A worldwide assessment of economic feasibility of HCPV power plants: Profitability and competitiveness

Energy 119 (2017) 408e424

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A worldwide assessment of economic feasibility of HCPV power plants: Profitability and competitiveness
rez-Higueras a, b, F. Almonacid a, b, E.F. Ferna
ndez a, b D.L. Talavera a, *, P. Pe a b

IDEA Research Group, University of Ja
en, Campus Lagunillas, 23071 Ja
en, Spain Centre for Advanced Studies in Energy and Environment, University of Ja
en, Campus Lagunillas, Ja
en, Spain

a r t i c l e i n f o

a b s t r a c t

Article history: Received 19 July 2016 Received in revised form 18 November 2016 Accepted 22 December 2016

Numerous exhaustive analyses of the economic assessment of conventional PV systems are available in the literature. However, there is a lack of these studies concerning High Concentrator Photovoltaic (HCPV) technology. Besides, future owners and potential investors on HCPV plant demand information relating to the economic feasibility of their investment. In this work the profitability and competitiveness of HCPV plants in several countries are analysed. To analyse the profitability the internal rate of return (IRR) criterion has been used, while the competitiveness has been analysed based on estimating the socalled HCPV generation parity. As a result of the economic profitability analysis conducted the group of countries where the investment in HCPV could be interesting has been identified. The results obtained could be also useful for researchers to identify the weaknesses of the HCPV technology and take actions at making it more competitive. From the competitiveness analysis carried out in several Eurozone countries and USA for two possible scenarios 2015 and 2020, the results show that HCPV could be competitive in some locations in 2020. Therefore, government organizations of the studied countries, which participate in the design or the selection of support mechanisms for HCPV, can be guided by the results obtained. © 2016 Elsevier Ltd. All rights reserved.

Keywords: Internal rate of return High Concentrator Photovoltaic Generation parity

1. Introduction Nowadays, the solar photovoltaic (PV) is one of the most extended renewable energy systems worldwide. Among the different PV technologies, the High Concentrator Photovoltaic (HCPV) technology, based on concentrating the sunlight on a smallsize solar cell, is one of the most promising to produce costcompetitive electricity. The HCPV technology uses an optical concentrator to collect the solar radiation and concentrate it, usually in a range from 500 up to 1000 times, onto small and highly efficient solar cells [1]. The optical concentrators used in HCPV are usually made up of a primary optical device to collect and concentrate the direct normal irradiation (DNI), and a secondary optical device to homogenize the light on the solar cell surface, thus improving the performance of the system [2e4]. Regarding the solar cells used in HCPV technology they consist of several p-n junctions of III-V semiconductor alloys with the aim of increasing the efficiency of the device [5e8]. The current efficiency of the solar

* Corresponding author. E-mail address: [email protected] (D.L. Talavera). http://dx.doi.org/10.1016/j.energy.2016.12.093 0360-5442/© 2016 Elsevier Ltd. All rights reserved.

cells used in HCPV is over 46%, and continues to increase meaning HCPV technology has a great potential for reducing costs. A HCPV grid-connected system is made up of HCPV modules mounted on a high-accuracy solar tracker, interconnected in series and parallel and connected to a high efficiency DC/AC inverter, and the rest of balance of system components (BOS) [9e12]. As mentioned, the efficiency of MJ solar cells used in the HCPV modules, and therefore, the efficiency of HCPV modules and systems, is increasing over time, and is expected to reach values up to 50%, 45% and 40% for MJ solar cells, HCPV modules and systems, respectively, within the next few years [13,14]. Moreover, HCPV technology has already provided promising results and shows a trend to decrease the cost of electricity generated with these systems at locations with high values of DNI [15,16]. All of this makes HCPV technology an alternative renewable power source with a great potential that could play an important role in the global energy market [17]. Despite the great potential of HCPV in of decreasing the associated costs of the electricity generation, additional costs are involved due to use of optical concentrators, trackers, and operation and management costs, etc. Therefore, further research is needed to remove technical and economic barriers, with the aim of

D.L. Talavera et al. / Energy 119 (2017) 408e424

decreasing the electricity production costs and to make this technology truly competitive in the marketplace. Concerning economic aspects the following two main concerns can be cited: on the one hand, a lack of studies that evaluate the economic profitability; on the other hand, the competitiveness of HCPV technology needs to be more thoroughly studied. In the case of conventional Photovoltaic (PV) technology (either crystalline or thin film ones) there is a significant number of studies and researches papers concerning different economic aspects related to PV systems [18,19]. Others studies analysing the economic profitability of PV systems by means of different methods such as: net present value (NPV), discounted payback time (DPBT) and internal rate of return (IRR) [20e27] and the competitiveness by means of the grid-parity analysis [28,29]. The results of these studies provide invaluable information to assess, on one hand, the feasibility of the investments and, on the other hand, to support policy makers in order to outline renewable energy promotion policies. However, in HCPV technology there is a lack of studies that evaluate the economic profitability or do a detailed analysis of the competitiveness of the power plants based on this technology, only the studies presented in Refs. [30e33] address some economical aspects related to HCPV technology. Thus, in Ref. [30] the authors conducted an analysis of economic profitability using the NPV, the benefit-to-cost ratio (BCR) and IRR criteria for two scenarios 2013 and 2020, while in Ref. [31] a cost analysis using the Levelised Cost of Electricity (LCOE) criterion was carried out at different scenarios. In Ref. [32], an analysis of economic viability using the NPV and the Levelised Cost of Electricity (LCOE) criteria was carried out at two locations (Las Vegas (Nevada) and Ottawa (Ontario)). In Ref. [33] the LCOE of HCPV grid connected systems worldwide is estimated and analysed. The present work tries to resolve this lack by conducting an economic profitability analysis and a competitiveness analysis for HCPV power plants in worldwide countries and regions. In order to analyse the economic profitability of these plants the internal rate return method has been used. From the internal rate return method the value of the required tariff of a specific HCPV power plant is obtained. The required tariff is the price obtained for kWh generated and injected to the electrical grid by a HCPV plant, and that allows the minimum profitability sought by future owners or investors of HCPV plants to be reached. In order to determine the required tariff, the specific parameters of each country have been taken into account: the irradiance (DNI), the financial cost, income tax rate and inflation. Other parameters such as the initial investment cost of HCPV plant have been considered the same for all locations. As result of this analysis, the required tariff for HCPV power plants will be estimated in countries around the world. In particular, the analysis will cover 133 countries and the results obtained will be graphically shown in a set of original worldwide maps. The competitiveness analysis of HCPV power plants has been analysed basing on the estimation of the so-called HCPV generation parity. The HCPV generation parity happens when the tariff required by owners or investor matches the electricity price in the wholesale market. Therefore, in the competitiveness analysis, the required tariff for a HCPV plant (in cV/kWh) is compared with the wholesale electricity price, in some locations considered. It will show where HCPV power plants could be competitive with respect to conventional electrical generation systems, how long it will take to reach parity or if it has already been reached in the country. The proposed methodology is going to be a useful tool to identify those countries where the HCPV plants can be a feasible technology as a power source. Moreover, the results obtained are an original contribution regarding HCPV electrical generation profitability on a global basis. Furthermore, the map-based methodology

409

proposed in the paper is easy to handle and can be consulted and managed by future owners, investors and financial entities involved in HCPV plants. But these studies are not only valid for future owners and investors, they will be also useful for researchers in order to identify the main weaknesses of the HCPV technology depending not only on technological but also economical and geographical parameters, and to propose improvements aimed of making this technology more competitive. Finally, it is important to highlight that in the present paper a HCPV power plant is defined as a HCPV grid-connected system with a nominal power greater than 10 MWp. On the other hand, concerning the data, i.e. direct normal irradiation (DNI), since this work is a global analysis and the values of the parameters can be obtained from different sources, the results obtained may differ slightly depending on the sources of data used (e.g. Meteonorm, PWATTS, PVGIS, etc.). 2. Methodology and data As mentioned above, in this paper, the economic profitability analysis is done through the internal rate return method while to evaluate the competitiveness of HCPV power plants the so-called HCPV generation parity is studied. In the first case, the values of the required tariff of a specific HCPV power plant is obtained with the IRR method, this tariff being that which satisfies the minimum profitability sought by the owners or investors. To evaluate the competitiveness of HCPV power plants, the required tariff is compared with wholesale market prices of electricity, in order to determine if generation parity has been reached or how long it will take. In this section, the methodology used to analyse economic profitability and competitiveness of HCPV power plants (>10 MWp) is described in detail. The analysis has been conducted from the point of view of owner or investor as power producers that sell the generated electricity to the wholesale market. 2.1. Economic analysis The most common criteria aimed at measuring the economic feasibility of the project investment are: Net Present Value (NPV, in V), Benefit-Cost Ratio (BCR), Internal Rate of Return (IRR) and Discounted Payback Time (DPBT, in years). Criteria based on NPV, BCR and IRR are addressed at measuring profitability, while DPBT is aimed at measuring the liquidity of the investment. As mentioned, the internal rate of return (IRR) criterion has been used for analysis of economic profitability in this paper. The procedure followed to calculate this criterion, similar to those presented in previous work [17,22,34,35], is shown below. First of all, the Net Present Values criterion is going to be formulated since it is necessary for calculating the IRR. The NPV of a project is defined as the difference between the present values of the cash inflows and cash outflows generated by the investment over the lifetime of the project. This is given by the expression:

