant operation. The diagram includes all the losses described in the Table 4 as well

as provides detailed information about amount of energy throughout the whole process. All the

information can be seen on the Figure 9. Regarding Spain and Portugal, the losses with the highest

share are related to the temperature. As for UK, the soiling losses represents the highest value.

Since in all the location the same plant design and the same components have been used, the

differences in produced electricity are mostly related to the irradiation levels.



Figure 9: Conversion process



Presented values describe the energy transformation process during only the first year of

operation, thus using the final values of energy injected to the grid, the further results have

been obtained. Table 8 contains yearly values of electricity injected to the grid as well as capacity

factor and performance ratio of the modelled solar PV plant. Additionally, the average values

for the project lifetime have been calculated.

Table 8: Results of the simulation: Generated Electricity and Plant Performance Indicators

Year Alcala de Guadaira (Spain) Evora (Portugal) Milton Keynes (UK)

Electricity [MWh] Cf PR Electricity [MWh] CF PR Electricity [MWh] CF PR

1 93215,00 21% 82% 89985,00 21% 83% 53819,00 12% 86%

2 90213,48 21% 79% 87087,48 20% 81% 52086,03 12% 83%

3 89551,65 20% 79% 86448,59 20% 80% 51703,91 12% 83%

4 88889,82 20% 78% 85809,70 20% 79% 51321,80 12% 82%

5 88228,00 20% 78% 85170,80 19% 79% 50939,68 12% 81%

6 87566,17 20% 77% 84531,91 19% 78% 50557,57 12% 81%

7 86904,34 20% 77% 83893,02 19% 78% 50175,45 11% 80%

8 86242,52 20% 76% 83254,12 19% 77% 49793,34 11% 80%

9 85580,69 20% 75% 82615,23 19% 76% 49411,22 11% 79%

10 84918,87 19% 75% 81976,34 19% 76% 49029,11 11% 78%

11 84257,04 19% 74% 81337,44 19% 75% 48646,99 11% 78%

12 83595,21 19% 74% 80698,55 18% 75% 48264,88 11% 77%

13 82933,39 19% 73% 80059,65 18% 74% 47882,76 11% 77%

14 82271,56 19% 72% 79420,76 18% 73% 47500,65 11% 76%

15 81609,73 19% 72% 78781,87 18% 73% 47118,53 11% 75%

16 80947,91 18% 71% 78142,97 18% 72% 46736,42 11% 75%

17 80286,08 18% 71% 77504,08 18% 72% 46354,30 11% 74%

18 79624,25 18% 70% 76865,19 18% 71% 45972,19 10% 74%

19 78962,43 18% 70% 76226,29 17% 70% 45590,07 10% 73%

20 78300,60 18% 69% 75587,40 17% 70% 45207,96 10% 72%

21 77638,77 18% 68% 74948,51 17% 69% 44825,85 10% 72%

22 76976,95 18% 68% 74309,61 17% 69% 44443,73 10% 71%

23 76315,12 17% 67% 73670,72 17% 68% 44061,62 10% 70%

24 75653,29 17% 67% 73031,83 17% 68% 43679,50 10% 70%

25 74991,47 17% 66% 72392,93 17% 67% 43297,39 10% 69%

∑ 2075674,33 19% 73% 2003749,99 18% 74% 1198419,96 11% 77%

According to the information presented in [1] the typical values of capacity factor are between

12-24%. Similar results have been obtained for the Cyprus island in [48], that has similar

irradiation values, thus it can be said that the power plant has been modelled correctly. Similarly

regarding the power ratio indicator; the yearly average values of high-performance PV power

plant are around 82%. The highest value can be observed in the UK installation, up to 86%. It is

due to low average, ambient temperatures and the lowest values of thermal losses. Energy



production during the life time of the project is decreasing because of degradation of used PV

panels.

Eventually, information regarding PV plant structure has been extracted from the PVSyst

software. Table 9 features all the details regarding PV plant structure.

Table 9: Solar PV plant parameters

Parameter Calculated Value

Nominal PV plant Power [MWp] 50

Number of Inverters 50

Number of Strings 7508

Number of Modules per String 18

Total Number of Modules 135144

Total Modules Area [m2] 262227

Basing on the given parameters as well as the information provided in [13] the following

assumptions regarding PV plant structure has been made:

• Due to its cheapness and simplicity, the radial collection grid topology, that connects

PV generators to the medium-voltage feeder line, has been selected.

• All the PV panels has been cluster together to form 50 arrays. Each array is connected

to the single inverter using the central topology

• Two inverters are connected to one three winding MV transformer as it is presented on

the Figure 10

Figure 10: Selected inverter topology [13]



5.2. ECONOMIC RESULTS

The results from the economic analysis have been divided into two parts. The first subchapter

will focus on the results that reflects current circumstances for development of large-scale PV

projects without subsidies, considering every of the examined location. The second subchapter

will present the results from the sensitivity analysis, that represents different factors that can

influence on the financial performance of the large-scale PV project.

5.2.1. BASE CASE RESULTS

Table 10 presents results from the economic evaluation of the project. These results indicate

the post-tax IRR, NPV and payback time, that have been calculated basing on the free cash flow

to firm FCFF for every of the examined location. Additionally, the discounted rate – WACC has

also been included in order to determine the project profitability.

