Energy 122 (2017) 801e810
Contents lists available at ScienceDirect
Energy journal homepage: www.elsevier.com/locate/energy
Methodology of determining the optimum performances of future concentrating solar thermal power plants in Algeria Sofiane Mihoub a, b, *, Ali Chermiti a, Hani Beltagy b a b
Research Unit of Materials and Renewable Energies (URMER), Abou Bakr Belkaid University, Tlemcen, Algeria Hydrogen Energy Applications Laboratory (LApEH), Mechanical Engineering Department, Blida University, Algeria
a r t i c l e i n f o
a b s t r a c t
Article history: Received 4 December 2015 Received in revised form 10 September 2016 Accepted 15 December 2016
The newly adopted version of the National Renewable Energy Program of Algeria offers the country the possibility to integrate 27% of renewable energy in the national energy mix. Preservation of fossil resources, diversification of electricity production and contribution to sustainable development are among challenges that face the country nowadays. The objective of this paper is to propose a methodology and outline a procedure to determine the best configuration and the optimum design of future solar thermal power plants with minimum levelized cost of electricity (LCOE) and maximum annual power generation as objectives. Our study is based on a Concentrating Solar Power (CSP) plant of capacity of 50 MW to be erected in Hassi R'mel City, in the south of Algeria. In this methodology, the size of the solar field, the fossil fill fraction of backup system and full load hours of storage are optimized for the minimum LCOE using the concept of solar multiple. Moreover, different models, technologies and scenarios for parabolic trough and central tower receiver power plant are presented. LCOE presents a basis of comparison for weighted average costs of different power generation technologies. It is clearly shown that the solar power plant based on central receiver tower technology with 48% of backup system and 8 h of storage is the most attractive and optimum plant. It was also found from financial analysis that the LCOE can decreases by 13% with less interest rate and tax deductions. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Electricity cost Parabolic trough Solar tower Solar multiple Thermal energy storage
1. Introduction It is obvious that energy is the major concern of the 21st century. In order to meet the world energy demand and reduces the effects of fossil fuels, renewable energies are becoming more and more interesting. Indeed, electricity generation from solar energy is currently one of the main research areas in the field of renewable energy. In a country such as Algeria, where this source of energy is abundant, it is possible that fossil fuels that generate electricity can be replaced by solar energy. From all solar technologies available for power generation up to now, Concentrating Solar Power (CSP) technologies are now the most competitive commercial solar options for large scale power plants as well as for smaller electricity and heat generating systems. CSP plant has an inherent capacity to store heat energy for short periods of time for later conversion to
* Corresponding author. Research Unit of Materials and Renewable Energies (URMER), Abou Bakr Belkaid University, Tlemcen, Algeria. Tel.: þ213 777896036. E-mail address: mihoubsofi
[email protected] (S. Mihoub). http://dx.doi.org/10.1016/j.energy.2016.12.056 0360-5442/© 2016 Elsevier Ltd. All rights reserved.
electricity. When combined with thermal storage capacity, CSP plants can continue to produce electricity even when clouds block the sun or after sundown. CSP plants must also be equipped with backup systems based on combustible fuels [1,2]. With these factors, CSP is set to take its place as an important part of the world's energy mix. The preferred choice for current CSP plants is based on large scale power generation units (often in the range of 20e50 MW) mainly due to their higher conversion efficiency and lower specific capital costs. However, the construction of large-size CSP units requires the availability of large areas and noteworthy capital investments (a typical 50 MWe CSP plant requires a total capital investment of about 250e300 MV and the availability of about 150e250 ha of land) [3]. Among the CSP technologies, plants based on parabolic trough collector (PTC), using synthetic or organic oil as heat transfer fluid (HTF), are found to be more attractive commercially [4,5]. In such plants, the maximum temperature can be reached to 400 C and it can be raised up to 540 C by using molten salt as a HTF, which allowing steam turbines to operate at much greater efficiency [6e9]. The direct steam generation (DSG) in plants with PTC field is
802
S. Mihoub et al. / Energy 122 (2017) 801e810
Nomenclature I0 At Mt,el i n t CAfter Tax N dnominal
Investment expenditures Annual total costs in year t Produced quantity of electricity in the respective year in kWh Real interest rate in % Economic operational lifetime in years Year of lifetime (1, 2, … n) After tax cash flow in Year n Analysis period in years Nominal discount rates
Abbreviations LCOE Levelized Cost Of Energy CSP Concentrating Solar Power SAM System Advisor Model DSG Direct Steam Generation NREL National Renewable Energy Laboratory CTRSTPP Central Tower Receiver Solar Thermal Power Plant SPT Solar Power Tower PTCSTPP Parabolic Trough Concentrating Solar Thermal Power Plant
also an economically viable option [10e16]. Several studies have been carried out to evaluate the performance of PTC technology for power generation [12,17e21]. Solar power tower (SPT) is the second most installed CSP plant technology after PTC, and gradually gaining acceptance [22,23]. Now, some commercial SPT plants are in operation using DSG option [24], and other plants use molten salts as HTF as well as storage medium [25,26]. Behar et al. [27] as well as Ho et Iverson [28], respectively, have presented a review on design of central receiver and SPT system. Detailed studies on economic aspects of CSP plants have been reported by Feldhoff JF et al. [12], Krishnamurthy et al. [29], and Kost et al. [30]. Feldhoff JF et al. [12], carried out a comparison in terms of techno-economic potential of two references PTC plants (the first one with DSG mode and the other with synthetic oil) of capacity 100 MWe with integrated thermal storage. The study tells that the LCOE of DSG mode is much higher compared to that of synthetic oil based plant integrated with storage system. Furthermore, it was found that there are a few comparative studies between PTC and SPT. Franchini et al. [31], have presented the comparative analysis between two CSP plants, using PTC and SPT technologies. Currently, for the case of Algeria, just five studies have been carried out to evaluate the performances of CSP plants, three of them for PTC plants and two others for SPT plants. Boukelia et al., have presented two studies; the first one based on the optimization of two parabolic trough solar thermal power plants integrated with thermal energy storage (TES), and fuel backup system (FBS). The first plant is using Therminol VP-1 as HTF in the solar field while the second plant based on molten salt [32]. Then, the second study is performed a thermodynamic, economic and environmental analyses of concentrating solar power plants which assist in identifying the most effective and viable configuration. The results of this study show that Tamanrasset is the best location for erection of a parabolic trough solar thermal power plant with a low LCOE of 7.55 ￠/kW h, and a high annual power generation (more than 266 GW h) [33]. Finally, the last study for PTC has been published by Ameur et al., with the scope of determining an optimum design for
