Optimal site selection for solar power stations in the Nakhichevan AR
Abstract
Since the electrical power output by converting total solar radiation using PV cells is low, it is necessary to identify areas with high solar radiation. However, low efficiency of PV panels (14‒18%) and the low intensity of total solar radiation on a horizontal surface require a large installation space to achieve a certain power level. Due to the high cost of installing solar power plants, a comprehensive systematic assessment of the geographic factors of a region is necessary to select the most suitable location. The reason we chos e Nakhichevan as a study area is that the radiation level is high compared to other regions of Azerbaijan (1220‒1699 kWh/m2 per year), and the annual duration of sunshine exceeds 2500 hours. Since the creation of solar power plants in regions with high values of the total radiation on a horizontal surface generally depends on technical, economic and environmental criteria, the areas corresponding to high criteria values in the model were thoroughly investigated using balanced comparison to identify suitable sites. The Analytical Process Hierarchy (AHP) model, based on Multi-Criteria Decision-Making (MCDM) methods, was used to identify suitable locations for solar power plants. In the first phase of the study seven criteria were analyzed to determine suitable locations, i.e. total solar radiation on a horizontal surface, slope gradient, land use, buffer distance from areas with high annual solar energy potential to residential areas, proximity to substations, highways and power supply lines. In the second stage the degree of accessibility and suitability of areas according to certain criteria was determined using the Weighted Overlay tool in Geographic Information Systems (GIS). As a result of the study, it was concluded that 9,5% (510 km2) of the area of Nakhichevan has high suitability, 12% (645 km2) ‒ average suitability and 24% (1290 km2) ‒ low suitability for placing solar power plants. The remaining 54,5% (2930 km2) of the region are unsuitable territories because of low radiation, high slope, the presence of protected areas, settlements and agricultural areas, and poorly developed infrastructure. Optimal locations are mainly in the southern and eastern parts of the region, as shown in the polygon shape on the suitability map.
About the Author
N. S. ImamverdiyevRussian Federation
Department of Economic and Political Geography, Scientifi c Researcher
References
1. Al Garni H.Z., Awasthi A. Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia, Applied Energy, 2017, vol. 206, р. 1225‒1240, DOI: 10.1016/j.apenergy.2017.10.024.
2. Asakereh A., Soleymani M., Sheikhdavoodi M.J. A GISbased Fuzzy-AHP method for the evaluation of solar farms locations: Case study in Khuzestan province, Iran, Solar Energy, 2017, vol. 155, р. 342‒353, DOI: 10.1016/j.solener.2017.05.075.
3. Babayev S. Geography Nakhchivan Autonomous Republic. Elm, Baku, 1999, p. 227.
4. Beccali M., Cellura M., Mistretta M. Decision-making in energy planning. Application of the Electre method at regional level for the diffusion of renewable energy techno logy, Renewable Energy, 2003, vol. 28(13), р. 2063‒2087, DOI: 10.1016/S0960-1481 (03)00102-2.
5. Devi K., Yadav S.P. A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method, The International Journal of Advanced Manufacturing Technology, 2013, vol. 66(9-12), р. 1219‒1229, DOI: 10.1007/s00170-012-4400-0.
6. Doorga J.R., Rughooputh S.D., Boojhawon R. Multi-criteria GIS-based modelling technique for identifying potential solar farm sites: A case study in Mauritius, Renewable Energy, 2019, vol. 133, р. 1201‒1219, DOI: 10.1016/j.renene.2018.08.105.
7. Effat H.A. Selection of potential sites for solar energy farms in Ismailia Governorate, Egypt using SRTM and multicriteria analysis, International Journal of Advanced Remote Sensing and GIS, 2013, vol. 2(1), p. 205–220.
8. Gardashov R., Eminov M., Kara G., Kara E.G.E., Mammadov T., Huseynova X. The optimum daily direction of solar panels in the highlands, derived by an analytical method, Renewable and Sustainable Energy Reviews, 2020, vol. 120, р. 109668, DOI: 10.1016/j.rser.2019.109668.
9. Khan G., Rathi S. Optimal site selection for solar PV power plant in an Indian state using geographical information system (GIS), International Journal of Emerging Engineering Research and Technology, 2014 , vol. 2(7), р. 260‒266.
10. Linkov I., Moberg E. Multi-criteria decision analysis: environmental applications and case studies, CRC Press, 2011, 179 p.
