Renewable and Sustainable Energy Reviews 42 (2015) 902–912

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Renewable and Sustainable Energy Reviews

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Assessment of solar thermal power generation potential in

Chandan Sharma, Ashish K. Sharma, Subhash C. Mullick, Tara C. Kandpal n

Centre for Energy Studies, Indian Institute of Technology , Hauz Khas, New Delhi 110016, India article info abstract

Article history: Realistic assessment of utilization potential of for thermal power generation and identification of Received 12 July 2014 niche areas/locations for this purpose is critically important for designing and implementing appropriate Received in revised form policies and promotional measures. This paper presents the results of a detailed analysis undertaken for 9 September 2014 estimating the potential of solar thermal power generation in India. A comprehensive framework is developed Accepted 20 October 2014 that takes into account (i) the availability of wastelands (ii) Direct Normal Irradiance (DNI) (iii) wastelands that are habitat to endangered species and/or tribal population and/or that is prone to earthquakes and (iv) Keywords: suitability of wasteland for wind power generation. Finally, using an approach developed for the allocation of Solar thermal power generation wastelands suitable for generation between thermal and photovoltaic routes, the potential of solar thermal power generation is assessed for two threshold values of DNI – 1800 kW h/m2 and 2000 kW h/m2. Potential Estimation for India With all the wastelands having wind speeds of 4 m/s or more allocated for wind power generation, the estimated potential for solar thermal power generation is 756 GW for a threshold DNI value of 1800 kW h/m2 and 229 GW for a threshold DNI value of 2000 kW h/m2. Results obtained can be used for identification of best suited areas for solar thermal power generation in India. & 2014 Published by Elsevier Ltd.

Contents

1. Introduction ...... 903 2. Review of CSP system requirements as reported in literature...... 903 2.1. Direct Normal Irradiance (DNI) ...... 903 2.2. Land requirement ...... 904 2.3. Water requirement ...... 904 2.4. Availability of transmission and supporting infrastructure ...... 905 2.5. Potential for auxiliary supply ...... 905 3. Methodology ...... 905 3.1. Identification of wastelands in the country ...... 905 3.1.1. Description of wastelands considered suitable for solar power generation ...... 905 3.2. Estimation of DNI and other climatic parameters for locations with wastelands...... 905 3.3. Identifying wastelands with acceptable annual value of DNI ...... 905 3.4. Accounting for the need to safeguard endangered species, wellbeing of tribal population etc...... 905 3.5. Accounting for potential of wind and PV power generation ...... 906 4. Results and discussion...... 906 4.1. Availability of wasteland (for a particular threshold value of DNI) ...... 907 4.2. Accounting for wasteland with large tribal population ...... 907 4.3. Accounting for wasteland with habitat of critically endangered species ...... 907 4.4. Excluding wasteland under seismic zone ...... 908 4.5. Exclusion of land with higher slopes ...... 908 4.6. Accounting for the land suitable for wind and PV power generation...... 908 4.7. Ground water availability in potential locations ...... 909 4.8. Potential for solar thermal power generation ...... 910 5. Concluding remarks...... 910

n Corresponding author. Tel.: þ91 11 26591262. E-mail address: [email protected] (T.C. Kandpal). http://dx.doi.org/10.1016/j.rser.2014.10.059 1364-0321/& 2014 Published by Elsevier Ltd. C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 903

Acknowledgment ...... 910 AppendixA...... 910 AppendixB...... 910 AppendixC...... 911 References...... 911