DLR German Aerospace Centre DNI Direct Normal Irradiation TMY Typical Meteorological Year HTF Heat Transfer Fluid TES Thermal Energy Storage NPV Net Present Value IR Inflation Rate TIC Total Installed Cost IRR Internal Rate of Return RES Renewable Energies FNERC National Fund of Renewable Energy and Cogeneration SM Solar Multiple FFF Fossil Fill Fraction CF Capacity Factor FLH Full Load Hours PTC Parabolic Trough Collector SCA Solar Collector Assembly HCE Heat Collector Element SONELGAZ Company of Electricity and gas (Algeria) BS Backup System HSS Hitec Solar Salt
a projected parabolic trough solar power plant (PTSPP) under Algerian climate through different funding scenarios [34]. For SPT technology, Boudaoud et al., have presented a technoeconomic analysis for the implementation of a probable molten salt cavity receiver thermal power plant in Algeria. The System Advisor Model (SAM) has been used to perform the technical performance and the economic assessment for different locations in Algeria. The analysis has shown that hybrid central receiver systems are really attractive solutions for rapid deployment of CSP technology in Algeria [35]. Benammar et al., have developed a mathematical model based on energy analysis for modeling and simulation of SPT plants performances without energy storage. The analysis of the results shows the existence of an optimal receiver efficiency value for each steam mass flow, receiver surface temperature and receiver surface area [36]. Now, there is no comparative study between different CSP technologies, destined for Algerian climate. For this reason and for limited studies represented previously, our study involves estimation of annual electricity output, levelized cost of electricity and capacity factor for different likely combinations of the values of solar multiple, full load hours and fossil fill fraction for plant models. Different scenarios have been simulated using SAM software [37], in order to determine the best configuration and optimum design of a PTC and SPT solar thermal power plant in Algeria with minimum cost of electricity and maximum annual energy to the end user for 50 MW of installed capacity. Finally, a financial analysis has been presented with new scenario concerning loan and taxes. 1.1. New RE program 2015 For the case of Algeria, it has been announced in the renewable energy and energy efficiency program a new motivated CSP projects. In this ambitious program, CSP plants represent about 70% of the total power projects to be installed [38,39]. Moreover CSP can be a competitive source of bulk power in peak and inter mediate loads in the sunniest regions by 2020, and of base load power by 2025e2030 [40].
S. Mihoub et al. / Energy 122 (2017) 801e810
According to the Renewable Energy (RE) program that has been announced in 2011, a total capacity of 22,000 MW will be implanted between 2011 and 2030, of which 12,000 MW will be intended to meet the domestic electricity demand and 10,000 MW destined for export [41]. The national development program for renewable energy in the latest edition updated by the services of the Department of Energy has just been adopted by the government. Indeed, the integration of renewable energy in the national energy mix is the major challenge in view of preservation of fossil resources, diversification of production chains electricity and contribution to sustainable development. Renewable energies are at the heart of the 2011e2030 energy development program adopted by the Government in 2015. The program includes development of photovoltaic and wind energy, the use of waste biomass, cogeneration, and geothermal. It also postpones solar thermal (CSP) to 2021. To meet national market need over the 2015e2030 period 22000 MW is required, of which 2000 MW is to come from solar thermal, and it is to be expanded to be more than 4500 MW by 2030. 1.2. New policy and incentives The implementation of this program benefits from substantial and multifaceted contributions of the State intervening mainly through the National Fund for Renewable Energy and Cogeneration (FNERC), supplied by a levy of 1% of oil royalties [41,42]. An incentive mechanism based on feed-in tariffs is established by regulation. Thus, the producer of renewable energy enjoys purchasing tariffs which are guaranteed for a period of 20 years for photovoltaic installations and wind power. The sectors not covered by the guaranteed purchase price will be financed by FNERC for 50%e90% of the investment cost according to the selected technology and industry [41,42].
803
to better fit with HTF, thermal energy storage system, and parameters of solar field, storage and power block. Then, to provide the required heat storage capacity, the solar field (i.e. mirrors and heat collectors) of the CSP plant must be oversized with respect to the nominal electric capacity (MW) of the plant. Thus, from a technical point of view, design requirements are the SM factor, FFF of BS, CF (efficiency), and storage system capacity (FLH). The solar multiple (SM) is the ratio of the actual size of the solar field to the solar field size needed to feed the turbine at nominal design capacity with maximum solar irradiance (about 1 kW/ m2) [2]. The capacity factor is the ratio of the system's predicted electrical output in the first year of operation to the nameplate output, which is equivalent to the quantity of energy the system would generate if it operated at its nameplate capacity for every hour of the year. Full Load Hours is the number of hours that the storage system can supply energy at the power block design turbine input capacity Fossil Fill Fraction is a fraction of the power block design turbine gross output that can be met by the backup boiler. It used to calculate the energy from the backup boiler.
2. Methodology 2.1. Off-design model description In this work, the selected location for performing the study is Hassi R'mel in the south of Algeria; weather data of this location, such as DNI and ambient temperature are taken from NREL database; an hourly timeframe is selected due to TMY3 standard format. Table 2 shows the parameters of our site.
1.3. Evolution of electricity demand in Algeria According to the company of electricity in Algeria (SONELGAZ), the demand of electricity increases rapidly during the period of 2004e2014. This demand is given in Table 1: 1.4. Solar potential in Algeria According to study of the German Aerospace Centre (DLR), Algeria has with 1,787,000 km2 of Sahara desert, the largest long term land potential for concentrating solar thermal power plants. The insolation time over the quasi-totality of the national territory exceeds 2000 h annually and may reach 3900 h (high plains and Sahara) [43]. The daily obtained energy on a horizontal surface of 1 m2 is of 5 kWh over the major part of the national territory, or about 1700 kWh/(m2 y) for the North and 2263 kWh/(m2 y) for the South of the country [44].
