Levelised cost of electricity in high concentrated photovoltaic grid connected systems: Spatial analysis of Spain

Applied Energy 151 (2015) 49–59

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Levelised cost of electricity in high concentrated photovoltaic grid connected systems: Spatial analysis of Spain D.L. Talavera a,⇑, P. Pérez-Higueras a, J.A. Ruíz-Arias b, E.F. Fernández c,a a

IDEA Research Group, University of Jaén, Campus Lagunillas, 23071 Jaén, Spain MATRAS Research Group, University of Jaén, Campus Lagunillas, 23071 Jaén, Spain c Environment and Sustainability Institute, University of Exeter, Penryn, Cornwall TR10 9EZ, United Kingdom b

h i g h l i g h t s  The LCOE of HCPV grid connected systems in Spain is estimated and analysed.  A new set of parameters and a deep explanation of the procedure are introduced.  A set of innovative maps relating to the LCOE and energy yield is presented.  The analysis and detection of the optimal zones for HCPV technology is conducted.  A comparison between the LCOE of HCPV and PV systems in a future scenario is done.

a r t i c l e

i n f o

Article history: Received 4 November 2014 Received in revised form 24 March 2015 Accepted 17 April 2015

Keywords: Levelised cost of electricity High Concentrator Photovoltaic Spatial analysis

a b s t r a c t Costs for High Concentrator Photovoltaic (HCPV) power plants dropped dramatically during 2013 and are expected to continue to fall in the next few years. Moreover, when viewed from the perspective of life cycle cost, HCPV becomes even more competitive than other renewable technologies in some geographical areas. Consequently, an analysis of the economic feasibility of the HCPV systems in future scenarios is necessary for comparison with other electricity generation technologies. One of the methods commonly used for the economic feasibility analysis in electricity generation projects is the levelised cost of electricity (LCOE). In this paper a cost analysis of electricity generation of HCPV technology in Spain by using the LCOE has been carried out. The results obtained in this LCOE analysis show that in 2020 the LCOE will be able to reach values for HCPV systems from 0.035 to 0.080 €/kW h, lower than LCOE for conventional PV systems, in some geographical areas of Spain. The results obtained in this analysis have been shown in innovative maps. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction High concentration photovoltaic (HCPV) systems use optical devices (lenses or mirrors) to concentrate the solar radiation onto small solar cells. Although there are a large number of possible configurations in order to implement HCPV grid connected systems [1,2], a typical system consists of modules composed of several electrically connected high efficiency III-V multi-junction solar cells with their associated optics that concentrate the solar light by a factor of 500 and 1000 times, an accurate two-axis solar tracker, an efficiency inverter and other components such as cables and connectors.

⇑ Corresponding author. Tel.: +34 953 212 809. E-mail address: [email protected] (D.L. Talavera). http://dx.doi.org/10.1016/j.apenergy.2015.04.072 0306-2619/Ó 2015 Elsevier Ltd. All rights reserved.

There are different types of concentration photovoltaic systems that are usually classified depending on the concentration ratio. This paper is exclusively focused on the analysis of high concentration photovoltaic systems as they have passed the demonstration phase and begun the industrialization and commercialization phase with 160 MW of installed power worldwide in 2013. In addition, the cumulative installed capacity of HCPV can jump from 358 MWp in 2014 to more than 1 GW in 2020 [3]. Due to the use of lenses to concentrate the light, HCPV systems only react to the direct component of the solar irradiance. Although the performance of these systems is mainly determined by the direct normal irradiance, they are also affected by other parameters such as temperature, spectrum and wind speed. [4]. As was noted, HCPV systems use accurate two-axis trackers since the modules must be always pointing towards the sun’s rays in order for the lenses to concentrate the direct normal irradiance on the