1. Introduction Results of a preliminary study towards identification of suitable areas for solar thermal power generation in India and estimation of To meet increasing global energy demand in an environmentally corresponding potential have been presented in this paper. Besides sustainable manner, greater emphasis is being given to the develop- the primary considerations of land and solar resource availability, an ment and dissemination of technologies. Solar attempt has also been made to consider (i) the availability restric- energy is an important renewable energy source that is expected to tions caused by the habitat of endangered species and tribal popula- play a significant role in the future energy supply mix [1–4]. tion on the identified wastelands, (ii) wastelands under seismic Concentrated Solar Power (CSP) technology is an important option zones, and (iii) the potential suitability of the same wasteland for for harnessing solar energy that has been receiving increasing atten- wind power generation. Finally the wastelands that can be allocated tion during past several decades [5–8]. Many CSP plants are opera- for solar power generation have been allocated between solar tional across the world and new plants are coming up. Currently four thermal power generation and photovoltaic generation on the basis candidate CSP technologies appear to have achieved reasonable level of the number of hours during the year the ambient temperature of of technological maturity [9,10]. These are parabolic trough, power the location exceeds a pre-defined value. tower, linear Fresnal reflector and parabolic dish. With the launch of the Jawaharlal Nehru (JNNSM) by the Govern- ment of India in January 2010, activities towards establishing CSP based solar thermal power generation in the country gathered 2. Review of CSP system requirements as reported in literature considerable momentum [11]. The mission aims to create an enabling policy framework for the deployment of 20,000 MW of solar power by 2.1. Direct Normal Irradiance (DNI) the year 2022 [12]. Such an initiative necessitates identification of areas suitable for CSP based solar electricity generation and also Unlike Solar photovoltaic systems that make use of direct as estimation of its overall potential. A detailed potential estimation for well as diffuse components of solar radiation, CSP systems can the whole country and identification of niche area shall be of great utilize only direct component with the need for high Direct fi help for the policy makers, researchers and project developers. Normal Irradiance for ef cient functioning. The locations having Efforts have been made towards assessing the potential of CSP high annual DNI availability are best suited for CSP installation. in some countries of the world. Trieb et al. [13] have estimated the Threshold values of annual DNI for solar thermal power generation potential of CSP on a global scale. They identified Africa, Australia, as suggested by some researchers are presented in Table 1.Asan China, South America, India and Middle East countries as potential areas for CSP installations. Breyer and Knies [14] commented that Table 1 CSP has immense potential to become a major source of global Threshold values of annual DNI suggested by some researchers. electricity supply and less than 3% of global CSP based energy Researcher (s) Threshold value of annual Reference supply potential can cater to the global electricity demand. Bravo DNI (kW h/m2/year) et al. [15] estimated the potential of renewable energy technolo- gies (including CSP) for Spain. Similarly potential assessment for Dawson and Schlyter, 2012 1800 [38] the state of Arizona in USA was carried out by Pletka et al. [16].In Breyer and Knies, 2009 2000 [14] Purohit and Purohit, 2010 1800 [32] the United States, potential assessment for other areas was under- Ummadisingu and Soni, 2011 2000 [9] taken by Dahle et al. [17], Karstaedt et al. [18], and Kirby et al. [19]. Similar attempts to estimate the potential of CSP in North Africa, South Africa, Serbia, Australia, Algeria, Brazil, Canada, China and Turkey have also been reported in the literature [20–30]. In context of India, while several researchers have made qualita- Table 2 tive statements regarding the potential of CSP [31–35], a recent study Reported land requirement for different CSP technologies.

[36] has presented quantitative estimates of CSP based power Technology Land requirement Remark Reference generation potential for northwestern India (the states of (m2/MW) and ). Though this study takes into account the availability of wastelands and solar resource, it does not consider the possibility of Parabolic trough 40,000 Including power block [39] 40,000 [32] wind power generation at some of the locations suitable for solar 25,505 Including power block [40] thermal power. Also distribution of wastelands between photovoltaic 20,000 [38] (PV) power and solar thermal power has not been considered in the 18,000 [41] study. Another recent study [37] presents district wise potential of Power tower 83,600 [39] CSP and solar PV in India using remotely sensed annual average GHI 50,000 1 h storage [41] 45,000 [41] and DNI values in Geographical Interface System (GIS) environment. Linear Fresnal 19,166 1 h storage [41] While this study considers all the categories of wastelands as suitable 34,000 Wet cooling [41] for solar power generation, it does not consider possibility of wind 25,555 1 h storage [41] power generation on the same wastelands and several other aspects Parabolic dish 16,000 [39] 40,460 [41] that may restrict the use of wastelands for solar thermal power 45,854 Closed loop cooling [41] generation. 904 C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 example, out of 23 solar thermal power plants of cumulative technologies as reported in the literature is given in Table 2. The installed capacity 1086 MW in Spain and USA, at most of the required land is expected to be available in abundance (and locations, the annual DNI is more than 2000 kW h/m2. Relevant perhaps at reasonable cost) in arid and semi-arid areas of the details of some of these plants are presented in Appendix A. country with high DNI.