2.2. Mathematical models 2.2.1. Levelized cost of electricity The method of LCOE makes it possible to compare power plants of different generation and cost structures with each other. The basic thought is that one forms the sum of all accumulated costs for building and operating a plant and comparing this figure to the sum of the annual power generation. The calculation of the average LCOE is done on the basis of the net present value method, in which the expenses of investment and the payment streams from earnings and expenditures during the plant's lifetime are calculated based on discounting from a shared reference date [46]. For calculating the LCOE for new plants, the following applies [47]:
P I0 þ nt¼1 At t ð1þiÞ LCOE ¼ P Mt;el n
(1)
t¼1 ð1þiÞt
1.5. Design parameters Where: 1.5.1. Solar field sizing and design requirements The components of CSP plants should have an optimized design Table 1 Growth of electricity demand in Algeria (2004e2014) [42]. GWh
2004
2014
Share (%)- (2004_2014)
High Voltage Medium Voltage Low Voltage Total (GWh)
5401 7996 12513 25910
9167 13253 26572 48992
5.4 5.2 7.8 6.6
Table 2 Hassi R'mel location Parameters [45]. Parameters
Values
Latitude (Degree) Longitude (Degree) Altitude (m) Climate Direct Normal Irradiation (DNI) kWh/(m2 y)
33.8 3E 776 Tropical 2008.4
804
S. Mihoub et al. / Energy 122 (2017) 801e810
Annual total costs At¼ Fixed operating costs þ Variable operating costs (þresidual value/disposal of the plant)
2.2.2. Net present value (NPV) A project's net present value is a measure of a project's economic feasibility that includes both revenue and cost. The NPV is the present value of the after tax cash flow discounted to year one using the nominal discount rate [48]:
NPV ¼
XN n¼0 ð1
CAftertax;n
(2)
þ dnominal Þn
2.2.3. Internal rate of return The internal rate of return is the nominal discount rate that corresponds to a net present value of zero for projects
NPV ¼
XN
CAftertax;n n¼0 ð1 þ IRRÞn
¼0
(3)
2.3. Plants optimization (configurations, technologies, models and scenarios) The optimization method used in simulation that is integrated in SAM software. Different configurations have been chosen for all plants based on HTF type (Synthetic Oil, molten salt), and condenser type (wet cooling: evaporative, dry cooling: air cooled), receiver type (external, cavity), in order to determine the best configuration, for different models: Model 1 (M1): solar field only (without storage and without backup system). Model 2 (M2): integration of backup system (without storage). Model 3 (M3): integration of solar thermal storage STE (without backup system). Model 4 (M4): integration of backup system and STE. Table 3 shows these configurations and scenarios:
Table 4 Fixed financing parameters (base case) [49]. Financing data
value
unit
Base Case Analysis Period Loan Term Loan Rate Inflation Rate Real Discount Rate Nominal Discount Rate Minimum Required IRR Assessed Percent Insurance Rate Sales Tax State Income Tax Rate
30 20 8 8.9 4 13.26 12 80 0.30 5 15
years years %/y %/y in 2013 %/y in 2013 %/y % % of installed cost % of installed cost % of installed cost %/y
2.4.2. Case study The role of financial analysis and incentive is to determine the different costs and taxes introduced in the implementation of plant, and to evaluate the effect of these factors on LCOE for the optimum plant. In this study, we proposed an incentive scenario in order to encourage the government to provide a reduced income tax for the whole lifetime of the plant. The other financial variables will remain the same as in the base case. 3. Results and discussion In these sections, and using the input parameters of Tables 4 and 6, sensitivity analyses of CF, LCOE, annual energy delivered from plants with and without storage and BS system for capacity of 50 MW with different configurations and scenarios of Table 3 have been optimized by changing SM, FFF of BS and FLH of STE. The simulation was done with a project's lifetime of 30 year, as estimated by many studies [50,51]. Moreover, an inflation rate of 8,9% per year was used in the economic calculations and with no incentives provided by the government (base case). In addition, the process for defining the system design follows the general procedure: first define the fixed design-point parameters, then fixe design gross output, finally parametrically optimize the solar multiple. Table 6 shows an overview of the technical data used in the simulation.
2.4. Financial scenarios
3.1. Sensitivity analysis of collector‘s and receiver's geometry
2.4.1. Base case The base case scenario represents the anticipated financial terms for the investment in normal conditions with no incentives provided by the government. In all models, plants have been simulated by base case financial scenario, and the fixed financing parameters for base case scenario used in the simulation are given in Table 4.
Unlike parabolic system designs, which are based on modular designs of individual components, the central tower receiver system designs require optimization of the tower height, receiver and heliostat geometry. The heliostat field of a SPT plant counts for roughly 50% of the investment costs. As a result, it is important to press on reducing the cost of heliostats as far as accomplishable in order to improve and strengthen the economic viability of the solar power tower technology [52]. Moreover, maintenance costs are higher for a heliostat field with small heliostats because of the far greater number of control systems required compared to a heliostat field of the same size with large heliostats [53]. So it's necessary to optimize the size of heliostat, to reduce investments and maintenance costs of CTRSTPP system.