Table 10: Free cashflow to firm - Results

Location Spain Portugal UK

NPV 1 309 281,72 EUR 2 395 179,56 EUR -7 178 325,21 EUR

IRR 6,17% 7,00% 2,22%

WACC 5,70% 6,12% 4,80%

Payback Time 12 years 11 years 20 years

It can be seen that in Spain and Portugal, the positive NPV values attest the profitability of the

investment. Moreover, the calculated post-tax IRR is higher than the assumed discount rate –

WACC, thus the return from the project will be higher than the initially expected one. The United

Kingdom results indicate the lack of project profitability considering the chosen assumptions.

The major reason is the lower energy production. This issue will be additionally analysed in the

following subchapter.

In order to estimate the payback time, the cumulative FCFF has been previously calculated. As

it can be seen on the Figure 11, the shortest payback period can be expected in Portugal – 11

years, while the longest in the United Kingdom – 20 years.



Figure 11: Cumulative FCFF for all the examined locations

The bend on the graph after 2030th is caused by the inverter replacement as it has been

assumed in the chapter 4.2.2.

Among the analysed locations, the best financial performance occurs in the Portuguese case,

even though the amount of energy injected to the grid in Spain is higher and the total value of

all the financial costs is lower. It is due to the highest overall costs during the lifetime of the

project compared with other locations. The high costs can be explained by the 7% tax on the

electricity that is injected to the grid. Considering the whole lifetime of the project this value is

equal to more than 6,5 million euros. The breakdown of the combined costs has been presented

on the Figure 12.

-€ 36

-€ 32

-€ 28

-€ 24

-€ 20

-€ 16

-€ 12

-€ 8

-€ 4

€ -

€ 4

€ 8

€ 12

€ 16

€ 20

€ 24

€ 28

€ 32

€ 36

2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038 2040 2042

Cu

mu

lati

ve F

CFF

Mill

ion

s

Project Lifetime

Cumulative FCFF over Project Lifetime

Spain

Portugal

UK



Figure 12: The cost division during the lifetime of the project

In general the highest taxation impact can be observed in Spain, followed by Portugal and Great

Britain. In United Kingdom the taxation represents only 1% of total costs due to the lowest value

of the corporate tax -19% as well as negative net profit value during first eight years of the

project operation.

O&M and depreciation costs represent the highest share also in the United Kingdom. It can be

explained by the highest CAPEX and OPEX among all of the analysed locations. On the other

hand the financing costs are the highest in Portugal due to the highest cost of debt that strongly

influences the credit rates.

The relation between revenues and all the aforementioned expenditures during the project

operation has been presented in the Figure 13.



Figure 13: Revenues vs Expenditures in all the examined locations

The decreasing revenues can be explained by the PV panels degradation effect while the

reduction in costs can be justified mostly by the descending values of the credit interests related

to the specification of the French method as well as grid connection costs. In case of Spain, the



electricity tax value is also decreasing since it is bounded directly with the amount of produced

electricity.

Once the costs of the project are decreasing the increase of the taxation costs can be observed.

It is due to higher net profit value of the project. On the graph it is represented by the increasing

area between the revenues and total expenditures.

As it was mentioned in the sub-chapter 4.2.4. the free cash flow to equity has been also

calculated basing on the values from free cash flow to the firm. The same economic indicators

have been obtained in order to determine, whether investors can expect equity return from the

project. Table 11 presents all the calculated results for every of the examined location.

Table 11: Free cashflow to equity - Results

Location Spain Portugal UK

NPV (FCFE) 234 501,60 EUR 1 271 048,57 EUR -6 851 030,54 EUR

IRR (FCFE) 8,23% 9,20% 0,64%

CE 8,00% 8,00% 7,00%

Similarly to the FCFF, the Spanish and Portuguese cases confirm the project potential for the

investors. The obtained IRR values indicates the profitability of the project because the

calculated return of the invested funds is expected to be higher than the assumed one. This fact

is additionally confirmed by the positive NPV indicators.

The cumulative FCFE has also been calculated for every location. The curves representing the

cumulative flow of equity have been presented on the Figure 14.

Figure 14: Cumulative FCFE for all the examined locations

-€ 14

-€ 10

-€ 6

-€ 2

€ 2

€ 6

€ 10

€ 14

€ 18

€ 22

2018 2023 2028 2033 2038 2043Cu

mu

lati

ve F

CFE

Mill

ion

s

Project Lifetime

Cumulated FCFE over Project Lifetime

Spain

Portugal

UK



The same as in case of FCFF, the best financial performance can be noticed in Portugal, closely

followed by Spain and then UK. Since, the FCFE values has been calculated basing on the results

from FCFF (see sub-chapter 4.2.1) the difference between Spain and Portugal are mostly due to

higher overal costs. Low financial performance of UK is caused by lower energy production.

Smaller differences between locations are reasoned by different values of principal credit rates

and interest, that has beem calculated according to the given assumptions.

Unlike in FCFF graph, the FCFE focuses mostly on the equity performance, thus two major cruves

bends can be observed. While the first one, around 2030th , represents the inverter

repleacement, the second one in 2038th indicates the moment of the full bank loan repay

(20-years loan period) . After this year, very sharp equity increase can be noticed in all of the

examined locations.