NPV ¼ HCPVI þ PV½NCFðNÞ

(1)

where HCPVI (V) is the initial investment cost of a HCPV power plant, PV[NCF(N)] (V) is the present value of the net cash flows over the lifetime of the power plant and N (years) is the lifetime of the HCPV power plant. The present value of the net cash flows PV[NCF(N)] may be written:

PV½NCFðNÞ ¼ PV½CIðNÞ  PV½COðNÞ þ PV½DEPðNdÞ

(2)

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The first term in the Eq. (2) PV ½CIðNÞ(V) represents the present value of the cash inflows over the lifetime of the HCPV plant and it may be expressed as:


 Kd 1  KdN PV½CIðNÞ ¼ YfHCPV $ps $ð1  TÞ$ 1  Kd

(3)

Regarding this parameter, cash inflows are obtained by means of the annual final yield (YfHCPV (kWh/(kWp year))), the generated electricity which is fed into the grid and compensated at a price (ps in V/kWh), the income tax rate (T in %) and the factor Kd. The factor Kd ¼ (1 þ Dps)$(1  rd)/(1 þ d), where Dps stands for the annual escalation rate of the electricity price that is fed to the grid, the factor rd (%) is the annual degradation rate in the efficiency of the HCPV power plant and d the nominal discount rate. The second term in Eq. (2) (V) represents the present value of the cash outflows over the lifetime of the HCPV plant and it may be written as:


KP $ 1  KPN PV½COðNÞ ¼ HCPVAOM ð1  TÞ$ 1  KP

(4)

where HCPVAOM (V) is the annual operation and maintenance cost, assumed constant over the system life time, this can be done because the factor Kp ¼ (1þ DO&M)/(1 þ d) has been taken into account. The factor DO&M represents the annual escalation rate of the operation and maintenance cost of the HCPV power plant. Finally the third term Eq. (2) PV½DEP ðNdÞ(V) represents the present value of the tax depreciation. Tax depreciation is a means of recovering part of the investment cost through reduced taxes. PV½DEP ðNdÞ may be rewritten as follows:

  q$ 1  qNd $T PV½DEPðNd Þ ¼ DEPy $ 1q

(5)

"

where DEPy (V) is the annual tax depreciation for the HCPV power plant. The method used (e.g. straight line or declining balance) and the tax depreciation period of time (Nd, in years) will affect the analysis. The factor q is related to the nominal discount rate (d) through the following equation:

q ¼ 1 =ð1 þ dÞ

(6)

Next, once the procedure to calculate the NPV has been defined, the procedure followed in this paper to calculate the IRR is going to be explained. The IRR is defined as the value of the discount rate d that leads to NPV equal to zero. The internal rate of return represents the profitability expected from a project expressed as a percentage, while net present value (NPV) is expressed in monetary value, as an absolute magnitude. According the above equations, this means:


3 Kd 1  KdN 5 0 ¼ HCPVI þ 4YfHCPV $ps ,ð1  TÞ, 1  Kd 3
2 KP $ 1  KPN 5  4HCPVAOM ð1  TÞ$ 1  KP "   # q$ 1  qNd þ DEPy, $T 1q

of view, a project of HCPV plant should be accepted if the IRR exceeds a profitability threshold fixed by the future owners or investors, exceeding a cut-off rate given by the opportunity cost or IRR is above weight average cost of capital (WACC). Organizations typically use the value of the organization's weighted average cost of capital as required IRR in investment project [26,37]. In this paper it is assumed that the required IRR of a HCPV power plant is equal to WACC in order to carry out an economic analysis. Hence, taking this into account, the procedure followed to calculate the WACC is going to be explained below. The project investment is usually financed by means of debt or equity capital. Some forms of debt include long-term loans, bonds and debentures. Other forms of financing include common stock and preferred stock (equity capital). The paid dividends (return on equity) from both, common and preferred stocks are not tax deductible, while paid debt interest is tax deductible. Making a decision on the most suitable financing option of the investment project implies choosing a specific one or, more commonly, a combination of them. In renewable energy projects, long-term debt financing may be chosen because the cost of debt is usually lower than that of equity capital. Therefore, initial investment cost of a HCPV power plant (HCPVI, in V) may be financed through long-term debt and/or by means of equity capital. In the case where HCPVI is financed through a loan (HCPVl) -debt- and the remainder by means of the issue of stocks (HCPVs) -equity capital-then HCPVI ¼ HCPVl þ HCPVs. Some of the first renewable energy policies applied in some countries considered a subsidy for the initial investment cost. This supporting mechanism is included in our analysis methodology to collect all the possible scenarios. In those cases where an investment subsidy (HCPVIS, in V) ein the form of grants, rebates, buy down subsidies, among otherse is applicable the amount to be financed through a loan and issue of stock would be: HCPVI  HCPVIS ¼ HCPVl þ HCPVs. Hence, the initial investment cost may be expressed as:

2

il ð1  TÞ

HCPVI ¼ HCPVl $ ,PVIFðNl Þ 1  ð1 þ il ð1  TÞÞNl i h þ ds $HCPVs $PVIFðNÞ þ HCPVs $qN   HCPVIS $T$PVIFðNIS Þ þ NIS

For a given project, the IRR equals the actual interest rate at which the project initial investment should be lent during its useful life to achieve the same profitability [36]. From an economic point

(8)

The first term in brackets of Eq. (8) is related to the loan (HCPVl) and corresponds with the amount of the initial investment cost that is borrowed at an annual loan interest (il) to be paid back in Nl years, which corresponds to the loan duration, where the impact of taxation on financing is taking into account by tax deduction applies to interest payments of loan (the income tax rate, T in %). In this term, the present value interest factor of year k is noted as PVIF(k), being k in this case the number of years of the loan (Nl). This factor is related to the nominal discount rate (d) through the following equation:

.
ð1  qÞ PVIFðNl Þ ¼ q$ 1  qNl

(7)

#

(9)

The second term in brackets of Eq. (8) corresponds to the share of equity (HCPVs) -issue of stocks-, with an annual payback in form of dividends (ds), that is, the return on equity, and it must be paid in full at the end of the life cycle of the system (N, years). The last term in brackets of Eq. (8) depicts the investment subsidy (HCPVIS). It should be noted that HCPVIS is also taxable in a given period of time over which the investment subsidy is amortized (NIS, years) and that the amount of the investment subsidized is non-repayable.

D.L. Talavera et al. / Energy 119 (2017) 408e424

From Eq. (8) the value of d that matchs the equation is obtained, this value being equal to the weighted average cost of capital (WACC) of the investment. Note that the WACC is the costs that must be paid by the owner or investor of a HCPV power plant for the use of capital sources in order to finance the investment. In Eq. (7), if nominal discount rate (d) is fixed equal to WACC, the value of ps that fits Eq. (7) will be the desired required tariff of future owners or investors in HCPV power plant, because this value of ps fits the IRR required by the owners or investors. Because of this, Eq. (8) will be used for determining the value of WACC that corresponds to the financial cost of the HCPV power plant. Once this value is known, it will be used as required IRR for future owners or investors in HCPV power plants. Finally, using the value of the required IRR in Eq. (7), the value of the price of HCPV electricity (ps) will be obtained. From now on, the required tariff mentioned is referred to as the value of ps.

2.2. Estimation of parameters involved in the economic analysis Before conducting the analysis of economic profitability of HCPV power plants, a review of the parameters used as inputs for the equations presented below is conducted. This review will lead to the identification of the parameter values for the analysis of the HCPV power plant for a scenario in the year 2015 and prospective scenario 2020. Furthermore, in Appendix A (Table A.1) the values of the main economic parameters used as inputs for the calculations in each country are available. It should be noted that the figures presented here referring to costs are all normalised-per-kWp. The symbols used for these factors are the same for those not normalised, except that they are shown in brackets and with the subscript ‘kWp’. The parameters involved in this study are: annual final yield (YHCPV), annual degradation rate (rd), lifetime of the HCPV plant (N), annual escalation rate of the HCPV electricity price (Dps), normalised-per-kWp initial investment cost of HCPV ([HCPVI]kWp), loan interest rate (il), repaying loan (Nl), dividends (dec), income tax rate (T), nominal discount rate (d), normalised-per-kWp annual operation and maintenance costs ([HCPVAOM]kWp), annual escalation rate of the operation and maintenance costs (rO&M) and inflation (i). Next, these parameters are described and the selected value for each of one of them is detailed, these values being those used as inputs for the economic analysis conducted.  The parameter that has the most impact on the economic profitability of a HCPV power plant is the annual final yield of the plant (Yf HCPV). The procedure to estimate this parameter is similar to those presented in previous work [16,33]. Briefly, the annual final yield of a HCPV power plant can be estimated using the following equation:

YfHCPV ¼ PR

DNI DNISTC

(10)