2.2. Land requirement 2.3. Water requirement CSP plants require large areas of land for deployment of solar field, power block and storage component. Requirement of land Since majority of CSP plants operate on Rankine cycle, water may vary according to the CSP technology used and the extent of requirement for a solar thermal power plant is expected to be similar storage with the plant. The land requirement for various CSP to that of coal based power plants of equivalent capacities (adjusted for lower capacity credit of CSP systems). Of the total water

Table 3 requirement, 90% of water is for cooling and remaining 10% is for Water requirement for various CSP technologies. mirror washing and other purposes [38]. Availability of water could be a challenge in some of the arid areas and, if feasible, dry cooling Technology Water requirement Remark Reference technologies may have to be used at such locations with some (L/MWh) compromise on efficiency of power block. Water requirements as Parabolic trough 3000–3500 Wet cooling [38] 2900–3500 [39] Table 4 3270 [42] Wasteland categories considered suitable for solar thermal power generation. 3180 [43] 2900–3500 [32] Category Description Area (km2) 300 Dry cooling [44] Power tower 2300 Wet cooling [38] 1 Gullied and/or Ravinous land 6145 2800 [39] 3 Land with dense scrub 86,979 2240 [43] 4 Land with open scrub 93,033 Linear Fresnal reflector 4000–4500 Wet cooling [38] 17 Sands – desert sand 3934 2900–3500 [39] 19 Sands semi-stabilized to stabilized dome 15–40 m 14,273 2800 [32] Total 204,364

Fig. 1. Schematic representation of methodology adopted for estimation of potential of solar thermal power generation in India. C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 905 reported in the literature for various CSP technologies are presented 3.1.1.4. Sands – deserts sand. These wastelands are confined to arid in Table 3. environment where the rainfall is scanty. These lands are characterized by accumulation of sand developed in situ or 2.4. Availability of transmission and supporting infrastructure transported by Eolian processes. Out of total available wastelands in the country, this category of wastelands is approximately 1%. CSP systems would require appropriate transmission infrastruc- – ture for evacuation of electricity produced. During construction and 3.1.1.5. Sands semi-stabilized to stabilized dune. These are active subsequent operation of plants, suitable roads are required so that dunal areas with semi stabilised to shifting sands dunes that are heavy construction and maintenance machinery can reach the site. more than 40 m high. There shapes and sizes vary depending upon Remote locations having higher DNI may sometimes not be preferred the prevailing wind conditions. These wastelands rarely support due to non-availability of required infrastructure. any vegetation. They constitute 3.5% of total available wastelands. The above mentioned categories of wastelands cannot be used for agricultural purposes and are far away from habitat thus 2.5. Potential for auxiliary supply having little or no competition with industrial, commercial or residential requirements. Hence in the present analysis these Though CSP systems can be designed as standalone systems, in categories are assumed suitable for solar power generation. many situations, arrangement of an auxiliary back up may be necessary. Availability and cost of fuel used in the auxiliary system 3.2. Estimation of DNI and other climatic parameters for locations would also be considered in decision making in such cases. with wastelands

Direct Normal Irradiance (DNI) values were obtained for each 3. Methodology district headquarter (defined by their respective latitudes and longitudes). Two data sources were used: (i) website of NASA – fi Details of a methodology developed for identi cation of poten- SSE which is satellite based [46] and (ii) the website of the Solar tial areas for solar thermal power generation in presented Energy Centre (SEC) of the Ministry of New and Renewable Energy in the following paragraphs (Fig. 1). (MNRE), [47]. A brief summary of these solar radiation data sources is presented in Table 5. 3.1. Identification of wastelands in the country It is possible to retrieve DNI values for any desired location from these data sources, hence these were used in the present The Department of Land Resources, Ministry of Rural Develop- analysis. As an example, Table 6 presents wastelands, DNI values ment (Government of India) has identified 23 categories of waste- and other climatic conditions for various districts in the state of land across India in the Wasteland Atlas 2011 [45]. Wasteland Rajasthan. Similar exercise was carried out for each state of the categories considered as suitable in the present study for deploy- country. ment of solar thermal power plants and the corresponding areas are presented in Table 4. 3.3. Identifying wastelands with acceptable annual value of DNI

Two scenarios were considered for this purpose. The first one 3.1.1. Description of wastelands considered suitable for solar power considered locations having DNI more than 2000 kW h/m2/year generation while in the second scenario, locations having DNI more than In the present study, the following 5 categories out of a total of 1800 kW h/m2/year were considered. A review of the DNI values 23 different categories of wastelands are considered suitable for given by SEC, MNRE and NASA reveals that there is considerable solar power generation. variation in the two values with the NASA data giving higher values of DNI in most of the cases. The variation can be as high as 3.1.1.1. Gullied and/or Ravinous land. Gullies are tiny water 35%. To obtain conservative estimates of the solar thermal power channels with few centimetres of depth. These are formed as a generation potential, in the present analysis, DNI values given by result of heavy rainfall and wearing action of run-off generated as SEC, MNRE were used. the first stage of excessive land dissection. Ravines are extensive system of gullies developed along river courses. Approximately 3.4. Accounting for the need to safeguard endangered species, 1.5% of total available wasteland belongs to this category. wellbeing of tribal population etc.