The dividends payment possibility has been checked according to the dividend policy described

in the sub-chapter 4.2.2. In case of Spain and Portugal, the overall amount paid to the investors

will be equal respectedly: 15 178 685,19 EUR and 17 757 173,90 EUR. Regarding the United

Kingdom the combined project net profit is lower than the proposed amounts of dividends, thus

the investors will not receive the expect equity return.

5.2.2. SENSITIVITY RESULTS

Once the profitability of the examined PV project has been determined in all of the locations,

the closer look will be made to the particular cashflow components that might affect the results.

Different components that influence different fields of PV project development have been

analysed. The description of all the components has been introduced in the chapter 4.2.5.

Technical Influence

The solar irradiation parameter has been checked. It is a very important parameter that has a

huge impact on the PV project site selection. It directly influences the amount of produced

energy and eventually the project incomes. The presents the location comparison considering

the irradiation factor and its effects.

Table 12: Location comparison

Location GHI [kWh/m2] Energy to the grid [MWh] Incomes [EUR]

Alcala de Guadaira 1852 2075674,33 € 94 129 236,45

Evora 1769 2003749,99 € 91 097 988,43

Milton Keynes 1010 1198419,96 € 64 594 836,08

As it can be seen, the GHI is around 1,75 times higher in Spain and Portugal than in United

Kingdom. It has a direct impact on the energy production and most importantly from the

developer point of view, on the plant incomes. Despite the fact, that the estimated in the

contract electricity prices in United Kingdom is higher by 18%, the overall incomes considering

the 25-years project lifetime are lower by approximately 30% compering to Spain and Portugal.



Assuming the scenario, that the contracted price of electricity is equal in every of the analysed

locations, the differences between less sun-filled Milton Keynes versus Alcala de Guadaira and

Evora would be even higher. The overall incomes in Spain and Portugal would be higher by more

than 40%. The calculated numbers indicate strong influence of solar irradiation on the incomes

and profitability of the PV project. Thus, proper site selection and solar resources measurement

is essential to have a thriving solar PV project.

Economic Influence

The impact of changing economic parameters such as costs and contracted electricity price has

also been examined. Firstly, the CAPEX and OPEX influence on the post-tax IRR has been

checked. The calculation has been performed, according to the values given in the Table 7,

considering both free cashflow to firm and equity. The obtained results for FCFF and FCFE have

been presented in the Table 13. The green colour represents the best financial performance

while the red one the worst. The marked values represent the results obtained from the base

case scenario, already described in the sub-chapter 5.2.1, while the slightly different first OPEX

value is due to different OPEX cost for UK. It is because of lower grid connection fee, explained

in chapter 4.2.2



Table 13: CAPEX & OPEX Sensitivity Analysis – post tax IRR

CAPEX\OPEX FCFF Spain FCFE Spain

[EUR/kWp] 15,22 14,50 13,50 12,50 11,50 10,50 9,50 15,50 14,50 13,50 12,50 11,50 10,50 9,50

500,00 7,87% 8,02% 8,21% 8,41% 8,60% 8,80% 8,99% 14,86% 15,29% 15,90% 16,50% 17,10% 17,70% 18,29%

525,00 7,31% 7,45% 7,64% 7,83% 8,02% 8,21% 8,40% 12,26% 12,64% 13,16% 13,68% 14,20% 14,72% 15,23%

550,00 6,80% 6,93% 7,12% 7,30% 7,49% 7,67% 7,85% 10,32% 10,66% 11,12% 11,58% 12,04% 12,50% 12,95%

575,00 6,32% 6,45% 6,63% 6,81% 6,99% 7,16% 7,34% 8,80% 9,10% 9,52% 9,94% 10,35% 10,76% 11,17%

600,00 5,87% 6,00% 6,17% 6,35% 6,52% 6,70% 6,87% 7,56% 7,84% 8,23% 8,61% 8,99% 9,36% 9,74%

615,00 5,62% 5,74% 5,92% 6,09% 6,26% 6,43% 6,60% 6,92% 7,19% 7,56% 7,92% 8,28% 8,64% 9,00%

650,00 5,06% 5,18% 5,35% 5,52% 5,69% 5,85% 6,01% 5,65% 5,90% 6,23% 6,56% 6,89% 7,22% 7,54%

675,00 4,69% 4,81% 4,98% 5,14% 5,30% 5,47% 5,63% 4,89% 5,12% 5,44% 5,75% 6,06% 6,37% 6,68%

700,00 4,34% 4,46% 4,62% 4,79% 4,94% 5,10% 5,26% 4,23% 4,44% 4,74% 5,04% 5,34% 5,63% 5,92%

CAPEX\OPEX FCFF Portugal FCFE Portugal

[EUR/kWp] 15,22 14,50 13,50 12,50 11,50 10,50 9,50 15,50 14,50 13,50 12,50 11,50 10,50 9,50

500,00 8,85% 9,00% 9,20% 9,40% 9,60% 9,80% 9,99% 16,49% 16,94% 17,57% 18,19% 18,82% 19,44% 20,05%

525,00 8,25% 8,39% 8,59% 8,78% 8,97% 9,17% 9,36% 13,65% 14,04% 14,58% 15,12% 15,66% 16,19% 16,72%

550,00 7,69% 7,83% 8,02% 8,21% 8,40% 8,58% 8,77% 11,52% 11,87% 12,35% 12,83% 13,30% 13,77% 14,24%

575,00 7,17% 7,31% 7,49% 7,68% 7,86% 8,04% 8,22% 9,86% 10,18% 10,61% 11,04% 11,47% 11,89% 12,32%