411

where DNI is the annual direct normal irradiation (kWh/m2∙year) and DNISTC is the direct normal irradiance at standard test condition (1 kW/m2). The value of performance ratio (PR) for a typical HCPV power plant should be in the range from 0.76 to 0.91 [10,38e47]. In this study, an intermediate value of PR ¼ 0.82 has been considered.  The annual final yield of any HCPV power plant is not only affected by the stochastic behaviour of the radiation available at a certain location but also by the influence of the intrinsic degradation that the modules suffer throughout their lifetime, therefore the annual final yield of a HCPV power plant is assumed to decrease every year. In this study an annual yield degradation rate of the power plant of 0.5% has been considered [48,49]. Finally, although conventional PV systems have a lifetime that can go beyond this figure, it has been considered that the lifetime of the systems will be N ¼ 30 years. Hence, the horizon of this economic analysis is then established in 30 years.  Another parameter needed for profitability analysis is the annual escalation rate of the HCPV electricity price (Dps), linked to the evolution of electricity markets that is always difficult to forecast. In the liberalized electricity markets, the electricity wholesale prices are typically a function of available supply and demand, and are dependent on the class of power plants, which is needed to cover supply. Average prices of wholesale electricity for some countries in the European Union between 2009 and 2014 are shown in Table 1 [50e54]. The average wholesale prices of electricity in the United States according to the specific company are listed in Table 2 for the period 2010e2015 [55]. Wholesale electricity prices are expected to grow in the remaining years of the decade (2014e2020) [56]. The annual increase rate of the electricity wholesale prices (Dpw) for USA markets and some European countries are shown in Fig. 1. Analysing the slope of the trend line in this figure shows that it is positive and with an annual value of 2.5%, thus using a conservative criterion, an annual escalation rate of the HCPV electricity price of 2% could be assumed. This value is also assumed by other studies [37].  Additionally to the annual final yield, the next most influential parameter on the economic profitability of a HCPV power plant is the HCPV unitary price per kilowatt installed (V/kWp), or in other words, the initial investments cost (HCPVI) of a power plant. The initial investment cost of the future HCPV power plants is derived from the learning curve for HCPV technology. This curve describes the cost reduction as a function of the accumulated experience in the manufacturing and in the use of a particular technology, and can be used to estimate the evolution of the initial investment cost in HCPV power plants for upcoming years. In previous studies [15,16,31,33], the cost of the initial investment has been analysed for the period 2013e2020 In Ref. [15] the price for HCPV power plant was provided for 2013 with values in the range from 2.3 to 3.4 $/W. In Ref. [16] two scenarios were analysed: a conservative one (2013) with HCPVI values of 1800 V/kWp and an accelerated one with HCPVI values of 1400 V/kWp. Again, two scenarios were also analysed

Table 1 Average wholesale electricity prices (V/kWh) for the selected European Union countries between 2004 and 2014. Country

2009

2010

2011

2012

2013

2014

Average price

Germany (EPEX) Denmark, Estonia, Finland, Latvia, Lithuania, Norway, Sweden (Nord Pool Spot) Italy (GME) Spain (OMIE) France (EPEX) CH (EPEX)

0.039 0.036 0.064 0.042 0.043 0.048

0.045 0.055 0.064 0.046 0.047 0.051

0.051 0.047 0.072 0.060 0.049 0.056

0.043 0.033 0.075 0.060 0.047 0.050

0.038 0.039 0.063 0.058 0.043 0.045

0.033 0.031 0.052 0.055 0.035 0.038

0.042 0.040 0.065 0.054 0.044 0.048

412

D.L. Talavera et al. / Energy 119 (2017) 408e424

Table 2 Selected hubs for the wholesale electricity average price ($/kWh) in the United States for the period 2010e2015. Region

Electricity Hub

2010

2011

2012

2013

2014

2015

New England PJM Midwest Northwest Northern California Southwest Southern California

Mass Hub PJM West Indiana Hub Mid-C NP-15 Palo Verde SP-15

0.056 0.054 0.041 0.036 0.040 0.039 0.040

0.053 0.052 0.041 0.029 0.036 0.036 0.037

0.042 0.041 0.034 0.023 0.033 0.030 0.036

0.066 0.046 0.038 0.037 0.044 0.037 0.048

0.076 0.064 0.041 0.039 0.053 0.042 0.052

0.052 0.045 0.035 0.027 0.037 0.028 0.035

in Ref. [31]: one with HCPVI values of 2050 V/kWp for 2013, and another one with HCPVI values of 950 V/kWp for 2020. Finally, in Ref. [33] two scenarios were studied: with HCPVI values of 1700 V/kWp for 2014, and of 900 V/kWp for 2020. In the present work, a normalised-per-kWp initial investment cost of a HCPV power plant ([HCPVI]kWp) of 900 V/kWp for the prospective scenario of 2020, and another of 1700 V/kWp for the scenario of 2015, have been assumed.  As mentioned in section 2.1, the initial investment cost (HCPVI) may be financed by means of debt and/or equity capital. In this work, it has been assumed that 70% of this amount is borrowed as a loan edebte, while the remaining investment amount, 30%, is contributed from equity capital; taking into account that commercial banks are generally accepting higher leverage in stable economies with secure property rights [57]. However, for remaining countries, the share of equity and debt in the project is assumed to be 50%, which is in line with the recommendations of the CDM Executive Board [58]. Regarding HCPV power plants, the loan (il) is specific for each country, Nl is equal to 20 years, and also equity capital (ds) is assumed specific for each country and being amortized at the end of the life time of the system (see Appendix A (Table A.1)).  The influence of an income tax rate (T) for the organization or taxpayer is also considered and it changes depending on each country's regulations. In this analysis, the value of the income tax rate is assumed specific for each country (see Appendix A (Table A.1)). The method used in the depreciation for tax purposes is assumed linear and constant over a given period of time,

using a maximum linear coefficient of 5%, with a depreciation period of 20 years [37,59] for all countries.  Another of the parameters used for the profitability analysis is the nominal discount rate (d). In this work d is assumed equal to the weighted average capital of cost (WACC) [26,37]. The value of WACC is not constant and will vary depending on the capital resources chosen to finance the initial investment cost of the HCPV plant (HCPVI), so that each country has a particular value of WACC that will be estimated from Eq. (8).  The normalised-per-kWp annual operation and maintenance costs ([HCPVAOM]kWp) are taken at 28 V/(kW year) for the HCPV power plants [60,61]. Besides, there are estimations that consider an annual fixed percentage of the normalised-per-kWp initial investment cost of 2% for HCPV power plants [62]. The latter approach has been chosen in this paper. Additionally, these costs will also be influenced by an annual escalation rate (DrO&M), which is going to be set equal to the value of the annual inflation rate from each country, so DO&M ¼ i. In those countries with an annual inflation rate above 12% a rO&M value of 12% will be considered, since consider increase of DO&M larger it is not representative. The averages of historical data of the inflation rate (i) for each country in the period 2009e2014 [63e65] have been reviewed and the resulting data of this analysis are shown in Appendix A (Table A.1). Additionally, the salvage value of the system at the end of itslifetime (SV) is taken as equal to zero and investment subsidy is not considered. A summary of the aforementioned assumptions together with

Fig. 1. Annual increase rate of the electricity wholesale prices (Dpw) for the USA market and for the selected European Union countries between 2008 and 2014.

D.L. Talavera et al. / Energy 119 (2017) 408e424 Table 3 Values of the factors assumed for the calculation of the required IRR, required tariff and generation parity of HCPV power plants in the two scenarios assumed. Factors

Scenario 2015

YHCPV [HCPVI]kWp [HCPVAOM]kWp rd Dp s DrO&M T i d il Nl ds N

Eq. (9) 1700 2 0.5 2 Equal to i According According According According 20 According 30

Units 2020 900

Appendix Appendix Appendix Appendix

A A A A

Appendix A

kWh/(kWp$year) V/kWp % %/year % %/year % % % % years % years

the values assigned to each factor is gathered in Table 3 for the countries considered. The estimation of required IRR, required tariff and generation parity of a HCPV power plant for each country is realised by solving the equations presented in Section 2.1 in combination with the figures shown in Table 3 in a spreadsheet. 3. Analysis and results The required IRR and required tariff for HCPV power plants have been estimated for 133 countries through solving the equations presented in Section 2.1. Hence, the competitiveness of the HCPV technology has been studied for some European and USA countries. The parameters and the input data used in this study are shown in Table 3, including the following factors: annual final yield (YHCPV), normalised-per-kWp initial investment cost of HCPV ([HCPVI]kWp), normalised-per-kWp annual operation and maintenance costs ([HCPVAOM]kWp), annual degradation rate (rd), annual escalation rate of the HCPV electricity price (Dps), annual escalation rate of the operation and maintenance costs (rO&M), income tax rate (T), inflation (i), nominal discount rate (d), loan interest rate (il), loan repayment (Nl), dividends (ds) and lifetime of the HCPV power plant (N). The worldwide maps and figures shown below represent the output results of the analysis conducted. Moreover, the detailed

413

numeric results of each country are available in Appendix A, Table A.2. In this work, the average value of DNI is taken for each country. However, those countries with larger areas or with areas where the required tariff variations are significant inside the own territory, are divided in two partitions: North-South or West-East. Although these partitions are not shown in Fig. 3, they have been considered for obtaining the results shown in Section 3.2. 3.1. Required tariff of HCPV power plants As a previous step to estimate the required tariff, the required IRR has to be calculated. This latter will be calculated using the Eq. (8) presented in section 2.1. Once the value of the required IRR is available, the Eq. (7) is used to obtain the value of the required tariff. Note that the required tariff has been calculated taking into account two possible scenarios: current one, for 2015, and prospective one, for 2020. Results obtained with the analysis conducted are shown in Figs. 2e5. The results shown in the map of Fig. 2 have been distributed in five categories according to the value of the required IRR: lower than 5%, in the range from 5% to 10%, in the range from 10% to 15%, in the range from 15% to 20%, and greater than 20%. Each country is marked with the colour that corresponds with the value of its required IRR. From this map different groups of countries can be established: two first groups with countries where the values of their required IRR are lower than 10%, a third and a fourth group with countries where the values of their required IRR are in the range from 10% to 20% and a fifth group of countries where the values of their required IRR are greater than 20%. The two first groups include those countries that could be considered as the most suitable for HCPV technology because they have the lowest values of WACC compared with the other countries: Australia, Belgium, Canada, China, Denmark, Finland, France, Germany, Greece, Ireland, Israel, Italy, Japan, Netherlands, New Zealand, Norway, Spain, Sweden, Switzerland, United Arab Emirates, United Kingdom and United States. Most countries are included in the third group and the fourth group. Finally, the fifth group includes those countries where it is less interesting to invest in HCPV technology since their WACC is greater than in the rest of the countries.