3.1.1.2. Land with scrub – dense. These wastelands possess shallow For this purpose, districts having more than 50% of population fi soils. In this case, the soil may be chemically degraded, severely belonging to tribal category as speci ed by Ministry of Tribal eroded and may have excessive aridity with scrub dominating the Affairs, Government of India [48], were excluded from the waste- fi landscape. In dense scrub wastelands, vegetable cover is often lands identi ed in Section 3.3 above. Similarly, the locations with fi more than 15% and these are associated with moderate slopes in endangered species as speci ed by the Ministry of Environment plains and foothills and are generally surrounded by agricultural lands. These wastelands are approximately 22% of the total Table 5 Details of NASA – SSE and SEC – MNRE radiation data sources. wastelands. Parameter NASA – SSE SEC – MNRE – 3.1.1.3. Land with scrub open. This category is similar to the dense Source Satellite derived Satellite derived scrub wastelands with the difference that these possess sparse Region Worldwide India vegetation, generally less than 15% or devoid of scrub. This type of Resolution 10 km 10 km 10 km 10 km wasteland is generally prone to deterioration due to erosion and Data GHI, DNI, Ta, wind speed etc. GHI and DNI Values Monthly, yearly Monthly has a thin soil cover. Approximately 23% of the total wastelands in Time period July 1983–June 2005 January 2002–December 2008 India belong to this category. 906 C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912

Table 6 Wasteland and climatic conditions for the state of Rajasthan.

District Wasteland(km2) Latitude(1N) Longitude(1E) DNI Wind speeds(m/s) Temp.(1C)

NASA (kW h/m2/day) SEC (kW h/m2/day)

Ajmer 1683 26.45 74.7 5.7 5.76 3.63 24.6 Alwar 592 27.56 76.63 5.36 5.13 3.17 24.1 Banswara 348 23.5 74.4 5.65 5.74 3.43 26.3 Baran 528 25.08 76.55 5.45 5.44 3.29 25.6 Barmer 2886 25.75 71.41 5.63 5.79 5.02 26.3 Bharatpur 413 27.25 77.5 5.32 4.62 3.08 24.5 Bhilwara 2231 25.35 74.66 5.62 5.82 3.66 25 Bikaner 6840 28.01 73.36 5.67 5.46 3.85 24.5 Bundi 419 25.45 75.68 5.55 5.54 3.29 25.3 Chittorgarh 1159 24.9 74.7 5.7 5.93 3.66 25.5 Churu 439 28.31 75.01 5.4 5.19 3.28 23.7 Dhaulpur 514 26.77 77.88 5.39 5.09 3.22 25 Duasa 264 26.9 76.36 5.42 5.44 3.25 24.9 Dungarpur 950 23.83 73.83 5.83 5.57 3.96 26.7 Ganganagar 1253 26.81 73.76 5.81 5.68 4.3 25 Hanumangarh 285 29.58 74.35 5.44 4.67 3.43 23.8 Jaipur 1238 26.91 73.36 5.56 5.56 4.3 25 Jaisalmer 16,762 26.91 70.95 5.72 5.78 4.89 25.9 Jalore 768 25.36 72.96 5.74 5.88 5.15 26.2 Jhalawar 1084 24.6 76.15 5.55 5.53 3.28 25.9 Jhunjhunu 394 28.1 75.33 5.38 5.31 3.28 23.7 Jodhpur 3661 26.3 73.06 5.77 5.68 4.3 25 Karauli 436 26.5 77.06 5.37 5.31 3.22 25 Kota 510 25.16 75.86 5.53 5.55 3.29 25.3 Nagaur 973 27 73.66 5.79 5.64 4.09 24.8 Pali 1627 25.76 73.88 5.73 5.89 4.41 25.1 Rajsamand 1448 25.07 73.88 5.69 5.99 4.41 25.1 Sawaimadhopur 427 25.96 76.05 5.51 5.49 3.29 25.6 Sikar 552 27.6 75.25 5.56 5.61 3.27 23.9 Sirohi 1012 24.88 72.86 5.62 6.15 5.16 26.5 Tonk 658 26.18 75.83 5.51 5.41 3.28 24.6 Udaipur 2784 27.7 75.55 5.69 6.16 3.27 23.9 Total 55,138