11. Mammadov F. Yearly average maps of solar radiation in Azerbaijan, Energy Power, 2013, vol. 3, р. 44‒50, DOI: 10.5923/j.ep.20130304.02.
12. Merrouni A.A., Elalaoui F.E., Mezrhab A., Mezrhab A., Ghennioui A. Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study, Eastern Morocco, Renewable Energy, 2018, vol. 119, р. 863‒873, DOI: 10.1016/j.renene.2017.10.044.
13. Noorollahi E., Fadai D., Akbarpour Shirazi M., Ghodsipour S.H. Land suitability analysis for solar farms exploitation using GIS and fuzzy analytic hierarchy process (FAHP) a case study of Iran, Energies, 2016, vol. 9(8), р. 643, DOI: 10.3390/en9080643.
14. Polatidis H., Haralambidou K., Haralambopoulos D. Multi-criteria decision analysis for geothermal energy: A comparison between the ELECTRE III and the PROMETHEE II methods, Energy Sources, р. B, Economics, Planning, and Policy, 2015, vol. 10(3), р. 241‒249, DOI: 10.1080/15567249.2011.565297.
15. Quijano R., Domínguez J., Botero S. Sustainable energy planning model (MODERGIS) application to integrate renewable energy in the Colombia case, 2010, 17 p.
16. Saaty T.L. The Analytic Hierarchy Process: Planning, Priority Setting, Resources Allocation, McGraw, New York, 1980, 214 p.
17. Uyan M. GIS-based solar farms site selection using analytic hierarchy process (AHP) in Karapinar region, Konya/ Turkey, Renewable and Sustainable Energy Reviews, 2013, vol. 28, р. 11‒17, DOI: 10.1016/j.rser.2013.07.042.
18. Vulkan A., Kloog I., Dorman M., Erell E. Modeling the potential for PV installation in residential buildings in dense urban areas, Energy and Buildings, 2018, vol. 169, р. 97‒109, DOI: 10.1016/j.enbuild.2018.03.052.
19. Watson J.J., Hudson M.D. Regional scale wind farm and solar farm suitability assessment using GIS-assisted multi-criteria evaluation, Landscape and Urban Planning, 2015, vol. 138, p. 20–31, DOI: 10.1016/j.landurbplan.2015.02.001.
20. Wang C.-N., Nguyen V.T., Thai H.T.N., Duong D.H. Multicriteria decision making (MCDM) approaches for solar power plant location selection in Viet Nam, Energies, 2018, vol. 11(6), р. 1504, DOI: 10.3390/en11061504.
21. Web sources
22. Alaska Satellite Facility, Making remote-sensing data accessible, URL: https://search.earthdata.nasa.gov/search?q=nakhchivan&m=35.399139134002!42.7060546875!6!1!0!0%2C2 (аccess data 16.10.2020).
23. Earth Data Search, ASTER Global Digital Elevation Model V003, URL: https://search.earthdata.nasa.gov/search/?hdr=1%20to%2030%20meters&fi=ASTER&fst0=Land%20Surface (access data 12.09.2020).
24. Global Solar Atlas 3.0, Azerbaijan, Nakhchivan Autonomy Republic, Solar energy resource, 2020. https://globalsolaratlas.info/map?r=AZE:AZE.7_1&c=39.30579,45.4625,9 (access data 09.08.2020).
25. Global Monitoring Laboratory, Earth System Research Laboratories, 2020, URL: https://www.esrl.noaa.gov/gmd/grad/solcalc/table.php?lat=40.417&lon=49.825&year=2020 (access data 05.10.2020).
26. Solar energy output, Simulation and design of solar systems, URL: https://photovoltaicsoftware.com/principle-ressources/how-calculate-solar-energy-power-pv-systems (access data 19.10.2020).
27. Sun power, URL: https://us.sunpower.com/blog/2019/05/09/how-solar-panels-work-cloudy-days (access data 14.11.2020).
28. Solargis, Solar resource maps of Azerbaijan, URL: https://solargis.com/maps-and-gis-data/download/azerbaijan (access data 17.08.2020).
Review
For citations:
Imamverdiyev N.S. Optimal site selection for solar power stations in the Nakhichevan AR. Vestnik Moskovskogo universiteta. Seriya 5, Geografiya. 2022;(4):36-51. (In Russ.)