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solar cell surface. Because of this, they are more appropriate for large-scale implementation in large PV plants (larger than 1 MWp) at locations with high annual direct normal irradiation levels such as in the south of Europe, MENA and Australia. Some methods commonly used for the economic feasibility analysis in electricity producing photovoltaic systems are the net present value (NPV), the discounted payback time (DPBT), the internal rate of return (IRR) and the levelised cost of electricity (LCOE) [5–10]. However, the LCOE method is the most often used when comparing electricity production technologies (both renewables and conventional energies) [11–18]. Besides, the LCOE of renewable energy technologies is a widely used measure by which renewable energy technologies can be evaluated for modelling or policy development [19]. Levelised cost of electricity can be defined as the constant and theoretical cost for every unit of electricity produced by the system over the analysis period (usually lifetime) in nominal or real monetary units [20]. The LCOE has been widely used for the analysis of conventional PVs [7,11,12,17,18,21,22]. However, due to the fact that HCPV is a new technology, there is a lack of studies concerning the analysis of the LCOE [13,23]. In [13], a report focusing on the analysis of the LCOE of several renewable energies was conducted by Fraunhofer ISE. This work is focused on the analysis of photovoltaics, wind power and biomass power plants in Germany. Regarding HCPV, the study is limited to two locations with different annual direct normal irradiations. In [23] the analysis of the LCOE of two HCPV power plants at locations with different annual direct normal irradiations in USA was presented by SolFocus Inc. at ICSC-5 conference. This work is focused on the LCOE of SolFocus technology and therefore has a commercial approach and is not a deep research analysis of the LCOE of HCPV technology. Bearing this in mind, an in-depth analysis of the LCOE of the HCPV technology is required to evaluate the potential of this emerging technology. Therefore, in the present contribution, the LCOE of HCPV at the end of 2013 is analysed for Spain. In addition, LCOE values in a future scenario based on HCPV technology learning curve and market have also been predicted. Also, several improvements in the estimation of the LCOE compared with the previous works in order to quantify tax, depreciation and annual escalation rate of the operations and maintenance cost have been introduced. Furthermore, a methodology based on a set of innovative maps relating to the LCOE and energy yield of HCPV is presented. These maps are a useful tool since they allow the spatial analysis of the LCOE at a wide range of productivity levels to be done. Furthermore, with the proposed methodology it is possible to identify the optimal locations for HCPV systems where they can be considered a more profitable technology than conventional PV. The current tools based on graphs and tables do not allow these zones to be detected. Moreover, the proposed methodology based on maps is easy to manage and could be consulted by future owners, investors and financiers of HCPV systems. Also, this methodology can be used at different worldwide regions in order to identify the optimal locations for HCPV technology. In this paper we define as HCPV systems a grid-connected power plant with a nominal power larger than 1 MWp made up of HCPV module with the features mentioned above. Also we define as conventional PV systems a grid-connected power plant with a nominal power larger than 1 MWp made up of fixed optimally oriented c-Si modules. It is worth mentioning that the spatially-distributed estimate of LCOE over the study region has been possible based on a spatiallydistributed estimate of the total annual DNI. The DNI annual amount has been determined from a 10-yr dataset of monthly DNIs [24], so that the effect of the inter-annual DNI variability is properly accounted for and the long-term DNI can be estimated with an uncertainty as low as 5% [25]. Any possible DNI tendency

which might be attributed to climate change has been neglected because the impact of climate change effects in the time scales of this study is hypothesized as small and any estimate of these effects would be highly uncertain, particularly concerning the effect of atmospheric aerosols. 2. Methodology for calculating the levelised cost of electricity As was explained, the method for the cost analysis used in this paper is the levelised cost of electricity. The calculation procedures are similar to those presented in previous works [8]. However, several improvements in order to quantify tax, depreciation and annual escalation rate of the operations and maintenance cost have been introduced. This method will be shown below. Levelised cost of electricity can be defined as the constant and theoretical cost of production of HCPV electricity over its life time expressed as:

LCOE ¼ PN

LCC

n¼1

ð1Þ

En ð1r d Þn ð1þdÞn

where LCC is the life cycle cost (€) of the system, rd is the annual degradation rate in the efficiency of the HCPV modules of the HCPV system, E is the annual HCPV electricity yield (kW h/(kWp year), d is the nominal discount rate and N is the useful life of the HCPV system. Assuming that annual HCPV electricity yield (E) remains constant over the life-cycle, the LCOE may be estimated by:

LCC LCOE ¼ PN ð1r Þn E n¼1 ð1þddÞn

ð2Þ

If the parameter Kd is equal to (1  rd)/(1 + d), the Eq. (2) can be expressed:

LCC

LCOE ¼ E

ð3Þ

K d ð1K N dÞ 1K d

The life cycle cost of the HCPV system (LCC) may be calculated by:

LCC ¼ HCPVI þ PW½HCPVOM ðNÞ  PW½DEP  T

ð4Þ

where HCPVI (€) is the initial investment cost of the HCPV system, PW[HCPVOM (N)] is the present worth of operation and maintenance cost of the system and PW[DEP] is the present worth of the tax depreciation and T is the tax rate. Concerning the operation and maintenance cost of the life cycle of the system, PW[HCPVOM (N)] can be written as:

PW½HCPVOM ðNÞ ¼

K P  ð1  K NP Þ HCPVAOM ð1  TÞ  1  KP

! ð5Þ

where HCPVAOM is the annual operation and maintenance costs which are fixed during the system life cycle. The parameter Kp = (1 + rO&M)/(1 + d) and rO&M is the annual escalation rate of the operation and maintenance cost of the system. N is the life cycle of the HCPV system. If the tax depreciation is calculated as lineal over the time period and DEP is the annual tax depreciation (€) for the HCPV system, the present worth of the tax depreciation may be calculated by:

PW½DEPðNd Þ ¼ DEPy 

q  ð1  qNd Þ 1q

ð6Þ

where the factor q is equal to (1/(1 + d)), Nd is the tax life for depreciation (years) and parameter DEPy is the annual tax depreciation for the HCPV system – DEPy is constant. The share of external financing and equity financing can be included in the analysis explicitly through the weighted average