and Forests, Government of India [49], were also excluded. In was carried out for all the remaining wastelands identified in addition, the districts that are known to be prone to earthquakes different states with the district headquarter assumed to represent [50] were not included in the potential estimation. Also the the entire district for the purpose of ambient temperature. To wastelands located in Jammu & Kashmir, , distribute the remaining wastelands among PV power and solar and the seven North Eastern states were excluded thermal power, for each district, the number of hours in a year the as most of the terrain has high slopes and thus may not be suitable ambient temperature is more than 25 1C and GHI is more than for CSP installation. 120 W/m2 was estimated by developing a program in Matlab. As a first approximation, in the present study, it is proposed that if 3.5. Accounting for potential of wind and PV power generation number of such hours in a year at the chosen location is more than 3000, then the location is suitable for solar thermal power Prioritization of wasteland allocation amongst wind, PV and generation or else the location is suitable for PV power generation. CSP systems is quite involved. In this study, as a preliminary Following this approach, the potential of solar thermal power measure, districts having annual average wind speeds more than a generation was estimated for two different threshold values of threshold value are excluded (even though the locations may also annual DNI. The land requirement (0.04 km2/MW) for the para- have high DNI values) as the same may preferably be used of bolic trough technology was assumed as reference being a com- installation of wind power plants. To decide the threshold value, mercially proven and mature technology [39]. The availability of wind speeds at the potential locations as identified by MNRE and surface and/or ground water for the selected locations was also C-WET [51] were examined (Appendix B). analyzed. Keeping in view the range of wind speeds presented in Anticipating some uncertainty in the reported values of DNI by Appendix B, a threshold value of 4 m/s has been selected and different solar radiation data sources, a more conservative esti- the wastelands that have annual average wind speeds more than mate of solar thermal power generation potential in the country the threshold value were excluded for installation of wind power has been obtained for each location by using 10% lower values of plants. DNI than those provided in the data source given by SEC, MNRE. To allocate wastelands between solar PV and solar thermal A mathematical framework for estimation of wastelands suitable power (after accounting for wastelands suitable for wind power for solar thermal power generation is presented in Appendix C. generation), hourly temperature at all the relevant locations was examined as performance of commercially available PV panels degrades at higher operating temperatures. To accomplish this, 4. Results and discussion Typical Meteorological Year 3 (TMY 3) files were generated from Meteonorm 7 software that provides temperature for 8760 h for Based on the above approach, calculations have been made to each selected location along with other parameters. This exercise estimate district wise potential of solar thermal power generation C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 907

Table 7 List of states in India having wasteland with DNI more than threshold value.

State Geographical area (km2) Wasteland availability (km2)

Total With DNI41800 kW h/m2/year With DNI42000 kW h/m2/year

Andhra Pradesh 275,068 16,767 15,907 1438 94,171 2581 270 0 135,194 4002 4002 1041 3702 287 287 0 Gujarat 196,024 16,484 16,484 15,092 Himachal Pradesh 55,673 3669 2549 873 Jammu & Kashmir 101,387 4071 3263 720 79,706 5495 3496 0 191,791 5678 5673 1335 38,863 1626 931 11 308,252 23,948 23,488 15,167 307,690 24,784 24,784 3208 21,081 2731 1949 0 Orissa 155,707 7154 5473 0 Punjab 50,362 605 82 52 Rajasthan 342,239 55,138 54,440 43,775 130,058 5100 5100 322 Uttarakhand 53,483 1752 1744 887 240,928 3810 923 308 Total 2,781,379 185,682 170,845 84,229

Table 8 Table 9 Wastelands inhabited by large tribal population in various states (data consolidated Wastelands highly prone to earthquakes in various states. district wise). State Wasteland (km2) State Wasteland (km2) With DNI4 With DNI4 With DNI4 With DNI4 1800 kW h/m2/year 2000 kW h/m2/year 1800 kW h/m2/year 2000 kW h/m2/year Gujarat 7357 7357 Chhattisgarh 1528 1041 Himachal Pradesh 1379 0 Gujarat 397 323 Jammu & Kashmir 34 0 Himachal Pradesh 259 157 Uttarakhand 619 419 Jammu & Kashmir 975 720 Total 9389 7776 Jharkhand 824 0 Madhya Pradesh 2370 1937 Mizoram 1949 0 Orissa 2303 0 Table 10 Rajasthan 1298 1298 Estimated wasteland area having wind speeds more than 4 m/s in different states. Total 11,903 5476 State Wasteland (km2) with wind speed44 m/s