600,00 6,69% 6,82% 7,00% 7,18% 7,36% 7,54% 7,71% 8,52% 8,81% 9,20% 9,60% 9,99% 10,38% 10,77%

615,00 6,42% 6,55% 6,73% 6,90% 7,08% 7,25% 7,43% 7,83% 8,10% 8,48% 8,86% 9,23% 9,60% 9,97%

650,00 5,82% 5,95% 6,12% 6,29% 6,46% 6,63% 6,80% 6,45% 6,70% 7,05% 7,39% 7,73% 8,06% 8,40%

675,00 5,43% 5,55% 5,72% 5,88% 6,05% 6,22% 6,38% 5,63% 5,87% 6,19% 6,51% 6,83% 7,15% 7,46%

700,00 5,05% 5,17% 5,34% 5,50% 5,66% 5,83% 5,99% 4,91% 5,14% 5,44% 5,75% 6,05% 6,35% 6,65%

CAPEX\OPEX FCFF UK FCFE UK

[EUR/kWp] 15,22 14,50 13,50 12,50 11,50 10,50 9,50 15,50 14,50 13,50 12,50 11,50 10,50 9,50

500,00 4,13% 4,31% 4,56% 4,81% 5,05% 5,29% 5,52% 5,22% 5,75% 6,49% 7,21% 7,94% 8,65% 9,37%

525,00 3,66% 3,84% 4,08% 4,32% 4,55% 4,78% 5,01% 3,80% 4,26% 4,91% 5,54% 6,17% 6,79% 7,41%

550,00 3,22% 3,40% 3,63% 3,86% 4,09% 4,32% 4,54% 2,69% 3,11% 3,69% 4,26% 4,82% 5,38% 5,93%

575,00 2,82% 2,98% 3,21% 3,44% 3,67% 3,89% 4,11% 1,79% 2,18% 2,71% 3,23% 3,75% 4,25% 4,76%

600,00 2,43% 2,60% 2,82% 3,05% 3,27% 3,48% 3,70% 1,04% 1,40% 1,89% 2,38% 2,85% 3,33% 3,79%

615,00 2,22% 2,38% 2,60% 2,82% 3,04% 3,25% 3,46% 0,64% 0,99% 1,46% 1,93% 2,39% 2,84% 3,29%

650,00 1,74% 1,90% 2,11% 2,33% 2,54% 2,75% 2,95% -0,17% 0,15% 0,59% 1,02% 1,44% 1,86% 2,27%

675,00 1,42% 1,57% 1,79% 2,00% 2,21% 2,41% 2,61% -0,67% -0,36% 0,06% 0,47% 0,87% 1,27% 1,66%

700,00 1,12% 1,27% 1,48% 1,69% 1,89% 2,09% 2,29% -1,11% -0,82% -0,42% -0,03% 0,36% 0,74% 1,11%

As it has been expected, in all the locations, the post-tax IRR is increasing while the total CAPEX

and OPEX costs are decreasing. However, the IRR values calculated based on the free cashflow

to equity are more subjected to the changing costs. Additionally, it can be observed that the

change of CAPEX value influences the IRR more significantly than change in OPEX costs. It is

mostly due to higher share of capital costs in the overall project expenditures.



Similarly to the base case scenario, the best financial performance can be observed in Portugal,

following by Spain and eventually United Kingdom.

Regarding the base case scenario, payback time has also been calculated, basing on the FCFF

and including the same values of changing CAPEX and OPEX. The results have been presented

in the Table 14. The marked numbers represent the calculated payback time for the

assumptions used in the base case scenario.

Table 14: CAPEX & OPEX Sensitivity Analysis – payback time

CAPEX [EUR/kWp] Spain [years] Portugal [years] UK [years]

500,00 10 10 16

525,00 11 10 17

550,00 11 10 18

575,00 12 11 18

600,00 12 11 20

615,00 14 12 20

650,00 14 12 21

675,00 15 14 22

700,00 15 14 22

OPEX [EUR/kWp] Spain [years] Portugal [years] UK [years]

9,50 11 11 17

10,50 12 11 18

11,50 12 11 18

12,50 12 11 18

13,50 12 11 19

14,50 14 11 19

15,22 14 12 20

Identically to the previous post-tax IRR, the payback time is more influenced by changing CAPEX,

rather than the OPEX values. In all the locations, the estimated payback time is reducing

together with the costs decrease. Additionally, the estimated period was shorter than the

assumed project lifetime. The best payback performance can be observed in the Portuguese

case while the worst in case of United Kingdom. The direct jump from twelve to fourteen years

in Spain and Portugal can be explained by the additional investment – inverter replacement,

`that has been assumed for 13th year of operation.

Moreover, for every of the examined location price sensitivity analysis has also been prepared

basing on the assumptions provided in sub-chapter 5.2.2. The influence of price fluctuation on

the same financial indicators has been check. The results of the analysis can be observed on the

Figure 15.



Figure 15: Price Sensitivity Analysis – post-tax IRR and payback time

In every of the analysed locations, the post-tax IRR is increasing linearly together with the

increase in price of electricity. Similarly to the previous analysis, the IRR growth is more visible

in case of FCFE. It can be noticed that the change in price of electricity has as strong impact on



both, the IRR value and the payback time. The best performance is observed in Portugal, then

Spain and United Kingdom. In the last one, for the prices lower than 45 EUR/MWh, the

calculated payback time is longer than the assumed project lifetime.