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cost of capital (WACC) over the discounting factor (nominal discount rate). HCPVI (€) is the initial investment cost of the HCPV system which may be financed through long-term debt and/or equity capital. If HCPVI is financed through a loan (HCPVl) and equity capital (HCPVec) so that HCPVI = HCPVl + HCPVec. Therefore, this can be written as:

HCPVI ¼

HCPVl  

il ð1  TÞ 1  ð1 þ il ð1  TÞÞ

þ ðdec  HCPVec Þ 

N l

q  ð1  qNl Þ  1q

!

q  ð1  qN Þ þ HCPVec  qN 1q

 ð7Þ

The first term of Eq. (7) depicts the loan: HCPVl is borrowed at an annual loan interest (il) to be repaid in Nl years. The second term depicts the equity capital, with an annual payback in the form of dividends (dec) and it is amortized at the end of the life cycle of the system. It is worth mentioning that the left-hand side of Eq. (7) only equals its right-hand side if the selected value of d is equal to the weighted average cost of capital (WACC) of the investment. WACC is the cost that the owner or investor of the project must pay for the use of capital sources in order to finance the investment. A widespread practice in organizations is to use a nominal discount rate (d) equal to the organization’s weighted average cost of capital [20]. In this paper nominal discount rate is assumed to be equal to WACC in order to calculate the LCOE.

3. Estimation of parameters involved in the calculation LCOE This review will lead to the identification of the value of the parameters for the analysis of the HCPV and conventional PV systems for a scenario in the year 2013 and a future scenario. In this future scenario the value of the parameters for the analysis of the HCPV and conventional PV systems will have the same values, except for the operation and maintenance costs and solar irradiation. It should be noted that the figures presented here referring to costs and electricity yields are all normalized-per-kWp. The symbols used for these factors are the same for those not normalized, except that they are shown in brackets and with the subscript ‘kWp’. 3.1. Calculation of the HCPV electricity yields There are different methods [26,27] to calculate the energy generated by a grid-connected photovoltaic system, the method based on the Performance Ratio (PR) being one of the most often used. According to the IEC standard 61724 [28], the year-round electricity generated by a conventional PV system with fixed panels optimally inclined over the horizontal and permanently oriented southward can be estimated using the following equation:

Y FV ¼ PR

Hopt A GSTC

ð8Þ

where YFV is the final AC annual energy yield in a conventional FV system (kW h/kWp year), Hopt A is the annual global irradiation on optimally inclined plane (kW h/m2 year) and GSTC is the global irradiance at standard test condition (1 kW/m2). The value of PR in a conventional PV system usually ranges from 0.70 to 0.80. In this case, we have used a value of 0.75 based on experience of this kind of system [29–33]. The annual electricity generated by a HCPV system can be estimated using the following equation:

Y HCPV ¼ PR

DNIA DNISTC

ð9Þ

where YHCPV is the final AC annual energy yield in a HCPV system (kW h/kWp year), DNIA is the annual direct normal irradiation (kW h/m2 year) and DNISTC is the direct normal irradiance at standard test condition (1 kW/m2). The value of PR in a typical HCPV system ranges from 0.76 to 0.91 [34–44], as shown in Table 1. Based on the analysis of these data, an intermediate value of PR = 0.82 has been considered for this study. Fig. 1 shows the final AC annual energy yield of a typical HCPV system in Spain. It has been obtained from Eq. (9), using a spatially distributed estimate of DNIA and assuming a constant PR value of 0.82. DNIA was evaluated following the approach described in [24], which is briefly outlined in the following, using the Weather Research and Forecasting (WRF) numerical weather prediction model [45]. Since release v3.6, the WRF model can output DNI [46,47] being, probably, the first model of its class with this added capability. The entire area of Spain was simulated at a spatial resolution of 10 km for the period from January 2003 to December 2012. The model’s DNI outputs were annually aggregated and averaged over the 10-year period to obtain the map of DNIA. Using this time scale, a data assimilation process was conducted to correct DNIA based on the annual DNI measured at the more than 50 radiometric stations of the National Radiometric Network of the Spanish National Weather Service. The data assimilation process ensures, an average, a DNI estimate with negligible bias and uncertainty of only 5% with respect to the ground observations. As can be seen in Fig 1, the available DNIA depends highly on the location of interest, thus being a source of strong spatial variability of the final AC annual yield of a HCPV system installed in the study region. The available normal direct irradiation depends highly on the location of the site and is a crucial factor for the calculation of the final AC electricity annual yield of an HCPV system. In this map, a blue coloured area located in the north can be seen, showing the lowest electricity annual yield, with a minimum value of 805 kW h/ (kWp year) (location number 3, Table 2). The area with the highest electricity annual yield is located in the south of the map with a maximum value of 1821 kW h/(kWp year) (location number 1, Table 2). Furthermore, there are high values of electricity annual yield in locations in the middle and northeast of the map, for example of 1743 kW h/(kWp year) (location number 4, Table 2). Table 2 shows the values of annual irradiation, Yield and LCOE of five locations with the following characteristics: Location number 1 presents the highest value of DNIA, Location number 2 has a medium value of DNIA, Location number 3 presents the minimum value of DNIA, Location number 4 has the maximum difference between DNIA and Hopt and Location number 5 has the minimum difference between DNIA and Hopt. These values will be discussed in future sections. 3.2. Estimation of remaining factors involved in the analysis According to the parameters described in the previous sections, the typical normalized-per kWp initial investment cost in HCPV or conventional PV systems are shown in Table 3. Table 1 Values provided by some HCPV Companies concerning DNI, yield and performance ratio. Company/location