Table 3 Technologies, configurations and scenarios of the proposed models. CSP plants
Technologies options and configuration
PTCSTPP
T1:Terminal VP-1 oil as HTF
CTRSTPP
scenarios
S1: Wet cooling technology T2: Molten salt as HTF S2: Dry cooling technology T1: Molten salt as HTF and external S1: Wet cooling receiver technology T2: Molten salt as HTF and cavity receiver S2: Dry cooling technology
Table 5 Incentive scenario financing parameters. Loan Rate(%/y)
6
State Income Tax Rate (%/y)
7
S. Mihoub et al. / Energy 122 (2017) 801e810 Table 6 Simulation data. Technical data
Value
1-CTRSTPP a-Heliostat properties Image Error (rad) Heliostat availability Mirror reflectance b- Mirror Washing Water Usage per Wash (L/m2) Washes per Year 2-PTCSTPP: EUROTROUGH a-Solar Field Parameters: Row Spacing (m) Stow Angle (deg) b-Collector Geometry Reflective Aperture Area (m2) Aperture Width (m) Length of Collector Assembly (m) Number of Modules per Assembly Mirror reflectance Washes per Year Water usage per wash (L/m2),aperture c-Receiver: Schott PTR70 Absorber Tube Inner Diameter (m) Absorber Tube Outer Diameter (m) Glass Envelope Inner Diameter (m) Glass Envelope Outer Diameter (m) 3-Thermal Energy Storage (TES) Tank height (m) Tank heater capacity (MWt) Tank heater efficiency
0.00153 0.99 0.9 0.7 63
15 170 817.5 5.75 150 12 0.935 63 0.7 0.066 0.07 0.109 0.115 20 30 0.98
Based on these assumptions, the optimal geometries of collector and receiver have been determined for CTRSTPP, but for PTCSTPP, the simulation has been done with Euro trough collector's geometry and Schott PTR70 receiver's geometry which is illustrated in Table 6. Table 7 shows the effect of heliostat's size on LCOE with different values of SM for different technologies and scenarios. The shape of heliostat chosen is rectangular due to its maximum ground coverage of 58% than other shapes. Then a span angle equal to 120 is chosen for cavity receiver and 360 for external receiver. In addition, the optimal distribution of heliostats is done by optimal technology (optimization wizard) used in SAM software, and heliostat's width and height are simulated for range from 10 to 20 m. The results show that LCOE decreases when heliostat field (SM) and length of heliostat increase because the energy produced increases due to the big amount of flux reflected on receiver, and it is clear that increasing SM beyond two is only marginally beneficial The optimal SM is 1.6 for all technologies and scenarios corresponding to heliostat width and height of 15 m and 13 m respectively. Finally, the optimal plant with optimal system designs and LCOE is T2-S1 (cavity receiver and wet cooling technology). 3.2. Model 1: solar only system (no storage and no backup system) Using the optimum parameters of section 3.1 for different plants, effect of solar field (SM) on CF, and LCOE have been Table 7 The optimum geometry of Heliostat for CTRSTPP: T: Technology and S: Scenario (see Table 3). Heliostat's geometry
T1-S1
T1-S2
T2-S1
T2-S2
Heightopt (m) LCOEopt (¢/kWh) Widthopt (m) LCOEopt (¢/kWh)
14 39.08 15 38.83
13 38.36 15 38.36
13 38.05 15 37.89
13 40.60 15 40.48
805
simulated for solar only system i.e without storage and without backup system, and for different technologies and scenarios. Then the optimum configurations have been obtained and given in Table 8, for each plant with low LCOE and optimal SM. Figs. 1 and 2 show these effects for PTCSTPP, CTRSTPP respectively. From these figures, it is clear that LCOE decreases with increasing SM until optimal value is attained which when net electricity generated is higher than life cycle cost, beyond this value LCOE increases due to high an investment and maintenance costs of large solar field plant. Concerning efficiency, it increases with increasing SM according to high thermal energy dumping from large solar field. Table 7 shows the optimum configurations and it can be seen that wet cooling is the better solution to both plant than dry cooling, and both plants have same optimum SM and HTF which is molten salt, but annual energy produced by solar field of CTRSTPP was higher than PTCSTPP by 12 GWh per year. In next steps, all simulations have been done with an optimum configurations obtained in Model 1. 3.3. Model 2: solar field and backup system (no storage) In this section, we have determined the effect of BS on performances of optimum plants of Model 1 for different values of FFF that vary from 0.1 to 0.8. From Table 9, it can be seen that the effect of BS began seen beyond FFF ¼ 0.3 for both plants. Moreover, LCOE decreases when increasing FFF, due to enough thermal energy produced, but it increases with increasing SM. Then, CF and annual energy output increase with FFF which confirms the benefit of backup system. In the solar only (model 1), the energy conversion efficiency and solar field are lower than in the case of BS (model 2). The need to develop more suitable components, such as turbines and heat exchangers, is necessary in order to increase the competitiveness of solar only mode. We get an optimum FFF and SM for each plant, which are illustrated in Table 12. For the same SM of model 1, the integration of BS leads to an increase of annual energy of 47% for PTCSTPP and 42% for CTRSTPP, which can be used in other applications as: cooling, heating, etc. 3.4. Model 3: solar field and storage (no backup system) Solar thermal power faces many economic and technical hurdles, which must be overcome to be truly competitive with fossil fuel energy. Thermal energy storage allows these systems to overcome many of the problems associated with solar power intermittency. Advanced control and optimization techniques are still needed to help these plants operate more efficiently, thereby making them more technically and economically viable [54]. Using optimum plants of Model 1, this section makes a sensitivity analysis of SM and FLH on LCOE and efficiency. For PTCSTPP, we have used two storage HTF fluids namely Hitec Solar Salt (HSS) and Therminol VP-1. Concerning CTRSTPP, two kinds of storage which are two tanks and thermocline were used, and both plants were simulated with Generic Summer Peak Thermal Storage Dispatch Schedule, and the storage dispatch and FFF for different period of the day and the year were introduced according to Table 10.
Table 8 Optimum configurations of M1. Plant
Technologies and scenarios
SMOpt
PTCSTPP CTRSTPP
T2-S1 T2-S1
1.6 1.6
806
S. Mihoub et al. / Energy 122 (2017) 801e810 28 47
Capacity Factor(%)
26
LCOE (¢/kWh)
45 43 41 39 37
24 22 20 18 16 14 12
35 1
1.3
1.6
1.9
2.2
2.5
1
2.8
1.2
1.4
1.6
1.8
T1-S1
T1-S2
2
2.2
2.4
2.6
2.8
3
SM
SM
T2-S1
T2-S2
T1-S1
T1-S2
T2-S1
T2-S2
Fig. 1. Effect of SM on LCOE and CF of M1 for PTCSTPP.
LCOE (¢/kWh)
Capacity Factor (%)
29 27 25 23 21 19 17 1
1.3
1.6
1.9
2.2
2.5
2.8
1
1.3
1.6
SM
1.9
2.2
2.5
2.8
SM
T2-S1
T2-S1 Fig. 2. Effect of SM on LCOE and CF of M1 for CTRSTPP.
Table 9 Optimum performances of M2. FFF (%)
FFF FFF FFF FFF FFF FFF FFF FFF
¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼
0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8
CTRSTPP
PTCSTPP
SMopt
LCOE (¢/kWh)
CF (%)
Annual Energy (GWh/y)
SMopt
LCOE (¢/kWh)
CF (%)
Annual Energy (GWh/y)
1.6 1.6 1.3 1 1 1 1 1
38.99 38.55 20.15 17.28 14.58 12.67 10.52 9.76
24.72 25.01 43.61 46.18 54.51 63 72.31 81.4
107.24 108.46 189.14 200.28 236.39 273.20 309.66 353
1.7 1.7 1.5 1.5 1.5 1.5 1.5 1.5
30.98 30.98 24.67 22.91 21.32 19.88 18.60 17.45
23.13 23.13 27.22 29.32 31.5 33.78 36.10 38.49
100.32 100.32 118 127.13 136.61 146.46 156.55 166.89
Table 11 shows that LCOE decreases with increasing FLH, but SMopt increases until value of 3.1 and 2.8 for PTCSTPP and CTRSTPP respectively. Beyond these values, LCOE starts to increase. This means that the solar field area increased with increasing storage capacity in order to capture enough energy for the TES system. Moreover efficiency of plant increases with an increase in SM and FLH with respect to high thermal energy produced with large solar field. The optimum configurations for this model are: 1 For CTRSTPP, the optimum configuration of Model 1 with two tank storage technology. 2 For PTCSTPP, the optimum configuration of Model 1 with Therminol VP-1 storage fluid.