Financial Influence

Eventually, the impact of the purely financial component has been checked. By modifying the

debt-to-equity ratio as described in sub-chapter 4.2.5, different post-tax IRR values have been

obtained. The analysis has been performed only basing on the FCFE since, FCFF IRR value is not

changing. It is an expected phenomenon because the FCFF represents the value of the project,

and the value should remain the same, no matter how the project is founded. The calculation

has been made for every location, however, the results focus mostly on the Spanish and

Portuguese cases. It is because of lack of profitability in the United Kingdom that will transfer

on lack of investors’ interest. The obtain results have been presented on the Figure 16.

Figure 16: Sensitivity Analysis – Debt-to-Equity Ratio

As it has been expected, the post-tax IRR value is increasing when there is a bigger bank loan

involved in the project, however, the relation is not linear. It is due to the fact, that the interest

rate required by the bank is lower than the rate expected from the external investors. Similarly

to the previous analysis, better performance can be observed in Portugal.

5,00%

7,00%

9,00%

11,00%

13,00%

15,00%

17,00%

19,00%

21,00%

10% 20% 30% 40% 50% 60% 70% 80% 90%

IRR

Debt-to-Equity Ratio

IRR vs D/E Ratio

FCFE Spain

FCFE Portugal



6. CONCLUSIONS

The major question of this dissertation was: Whether it is profitable to develop a large-scale PV

project without any form of governmental support? Basing on the performed analysis and

assumed conditions, it can be stated that in the selected locations in Spain and Portugal, the

large-scale photovoltaic installations can bring benefits to the investors. The obtain results

corresponds to the one from the real-life project already introduced in the sub-chapter 1.4.

Additionally, the results reflect the current solar market situation that according to the

information provided on the conference [12], is strongly focused on the transition towards the

subsidy-free PV projects. Only in Spain and Portugal, there is in total 479 MW of subsidy-free

PV projects that are currently built or under construction [15].

The final results obtained for the selected location in United Kingdom present lack of

profitability, however performed sensitivity analysis shows that if PV CAPEX and OPEX will

continue their current decreasing trend, the profitability can be reached within few years. This

information has been additionally confirmed during the aforementioned conference [12].

Moreover, there are already subsidy-free PV projects under construction in the United

Kingdom. The 10 MW Clayhill solar farm in Milton Keynes is already operating without any form

of subsidies. The plant, however, is co-located with 5 energy storage units of total capacity of

6 MW [20]. The EES implementation is fully understandable considering the insolation

conditions present in the United Kingdom. It is believed that the storage implementation will

significantly increase the profitability of the solar PV projects in the nearest future.

Besides the storage implementation, the profitability of the solar PV plant can be also increased

by the favourable policy towards solar power installation. This fact could be observed by the

differences between the results obtained for locations in Portugal and Spain. Despite similar

solar conditions as well as set electricity price, the obtained IRR values were higher in the

Portuguese case. It is mostly due to higher tax rates present in Spain. Considering purely

financial aspect, the results of the sensitivity analysis show that the IRR values are increasing

significantly together with higher share of debt in the project financing.

It can be noticed that the obtain results additionally supplement the described in the

introduction chapter solar grid and market parity. It shows that the solar energy is becoming

more and more competitive on the wholesale electricity market and that this trend is slowly

going to the north of Europe. According to [67] if the carbon prices get higher, the solar plants

might advantage even more over the conventional energy sources. This phenomenon is

additionally supported by the environmental aspect. According to the information contained in

[47], the comparison of PV plants with conventional sources of energy, that uses fossil fuels,

estimates the environmental savings at 690 gCO2/kWh of produced electricity. Considering the

assumed project lifetime (25-years), the environmental benefits can be equal to approximately:

• 28,64 tons of CO2 eq. per kW installed in Spain

• 27,65 tons of CO2 eq. per kW installed in Portugal

• 16,54 tons of CO2 eq. per kW installed in United Kingdom



These values could increase if the recycling process of the PV modules would be included in the

calculations. However, the recycling also increases the overall costs of the PV project thus, it

has not been included in the analysis in any form.

Despite many advantages of further implementation of PV technologies, there are several issues

that have to be addressed in order to prevent from the unexpected situations in the future. The

grid stability, that concerns not only further increase of the PV installations in the system, but

almost whole renewable sources of energy has to be control and constantly improved in order

to avoid power blackouts. Another issue that has to be monitored is the huge boom towards

further development of the solar PV project mostly caused by constantly decreasing PV prices.

Such phenomenon, if not controlled properly, can lead to the price cannibalisation effect, that

describe the situation when the large volumes of energy will lead to reduction of the wholesale

electricity prices, that may eventually result in decrease of the PV projects profitability.

The conducted analysis has been performed in a detailed way with the observance of due

diligence. The obtained results are credible and confirmed the current solar market activities as

well as are coherent with similar projects. However, considering further work on the following

topic, several improvements could be made:

• Since every PV project consist of different internal conditions, it is difficult to perform

a general comparison between different locations in different countries. In order to do

so, several assumptions have been made identical for every of the examined location

such e.g. the land rental cost. Access to the real-life, more specific data regarding

project implementation would be recommended in order to improve the quality and

credibility of this analysis.