DNIA (kW h/m2)

YHCPV (kW h/kWp year)

PR (%)

Reference

Soitec/Touwsrivier Solfocus/ISFOC MagPower/Portugal Semprius/NREL Solar systems/ Hermannsburg

2447 1861 1978 2446 2464

1878 1914 2113 2079 2104

76–81 88.7 91 85 85.4

[42] [34] [43] [44] [40]

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Fig. 1. Annual electricity yields in Spain produced by a 1-kWp HCPV system (kW h/kWpyear) with performance ratio equal to 0.82.

Table 2 Irradiation, yield and LCOE values for different Spanish locations. Number

Location

Latitude Longitude

DNIA Hopt YHCPV (kW h/(m year)) (kW h/(m2 year)) (kW h/(kWp year))

YPV LCOEHCPV (€/kW h) (kW h/(kWp year)) Scenario

1 2 3 4 5

Granada Cuenca Cantabria Toledo Burgos

37.43 39.90 43.09 39.93 43.09

2221 1960 982 2126 1044

1532 1401 878 1428 937

3.22 1.96 4.37 5.35 3.74

2043 1868 1171 1904 1249

1821 1607 805 1743 856

Table 3 Installed system prices for 2013. (Sources: Conventional PV systems [48], HCPV systems [13,14]). Power (>1 MW)

Conventional PV

HCPV

Units

Normalized-per-kWp initial investment cost

1000–1400

1400–2200

€/kWp

2013

2020

0.081 0.092 0.184 0.085 0.173

0.035 0.040 0.080 0.037 0.075

DNI maximum DNI median DNI minimum (DNI–Hopt) maximum (DNI–Hopt) minimum

Initial investment cost may be financed by means of debt and/or equity capital. Long-term loans and equity capital have been selected in this paper. It has been assumed that 80% of this amount is borrowed as a loan – debt, while the remaining investment amount, 20%, is contributed from equity capital. Regarding the conventional PV systems, the loan, il is considered equal to 4%, Nl equal to 20 years [53,54], while equity capital, dec equal to 8% [13] being amortized at the end of the life cycle of the system, for PV. Concerning the HCPV, the loan, il is considered equal to 6%, Nl equal to 20 years, while the equity capital, dec equal to 12% and being amortized at the end of the life-cycle of the system. HCPV projects

Regarding the inflation rate (i), reviewing the averages of historical data for Spain in the period 2007–2013 [49–52], a value for the inflation rate equal to 2.2% can be assumed, see also Table 4.

Table 4 Average rate of inflation in the period 2007–2013. Year

2007

2008

2009

2010

2011

2012

2013

Average rate of Inflation (2007–2013) (%)

Reference

Annual average rate of inflation (%)

2.8 2.8 2.8

4.1 4.1 4.1

0.2 0.3 0.2

2.0 1.8 2.1

3.1 3.2 3.1

2.4 2.4 2.4

1.5 1.4 1.5

2.24 2.20 2.26

[51] [52] [50]

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have a risk higher than conventional PV system, so return on equity capital (dec) and cost of the loan (il) are higher values. The income tax rate (T) for the organization or taxpayer, changes depending on each country’s regulations. The value of income tax rate is assumed equal to 30% for this study. The method used in the tax depreciation, have been based on a general method, using a maximum linear coefficient of 5%, with a tax life for depreciation of 20 years [55,56]. The annual HCPV electricity yield generated by the system is assumed to decrease every year. Annual degradation rate (rd) in the efficiency of the PV panels is 0.5%/year [11,57]. The analysis period is equal to the life time of the HCPV system, therefore N = 30 years. Nowadays, conventional PV systems have a life cycle of around 30 years and more. Salvage value of the system at the end of their life-cycle (SV) is taken as equal to zero. The nominal discount rate (d) is assumed equal to the weighted average cost of capital in order to calculate the LCOE [13,20]. This

Table 5 Values of the factors assumed for the calculation of LCOE on HCPV systems in the scenario for 2013. Factors