Fig. 2. Global map of the required IRR, sought for investors in a project of a HCPV power plant.

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Fig. 3. Global map of the investor's required tariff for the year 2015.

The values of the required tariff for energy generated by a HCPV power plant and sold to the wholesale market have been calculated from the values of the required IRR shown in Fig. 2. This required tariff is that which satisfies the IRR required by the owner or investor in HCPV power plant. The required tariffs for the current scenario (2015) and for the prospective scenario (2020) are shown in Figs. 3 and 5 respectively. In countries where the tariff required by future owners or investors of a HCPV power plant has a higher value than the electricity price on the wholesale market, the investment in a HCPV power plant will not be feasible. Therefore, from an economic point of view, those countries in which the values of the required tariff are higher than the wholesale electricity price have no interest for HCPV technology. On the other hand, those countries where the values of the required tariff are lower than the wholesale electricity price have an interest for future owners or investors of HCPV power plant. The results shown in the map of Fig. 3 have been distributed in six categories according to the value of the required tariff for the year 2015: lower than 5 cV/kWh, in the range from 5 cV/kWh to 10 cV/kWh, in the range from 10 cV/kWh to 15 cV/kWh, in the range from 15 cV/kWh to 20 cV/kWh, in the range from 20 cV/kWh to 25 cV/kWh and greater than 25 cV/kWh. Each country is marked with the colour that corresponds with the value of its required tariff, as can be seen there are no countries with required tariff lower than 5 cV/kWh. There are only a few countries with required tariff in the range from 5 cV/kWh to 10 cV/kWh: Australia, Cyprus, Qatar, Somalia, Spain, United States west, with required tariff values of 9.4, 9.0, 10.0, 8.8, 8.9 y 9.5 cV/kWh, respectively. If these values of required tariff for the 2015 scenario are compared with wholesale electricity prices shown in Tables 2 and 3 it can be observed that there are significant differences. In Fig. 4, the values of the required tariff obtained for 2015 are plotted versus DNI, for different ranges of values of the required IRR. In this figure, the countries have been classified in five groups: required IRR<5%, 5% < required IRR<10%, 10% < required IRR<15%, 15% < required IRR<20% y required IRR> 20%. For the countries of the same group, it can be observed that those with higher values of DNI have the lower values of required tariff. Among the different groups of the countries, for the same value of DNI, it can be

observed that higher values of required IRR correspond with higher values of required tariff. The countries with values of DNI above 2500 kWh/(m2$year), from the highest to the lowest values, are listed in Table 4. As can be observed from the table, those countries with the highest values of DNI: Niger, Egypt, Libya and Yemen Rep, have the required tariff for HCPV power plant greater than other countries with lower values of DNI than these, as for example: Chile, Cyprus, Saudi Arabia and Oman. It can be explained due to the fact that the required IRR depends on the financial costs or WACC, so, for a higher WACC of the investment of the HPCV power plant, a higher required tariff will be needed. Hence, countries with relative lower DNI levels, such as Chile, Cyprus, Saudi Arabia and Oman, will be more interesting for future owner and investor of HCPV power plant than other countries with a great potential for this technology, such as Niger, Egypt, Libya and Yemen Rep, but where the financial costs are high. It will be necessary to reduce WACC to make this technology attractive for future investors in these countries. It is worth mentioning that in countries like Canada the value of required tariff indicated in the map is only representative for locations with latitude lower than 60 , as well as for Norway and Sweden, where the required tariff value corresponds only for locations above latitude of 65 . For other countries like Syria and Sudan that are involved in different wars, or Venezuela with political instability, some economic parameters like inflation and the financial cost are relatively very high. Similar to Fig. 3, the results shown in the map of Fig. 5 have been distributed in the same six categories according to the value of the required tariff for the year 2020: lower than 5 cV/kWh, in the range from 5 cV/kWh to 10 cV/kWh, in the range from 10 cV/kWh to 15 cV/kWh, in the range from 15 cV/kWh to 20 cV/kWh, in the range from 20 cV/kWh to 25 cV/kWh and greater than 25 cV/kWh. From this map it can be observed that there is a group of 59 countries with the values of the required tariff lower than 10 cV/kWh. However required tariff lower than 5 cV/kWh corresponds to a small group of five countries: Australia, Cyprus, Somalia, Spain, United States, with values of the required tariff of 5.0, 4.8, 4.7, 4.7 y 5.0 cV/kWh, respectively. If the required tariff for Spain and USA is analysed in both scenarios (2015 and 2020) it can be observed that

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415

Fig. 4. Required tariff as a function of normal direct irradiation and required IRR for the scenario 2015.

there is a decrease of almost 47%. This important decrease in the value of the required tariff along with the trend to increase the electricity price in the wholesale market will make the investment in a HCPV power plant attractive for future owners and investors in 2020. So, in subsection 3.2, the competitiveness of the HCPV technology in a group of countries will be studied for the two scenarios considered (2015 and 2020). For those countries where the values of the required tariff will be higher than 5 cV/kWh in

2020 the investment in HCPV power plants will be of interest or not depending on the electricity price in their wholesale markets.

3.1.1. Statistical analysis In this section a statistical analysis of the results obtained for the required tariff in 2015 scenario, has been conducted. Fig. 6 shows the histogram of relative frequencies and the probability density function of this parameter. This probability density function is

Fig. 5. Global map of the investor's required tariff for the year 2020.

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Table 4 Values of required IRR and required tariff, for countries with DNI >2500 kWh/ (m2 year). Country

DNI

Required IRR

Required tariff

Niger Egypt Libya Yemen. Rep. Namibia Chile Chad Sudan Cyprus Saudi Arabia Oman Botswana United Arab Emirates

2804 2716 2664 2662 2661 2648 2646 2633 2559 2554 2538 2503 2502

13.9 16.6 11.9 23.5 13.9 10.2 13.8 25.4 9.2 11.1 10.2 14.1 8.4

13.4 17.5 12.1 23.4 15.5 10.1 16.0 29.6 9.0 11.6 10.1 17.7 12.3

This coefficient provides a measure of the variability of the data with respect to the average value: a high value of this coefficient implies high heterogeneity of the data while a low value of this coefficient implies high homogeneity of the data for the parameter under study. The obtained values of Cv for the probability density functions of the required tariff and DNI are 39% and 24%, respectively. This mean that the variability of the required tariff is higher than the variability of the DNI, that can be observed in Fig. 7 where the shape of the probability density function of the required tariff is smoother than the other one. This higher variability in the values of the required tariff is due to the varied range of values of the economic parameters involved in its calculation depending on the country, namely: inflation (i), loan interest rate (il), dividends (ds) and income tax rate (T).

3.2. Competitiveness of HCPV power plants characterised by the following values: minimum value equal to 9, maximum value equal to 55, average value (m) equal to 21, standard deviation (s) equal to 8.17 and correlation coefficient (R2) equal to 0.917. In order to establish the relation between the required tariff and the DNI, the probability density function of the DNI has also been obtained, with the values: minimum value equal to 811, maximum value equal to 2804, average value (m) equal to 1877, standard deviation (s) equal to 455 and correlation coefficient (R2) equal to 0.922. In Fig. 7, both functions are plotted together with the aim of comparing and analysing them. In order to compare both of them, the dispersion coefficient is used. The dispersion coefficient is defined as the ratio between the standard deviation and the average, as a percentage according to Eq. (11).

s m

Coefficient of variation ðCvÞ ¼ $100

(11)

The competitiveness analysis of HCPV plants is based on estimating the so-called HCPV generation parity. This happens when the tariff required by owners or investors, matches the electricity price in the wholesale market. Therefore, the required tariff for a HCPV power plant, is compared with the wholesale electricity price. The competitiveness analysis of the HCPV technology is conducted over USA and some European countries, moreover this analysis has been done taking into account two possible scenarios: current one, for 2015, and prospective one, for 2020. The results obtained from this analysis are shown in Figs. 8 and 9 for Europe and USA respectively. Fig. 8 shows the electricity price in the wholesale market, as well as the required tariff for several Eurozone countries for the two scenarios considered (2015 and 2020). As can be seen the electrical generation with HCPV plants is not competitive in any of countries considered if it is compared with the electricity price on the wholesale market for the current scenario (2015). However, the HCPV power plants begin to be competitive in countries such as

Fig. 6. Histogram of relative frequencies and probability density function of the required tariff.