• Due to lack of specific information, the taxation calculations have been performed using

the same method for every of the examined location. More detailed research of this

aspect should be performed in order to increase the credibility of this analysis. Country

related taxation process, additionally including the regional and municipal taxation

rates, should be applied for every of the examined location.

• The performed technical analysis have been made using the PVSyst software that is

considered to be a very respectful tool. The obtained technical parameters such as PR

and CF confirm proper plant modelisation, however the values of the project losses

presented in the Table 4 have been assumed using quite conservative approach. It

directly influences the amount of produced electricity, that is slightly lower in

comparison with another real-life PV project with similar parameters. Less conservative

approach could additionally increase the profitability of the examined project.

Despite the aforementioned possibilities of improvement, the performed work presents wide

analysis of the research topic and can serve as a valuable source of information regarding the

profitability assessment of the large-scale PV projects, considering different technical,

economical and geographical factors. It can be additionally used as a base for other analysis of

the given research question, that considering current movement towards unsubsidized PV

projects can become more popular in the nearest future.



7. BIBLIOGRAPHY

[1] Sgurr Energy, Utility-Scale Solar Photovoltaic Power Plants, A Project Developer's Guide,

Washington: International Finance Corporation, World Bank Group, 2015.

[2] S. Evans, “Eco-Business,” 28 March 2018. [Online]. Available: http://www.eco-

business.com/news/what-does-subsidy-free-renewables-actually-mean/. [Accessed 3

September 2018].

[3] L. Abend, “nature - International weekly journal of science,” 19 December 2008.

[Online]. Available: https://www-nature-

com.focus.lib.kth.se/news/2008/081219/full/news.2008.1326.html. [Accessed 3

September 2018].

[4] M. A. Noceda, “El Pais In English,” 5 May 2017. [Online]. Available:

https://elpais.com/elpais/2017/05/05/inenglish/1493988308_857826.html. [Accessed

3 September 2018].

[5] “Solar Market Parity,” Solarplaza, 4 April 2018. [Online]. Available:

https://solarmarketparity.com/webinar/. [Accessed 3 September 2018].

[6] J. D. Mondol and S. K. Hillenbrand, “Grid parity analysis of solar photovoltaic systems in

Europe,” International Journal of Ambient Energy, vol. 35, no. 4, pp. 200-210, 2013.

[7] BayWa r.e., “Case study: a utility-scale subsidy-free plant in Spain,” Benedikt Ortmann,

Milan, 2018.

[8] Aurora Energy Research , “Aurora Energy Research,” April 2018. [Online]. Available:

https://www.auroraer.com/insight/subsidy-free-revolution/. [Accessed 3 September

2018].

[9] Aurora Energy Research , “Aurora Energy Research,” March 2018. [Online]. Available:

https://www.auroraer.com/insight/managing-merchant-risk-in-renewables/. [Accessed

3 September 2018].

[10] J. Deign, “Solarplaza,” Solarplaza, 4 April 2018. [Online]. Available:

https://www.solarplaza.com/channels/finance/11813/who-needs-subsidies-when-

there-solar-market-parity/. [Accessed 3 September 2018].

[11] S. Media, “Large Scale Solar Europe The Transition To Subsidy Free,” Dublin, 2018.

[12] Solarplaza, “Solar Market Parity Conference,” Milan, 2018.



[13] A. Cabrera-Tobar, E. Bullich-Massague, M. Aragues-Penalba and O. Gomis-Bellmunt,

“Topologies for large scale photovoltaic power plants,” Renewable and Sustainable

Energy Reviews, no. 59, pp. 309-319, 2015.

[14] EDIFICIO GRUPO ENERPRO, “Grupo Enerpro,” [Online]. Available:

http://www.grupoenerpro.es/unsubsidized-solar-power-gives-it-a-go-in-spain-2/.

[Accessed 3 September 2018].

[15] Bloomberg New Energy Finance, “Europe's new era of subsidy-free PV,” Pietro Radoia,

Milan, 2018.

[16] S. Dunlop and A. Roesch, “EU-Wide Solar PV Business Models,” Solar Power Europe,

2016.

[17] P. Donnelly-Shores, 30 July 2013. [Online]. Available:

https://www.greentechmedia.com/articles/read/what-does-utility-scale-solar-really-

mean#gs.pmCTw_U. [Accessed 3 September 2018].

[18] Solar Energy Industries Association, “SEIA,” [Online]. Available:

https://www.seia.org/initiatives/utility-scale-solar-power. [Accessed 3 September

2018].

[19] E. Bellini, “Pv Magazine,” 12 January 2018. [Online]. Available: https://www.pv-

magazine.com/2018/01/12/portugal-unsubsidized-approved-large-scale-pv-projects-

top-756-mw-first-solar-private-ppa-signed/. [Accessed 3 September 2018].

[20] Anesco, Anesco, [Online]. Available: https://anesco.co.uk/clayhill-uks-first-subsidy-free-

solar-farm/. [Accessed 3 September 2018].

[21] European Comission, [Online]. Available:

https://ec.europa.eu/energy/en/topics/markets-and-consumers/market-legislation.


[22] European Comission, [Online]. Available:

https://ec.europa.eu/energy/en/topics/energy-strategy-and-energy-union/clean-

energy-all-europeans. [Accessed 3 September 2018].

[23] G. Erbach, “Understanding electricity markets in the EU,” European Parliment, 2016.