Case base values

Units

YHCPV [HCPVI]kWp [HCPVAOM]kWp rd rO&M T i d il Nl dec N

According Fig. 1 1800 28 0.5 2.2 30 2.2 6.49 6 20 12 30

kW h/(kWp year) €/kWp €/kWp %/year %/year % % % % years % years

53

capital cost will vary depending on how the capital resources are chosen to finance the initial investment cost. The after-tax WACC values are shown in Tables 5 and 9. Normalized-per-kWp annual operation and maintenance costs are estimated to be 20 €/kW year for the conventional PV systems [48,58,18]. Meanwhile, normalized-per-kWp annual operation and maintenance cost is taken at 28 €/kW year for the HCPV systems [14,58]. Annual escalation rate of the operation and maintenance cost (rO&M) is set equal to the value of the annual inflation rate, so rO&M = 2.2% for both systems. To summarise, the figures selected and assumed for each of the factors that define the case base for the HCPV systems are shown in Table 4, while Table 8 shows the figures for the case base of conventional PV systems and HCPV systems in the future scenario. Solving the equations presented in Section 2 together with the figures shown Tables 5 and 9 in a spreadsheet, paves the way to the estimation of the LCOE for each of the scenarios. 4. Analysis and results In this section the levelised cost of electricity of HCPV technology in Spain has been estimated. This study has taken solar irradiation according to the area selected geographically, while the remaining parameters involved in the analysis, were kept constant. Furthermore, the results obtained in this analysis have been shown in innovative maps. 4.1. Levelised cost of electricity of HCPV Solving the equations and following the procedure presented in Section 2 using the values provided in Table 5 and the annual HCPV electricity yields of Fig. 1, the LCOE for HCPV systems in Spain in the year 2013 has been estimated.

Fig. 2. LCOE for HCPV systems in Spain in the scenario for 2013.

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D.L. Talavera et al. / Applied Energy 151 (2015) 49–59

Fig. 2 represents the levelised cost of electricity of HCPV systems larger than 1 MWp and assuming a system performance ratio 0.82 for 2013. In Fig. 2 all data values are given as €/kW h. As can be seen, the area with the highest values of LCOE is located in the north of the map with a maximum value of 0.184 €/kW h (location number 3, Table 2). The area with the lowest values of LCOE is located in the south of the map with a minimum value of 0.081 €/kW h (location number 1, Table 2). Furthermore, there are also other locations with low values of LCOE in the middle of the map with values of 0.085 €/kW h (e.g. location number 4, Table 2) and in the northeast of the map with values around 0.089 €/kW h. In this scenario, HCPV systems with a DNIA ranging from 2221 to 982 kW h/(m2 year) can reach LCOE values ranging from 0.081 to 0.184 €/kW h respectively. The validation of the results obtained is difficult since there are no studies concerning the analysis of the LCOE of HCPV systems in Spain. However, in order to validate the results found, Table 6 shows the values of LCOE obtained for similar technologies and scenarios for different organizations. It is important to note that, although similar, the scenarios and inputs for the estimation of the LCOE are not the same. Because of this, different results are expected. However, as can be seen the values of LCOE obtained in this work are similar to those presented by other authors. For example, the study performed by Fraunhofer ISE analyses locations whose DNIA range from 2000 to 2500 kW h/(m2 year) and the values of LCOE obtained range from 0.08 to 0.15 €/kW h. These results are almost equal to those obtained in this study with values of LCOE ranging from 0.08 to 0.18 €/kW h (the values are slightly higher since the DNIA in Spain varies from 1000 to 2200 kW h/(m2 year)). Also, Solfocus Inc. [59] estimates a LCOE of 0.08 €/kW h for ‘‘Victor Valley College’’ power plant located in Victorville, CA (USA) with an DNI of 2628 kW/(m2 year) and GTM Research Inc. [60] estimates a LCOE of 0.07 €/kW h for a power plant located in Phoenix, AZ (USA) with an DNI of 2518 kW/(m2 year). Hence, it can be considered that the results found here are accurate and are representative of HCPV systems located in Spain.

distribution of costs in a HCPV system has a wider spectrum, the cost of cells not having such an important influence on the global cost. The result is that a great part of the system cost is transferred from the cells to other more varied and readily available technologies, leaving room in projects and investments from other very different industrial sectors that can easily be adapted to manufacture these new products (plastic, glass, metal mechanical industries, etc). The high efficiency of the elements of HCPV implies a reduction of the area required for these systems, leading to a substantial decrease, both in the investment and the price of the electricity generated. Concentration cells have reached an in lab maximum efficiency of 44% [64]. Therefore, concentration modules are being manufactured with about 30–35% [65] efficiencies and the results of the measurements performed to the already installed HCPV systems show values that double the efficiencies of the conventional PV systems. Several market analyses [3,66,67] indicate that the HCPV world cumulative installed capacity in 2013 was 160 MWp and that this could exceed 1400 MWp in 2020. Based on the available information, three different annual growth (QA, in%) scenarios of this capacity can be assumed as shown in Fig. 3: a base case with a growth of 30% (Conservative), a pessimistic case with a growth of 27% (Low) and an optimistic case with a growth of 33% (Accelerated). Learning curves can be used to estimate the evolution of the initial investment cost of HCPV systems for upcoming years. These curves described the cost reduction as a function of the accumulated experience in the manufacturing and in the use of a particular technology. The learning curve of a HCPV system can be expressed as:

HCPVI

year

  ð1LRÞ Q HCPV year log2 ¼ HCPVI 2013 Q HCPV2013

ð10Þ

where HCPVI year is the HCPV initial investment cost in the year under review, HCPVI 2013 is the HCPV initial investment cost in