The optimum parameters (SM, FLH) of each configuration are summarized and given in Table 12. 3.5. Model 4: solar field with storage and backup system In the last step, we have determined the interest of STE and BS for CTRSTPP and PTCSTPP on LCOE and CF. The optimum configurations of Model 3 were used for storage, and FFF of BS have been optimized for different values of SM and FLH. Moreover the storage dispatch and optimum FFF for different period of the day and the year were introduced according to Table 10. The variation of LCOE and CF with SM, FLH for optimum FFF were computed and it was found that the optimum FLH did not change and was equal to that of Model 3, SM remained also in the same as Model 1, but FFF increases which demonstrate the benefit of BS.
S. Mihoub et al. / Energy 122 (2017) 801e810
807
Table 10 Storage and FFF dispatch for different period of the day and the year (X represents the optimum value of FFF; A value of zero will always dispatch the TES in any hour assigned to the given dispatch period; a value of one will never dispatch the TES). Dispatch Period
1 2 3 4 5 6
STE
STE þ Hybrid
Hybrid
With Solar
W/Out Solar
FFF
FLH
FFF
With Solar
W/Out Solar
FFF
0 0 0 0 0 1
1 0 0 0 0 0
0 0 0 0 0 0
0 0 0 0 0 0
O X X X X X
0 0 0 0 0 1
1 1 0 1 0 0
0 X X X X 0
Table 11 Optimum performances of M3. FLH (h)
PTCSTPP
CTRSTPP
Storage fluid: VP-1
FLH FLH FLH FLH FLH FLH FLH FLH
¼ ¼ ¼ ¼ ¼ ¼ ¼ ¼
2 4 4.5 6 7.5 8 10 12
Storage fluid: Molten Salt
Two Tank Storage
Thermocline Storage
SMopt
LCOE (¢/kWh)
CF (%)
SMopt
LCOE (¢/kWh)
CF (%)
SMopt
LCOE (¢/kWh)
CF (%)
SMopt
LCOE (¢/kWh)
CF (%)
1.9 2.2 2.5 2.8 3.1 3.1 3.1 3.1
34.49 34.25 34.14 34.09 34.49 34.55 34.94 35.52
27.62 32.49 35.49 39.67 43.30 43.79 45.49 46.90
1.9 2.2 2.5 2.8 3.1 3.1 3.1 3.1
34.54 34.52 34.50 34.55 34.79 34.87 35.34 36.08
27.59 32.24 35.11 39.14 42.93 43.38 44.97 46.18
1.8 2 2.2 2.4 2.4 2.4 2.6 2.8
34.24 31.88 31.47 30.23 29.36 29.17 28.62 28.01
30.62 35.40 37.74 42.03 43.90 44.40 48.32 52.36
1.8 2 2 2.4 2.4 2.4 2.6 2.8
35.08 32.77 32.22 31.39 30.48 30.21 29.63 28.96
29.89 34.34 35.12 40.48 42.29 42.87 46.58 50.64
Table 12 The optimal results of different configurations for both plants. CTRSTPP M2
M3
M4
M1
M2
M3
M4
1.6 e e 37.9 25.92 109
1.3 e 0.3 20.15 43.61 188
2.2 8 e 29.88 41.17 172
1.6 8 0.48 23.57 45 193
1.6 e e 35.82 22.25 97
1.5 e 0.3 24.67 27.22 183.5
2.8 8 e 34.43 41.5 180
1.5 8 0.55 24.12 44.38 192
From Fig. 3, LCOE decreases with FFF and increases with SM, and shows the benefit of BS that is maximum at FFF ¼ 0.6. The optimum parameters of optimum configurations for all plants are given in Table 12. From Table 12, it can be seen that: 1 the storage requires large solar field (M3) 2 The benefits of BS can be seen in small solar field, with reduction in LCOE and increasing of CF. 3 The integration of storage and BS (M4) increases CF with small solar field compared to M1 and M3.
28 27 26
LCOE (¢/kWh)
SMopt FLHopt (h) FFFopt (%) LCOE (¢/kWh) CF (%) Annual Energy (GWh/y)
PTCSTPP
M1
25 24 23 22 21 20 19 2
4
6
3.6. Economic and financial analysis Levelized cost of electricity presents a basis of comparison for weighted average costs of different power generation technologies. In addition, this concept allows the accurate comparison of different technologies. Based on this and simulation results presented above, two optimum plants are selected, which are: PTCSTPP: solar field with storage and backup system (M4). CTRSTPP: solar field with storage and backup system (M4).
8
10
12
FLH (h) FFF=0.4
FFF=0.45
FFF=0.48
FFF=0.5
FFF=0.6
Fig. 3. Optimization of FFF for CTRSTPP.
Sometimes LCOE became insufficient to make best comparison. So it's necessary to use other factors. For our study, we have used efficiency (CF), annual energy, and Total Installed Cost (TIC) as other factors, in order to compare
808
S. Mihoub et al. / Energy 122 (2017) 801e810
between these two optimum plants and select the best one for Algeria. From Table 13, it's clear found that: 1 for both plants, the solar field was the most expensive component, contributing between 28% and 52% of the TIC. It decreases in M2 and M4, and decreases also TIC of plants, which prove the benefit of BS in CSP plants. 2 The next largest component cost is the cost of storage for PTCSTPP and the cost of power block for CTRSTPP. The financial analysis is introduced here to encourage the Algerian government to use renewable energies in producing electricity. The proposed scenario is the reduction in income tax and the other financial variables (Table 5) will remain the same as in the base case. Table 14 shows that: 1 LCOE is very low in case study for both plants, which allows the Algerian government to provide help, reduced income tax for the whole lifetime of the plant, and encourages the investment in renewable energies. 2 For our proposed financial scenario, a reduction of 25% in loan rate and 53% in state income tax rate causes a reduction of 3 ¢/kWh in LCOE, which confirms the importance of tax in determining LCOE. Based on these results, CTRSTPP with 48% of backup system and 8 h of storage is the best and optimum solution under Algerian climates, with minimum LCOE and TIC, and maximum efficiency and annual energy output.