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417

Fig. 7. Probability density functions of the required tariff and DNI.

Fig. 8. Wholesale electricity price and investor's required tariff for the some countries of the European market.

Spain and Italy, are near to reaching the generation parity in France but they are far away in Germany and Nord Pool Spot (Denmark, Norway, Sweden, and Finland, among others) for the future scenario (2020). USA is a wide area and consequently the variations of DNI are significant inside its territory, so USA has been divided into different regions. Although these partitions are not shown in Figs. 2 and 3, they have been considered for obtaining the results shown in Fig. 9.

Fig. 9 shows the electricity price in the wholesale market, as well as the required tariff for different USA regions for the two scenarios considered (2015 and 2020). As in the previous case, it can be observed that generation with HCPV power plants is not competitive since the electricity prices of the USA companies that operate on the electricity wholesale market are much lower than the required tariff for the current scenario (2015). Furthermore, it can be shown that the HCPV generation parity is far from being reached. However, the HCPV power plants begin to be competitive

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Fig. 9. Wholesale electricity price and investor's or owner's required tariff for the USA market.

in some regions of the east of USA, particularly in the region denoted New England -Mass Hub-for the future scenario (2020). Other regions such as Northern California -NP-15- and Southern California -SP-15- are near to reaching the generation parity in this future scenario. 4. Conclusions The market of solar photovoltaic energy and, specifically, that of the HCPV power plants, is continuously growing, mainly due to the economies of scale and to the effects of learning curves. This growth will result in the extension of the number of countries where HCPV technology will be competitive in relation to other sources of electricity generation. One of the methods used for the study of HCPV power plants' economic profitability is the IRR. In the work here presented an analysis of the required IRR of HCPV power plants has been carried out over 133 countries, together with required tariff which fulfils profitability requirements for owners or investors in the HCPV power plants in those countries. Besides, this investor's required tariff has been compared to wholesale electricity prices in order to determine the competitiveness of the HCPV power plant by means of the concept “generation parity” within the analysed countries, for a scenario at 2015 and a mid-term scenario at 2020. The results obtained are shown in a set of innovative maps. These maps are easy to handle and can be consulted by future owners, investors and financial entities involved in HCPV power plants. One important conclusion obtained from the analysis of the profitability conducted is that the required tariff in countries like USA, Spain, Italy, Greece and Japan is lower than in countries like Algeria, South Africa and Mauritania, with higher values of DNIA, which highlight the relevant effect that parameters like loan interest rate, dividends (return on equity) and inflation produce.

Results suggest that, from a worldwide economic perspective, current growth pattern will continue, in large part concentrated in countries with low WACC for HCPV projects and low inflation rates, instead of those with high DNI values but with a high project financing cost. Therefore, it would be an advantageous achievement for renewable energies and particularly for HCPV technology to reduce the WACC of this type of project. Another important conclusion that can be extracted from the competitiveness analysis conducted is that the electricity generated by HCPV plants will be competitive with regard to other power sources in some of the countries studied for the future scenario (2020). The HCPV technology will be competitive in countries like Spain, Italy and the region of New England in USA, where the required tariff by owners or investors of HCPV power plants will be cheaper than the wholesale electricity price. This is mainly due to relative low values of the required IRR, values of DNIA above 1600 kWh/(m2 year) and the trend to increase the electricity price on the wholesale market. In other countries like France or some USA regions like Northern California and Southern California, HPCV power plants will be near to reaching the generation parity. Finally, countries like Germany or the countries of the Nord Pool Spot (Denmark, Norway, Sweden, and Finland, among others) are far from reaching the generation parity. Despite this, currently the HCPV technology is not competitive in any of the countries and regions studied, mainly due to the investor's required tariff in HCPV power plants being greater than the kWh price in wholesale market. It is worth mentioning that the fact that the generation parity of the HCPV technology has not been reached yet, is not an obstacle for the HCPV market to continue to develop. There are different reasons for which future owners and investors could decide to invest in HPCV technology and factors such as environmental needs, green certificate requirements or long-term energy security that also could contribute to the development of this new

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technology. For all these reasons, this paper provides valuable information for future owners and potential investors in HCPV power plants that demand information on the economic return on investment. That is why one of the main aims of this document has been to provide information about the required IRR in HCPV power plant. Besides, government organizations of each one of the countries that have been studied here, which participate either in the design or the selection of support mechanisms for HCPV, can be guided by the results obtained in this work. Furthermore, the information provided in this paper is very useful for researchers in this field to identify the main weaknesses of the HCPV technology and propose improvements aimed to make this technology more competitive. Acknowledgments This work is part of the project ENE2013-45242-R supported by the Spanish Economy Ministry and the European Regional Development Fund/Fondo Europeo de Desarrollo Regional (ERDF/ FEDER). Terminology [HCPVAOM]kWp Normalised per-kWp annual operation and maintenance cost of the HCPV power plant (V) [HCPVI]kWp Normalised per-kWp initial investment cost of HCPV(V/kWp) D Nominal discount rate (%) ds Annual dividend the equity capital ereturn on equity- (%) DEPy Annual tax depreciation (V) DNI Annual Direct Normal Irradiation (kWh/(m2 year)) DNISTC Direct normal irradiance at standard test condition (1 kW/m2) DPBT Discounted pay-back time (years) HCPVAOM Annual operation and maintenance cost of the HCPV power plant (V) HCPVI Initial investment cost on the HCPV power plant (V) HCPVIS Investment subsidy (V) HCPVl Amount equal to the portion of the initial investment financed with loan (V) HCPVs Amount equal to the portion of the initial investment financed with stocks (V) IRR Internal rate of return (%)

Table A.1 Input data (Sources:

(a)

[66],

(b)

[64],

(c)

[58,67],

(d)

419

I il Kd Kp LCC N

Annual inflation rate (%) Annual loan interest (%) Factor equal to (1 þ Dps)$(1-rd)/(1 þ d) Factor equal to (1 þ DO&M)/(1 þ d) Life cycle cost of the HCPV power plant (V) Life cycle of the HCPV power plant, equal to analysis period (years) Nd Tax life for depreciation (years) NIS Period of time over which the investment subsidy is amortized (years) Nl Period of amortization of loan (years) ps HCPV electricity price (cV/kWh) PR Performance Ratio (%) PV [CI(N)] Present value of the cash inflows over the lifetime of the system (V) PV [CO(N)] Present value of the operation and maintenance cost over the system life (V) PV [DEP(Nd)] Present value of the tax depreciation (V) PV[HCPVOM (N)] Present value of the HCPV power plant operation and maintenance cost (V) PVIF(k) Present value interest factor of year k Q Factor equal to (1/1 þ d) R2 Correlation coefficient rd Annual degradation rate in the efficiency of the HCPV plant (%) DO&M Annual escalation rate of the operation and maintenance cost of the HCPV power plant (%) SV Salvage value of the system at the end of their life cycle (V) T Income tax rate (%) VAN Net present value (V) WACC Weighted Average Cost of Capital (%) Y f HCPV Annual Final yield of a HCPV power plant (kWh/ (kWp year) Dps Annual escalation rate of the HCPV electricity price (%) Dpw Annual increase rate of the electricity wholesale prices (%) m average value of a probability density function s standard deviation of a probability density function Appendix A. Input data and results.

[68e70]).

Country

Average nominal lending interest rate (il) 2009e2014(a)

Average inflation (i) 2009e2014(b)

Nominal equity IRR (ds) 1900e2000(c)

Tax (T)(d)

Afganistan Albania Algeria Angola Argentina Armenia Australia Azerbaijan Bangladesh Belgium Belize Benin Bolivia Bosnia and Herzegovina Botswana Brazil Burkina Faso Burundi Cambodia

15.2% 11,2% 8,0% 17,6% 15,9% 17,6% 6,7% 19,0% 13,3% 3,9% 12,7% 16,8% 10,8% 7,3% 11,1% 37,4% 16,8% 14,1% 13,0%

3,7% 2,5% 4,9% 11,3% 9,5% 5,1% 2,4% 3,3% 7,5% 1,7% 0,6% 2,3% 5,3% 1,1% 6,9% 5,7% 1,5% 9,6% 3,1%

18,8% 15,8% 18,4% 25,8% 25,4% 18,2% 11,8% 14,9% 21,3% 6,8% 15,2% 15,9% 19,8% 15,0% 18,4% 18,2% 15,5% 25,5% 17,3%

20.0% 15.0% 19.0% 35.0% 35.0% 20.0% 30.0% 20.0% 27.5% 34.0% 25.0% 30.0% 25.0% 10.0% 22.0% 34.0% 30.0% 30.0% 20.0% (continued on next page)

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Table A.1 (continued ) Country

Average nominal lending interest rate (il) 2009e2014(a)

Average inflation (i) 2009e2014(b)

Nominal equity IRR (ds) 1900e2000(c)

Tax (T)(d)