[24] OMiE, [Online]. Available: http://www.omie.es/en/home/markets-and-

products/european-market/market-coupling-operator-mco-plan. [Accessed 3

September 2018].

[25] OMiE, “PCR Project,” [Online]. Available: http://www.omie.es/en/home/markets-and-

products/european-market/pcr/presentations. [Accessed 3 September 2018].



[26] World Business Council for Sustainable Development, “Corporate Renewable Power

Purchase Agreements,” Geneva, 2015.

[27] Solar Power Europe, “Corporate Renewable Energy Sourcing - The future of PPAs in

Europe,” 5 March 2018. [Online]. Available:

https://register.gotowebinar.com/recording/viewRecording/6027938747205066497/3

490106481958770178/[email protected]?registrantKey=511069866012921652

3&type=ABSENTEEEMAILRECORDINGLINK. [Accessed 3 September 2018].

[28] L. T. Maurer and L. A. Barroso, Electricity Auctions: An Overview of Efficient Practices,

Washington: The World Bank, 2011.

[29] N. Mazzi, A. Lorenzoni, S. Rech and A. Lazzaretto, “Electricity auctions: an European view

on merkets and practices,” IEEE, 2015.

[30] OMiE, [Online]. Available: http://www.omie.es/en/home/markets-and-

products/electricity-market/our-electricity-markets/daily-and-intradaily. [Accessed 3

September 2018].

[31] M. Dorothal, Solarplaza, [Online]. Available: https://solarmarketparity.com/market-

parity-watch-source/2018/5/1/top-15-merchant-solar-

plants?utm_source=solarplaza&utm_medium=email&utm_campaign=top-15-

merchant-solar. [Accessed 3 September 2018].

[32] European Comisson, [Online]. Available: https://ec.europa.eu/energy/en/topics/energy-

strategy-and-energy-union/building-energy-union. [Accessed 3 September 2018].

[33] International Energy Agency, “Renewables information: Overview,” IEA, 2017.

[34] European Comission, “EU Energy in Figures: Statistical Pocketbook,” Luxembourg, 2017.

[35] EY, “Capturing the sun. The economics of solar investment,” 2016.

[36] IRENA, “Renewable Power Generation Costs in 2017,” Internation Renewable Energy

Agency, Abu Dhabi, 2018.

[37] D. Feldman, J. Hoskins and R. Margolis, “Q4 2017/Q1 2018 Solar Industry Update,”

National Renewable Energy Laboratory, Denver, 2018.

[38] R. Fu, D. Feldman, R. Margolis, M. Woodhouse and K. Ardani, “U.S. Solar Photovoltaic

System Cost Benchmark: Q1 2017,” National Renewable Energy Laboratory, Denver,

2017.

[39] C. S. Lai and M. D. McCulloch, “Levelized cost of electricity for solar photovoltaic and

electrical energy storage,” Applied Energy, no. 190, pp. 191-203, 2017.



[40] F. Díaz-González, Interviewee, [Interview]. 15 July 2018.

[41] L. Dusonchet and E. Telaretti, “Comparative economic analysis of support policies for

solar PV in the most representative EU countries,” Renewable and Sustainable Energy

Reviews, no. 42, pp. 986-998, 2015.

[42] L. Dusonchet and E. Telaretti, “Economic analysis of different supporting policies for the

production of electrical energy by solar photovoltaics in western European Unione

countries,” Energy Policy, no. 38, pp. 3297-3308, 2010.

[43] J. d. l. Hoz, H. Martin, B. Martins, J. Matas and J. M. Guerrero, “Comments on‘‘Economic

analysis of different supporting policies for the production of electrical energy by solar

photovoltaics in western European Union countries",” Energy Policy, no. 48, pp. 846-

849, 2012.

[44] Y. Karneyeva and R. Wustenhagen, “Solar feed-in tariffs in a post-grid parity world: The

role of risk, investor diversity and business models,” Energy Policy, no. 106, pp. 445-456,

2017.

[45] P. Mir-Artigues, E. Cerda and P. d. Rio, “Analyzing the impact of cost-containment

mechanisms on the profitability of solar PV plants in Spain,” Renewable and Sustainable

Energy Reviews, no. 46, pp. 166-177, 2015.

[46] F. Cucchiella, I. D'Adamo and M. Gastaldi, “A profitability assessment of small-scale

photovoltaic systems in an electricicty market without subsidies,” Energy Conversion and

Management, no. 129, pp. 62-74, 2016.

[47] F. Cuchiella, I. D'Adamo and P. Rosa, “Industrial Photovoltaic Systems: An Economic

Analysis in Non-Subsidized Electricity Markets,” Energies, 2015.

[48] A. Poullikkas, “Parametric cost-benefit analysis for the installation of photovoltaic parks

in the island of Cyprus,” Energy Policy, no. 37, pp. 3673-3680, 2009.

[49] P. Caballero, G. Srinivasan and M. Suri, “Solargis,” 26 July 2018. [Online]. Available:

https://solargis.com/blog/best-practices/how-to-calculate-p90-or-other-pxx-pv-

energy-yield-estimates/. [Accessed 3 September 2018].

[50] PVTech, “Levelized Cost of Electricity of PV- Large Scale Plants with JinkoModules

Technologies,” 30 May 2018. [Online]. Available: https://www.pv-

tech.org/webinars/webinar-levelized-cost-of-electricity-of-pv-large-scale-plants-with-

jinkomo. [Accessed 3 September 2018].