4.2. Comparison between the LCOE of HCPV and conventional PV systems The forecasting of the evolution of the market for a new technology is a complex issue mainly due to the lack of historical data and because of the rapid advances that occur in the first stages of development. In addition, this evolution will be dependent on other factors such as the economic crisis and the support programs implemented by several countries. Because of this, a reduction in the manufacturing costs of the solar cells and the introduction of low cost materials for manufacturing new optical devices are expected in the next few years. These will bring important industrial growth and consolidation in the manufacturing of HCPV modules. HCPV technology has two main advantages when compared with other sources of energy [63]. Firstly, the high potential cost reduction because of the reduction of expensive semiconductor materials by cheaper optical devices. The other main advantages of HCPV compared with conventional PV technology are that the

Fig. 3. Forecast of the HCPV world cumulative capacity based on the three scenarios considered: Low, Conservative and Accelerated. Market forecast conducted by the private companies IHS (HIS), Globaldata (GD) and SPV Market (SPV).

Table 6 LCOE for 2013 using the exchange rate 1€ = 1.36$ [13,61,62].

Table 7 Learning ratio values of conventional PV as estimated by several authors [68–72].

Technology

Organization

LCOE (€/kW h)

Author/Date

Period of time analysed

Region studied

LR (%)

Conventional PV Conventional PV Conventional PV HCPV HCPV

EPIA IEA Fraunhofer ISE Fraunhofer ISE University of Jaén

0.09–0.19 0.12–0.16 0.07–0.10 0.08–0.15 0.08–0.18

Poponi/2003 Parente/2002 IEA/2000 Harmon/2000 Poponi/2003

1976–2002 1981–2000 1976–1996 1968–1998 1989–2002

World World EU World World

25 23 21 20 20

55

D.L. Talavera et al. / Applied Energy 151 (2015) 49–59 Table 8 Values of parameters for the estimation of the learning curve for the three scenarios considered. Factor

Accelerated

Conservative

Low

Normalized-per-kWp initial investment cost [HCPVI 2013]kWp Annual growth (QA) Learning rate (LR)

1400 €/kWp 33% 28%

1800 €/kWp 30% 25%

2200 €/kWp 27% 22%

Fig. 4. Learning curves of the normalized-per-kWp initial investment cost of HCPV systems in different scenarios and of conventional PV systems. Also, the normalized-per-kWp initial investment cost of HCPV forecast conducted by the private company GTM Research Inc [60].

Table 9 Values of the factors assumed for the calculation of the LCOE in the future scenario (2020) for HCPV and conventional PV systems. Factors

Annual yield [HCPVI]kWp [HCPVAOM]kWp [PVAOM]kWp rd rO&M T i d il Nl dec N

Case base values

Units

HCPV

Conventional PV

According Fig. 1 700 28

According (Eq. (8))

20 0.5 2.2 30 2.2 4.48 44 20 20 88 30

kW h/(kWp year) €/kWp €/kWp €/kWp %/year %/year % % % % years % years

2013, QHCPV year is the HCPV world cumulative installed capacity in the year under review, QHCPV 2013 is the HCPV world cumulative installed capacity in 2013 and LR is the Learning Rate. As was indicated in Table 3 the HCPV normalized-per-kWp initial investment cost may be taken at 1800 €/kWp with a variation ranging from 1400 to 2200 €/kWp. As can be seen in Table 7, the learning rate of conventional PV has decreased with time as more experience in this technology has been gained. This ratio has increased from a value of 25% in the first stage of this technology (the seventies) until a current value of 20%. As mentioned, HCPV technology is still in its first stages and therefore has a learning ratio varying from 22% to 28%. Based on the data examined above, three scenarios for the estimation of the learning curve of the initial investment cost of HCPV systems should be considered. Table 8 summarizes the values of

Fig. 5. Levelised cost of electricity of the HCPV systems in the future scenario (2020).

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Fig. 6. Sensitivity analysis on LCOE of the HCPV systems as a function of the normalized-per-kWp initial investment cost for different values of the annual direct normal irradiation.