Cameroon Canada Central African Rep. Chad Chile China Colombia Congo. Dem. Rep. Congo. Rep. Costa Rica Cote d'Ivoire Cuba Cyprus Denmark Djibouti Dominican Republic Ecuador Egypt El Salvador Eritrea Ethiopia Fiji Finland France Gabon Georgia Germany Ghana Greece Guatemala Guinea Bassau Guyana Haiti Honduras India Indonesia Iran. Islamic Rep Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea. Dem.Rep. Korea. Rep. Kuwait Kyrgyz Republic Lao. PDR Lebanon Liberia Libya Macedonia. FYR Madagascar Malawi Malaysia Mali Mauritania Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan

15,2% 2,8% 15,2% 15,2% 8,1% 5,9% 11,3% 38,7% 15,2% 16,9% 16,8% 18,0% 6,7% 7,1% 11,7% 14,8% 12,4% 11,7% 14,0% 14,2% 7,5% 6,9% 2,4% 3,7% 15,2% 14,8% 4,3% 25,6% 6,2% 13,6% 19,4% 14,0% 12,5% 19,3% 10,3% 12,7% 11,8% 13,7% 2,6% 4,9% 4,8% 18,2% 1,5% 9,0% 11,2% 16,3% 6,1% 5,2% 5,0% 23,2% 26,0% 7,9% 13,8% 6,0% 8,7% 54,4% 32,7% 4,8% 16,8% 17,5% 5,0% 14,7% 19,0% 11,5% 16,3% 14,9% 9,2% 8,0% 1,9% 6,0% 13,1% 16,8% 17,0% 5,7% 6,1% 13,4%

2,3% 1,6% 2,7% 3,3% 2,3% 2,5% 3,0% 6,1% 3,6% 5,4% 2,0% 4,5% 1,1% 1,7% 3,3% 4,6% 4,1% 10,0% 1,8% 17,5% 14,7% 3,5% 2,0% 1,2% 2,1% 3,2% 1,3% 12,5% 1.4% 3,9% 1,3% 2,9% 5,1% 5,6% 9,7% 5,4% 21% 4,3% 0,1% 2,2% 1,6% 9,0% 0,1% 3,6% 6,7% 8,2% 8,0% 2,4% 3,8% 8,0% 4,7% 1,0% 7,9% 5,9% 1,7% 7,7% 16,1% 2,1% 2,0% 4,5% 4,1% 4,9% 10,4% 1,1% 6,0% 4,4% 6,2% 9,4% 1,8% 2,0% 6,3% 1,0% 10,8% 1,8% 2,7% 10,7%

15,7% 9,0% 17,6% 17,6% 12,9% 13,3% 15,4% 21,5% 17,1% 18,1% 15,6% 20,7% 11,5% 8,7% 16,7% 19,1% 21,8% 23,2% 14,0% 34,5% 31,3% 17,0% 11,5% 6,9% 14,1% 16,5% 9,5% 27,5% 10.5% 16,9% 16,0% 11,0% 18,8% 20,1% 22,7% 18,6% 37,0% 14,2% 6,3% 12,9% 7,8% 25,9% 8,6% 16,6% 19,0% 22,6% 9,5% 13,5% 14,3% 22,4% 18,7% 14,1% 23,6% 17,0% 14,9% 22,5% 32,9% 13,2% 16,1% 18,9% 15,8% 14,8% 23,7% 13,2% 21,3% 14,4% 19,9% 25,3% 9,0% 9,7% 22,7% 15,7% 25,2% 9,1% 13,5% 26,7%

38.5% 26.0% 30.0% 40.0% 20.0% 25.0% 25.0% 25.0% 33.0% 30.0% 25.0% 30.0% 12.5% 24.5% 25.0% 28.0% 22.0% 25.0% 30.0% 30.0% 30.0% 20.0% 20.0% 33.3% 35.0% 15.0% 29.6% 25.0% 26.0% 28.0% 35.0% 35.0% 30.0% 30.0% 34.0% 25.0% 25.0% 15.0% 12.5% 26.5% 31.4% 25.0% 33.1% 14.0% 20.0% 30.0% 25.0% 24.0% 15.0% 10.0% 24.0% 15.0% 25.0% 20.0% 10.0% 20.0% 30.0% 25.0% 30.0% 25.0% 30.0% 12.0% 25.0% 30.0% 32.0% 25.0% 33.0% 20.0% 25.0% 28.0% 30.0% 30.0% 30.0% 27.0% 12.0% 34.0%

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Table A.1 (continued ) Country

Average nominal lending interest rate (il) 2009e2014(a)

Average inflation (i) 2009e2014(b)

Nominal equity IRR (ds) 1900e2000(c)

Tax (T)(d)

Panama Paraguay Peru Philippines Puerto Rico Qatar Russian Federation Rwanda Saudi Arabia Senegal Serbia Sierra Leone Somalia South Africa Spain Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tunisia Turkmenistan Uganda United Arab Emirates United Kingdom United States Uruguay Uzbekistan Venezuela. RB Vietnam Yemen. Rep. Zambia Zimbabwe

7,2% 21,6% 18,6% 6,6% 5,1% 5,9% 10,7% 16,3% 6,9% 16,8% 16,1% 20,9% 14,2% 9,5% 4,3% 11,9% 11,8% 9,3% 3,3% 2,7% 9,7% 23,1% 15,3% 6,6% 17,5% 4,8% 27,2% 22,3% 8,1% 0,5% 3,3% 12,4% 27,2% 17,5% 12,1% 22,7% 15,8% 14.0%

4,0% 4,5% 2,9% 3,8% 1,5% 0,5% 7,8% 5,0% 4,2% 0,6% 7,1% 12,1% 4,0% 5,6% 1,4% 25,1% 5,8% 6,4% 0,7% 0,1% 27,2% 7,0% 10,2% 2,2% 2,2% 4,6% 4,6% 9,9% 1,2% 2,8% 1,6% 7,9% 4,3% 34,2% 9,1% 13,5% 8,3% 2,2%

16,5% 19,6% 15,1% 17,1% 9,9% 10,6% 20,2% 19,5% 15,0% 13,9% 19,7% 28,3% 5,1% 17,2% 7,3% 41,4% 19,6% 20,1% 9,5% 6,0% 43,6% 21,8% 25,4% 13,7% 16,3% 16,6% 19,0% 25,1% 11,5% 10,2% 10,0% 21,7% 18,2% 52,7% 23,0% 28,6% 22,7% 15,7%

25.0% 10.0% 30.0% 30.0% 39.0% 10.0% 20.0% 30.0% 20.0% 30.0% 15.0% 30.0% 35.0% 28.0% 30.0% 35.0% 36.0% 27.5% 22.0% 17.9% 22.0% 25.0% 30.0% 20.0% 29.0% 25.0% 20.0% 30.0% 55.0% 21.0% 40.0% 25.0% 8.0% 34.0% 22.0% 20.0% 35.0% 25.7%

Table A.2 Analysis results. Country

Required IRR (%)

Required tariff in 2015 (cV/kWh)

Required tariff in 2020 (cV/kWh)

Afghanistan Albania Algeria Angola Argentina Armenia Australia Azerbaijan Bangladesh Belgium Belize Benin Bolivia Bosnia and Herzegovina Botswana Brazil Burkina Faso Burundi Cambodia Cameroon Canada Central African Rep. Chad Chile China Colombia Congo. Dem. Rep. Congo. Rep. Costa Rica

15.7 13.0 13.2 19.6 18.3 16.3 7.6 15.0 16.0 4.5 12.7 14.0 14.6 11.5 14.1 21.4 13.8 18.2 14.2 12.9 5.2 14.5 13.8 10.2 9.7 12.4 25.2 14 15.2

18.7 14.5 13.8 29.8 27.5 25.4 9.4 23.5 20.5 16.5 20.5 19.1 21.8 18.9 17.7 34.6 16.2 33.3 19.9 20.9 13.6 19.3 16.0 10.1 14.3 23.5 40.2 30.4 33.6

9.1 7.7 7.3 15.3 14.6 13.5 5.0 12.4 10.9 8.7 10.8 10.1 11.5 10.0 9.4 18.3 8.5 17.6 10.5 11.1 7.2 10.2 8.5 5.3 7.6 12.5 21.3 15.0 17.8 (continued on next page)

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Table A.2 (continued ) Country

Required IRR (%)

Required tariff in 2015 (cV/kWh)

Required tariff in 2020 (cV/kWh)

Cote d'Ivoire Cuba Cyprus Denmark Djibouti Dominican Republic Ecuador Egypt El Salvador Eritrea Ethiopia Fiji Finland France Gabon Georgia Germany Ghana Greece Guatemala Guinea Bassau Guyana Haiti Honduras India Indonesia Iran. Islamic Rep. Iraq Ireland Israel Italy Jamaica Japan Jordan Kazakhstan Kenya Korea. Dem. Rep. Korea. Rep. Kuwait Kyrgyz Republic Lao. PDR Lebanon Liberia Libya Macedonia. FYR Madagascar Malawi Malaysia Mali Mauritania Mexico Moldova Mongolia Morocco Mozambique Myanmar Namibia Nepal Netherlands New Zealand Nicaragua Niger Nigeria Norway Oman Pakistan Panama Paraguay Peru Philippines Puerto Rico Qatar Russian Federation Rwanda Saudi Arabia