[51] JinkoSolar, “JinkoSolar Datasheets,” [Online]. Available:

https://www.jinkosolar.com/download_356.html. [Accessed 3 September 2018].



[52] JinkoSolar, [Online]. Available: https://www.jinkosolar.com/about_1.html?lan=en.


[53] E. Bullich-Massague, Interviewee, [Interview]. 2 July 2018.

[54] SMA, “Sunny Central 1000 CP XT,” [Online]. Available:

https://www.sma.de/en/products/solarinverters/sunny-central-1000cp-xt.html.


[55] A. Mermoud and B. Wittmer, “Tutorial PVSyst SA - PVSyst 6,” Satigny, 2017.

[56] PVSyst, “Irradiance Loss,” [Online]. Available:

http://files.pvsyst.com/help/irradiance_loss.htm. [Accessed 4 September 2018].

[57] National Renewable Energy Laboratory, “Solar PV AC-DC Translation,” [Online].

Available: https://atb.nrel.gov/electricity/2017/pv-ac-dc.html. [Accessed 4 September

2018].

[58] SMA Solar Technology AG, “Performance ratio - Oulity factor for the PV plant,” SMA.

[59] Investopedia, “Free Cash Flow for the Firm,” [Online]. Available:

https://www.investopedia.com/terms/f/freecashflowfirm.asp. [Accessed 4 September

2018].

[60] Investopedia, “Free Cash Flow to Equity - FCFE,” [Online]. Available:

https://www.investopedia.com/terms/f/freecashflowtoequity.asp. [Accessed 4

September 2018].

[61] Investopedia , “Weighted Average Cost of Capital (WACC),” [Online]. Available:

https://www.investopedia.com/terms/w/wacc.asp. [Accessed 4 September 2018].

[62] Investopedia, “Net Present Value - NPV,” [Online]. Available:

https://www.investopedia.com/terms/n/npv.asp. [Accessed 4 Septemebr 2018].

[63] Investopedia, “Internal Rate of Return - IRR,” [Online]. Available:

https://www.investopedia.com/terms/i/irr.asp. [Accessed 4 September 2018].

[64] Investopedi, “Payback Period,” [Online]. Available:

https://www.investopedia.com/terms/p/paybackperiod.asp. [Accessed 4 September

2018].

[65] OMiE, “Price Report,” 2017.

[66] OFGEM, “Wholesale Market Indicators,” [Online]. Available:

https://www.ofgem.gov.uk/data-portal/wholesale-market-indicators. [Accessed 4

September 2018].



[67] J. Garrido, Interviewee, [Interview]. 28 August 2018.

[68] J. Beese, Interviewee, [Interview]. 10 August 2018.

[69] F. Horta, Interviewee, [Interview]. 10 July 2018.

[70] A. Damodaran, “Data: Current,” [Online]. Available:

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datacurrent.html. [Accessed

4 September 2018].

[71] A. Damodaran, “Country Default Speads and Risk Premiums,” [Online]. Available:

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/ctryprem.html.


[72] KPMG, “Corporate Marginal Tax Rates - By country,” [Online]. Available:

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/countrytaxrate.htm

. [Accessed 4 September 2018].

[73] S. Pfeifer and M. Pooler, “UK industry pays 33% more for electricity than rest of Europe,”

Financial Times, 5 February 2018. [Online]. Available:

https://www.ft.com/content/2ffd8d62-0828-11e8-9650-9c0ad2d7c5b5. [Accessed 5

September 2018].

[74] A. E. Specialist, Interviewee, [Interview]. 27 August 2018.

[75] “Collins,” [Online]. Available:

https://www.collinsdictionary.com/dictionary/english/learning-curve. [Accessed 3

September 2018].

[76] Investopedia, “Net Income,” [Online]. Available:

https://www.investopedia.com/terms/n/netincome.asp. [Accessed 4 September 2018].

[77] Investopedia, “Retained Earnings,” [Online]. Available:

https://www.investopedia.com/terms/r/retainedearnings.asp. [Accessed 4 September

2018].

[78] Investopedia, [Online]. Available:

https://www.investopedia.com/terms/e/economiesofscale.asp. [Accessed 8 September

2018].



APPENDIX I The follwoing appendix will provide detailed information regarding the selected components:

PV Pannel - Eagle PERC 72M



Inverter - Sunny Central 1000CP XT



APPENDIX: II The following appendix will provide information regarding the major project settings selected

in the PVSyst software for the analysis.

APPENDIX: III The following table contains the average wholesale electricity prices from last 8 years for every

of the examined location. The prices have been given in EUR/MWh.

2010 2011 2012 2013 2014 2015 2016 2017 Average

Spain 37,01 49,93 47,23 44,26 42,13 50,32 39,67 52,24 45,35

Portugal 37,33 50,45 48,07 43,65 41,86 50,43 39,44 52,48 45,46

UK 50,40 56,00 51,52 60,48 47,04 45,92 67,20 52,64 53,90



APPENDIX: IV The following figure presents the equities/liabilities and assets included in the balance sheet.

SPAIN



PORTUGAL



UNITED KINGDOM



Additionally, the following picture presents the method for calculating the cash position. Numbers have been taken from the Spanish case:

is it profitable to develop a large-scale pv plant without

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