Threshold DNI Threshold DNI for the entire country. The results obtained are summarized in this 1800 kW h/m2/year 2000 kW h/m2/year section. 6758 0 4.1. Availability of wasteland (for a particular threshold value Goa 287 0 Gujarat 1442 1442 of DNI) Karnataka 1506 272 Kerala 819 11 The estimated values of total wastelands in different states of Maharashtra 5078 0 the country in the five categories as identified in Table 4 are Punjab 30 0 presented in Table 7. Also the wastelands in various states having Rajasthan 31,628 31,628 Tamil Nadu 929 118 DNI more than two different threshold values are presented in this Total 48,477 33,471 table. In the case of considering locations with annual average DNI of more than 2000 kW h/m2/year for CSP plants, (or annual daily average DNI of 5.47 kW h/m2/day) a total of 84,229 km2 of waste- unavailability of tribal population dominated wastelands for solar lands spread across 14 states of the country was identified. As thermal power generation (or for harnessing renewable energy expected, for a threshold DNI value of 1800 kW h/m2/year (or using large systems), the revised values of wasteland are annual daily average DNI of 4.93 kW h/m2/day), a total of 78,753 km2 and 158,942 km2 respectively for threshold DNI values 170,845 km2 of wasteland spread across 19 states of the country of 2000 kW h/m2/year and 1800 kW h/m2/year. was identified. 4.3. Accounting for wasteland with habitat of critically endangered 4.2. Accounting for wasteland with large tribal population species

Wastelands in the districts having more than 50% of their As per the Ministry of Environment and Forest, Government of population as tribal is presented in Table 8. Accounting for the India [49], only one critically endangered animal species 908 C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912

(Mammals) namely – Kondana Rat is found in the identified revised to 69,793 km2 (threshold DNI 2000 kW h/m2/year) and to potential areas for solar power generation. The location is near 142,216 km2 (threshold DNI 1800 kW h/m2/year). (Maharashtra). Excluding district of Pune, the potential area for solar power generation in the country further reduces to 78,753 km2 (for threshold DNI of 2000 kW h/m2/year) and to 4.6. Accounting for the land suitable for wind and PV power 155,895 km2 (for threshold DNI of 1800 kW h/m2/year). generation

Ministry of New and Renewable Energy Sources (MNRE) and 4.4. Excluding wasteland under seismic zone Centre for Wind Energy Technology (C-WET) have identified 233 potential sites for wind power projects in India [51]. All these As per the National Disaster Management Authority, Govern- ment of India [50], few districts in various states are in the seismic zone – V and highly prone to earthquakes (Table 9). Excluding wastelands in these areas, revised estimates of suitable wasteland availability for solar power generation reduces to70,977 km2 (threshold DNI 2000 kW h/m2/year) and to 146,506 km2 (thresh- old DNI 1800 kW h/m2/year).

4.5. Exclusion of land with higher slopes

As mentioned earlier, due to unavailability of flat land, locations in the states of Jammu & Kashmir, Himachal Pradesh, and Uttarak- hand were not considered while estimating the potential for solar Fig. 2. Allocation of wastelands between PV power and CSP for threshold DNI power generation. As a result, total available wasteland area is 1800 kW h/m2.

Table 11 Allocation of land for wind power, PV power and solar thermal power (DNI more than 1800 kW h/m2 and wind speed more than 4 m/s).

State Available wasteland (km2) Wasteland allocated in (km2) for

Wind power with Solar PV power with Solar thermal power with v44m/s TaZ25 1C for less than 3000 h Ta Z25 1C for more than 3000 h (1)(2) (3) (1)(2)(3)

Andhra Pradesh 15,907 6758 0 9149 Bihar 270 0 60 210 Chhattisgarh 2474 0 1344 1130 Goa 287 287 0 0 Gujarat 8730 1442 0 7288 Jharkhand 2672 0 2672 0 Karnataka 5673 1506 2708 1459 Kerala 931 819 0 112 Madhya Pradesh 21,118 0 21,118 0 Maharashtra 21,737 5078 12,055 4604 Orissa 3170 0 2047 1123 Punjab 82 30 52 0 Rajasthan 53,142 31,628 19,405 2109 Tamil Nadu 5100 929 1084 3087 Uttar Pradesh 923 0 923 0 Total 142,216 48,477 63,468 30,271

Table 12 Allocation of land for wind power, PV power and solar thermal power (DNI more than 2000 kW h/m2 and wind speed more than 4 m/s).