3.7. Comparison of LCOE of plants Based on simulation results represented above, we have compared our models to existing operating plants considering thermal storage and backup system with same capacity (see Table 15).
4. Conclusion In this study, we have presented a methodology for determination of optimum design and operation of CSP plants in Algeria, based on different technologies and scenarios, using the concept of solar multiple, solar thermal storage and backup system. SAM (System Advisor Model) is used to determine the optimum design parameters (SM, CF, Annual Energy, and TIC) of plants. From the results presented in this paper, we can conclude that:
Table 14 Financial results. CTRSTPP
LCOE (¢/kWh)
PTCSTPP
Base Case
Case Study
Base Case
Case Study
23.57
20.72
24.12
20.90
Table 15 Comparison of LCOE for the optimal models with plant's data.
PTCSTPP Our model Hernandez [55] Nishith [56] Ming Liu [57] CTRSTPP Our model Ming Liu [57]
LCOE (¢/kWh)
FLH (h)
CF (%)
20.90 25 19.9 22e34
8 7.5 e e
44 e e 40e53
20.72 20e29
8 6e7.5
45 40e45
(i) The solar field of central tower receiver plant design depends on geometry and cost of maintenance of collector and receiver, which are important to be optimized it in order to improve and strengthen the economic viability of the plants. The optimum width of heliostat is 15 m and heights are 14 m and 13 m for external and cavity receiver respectively (ii) The wet cooling is the best technology for both CSP plants under Algerian climates. (iii) The integration of backup system leads to an increase of annual energy of 47% for PTCSTPP and 42% for CTRSTPP than solar field only, which can allow the power block to operate at better part load conditions, and can used in other applications such as: production of heating, cooling. (iv) Levelized Cost Of Electricity become sometimes insufficient to take decision for comparing between solar technologies and it is necessary to use other factors such as efficiency of plant, annual energy output and total installed cost. (v) Central Tower Receiver Solar Plant with 48% of backup system and 8 h storage is the best and optimum solution under Algerian climates, with minimum LCOE and TIC, and maximum efficiency and annual energy output (23,57 ¢/kWh; 309 Mio$; 45% and 193 GWh/y). Parabolic Trough Solar Plant with 8 h of storage and 55% of backup system tend to perform slightly less than Central Tower Receiver Solar Plant (24,12 ¢/kWh; 312 Mio$; 44% and 192 GWh/y). Finally, the results of financial scenario studied in this paper can hopefully help Algerian government to decide on policies to adopt related to these technologies. It was proven that a reduction of taxes decreases levelized cost of electricity generated by CSP solar technologies.
Table 13 Economic results. CTRSTPP
Site Improvements (%) Solar field (%) HTF system (%) Power Plant (%) Balance of Plant (%) Storage (%) Indirect Cost (%) Total Installed Cost (Mio$)
PTCSTPP
M1
M2
M3
M4
M1
M2
M3
M4
2 47.3 e 25 7 e 18.5 274
1.8 44 e 28 8 e 18.2 243
2 47 e 18.4 5 8.2 19.2 370
1.8 42 e 22 6.5 9.66 18 309
4.8 43 13 21 3 e 15 215
4.7 42 12.5 22 3 e 15 204.2
4.1 37 11 10 1.3 21 15 437.5
3 28 8 14.6 1.9 30 15 312.4
S. Mihoub et al. / Energy 122 (2017) 801e810
Perspectives (future works) Based on results presented above, it was found that the wet cooling technology is the best solution to both plants in Algeria, but this technology requires more quantity of water, which increases the maintenance and operation cost, and the levelized cost of electricity. We propose the hybrid cooling technology (a wet cooling and dry cooling) as another solution for future work, which can be the best than wet cooling, because a wet-cooling system and drycooling share the heat rejection load, and decreases water requirement. Acknowledgements The authors are grateful to Dr Said N from CDER (centre de veloppement des Energies Renouvelables. Algeria) for his conde stant guidance and critical review in improving the manuscript. Appendix A. CSP technology Concentrating Solar Power plants use mirrors to concentrate sunlight onto a receiver, which collects and transfers the solar energy to a heat transfer fluid that can be used to supply heat for enduse applications or to generate electricity through conventional steam turbines. Large CSP plants can be equipped with a heat storage system to allow for heat supply or electricity generation at night or when the sky is cloudy [58]. Basically there are four CSP concepts namely: the solar tower (also called central receiver system), parabolic trough technology, dish stirling system, and Fresnel technology. Each concept has specific design, configuration of mirrors and receivers, heat transfer fluid used and whether or not heat storage is involved (see Fig. 4).
809
A.1. Parabolic trough system Parabolic Trough Concentrating Solar Thermal Power Plants (PTCSTPP) use parabolic trough collectors to concentrate the direct solar radiation onto a tubular receiver. Large collector fields supply the thermal energy, which is used to drive a steam turbine, which, on its part, drives the electric generator. Systems with light structures and low cost technology for process heat applications up to 400 C could be obtained with parabolic Trough Collectors (PTCs). PTCs can effectively produce heat at temperatures between 50 and 400 C [60]. The basic component of the solar field is the Solar Collector Assembly (SCA). Each SCA is an independently tracking parabolic trough solar collector made up of parabolic reflectors (mirrors), the metal support structure, the receiver tubes, and the tracking system that includes the drive, sensors, and controls. In addition, the Heat Collection Element (HCE) consists of an absorber surrounded by a glass envelope. The absorber is typically a stainless steel tube with a selective absorber surface which provides the required optical and radiative properties [61]. A recent development in cost effective concentrators is the design of the Euro Trough, a new parabolic trough concentrator, in which an advanced light weight structure is used to achieve costefficient solar power generation [62,63]. There are three types of collectors include: 1. Luz system 2. EuroTrough 3. Solargenix
A.2. Central tower receiver system: Central Tower Receiver Solar Thermal Power Plant (CTRSTPP), also known as solar power tower, uses a large amount of flat or slightly concave mirrors, which are sun tracking in two axes, so called heliostats, that concentrate the sunrays onto a central receiver mounted on the top of a fixed tower, where a thermal heating fluid is circulated which is being heated to a high temperature, then the solar heat drives a thermodynamic cycle and generates electricity. Different kind of thermal heating fluids are used in power tower system like water-steam (DSG), synthetic oil or molten salt. Molten nitrate (molten salt) is also the most common medium used in thermal heating storage that eliminates the need for a heat exchanger between the thermal heating fluid and the fluid used in the thermal storage [64]. In recent years, different CTRSTPP are under construction with larger capacity using molten salt as heat transfer fluid (HTF) and storage fluid. One of the largest CTRSTPP being developed right now is the Ivanpah project in the California Mojave desert in USA. Ivanpah consist of three power towers standing side by side and will be delivering 377 MW of electricity when it's finished [65]. References
Fig. 4. Flow diagram for typical Solar Thermal Power Plant [59].