the parameters for the estimation of the learning curves of each scenario. Also, in order to compare the results with conventional fixed PV technology, a scenario with normalized-per-kWp initial investment cost [PVI]kWp of 1200 €/kWp in 2013, an annual growth of 8% and a learning rate of 8% is presented. Fig. 4 shows the results obtained for each of the cases examined and commented on. These results depend on multiple variables that can change over time and therefore modify the data obtained. However, it is possible to expect a future scenario in which the normalized-per-kWp initial investment cost of HCPV and conventional PV systems will be equal at a value ranging from 500 to 900 €/kWp. In this future scenario (the year 2020) the same normalizedper-kWp initial investment cost for conventional PV and HCPV systems (700 €/kWp) has been considered, together with the values of the factors shown in Table 9, the estimation of the levelised cost of electricity of HCPV and conventional PV systems in Spain. The map in Fig. 5 shows the levelised cost of electricity of HCPV systems in the future scenario. As can be seen, the area with the highest values of LCOE is located in the north of the map with a maximum value of 0.080 €/kW h (location number 3, Table 2). The area with the lowest values of LCOE is located in the south of the map with a minimum value of 0.035 €/kW h (location number 1, Table 2). Furthermore, there are also other locations with low values of LCOE in the middle of the map with values of 0.037 €/kW h (e. g. location number 4, Table 2) and in the northeast of the map with values about 0.040 €/kW h. In this future scenario (2020), HCPV systems with a DNI ranging from 2221 to 982 kW h/(m2 year) can reach LCOE values ranging from 0.035 to 0.080 €/kW h respectively. The value of the factors that are involved in the estimation of the LCOE of HCPV systems may change according to government support programmes and policies, technology (the learning curves and the economic scales), etc. In order to analyse this in more detail, the study of the influence on the LCOE caused by the possible change of the values of some of these factors has been carried out. In particular, a sensitivity analysis regarding the influence of the normalized per-kWp initial investment cost ([HCPVI]kWp), the normalized per-kWp annual operation and maintenance cost ([HCPVAOM]kWp) and the nominal discount rate (d) has been conducted. Figs. 6–8 show the estimated LCOE of HCPV systems as a function of the [HCPVI]kWp, [HCPVAOM]kWp and d respectively, for different values of the annual direct normal irradiation. It is important to mention that the rest of the factors involved in the estimation of the LCOE shown in each figure were kept constant at the values given in Table 9. Fig. 6 shows the estimation of the LCOE as a function of the normalized-per-kWp initial investment cost for an annual direct

Fig. 7. Sensitivity analysis on LCOE of the HCPV systems as a function of the normalized-per-kWp annual operation and maintenance cost for different value of the annual direct normal irradiation.

Fig. 8. Sensitivity analysis on LCOE of the HCPV systems as a function of the nominal discount rate for different values of the annual direct normal irradiation.

normal irradiation ranging from 1000 to 2200 kW h/m2. This figure considers variations of the normalized-per-Wp initial investment cost from 500 to 2200 €/kWp. If the worst case is assumed ([HCPVI]KWp = 2200 €/kWp and DNIA = 1000 kW h/m2), the value of the LCOE would be at around 0.174 €/kW h. On the other hand, if the best case is assumed ([CPVIN]kWp = 500 €/kWp and DNIA = 2200 kW h/(m2 year)), the value of the LCOE would be at around 0.030 €/kW h. Fig. 7 shows the calculation of the LCOE as a function of the normalized per-kWp annual operation and maintenance cost of HCPV systems for an annual direct normal irradiation ranging from 1000 to 2200 kW h/m2. If the worst case is assumed ([HCPVAOM]KWp = 45 €/kWp and DNIA = 1000 kW h/(m2 year)), the value of the LCOE would be at around 0.098 €/kW h. In contrast if the best case is assumed ([HCPVAOM]kWp = 15 €/kWp and DNIA = 2200 kW h/ (m2 year)), the value of the LCOE would be at around 0.028 €/kW h. Finally, Fig. 8 shows the calculation of the LCOE as a function of the nominal discount rate for the same values of the annual direct normal irradiation previously considered. If the worst case is assumed (d = 8% and DNIA = 1000 kW h/(m2 year)), the value of the LCOE would be at around 0.101 €/kW h. At the same time, if the best case is assumed (d = 2% and DNIA = 2200 kW h/(m2 year)), the value of the LCOE would be at around 0.031 €/kW h. The influence on the LCOE of HCPV systems of the variations of three different factors was conducted above. It is also interesting to compare the influence of these factors on the estimated value of the LCOE of HCPV systems. To carry out this analysis, the base case of the future scenario (Table 9) and a typical DNIA of

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Fig. 9. Difference between the LCOE of HCPV and conventional PV systems in the future scenario analysed (2020).

1800 kW h/(m2 year) were considered. In this case, the LCOE is 0.043 €/kW h. At the same time, the value of [HCPVI]kWp, [HCPVAOM]KWp or d where varied a +20% respectively while the rest of the factors involved in the analysis were kept constant. Based on this analysis, a value of LCOE = 0.046 €/kW h was obtained considering the individual variation of [HCPVAOM]KWp or d, and a value of LCOE = 0.048 €/kW h was obtained considering the individual variation of [HCPVI]kWp. Thus, it can be concluded that LCOE has a similar sensitivity to the variations of [HCPVAOM]KWp and d, and different and larger sensitivity to the variations of [HCPVI]kWp. Fig. 9 shows the difference between the LCOE of HCPV and conventional PV systems in the future scenario examined in this paper (2020). The LCOE of both technologies has been estimated solving the equations and following the procedure outlined in Section 2, together with the figures shown in Table 9 in a spreadsheet. The annual electricity yield by a conventional PV system with the panels optimally inclined over the horizontal and permanently oriented southward was estimated using Eq. (8) considering a performance ratio of 0.75. In Fig. 9, positive values indicate that the LCOE of HCPV systems is higher than the LCOE of conventional PV systems, while negative values indicate that the LCOE of HCPV systems is lower than the LCOE of conventional PV systems. In this future scenario (2020), the calculated LCOE of conventional PV systems varies from 0.037 to 0.064 €/kW h for locations with a Hopt from 2043 (location number 1, Table 2) to 1171 kW h/(m2 year) (location number 3, Table 2) respectively. The blue areas of the map located in the south, middle and northeast of the map represent locations where the LCOE of HCPV systems is lower than the LCOE of conventional PV systems (e. g. locations number 1, 2 and 4, Table 2). As can be seen, there are a wide number of areas where HCPV would be a more profitable technology from an economic point of view. The green areas of the map represent locations where the values of the LCOE for HCPV and conventional PV