State Available wasteland (km2) Wasteland allocated in (km2) for

Wind power with Solar PV power with Solar thermal power with v44m/s Ta Z25 1C for less than 3000 h TaZ 25 1C for more than 3000 h (1)(2)(3) (1)(2 )(3)

Andhra Pradesh 1438 0 0 1438 Gujarat 7412 1442 0 5970 Karnataka 1335 272 1063 0 Kerala 11 11 0 0 Madhya Pradesh 13,230 0 13,230 0 Maharashtra 3208 0 2793 415 Punjab 52 0 52 0 Rajasthan 42,477 31,628 9690 1159 Tamil Nadu 322 118 0 204 Uttar Pradesh 308 0 308 0 Total 69,793 33,471 27,136 9186 C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 909 locations have annual average wind speeds more than 4 m/s. Therefore, in this study, wastelands having annual average wind speed of more than 4 m/s are prioritized for wind power genera- tion and thus excluded from the potential wastelands that can be used for solar power generation. The values obtained are pre- sented in Table 10 with the wind speed data taken from NASA website [46]. On accounting for the wastelands suitable for wind power generation, the wasteland available for solar power gen- eration is revised to 36,322 km2 (threshold DNI 2000 kW h/m2/ year) and to 93,739 km2 (threshold DNI 1800 kW h/m2/year). As explained in Section 3.5, wastelands allocated for wind power generation, PV power generation and solar thermal power generation are presented in Tables 11 and 12. Figs. 2 and 3 present Fig. 3. Allocation of wastelands between PV power and CSP for threshold DNI the allocation of wasteland (in the form of a bar chart) suitable for 2000 kW h/m2. solar power generation between PV and CSP modes for two threshold values of DNI. It is to be noted that in Fig. 2, the bar shown as other states includes the states of Bihar, Chhattisgarh, Jharkhand, Karnataka, Kerala, Orissa, Punjab, Tamil Nadu and Uttar Table 13 Pradesh. In Fig. 3, the bar shown as other states includes the states Potential for solar thermal power generation in various states. of Karnataka, Punjab, Tamil Nadu and Uttar Pradesh. State Potential for solar thermal power generation (GW)

Threshold DNI Threshold DNI 2 2 4.7. Ground water availability in potential locations 1800 kW h/m /year 2000 kW h/m /year

Andhra Pradesh 229 36 As per the Central Ground Water Board, Government of India Bihar 5 0 [52], the stage of ground water development in the country is 61%. Chhattisgarh 28 0 The status of ground water development is very high in the states Gujarat 182 149 of Punjab and Rajasthan (more than 100%) implying that, in these Karnataka 36 0 Kerala 3 0 states, annual ground water consumption is more than annual Madhya Pradesh 0 0 ground water recharge. So except these two states, ground water Maharashtra 115 10 can fulfill the water requirement for CSP systems. In Rajasthan, Orissa 28 0 canal can meet the water requirement as it is Rajasthan 53 29 Tamil Nadu 77 5 already doing in the CSP projects sanctioned under JNNSM Total 756 229 phase-1.

Fig. 4. CSP potential in various states with annual threshold DNI of 1800 kW h/m2 (figures in brackets denotes CSP potential with annual threshold DNI of 2000 kW h/m2). 910 C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912

CSP Potential (in GW) in various states bearing on the accuracy of data sources used for analysis. Though 250 the economics of solar thermal power generation and its relative 200 competitiveness with photovoltaic electricity is directly affected by

150 the value of available DNI, the actual realizable potential may also depend upon market conditions and other factors. 100