[1] Smalley RE. Future global energy prosperity: the terawatt challenge. MRS Bull 2005;30:412e7. [2] International Energy Agency (IEA). Technology roadmap concentrating solar power. Paris, France: IEA/OECD; 2010. p. 1e52. [3] Daniele C, Fabio S. Performance comparison of two-tank direct and thermocline thermal energy storage systems for 1 MWe class concentrating solar power plants. Energy 2015;81:526e36. [4] Nishith BD, Shireesh BK, Santanu B. Optimization of design radiation for concentrating solar thermal power plants without storage. Sol Energy 2014;107:98e112. [5] Purohit I, Purohit P, Shekhar S. Evaluating the potential of concentrating solar power generation in Northwestern India. Energy Policy 2013;62:157e75. nchez M, Astrain D. Object-ori[6] Zaversky F, Medina R, García-Barberena J, Sa ented modeling for the transient performance simulation of parabolic trough collectors using molten salt as heat transfer fluid. Sol Energy 2013;95: 192e215. [7] Yang Z, Garimella SV. Cyclic operation of molten-salt thermal energy storage
810
S. Mihoub et al. / Energy 122 (2017) 801e810
in thermoclines for solar power plants. Appl Energy 2013;103:256e65. [8] Giostri A, Binotti M, Astolfi M, Silva P, Macchi E, Manzolini G. Comparison of different solar plants based on parabolic trough technology. Sol Energy 2012;86:1208e21. [9] Montes MJ, Abanades A, Martınez-Val JM. Thermofluidynamic model and comparative analysis of parabolic trough collectors using oil, water/steam, or molten salt as heat transfer fluids. J Sol Energy Eng 2010;132:0210011e7. ry V, Bezian JJ. Control systems for direct steam generation in [10] Antoine A, Vale linear concentrating solar power plants e a review. Renew Sustain Energy Rev 2016;56:611e30. [11] Hirsch T, Taylor P, Feldhoff JF, Hennecke K, Pitz-paal R. Advancements in the field of direct steam generation in linear solar concentrators e a review. Heat Transf Eng 2013:37e41. [12] Feldhoff JF, Schmitz K, Eck M, Schnatbaum-Laumann L, Laing D, Ortiz-Vives F, Schulte-Fischedick J. Comparative system analysis of direct steam generation and synthetic oil parabolic trough power plants with integrated thermal storage. Solar Energy 2012;86:520e30. [13] Eck M, HirschT. Dynamics and control of parabolic trough collector loops with direct steam generation. Sol Energy 2007;81:268e79. [14] Eck M, Steinmann WD. Modelling and design of direct solar steam generating collector fields. J Sol Energy Eng 2005;127:371e80. n J, Weyers HD, Eickhoff M, Eck M, et al. The DISS [15] Zarza E, Valenzuela L, Leo project: direct steam generation in parabolic trough systems operation and maintenance experience and update on project status. J Sol Energy Eng 2002;124(2):126e33. [16] Odeh SD, Morrison GL, Behnia M. Modeling of parabolic trough direct steam generation solar collectors. Sol Energy 1998;62:395e406. [17] Garcia IL, Alvarez JL, Blance D. Performance model for parabolic trough solar thermal power plants with thermal storage: comparison to operating plant data. Sol Energy 2011;85:2443e60. [18] Fichtner. Assessment of Technology Options for Development of Concentrating Power in South Africa. The world Bank & ESMAP. Available at: www. climateinvestmentfunds.org/cif/sites/climateinvestmentfunds.org/files/ Presentation%20%20WB%20(Eskom)%20Project%20-%202010_12_07%20.pdf [Accessed 13 April 2010]. [19] Montes MJ, Abanades A, Val Martinez, Valdes M. Solar multiple optimization for a solar-only thermal power plant, using oil as heat transfer fluid in the parabolic trough collectors. Sol Energy 2009;83:2165e76. [20] Patnode AM. Simulation and performance evaluation of parabolic trough solar power plants [Ph.D Thesis]. USA: University of Wisconsis; 2006. [21] Herrmann Ulf, Kelly Bruce, Price Henry. Two-tank molten salt storage for parabolic trough solar power plants. J Energy 2004;29:883e93. [22] Avila-Marin AL, Fernandez-Reche J, Tellez FM. Evaluation of the potential of central receiver solar power plants: configuration, optimization and trends. Appl Energy 2013;112:274e88. ve J, Cace res G. Concentrated solar power plants: [23] Zhang HL, Baeyens J, Degre review and design methodology. Renew Sustain Energy Rev 2013;22:466e81. [24] Muller-Steinhagen H, Trieb F. Concentrated solar power. Ingenia: Quarterly of the Royal Academy of Engineering; 2004. [25] Amadei CA, Allesina G, Tartarini P, Yuting W. Simulation of GEMASOLARbased solar tower plants for the Chinese energy market: influence of plant downsizing and location change. Renew Energy 2013;55:366e73. [26] Caceres G, Anrique N, Girard A, Degreve J, Baeyens J, Zhang HL. Performance of molten salt solar power towers in Chile. J Renew Sustain Energy 2013;5: 0531421e5. [27] Behar O, Khellaf A, Mohammedi K. A review of studies on central receiver solar thermal power plants. Renew Sustain Energy Rev 2013;23:12e39. [28] Ho CK, Iverson BD. Review of high-temperature central receiver designs for concentrating solar power. Renew Sustain Energy Rev 2014;29:835e46. [29] Krishnamurthy P, Mishra S, Banerjee R. An analysis of costs of parabolic trough technology in India. Energy Policy 2012;48:407e19. [30] Kost C, Flath CM, Most D. Concentrating solar power plant investment and operation decisions under different price and support mechanisms. Energy Policy 2013;61:238e48. [31] Franchini G, Perdichizzi A, Ravelli S, Barigozzi G. A comparative study between parabolic trough and solar tower technologies in Solar Rankine Cycle and Integrated Solar Combined Cycle plants. Sol Energy 2013;98:302e14. [32] Boukelia TE, Mecibah MS, Kumar BN, Reddy KS. Optimization, selection and feasibility study of solar parabolic trough power plants for Algerian conditions. Energy Convers Manag 2015;101:450e9. [33] Boukelia TE, Mecibah MS, Kumar BN, Reddy KS. Investigation of solar parabolic trough power plants with and without integrated TES (thermal energy storage) and FBS (fuel backup system) using thermic oil and solar salt. Energy 2015;88:292e303. [34] Ameur T, Mohand AA-A. Determination of the optimum design through different funding scenarios for future parabolic trough solar power plant in Algeria. Energy Convers Manag 2016;91:267e79. [35] Boudaoud S, Khellaf A, Mohammedi K, Behar O. Thermal performance prediction and sensitivity analysis for future deployment of molten salt cavity receiver solar power plants in Algeria. Energy Convers Manag 2015;89:
655e64. [36] Benammar S, Khellaf A, Mohammedi KA. Contribution to the modeling and simulation of solar power tower plants using energy analysis. Energy Convers Manag 2014;78:923e30. [37] System Advisor Model (SAM) version 2013.1.15. https://sam.nrel.gov. [38] Renewable energy policy network for the 21stcentury (REN21). Renewable 2012. 2012. Global status report. [Online]. Available: http://www.map.ren21. net/GSR/GSR2012_low.pdfS. [39] Abbas M, Kasbadji Merzouk N. Techno economic study of solar thermal power plants for centralized electricity generation in Algeria. In: Proc. 2012, 2nd international symposium on environment-friendly energies and applications EFEA2012; 2012. p. 179e83. [40] Ministry of Energy and Mines, Renewable energy and energy efficiency program 2011. [Online]. Available: www.mem-algeria.org. rienne de l’e nergie N 4, [41] Ministry of energy Algeria (2015, May.). Revue alge ISSN : 2437e0479. [Online]. Available: www.mem-algeria.org. rienne de l’e nergie N 2, [42] Ministry of energy Algeria (2015, Feb.). Revue alge [Online]. Available: www.mem-algeria.org. [43] Stambouli AB. Promotion of renewable energies in Algeria. Renew Sustain Energy Rev 2011;15:1169e81. veloppement des Energies Renouvelables) Algeria (2013, [44] CDER (Centre de De Jan), [Online]. Available: http://www.cder.dz./. [45] Zeroual B, Moummi A. Design of parabolic trough collector solar field for future solar thermal power plants in Algeria. In: Proc. 2012, 2nd international symposium on environment-friendly energies and applications EFEA2012; 2012. p. 168e72. [46] Kost Christoph. Levelized cost of electricity, renewable energy technologies, ; fraunhofer institut for solar energy systems ISE. technical report. 2013. [47] Konstantin P, Energiewirtschaft Praxisbuch. Energieumwandlung, -transport und -beschaffung im liberalisierten Markt. Springer; 2009. [48] Short W. Manual for the economic evaluation of energy efficiency and renewable energy technologies. National Renewable Energy Laboratory; 1995. NREL/TP-462e5173, [Online]. Available: http://www.nrel.gov/docs/legosti/ old/5173.pdf. [49] OECD Development Centre. African Economic Outlook 2013, structural transformation and natural resources. 2013. http://dx.doi.org/10.1787/aeo2013-9-en. [50] Nezammahalleh H, Farhadi F, Tanhaemami M. Conceptual design and technoeconomic assessment of integrated solar combined cycle system with DSG technology. Sol Energy 2010;84:1696e705. [51] Caldes N, Varela M, Santamarıa M, Saez R. Economic impact of solar thermal electricity deployment in Spain. Energy Policy 2009;37:1628e36. [52] Kolb Greg. Heliostat cost reduction study. 2007, June [Online]. Available: http://prod.sandia.gov/techlib/accesscontrol.cgi/2007/073293.pdf. [53] Solar-Institut Jülich, D-52428, [Online].Available: www.sij.fh-aachen.de. [54] Powell Kody M, Edgar Thomas F. Modeling and control of a solar thermal power plant with thermal energy storage. Chem Eng Sci 2012;71:138e45. [55] Hernandez-Moro J, Martınez-Duart JM. Analytical model for solar PV and CSP electricity costs: present LCOE values and their future evolution. Renew Sustain Energy Rev 2013;20:119e32 [Online]. Available: http://dx.doi.org/10. 1016/j.rser.2012.11.082. [56] Desai Nishith B, Bandyopadhyay Santanu. Optimization of concentrating solar thermal power plant based on parabolic trough collector. J Clean Prod 2015;89:262e71 [Online].Available: http://dx.doi.org/10.1016/j.jclepro.2014. 10.097. [57] Liu Ming, Steven Tay NH, Bell Stuart, Belusko Martin, Jacob Rhys, Will Geoffrey, et al. Review on concentrating solar power plants and new developments in high temperature thermal energy storage technologies. Renew Sustain Energy Rev 2016;53:1411e32 [Online].Available: http://dx. doi.org/10.1016/j.rser.2015.09.026. [58] International Energy Agency (IEA). Concentrating solar power: technology brief. Paris, France: IEA/OECD; 2013. p. 1e32. [59] Eduardo ZMR. Alvarez; Concentrating solar thermal power plant, Handbook of Energy efficiency and renewable energy. SPAIN: Plataforma Solar de Almeria; 2016. p. 1e98 [Chapter 21]. [60] Soteris AK. Solar thermal collectors and applications. Prog Energy Combust Sci 2004;30:231e95. [61] Ghoneim A, Mohammedein M, Kandil Kandil M. Performance analysis of parabolic trough collector in hot climate. Br J Appl Sci Technol 2014;4(14): 2038e58. [62] Siva Reddy V, Kaushik SC, Ranjan KR, Tyagi SK. State-of-the art of solar thermal power plants-a review. Renew Sustain Energy Rev 2013;27:258e73. [63] Geyer M, Lupfert E, Osuna R, Zarza E, Nava P, Langenkamp J, et al. EUROTROUGHdparabolic trough collector developed for cost efficient solar power generation. In: Proc 2002, 11 th international symposium on concentrating solar power and chemical energy technologies, Zurich, Switzerland; 2002. [64] Technology characterization solar power towers. 2013, Oct [Online].Available: http://www.solarpaces.org/CSP_Technology/docs/solar_tower.pdf. [65] Ivanpah solar project. 2013, Oct [Online].Available: http://www. brightsourceenergy.com/ivanpahe-solare-project.