systems are the same, which indicate that both technologies can represent a similar economic profitability Also, there are a wide number of areas where the LCOE of HCPV systems are higher than the LCOE of conventional PV systems (e. g. location number 3 and 5, Table 2) in which conventional PV technology is a more profitable investment from an economic point of view. These locations are mainly located in the north of Spain and can be explained due to the low annual direct normal irradiation levels which cause low annual energy yields as shown in Fig. 1.

5. Conclusions The economic feasibility of HCPV systems is increasingly being evaluated using the levelised cost of electricity (LCOE) generation in order to be compared to other electricity generation technologies. This is vital in terms of industrial perspective in order to analyse the potential of this young technology. In this paper an analysis of the LCOE of HCPV systems has been carried out in Spain. The results obtained are shown in an innovative set of maps. According to the cost analysis, HCPV systems at locations with annual direct normal irradiation ranging from 2221 to 982 kW h/(m2 year) reached a LCOE ranging from 0.081 up 0.18 €/kW h in 2013. Also, considering a positive market evaluation over the next few years, In 2020 HCPV systems could reach a LCOE value ranging from 0.035 to 0.080 €/kW h from the maximum to minimum the annual direct normal irradiation values. Considering a future scenario in which the initial investment cost for conventional PV and HCPV systems is the same, it can be also concluded that PV is not a more profitable technology than HCPV for the whole of Spain -from an economic point of view-. The selection of the technology for a specific location will mainly depend on its annual direct and global irradiation. In the case of

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Spain, an area located in the southwest and northeast where HCPV would represent a more profitable investment and another area located in the north where conventional PV systems would be a more profitable investment. It is also important to note that, although this analysis has been carried out for Spain, this conclusion can be extended for other regions worldwide. Future owners and potential investors of HCPV systems demand valuable information about the economic feasibility of their investment, so one aim of this document is to provide information about the LCOE of HCPV systems with power higher than 1 MWp. Furthermore, Spanish governmental bodies which are involved in the design or selection of the support mechanisms addressed to HCPV may be enlightened by the results of the present paper.

rd rO&M

SV T WACC YHCPV YPV

Annual degradation rate in the efficiency of the HCPV panels (%) Annual escalation rate of the operation and maintenance cost of the HCPV system (%) Salvage value of the system at the end of their life cycle (€) Income tax rate (%) Weighted Average Cost of Capital (%) Final A.C. annual energy yield in a HCPV grid connected system (kW h/(kWp year) Final A.C. annual energy yield in a conventional fixed FV grid connected system kW h/(kWp year)

Appendix A. Terminology

[HCPVAOM]kWp

[HCPVI]kWp [PVAOM]kWp

[PVI]kWp d dec DEP DNIA DNISTC GSTC HCPVAOM HCPVec

HCPVI HCPVl Hopt

A

i il LCC LCOE LR N Nd Nl PR PW [DEP] PW [HCPVOM (N)] q QHCPV QA

Normalized per-kWp annual operation and maintenance cost of the HCPV system (€) Normalized per-kWp initial investment cost of HCPV (€/kWp) Normalized per-kWp annual operation and maintenance cost of the PV system (€) Normalized per-kWp initial investment cost of PV (€/kWp) Nominal discount rate (%) Annual dividend the equity capital – return on equity– (%) Annual tax depreciation (€) Annual Direct Normal Irradiation (kW h/(m2 year)) Direct Normal Irradiation in Standard Test Condition (1 kW h/m2) Global Irradiance in Standard Test Condition (1 kW/m2) Annual operation and maintenance cost of the HCPV system (€) Amount equal to the portion of the initial investment financed with equity capital (€) Initial investment cost on the HCPV system (€) Amount equal to the portion of the initial investment financed with loan (€) Annual Global Irradiation on optimally inclined plane (kW h/(m2 year)) Annual inflation rate (%) Annual loan interest (%) Life cycle cost of the HCPV system (€) Levelised cost of electricity (€/kW h) Learning rate Life cycle of the HCPV system, equal to analysis period (years) Tax life for depreciation (years) Amortization of loan (years) Performance ratio (%) Present worth of the tax depreciation (€) Present worth of the HCPV system operation and maintenance cost (€) Factor equal to (1/1 + d) HCPV world cumulative installed capacity Annual growth installed capacity (%)

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