14.2 16.9 9.2 6.7 13.2 15.2 16.3 16.6 12.1 22.8 19.5 12.1 6.1 4.5 12.4 14.7 5.8 23.5 8.2 13.7 14.4 10.2 14.3 17.0 15.6 14.5 23.7 13.1 4.1 9.2 5.3 20.1 4.5 12.8 14.5 17.4 7.6 9.7 10.2 22.3 19.2 11.0 17.5 11.9 11.9 33.0 28.0 9.4 14.1 16.2 10.8 14.0 19.2 11 16.7 12.6 13.9 13.2 4.9 6.6 16.5 13.9 19 6.2 10.2 18.4 11.8 19.5 14.1 11.9 7.3 8.5 12.7 15.8 11.1

21.0 21.8 9.0 17.4 14.1 21.4 38.0 17.5 30.1 28.7 27.4 19.9 16.4 12.7 28.0 22.9 19.3 37.8 12.5 21.7 20.2 19.0 19.7 28.5 24.8 25.9 29.5 14.5 17.1 11.2 10.4 24.6 11.9 13.2 24.4 24.3 17.7 16.2 11.4 26.7 34.6 12.7 31.3 12.1 18.2 39.2 41.8 16.8 15.7 17.6 13.9 27.8 27.2 12.8 23.8 20.7 15.5 16.2 16.5 14.3 31.2 13.4 27.2 22.4 10.1 25.3 22.5 25.3 24.7 20.2 10.5 10.0 28.5 29.5 11.6

11.1 11.6 4.8 9.2 7.5 11.4 20.1 9.3 15.9 15.2 14.5 10.5 8.7 6.7 14.8 12.1 10.2 20.0 6.6 11.5 10.7 10.0 10.4 15.1 13.1 13.7 15.6 7.7 9.1 5.9 5.5 13.0 6.3 7.0 12.9 12.9 9.4 8.6 6.0 14.1 18.3 6.7 16.6 6.4 9.6 20.7 22.1 8.9 8.3 9.3 7.4 14.7 14.4 6.7 12.6 11.0 8.2 8.6 8.8 7.5 16.5 7.1 14.5 11.8 5.4 13.4 11.9 13.4 13.1 10.7 5.5 5.3 15.1 15.7 6.1

D.L. Talavera et al. / Energy 119 (2017) 408e424

423

Table A.2 (continued ) Country

Required IRR (%)

Required tariff in 2015 (cV/kWh)

Required tariff in 2020 (cV/kWh)

Senegal Serbia Sierra Leone Somalia South Africa Spain Sudan Suriname Swaziland Sweden Switzerland Syrian Arab Republic Tajikistan Tanzania Thailand Togo Tunisia Turkmenistan Uganda United Arab Emirates United Kingdom United States United States west United States east Uruguay Uzbekistan Venezuela. RB Vietnam Yemen. Rep. Zambia Zimbabwe

13.0 16.9 21.7 6.8 12.7 4.9 25.4 14.2 14.2 5.6 4.0 26.4 19.7 18.5 10.3 14.5 11.3 20.3 20.5 8.4 5.0 5.5 5.5 5.5 16.1 21.5 32.6 16.8 23.5 17 13.3

16.1 29.1 36.0 8.8 14.5 8.9 29.6 25.5 21.0 15.9 11.1 32.5 25.8 27.3 15.8 20.5 14.6 26.1 29.5 12.3 19.8 10.5 9.5 12.2 24.2 24.9 55.0 33.6 23.4 22.9 15.3

8.6 15.4 19.1 4.7 7.6 4.7 15.7 13.5 11.1 8.4 5.9 17.2 13.7 14.5 8.3 10.9 7.7 13.8 15.6 6.5 10.5 5.6 5.0 6.5 12.8 13.2 29.1 17.8 12.4 12.1 8.2

Reference
rez-Higueras P, Garcia Loureiro AJ, Vidal PG. Outdoor eval[1] Fern
andez EF, Pe uation of concentrator photovoltaic systems modules from different manufacturers: first results and steps. Prog Photovoltaics Res Appl 2013;21: 693e701. [2] Ota Y, Nishioka K. Three-dimensional simulating of concentrator photovoltaic modules using ray trace and equivalent circuit simulators. Sol Energy 2012;86:476e81. ~ n I, Askins S, Sala G. Characterization [3] Victoria M, Herrero R, Domínguez C, Anto of the spatial distribution of irradiance and spectrum in concentrating photovoltaic systems and their effect on multi-junction solar cells. Prog Photovoltaics Res Appl 2013;21:308e18.
rez-Higueras PJ. Outdoor measure[4] Rodrigo P, Fern
andez EF, Almonacid F, Pe ment of high concentration photovoltaic receivers operating with partial shading on the primary optics. Energy 2013;61:583e8. [5] Cotal H, Fetzer C, Boisvert J, Kinsey G, King R, Hebert P, et al. III-V multijunction solar cells for concentrating photovoltaics. Energy Environ Sci 2009;2:174e92. [6] Fern
andez EF, García-Loureiro AJ, Smestad GP. Multijunction concentrator
rez-Higueras Pedro, solar cells: analysis and fundamentals. In: Pe Fern
andez Eduardo F, editors. High concentrator photovoltaics: fundamentals, engineering and power plants. Springer; 2015. p. 9e37. [7] Fern
andez EF, Almonacid F, Garcia-Loureiro AJ. Multi-junction solar cells electrical characterization by neuronal networks under different irradiance, spectrum and cell temperature. Energy 2015;90:846e56.
rez-Higueras P. A two [8] Fern
andez EF, Siefer G, Almonacid F, Loureiro AJG, Pe subcell equivalent solar cell model for III-V triple junction solar cells under spectrum and temperature variations. Sol Energy 2013;92:221e9. [9] International Electrotechnical Commission. IEC 62108. Concentrator photovoltaic (CPV) modules and assemblies e design qualification and type approval. 2007. Edition 1.0, Geneve.
mez-Gil FJ, Wang X, Barnett A. Energy production of photovoltaic systems: [10] Go fixed, tracking, and concentrating. Renew Sustain Energy Rev 2012;16: 306e13. ~ oz E, Vidal PG, Nofuentes G, Hontoria L, Pe
rez-Higueras P, Terrados J, et al. [11] Mun CPV standardization: an overview. Renew Sustain Energy Rev 2010;14: 518e23.
ndez EF, Pe
rez-Higueras P, Almonacid F, Ruiz-Arias JA, Rodrigo P, [12] Ferna Fernandez JI, et al. Model for estimating the energy yield of a high concentrator photovoltaic system. Energy 2015;87:77e85. ~ oz-Rodríguez F, Mun ~ oz-Cero
n E, Almonacid F, Ferna
ndez EF. Efficiencies [13] Mun

[14]

[15]

[16]

[17]

[18]

[19]

[20]

[21]

[22]

[23]

[24]

[25]


rezand energy balance in high-concentrator photovoltaic devices. In: Pe
ndez Eduardo F, editors. High concentrator photovolHigueras Pedro, Ferna taics: fundamentals, engineering and power plants. Springer; 2015. p. 239e60. Philipps SP, Bett AW, Horowitz K, Kurtz S. Current status of concentrator photovoltaic (CPV) technology. Fraunhofer ISE and National Renewable Energy Laboratory (NREL); September 2015. Version 1.1, TP-6A20e63916. Haysom JE, Jafarieh O, Anis H, Hinzer K, Wright D. Learning curve analysis of concentrated photovoltaic systems. Prog Photovoltaics Res Appl 2015;23: 1678e86.
rez-Higueras P, Ruíz-Arias JA, Ferna
ndez EF. Levelised cost of Talavera DL, Pe electricity in high concentrated photovoltaic grid connected systems: spatial analysis of Spain. Appl Energy 2015;151:49e59.
rez-Higueras P, Fern
Pe andez EF. High concentrator photovoltaic fundamentals, engineering and power plants. Springer International Publishing; 2015. 477-ISBN: 978-3-319-15038-3 (Print) 978-3-319-15039-0 (Online). European Photovoltaic Industry Association (EPIA). Global market outlook for photovoltaics 2014-2018. June 2014. Available at, http://www.epia.org/ fileadmin/user_upload/Publications/EPIA_Global_Market_Outlook_for_ Photovoltaics_2014-2018_-_Medium_Res.pdf (accessed December 2014). International Energy Agency (IEA). Trens 2015 in photovoltaic application: survey report of selected IEA countries between 1992 and 2014. 2015. Report IEA-PVPS T1-27:2015. Danchev S, Maniatis G, Tsakanikas A. Returns on investment in electricity producing photovoltaic systems under de-escalating feed-in tariffs: the case of Greece. Renew Sustain Energy Rev 2010;14:500e5. Spertino F, Di Leo P, Cocina V. Economic analysis of investment in the rooftop photovoltaic systems: a long-term research in the two main markets. Renew Sustain Energy Rev 2013;28:531e40. ~ oz-Cero
n E, De La Casa J, Ortega MJ, Almonacid G. Energy and Talavera DL, Mun economic analysis for large-scale integration of small photovoltaic systems in buildings: the case of a public location in Southern Spain. Renew Sustain Energy Rev 2011;15:4310e9. ~ oz-Cero
n E, Almonacid G. Grid parity and selfTalavera DL, de la Casa J, Mun consumption with photovoltaic systems under the present regulatory
n Campus. Renew Sustain framework in Spain: the case of the University of Jae Energy Rev 2014;33:752e71. Drury E, Denholm P, Margolis R. The impact of different economic performance metrics on the perceived value of solar photovoltaics. October 2011. Technical Report NREL/TP-6A20e52197. Orioli A, Di Gangi A. The recent change in the Italian policies for photovoltaics: effects on the payback period and levelized cost of electricity of gridconnected photovoltaic systems installed in urban contexts. Energy