Potential in GW 50

0 Acknowledgment Andhra Gujarat Maharashtra Rajasthan Tamilnadu Other states Pradesh Chandan Sharma gratefully acknowledges the permission Threshold DNI 1800 kWh/m2 Threshold DNI 2000 kWh/m2 granted by the Department of Technical Education, Government Fig. 5. CSP potential in various states (other states include Bihar, Chhattisgarh, of State of Rajasthan and the administration of Government Karnataka, Kerala and Orissa). Engineering College Ajmer to undertake doctoral research at the Indian Institute of Technology Delhi. 4.8. Potential for solar thermal power generation Appendix A Considering parabolic trough as a reference technology, having land requirement of 0.04 km2/MW [39], the estimated potential See Table A1. for solar thermal power generation for the two threshold values of DNI is presented in Table 13. It is worth mentioning that the footprint (land area per MW) has been considered to be the same Appendix B for the two chosen values of threshold DNI. With higher DNI, for the same land area, power output and capacity utilization factor See Table B1. are expected to be more compared to their corresponding values for the case with lower DNI. State wise potential is shown on the Table A1 map of India in Fig. 4 and also in the form of a bar chart in Fig. 5. Details of some operational solar thermal power plants in Spain and USA. A more conservative estimate of solar thermal power generation (Source: http://www.nrel.gov/csp/solarpaces/by_status.cfm). potential was also attained with a reduction of 10% in the DNI Plant name Country Capacity (MW) Annual DNI (kW h/m2/year) values as provided by the data source used for each of the locations considered in the analysis as expected, with lower values of DNI the Andasol-1 Spain 50 2136 estimated potential for solar thermal power generation reduces Andasol-2 Spain 50 2136 considerably (as compared to the potential estimated with the use La Dehesa Spain 50 2200 of DNI values provided by SEC, MNRE). For example, solar thermal La Florida Spain 50 2193 Extresol-1 Spain 50 2168 power generation potential of 756 GW in the base case (annual DNI Extrasol-2 Spain 50 2168 2 1800 kW h/m , annual average wind speed 4 m/s) reduces to Alvarado I Spain 50 2174 229 GW for the same values of threshold DNI and wind speed. Manchasol-I Spain 50 2208 Palma del Rio II Spain 50 2291 Puertollano Spain 50 2061 Solnova 1 Spain 50 2012 5. Concluding remarks Solnova 3 Spain 50 2012 Solnova 4 Spain 50 2012 The estimated potential for solar thermal power generation is Nevada Solar 1 USA 64 2606 SEGS USA 372 2725 756 GW for a threshold DNI value of 1800 kW h/m2 and 229 GW for a threshold DNI value of 2000 kW h/m2 (with all the waste- lands having wind speeds of 4 m/s or more allocated for wind power generation). From the results it is also noted that on a Table B1 reasonably large area of wastelands in India, potential exists for State wise number of potential locations for wind power installations and range of both wind and solar power generation. It is therefore necessary to annual average wind speed. develop appropriate methods for prioritization of one over the (Source: http://www.cwet.tn.nic.in/Docu/233_potential_stations_as_on_31.05.11. pdf). other mode of power generation so as to avoid any potential conflict between wind and solar power projects (wind turbines State No. of potential Range of annual average wind installed in the vicinity of solar power plants may cause shading locations speed (m/s) and thus affect their performance). Andhra 32 4.97–6.42 It is worth mentioning that the estimates arrived in the present Pradesh study are based on simplifying assumptions regarding relative share Gujarat 40 4.33–6.97 of wind, PV and solar thermal routes of electricity generation and Karnataka 26 5.19–4.52 further elaborate studies are needed to identify niche locations. To Kerala 17 4.41–8.42 – assess the values of DNI, wind speed and ambient temperature, data Maharashtra 39 4.31 6.44 Rajasthan 8 4.02–5.73 sources (NASA and SEC, MNRE) that were available in the public Tamil Nadu 45 4.47–7.32 domain were used. Estimated potential shall have a significant C. Sharma et al. / Renewable and Sustainable Energy Reviews 42 (2015) 902–912 911

Appendix C

See Table C1.

Table C1 Framework for estimation of wastelands for solar thermal power generation.

S. no. Description Value

1. Total wasteland available in the country TWL

2. Fraction of total wasteland that is suitable for installation of RET based power generation fsret

3. Fraction of wastelasnd at S. no. 2 (¼fsret TWL) having DNI more than the threshold value fthDNI

4. Fraction of wasteland at S. no. 3 (¼fsret fthDNI TWL) that is habitat for tribal population, endangered species, under seismic ftesh zones and has hilly terrains

5. Fraction of remaining wasteland at S. no. 4 [¼fsret fthDNI TWL(1– ftesh)]having wind speed more than 4 m/s fthwind

6. Fraction of remaining wasteland at S. no. 5 [¼fsret fthDNI TWL(1ftesh)(1fthwind )] having ambient temperature more than fthtemp 25 1C for less than 3000 h in a year

Wasteland suitable for solar thermal power generation (WLsstp)¼¼fsret fthDNI TWL(1ftesh)(1fthwind )(1fthtemp )

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