424

D.L. Talavera et al. / Energy 119 (2017) 408e424

2015;93:1989e2005. [26] Short W, Packey DJ, Holt T. A manual for the economic evaluation of energy efficiency and renewable energy technologies. National Renewable Energy Laboratory; 1995. NREL/TPe462-5173: 1e120. [27] Edalati S, Ameri M, Iranmanesh M, Tarmahi H, Gholampour M. Technical and economic assessments of grid-connected photovoltaic power plants: Iran case study. Energy 2016;114:923e34. [28] Biondi T, Moretto M. Solar Grid Parity dynamics in Italy: a real option approach. Energy 2015;80:293e302. [29] Breyer C, Gerlach A. Global overview on grid-parity. Prog Photovoltaics Res Appl 2013;21:121e36. [30] Talavera DL, Nofuentes G. Economic evaluation of high-concentrator photovoltaic systems. In: Perez-Higuerra P, Fern
andez EF, editors. High concentrator photovoltaics: fundamentals, engineering and power plants. Springer; 2015. p. 401e42. [31] Algora C, Talavera DL, Nofuentes G. Cost analysis. In: Carlos Algora, Ignacio Rey-Stolle, editors. Handbook on concentrator photovoltaic technology. 1a ed. John Wiley & Sons; 2016. p. 711e58. ISBN: 978-1-118-47296-5. [32] Tomosk S, Wright D, Hinzer K, Haysom JE. Analysis of present and future financial viability of high-concentrating photovoltaic projects. In: Perez
ndez EF, editors. High concentrator photovoltaics: fundaHigueras P, Ferna mentals, engineering and power plants. Springer; 2015. p. 377e400.
rez-Higueras P, Terrados J, Fern
[33] Talavera DL, Ferrer-Rodríguez JP, Pe andez EF. A worldwide assessment of levelised cost of electricity of HCPV systems. Energy Convers Manag 2016;127:679e92. [34] Talavera DL, Nofuentes G, Aguilera J. The internal rate of return of photovoltaic grid-connected systems: a comprehensive sensitivity analysis. Renew Energy 2010;35:101e11. [35] Talavera DL, Nofuentes G, De La Casa J, Aguilera J. Sensitivity analysis on some profitability indices for photovoltaic grid-connected systems on buildings: the case of two top photovoltaic European Areas. J Sol Energy Eng Trans ASME 2013;135. [36] Chabot B. From costs to prices: economic analysis of photovoltaic energy and services. Prog Photovoltaics Res Appl 1998;6:55e68. [37] CREARA ENERGY EXPERTS. PV grid parity monitor utility-scale. September 2015. 2nd issue. [38] King C. Site data analysis of CPV plants. In: Photovoltaic specialists conference (PVSC), 35th IEEE; 2010. p. 3043e7. [39] Kea Stone. Analysis of five years of field performance of the Amonix High Concentration PV system. In: Proceedings of the power-gen renewable conference; 2006. [40] Kinsey GS, Stone K, Brown J, Garboushian V. Energy prediction of Amonix CPV solar power plants. Prog Photovoltaics Res Appl 2011;19:794e6. [41] Hea Husna. Impact of spectral irradiance distribution and temperature on the outdoor performance of concentrator photovoltaic system. In: AIP conf proc 1556; 2013. http://dx.doi.org/10.1063/1.4822243:252-255. [42] Lecoufle D, Kuhn F. A Place for PV, tracked-PV and CPV. In: 2nd international workshop on concentrating photovoltaic power plants, Germany; 2009. [43] Nishikawa W, Horne S. Key advantages of concentrating photovoltaics (CPV) for lowering levelized cost of electricity (LCOE). In: Proceedings of the 23rd european PV solar energy conference Valencia; 2008. p. 3765e7. [44] Verlinden P, Lasich J. Energy rating of Concentrator PV systems using multijunction IIIeV solar cells. In: Photovoltaic specialists conference, 33rd IEEE; 2008. [45] Consortium C. In: Concentrator photovoltaic (CPV) workshop. Understanding the technology and related implications for scaled deployment. Dallas: Solar Power International; 2011. [46] Magpower. Performance in practice CPV versus PV, 1.5 Year of operation. In: 3rd concentrated photovoltaic summit USA; 2011. [47] King B, Riley D, Hansen C, Erdman M, Gabriel J, Ghosal K. HCPV characterization: analysis of fielded system data. AIP Conf Proc 2014;1616:276e9. [48] Branker K, Pathak MJM, Pearce JM. A review of solar photovoltaic levelized cost of electricity. Renew Sustain Energy Rev 2011;15:4470e82.

[49] Jordan DC, Kurtz SR. Photovoltaic degradation rates - an analytical review. Prog Photovoltaics Res Appl 2013;21:12e29. [50] Gestore Mercati Energetici (GME). Summary Data - MPE-MGP e Overview. http://www.mercatoelettrico.org/En/Statistiche/ME/DatiSintesi. aspx;(accessed December 2015). [51] Nord Pool Spot. Market data. http://www.nordpoolspot.com/Market-data1/ Elspot/Area-Prices/ALL1/Yearly/?view¼table;(accessed December 2015). [52] ACER/CEER. Annual Report on the Results of Monitoring the Internal Electricity and Natural Gas Markets in 2014.;http://www.acer.europa.eu/Official_ documents/Acts_of_the_Agency/Publication/ACER_Market_Monitoring_ Report_2015.pdf (accessed December 2015). ~ ol SA(. http://www.omie.es/files/flash/ResultadosMercado. [53] OMI-polo Espan swf;(accessed December 2015). [54] European power exchange (EPEX). Prices, volumes and statistics: the markets0 core figures at a glance.;http://www.epexspot.com/en/(accessed December 2015). [55] U.S. Energy Information Administration. Wholesale electricity and natural gas market data. 2014. http://www.eia.gov/electricity/wholesale/index.cfm (accessed September 2014). [56] European Photovoltaic Industry Association. Solar photovoltaics competing in the energy sector: on the road to competitiveness. 2011. Available at, http:// helapco.gr/pdf/tn_jsp.pdf (accessed December 2015). [57] UNEP/BNEF. Private financing of renewable energy: a guide for policymakers. Sustainable Energy Finance Initiative (UNEP), Bloomberg New Energy Finance (BNEF), Chatham House London; 2009. Available at, http://fs-unep-centre.org/ sites/default/files/media/financeguide20final.pdf (accessed January 2015). [58] CDM Executive Board. Guidelines on the assessment of investment analysis. Bonn: UNFCCC Secretariat; 2011. Available at, https://cdm.unfccc.int/ Reference/Guidclarif/reg/reg_guid03.pdf (accessed January 2015). [59] Reuters Thonson. Consulta A.E.A.T. 128308., IS. Central fotovoltaica. Amor
n. tizacio 2014. http://portaljuridico.lexnova.es/doctrinaadministrativa/ JURIDICO/77405/consulta-aeat-128308-is-central-fotovoltaica-amortizacion. [60] Drury E, Lopez A, Denholm P, Margolis R. Relative performance of tracking versus fixed tilt photovoltaic systems in the USA. Prog Photovoltaics Res Appl 2014;22(12):1302e15. [61] Fraisopi F. The CPV market: an industry perspective. GTM Res June 2013. Intersolar München, 20.06.2013. [62] Extance A, M
arquez C. The concentrated photovoltaics industry report. CPV today. 2010. [63] European Central Bank. Inflaction in the euro area. 2014. Available at, http:// www.ecb.europa.eu/stats/prices/hicp/html/inflation.en.html (accessed July 2014). [64] Trading Economics. Inflation rate -countries- list 2015. 2015. Available at, http://www.tradingeconomics.com/country-list/inflation-rate (accessed January 2015). [65] The World Bank. Inflation, consumer prices (annual %). 2015. Available at, http://data.worldbank.org/indicator/FP.CPI.TOTL.ZG?page¼1 (accessed January 2015). [66] World Bank. Lending interest rate. 2015. Available at, http://dataworldbank. org/indicator/FR.INR.LEND (accessed January 2015). [67] Dimson E, Marsh P, Staunton M. Equity premiums around the world. Research foundation publications. 2011. p. 32e5. Available at, http://www.cfapubs.org/ doi/pdf/10.2470/rf.v2011.n4.5 (accessed January 2015). [68] World Bank Group. Doing business: paying taxes 2014. 2015. Available at, http://www.doingbusiness.org/data/exploreeconomies/spain/#paying-taxes (accessed January 2015). [69] Santander Banco. Portal santander trade. 2015. Available at, https://es. santandertrade.com/establecerse-extranjero/espana/fiscalidad (accessed January 2015). [70] Ernst & Young Global Limited. Worldwide corporate tax guide 2014. 2014. EYG no. DL0917:Available at, http://www.ey.com/Publication/vwLUAssets/ Worldwide_corporate_tax_guide_2014/$FILE/Worldwide%20Corporate% 20Tax%20Guide%202014.pdf (accessed January 2015).