Site suitability analysis for solar farms using the geographic information system and multi-criteria decision analysis: the case of Antalya, Turkey

Abstract

The need for renewable energy is continually increasing in developing countries. In Turkey, that need has been felt strongly for a long time. Due to various state's laws, regulations, and incentives, interest in renewable energies, especially solar energy, has been increasing rapidly since the 2000s. The annual amount of sun and therefore the solar potential in Turkey is quite high. In this context, it is crucial to identify suitable locations for solar farms in order to make maximum use of solar energy. The main objective of this study is to identify suitable potential sites for solar farms in the province of Antalya, which contains Turkey's fifth-largest city in terms of population. The geographic information system and analytical hierarchy process (AHP) were used to assess sites based on various logistical, geographic, and solar criteria. The map data used in the study were open access, and other data were obtained from local administrations. The sites in the study area were classified into four classes according to the results of the suitability index calculation: very suitable, suitable, less suitable, and not suitable. In total, 484,795 hectares, 24.02% of the study area were deemed suitable for solar farms, while 731,094 hectares (36.31%) were less suitable. Currently, very little of the suitable area is used for solar energy generation. The results of the study indicate that the province has a high potential in terms of solar energy. This is the most comprehensive study conducted in Antalya Province by using the widely preferred site selection criteria for solar farms together with AHP.

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Data availability and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Al Garni HZ, Awasthi A (2017) Solar PV power plant site selection using a GIS-AHP based approach with application in Saudi Arabia. Appl Energy 206:1225–1240. https://doi.org/10.1016/j.apenergy.2017.10.024

    Article  Google Scholar 

  2. Aleksandrowicz L, Green R, Joy EJ, Smith P, Haines A (2016) The impacts of dietary change on greenhouse gas emissions, land use, water use, and health: a systematic review. PLoS ONE. https://doi.org/10.1371/journal.pone.0165797

    Article  Google Scholar 

  3. Algarín CR, Llanos AP (2017) Castro AO (2017) An analytic hierarchy process based approach for evaluating renewable energy sources. Int J Energy Econ Policy 7(4):38–47

    Google Scholar 

  4. Ali S, Taweekun J, Techato K, Waewsak J, Gyawali S (2019) GIS based site suitability assessment for wind and solar farms in Songkhla, Thailand. Renew Energy 132:1360–1372. https://doi.org/10.1016/j.renene.2018.09.035

    Article  Google Scholar 

  5. Amjad F, Shah LA (2020) Identification and assessment of sites for solar farms development using GIS and density based clustering technique–a case of Pakistan. Renewable Energy. https://doi.org/10.1016/j.renene.2020.03.083

    Article  Google Scholar 

  6. Antalya Provincial Culture and Tourism Directorate (2010) Antalya from Past to Present. TR Antalya Governorship Provincial Directorate of Culture and Tourism Publications, Antalya

    Google Scholar 

  7. Budak G, Chen X, Celik S, Ozturk B (2019) A systematic approach for assessment of renewable energy using analytic hierarchy process. Energy Sustain Soc 9(1):37. https://doi.org/10.1186/s13705-019-0219-y

    Article  Google Scholar 

  8. Castillo CP, Silva FB, Lavalle C (2016) An assessment of the regional potential for solar power generation in EU-28. Energy Policy 88:86–99. https://doi.org/10.1016/j.enpol.2015.10.004

    Article  Google Scholar 

  9. Çolak HE, Memisoglu T, Gercek Y (2020) Optimal site selection for solar photovoltaic (PV) power plants using GIS and AHP: a case study of Malatya Province, Turkey. Renew Energy 149:565–576. https://doi.org/10.1016/j.renene.2019.12.078

    Article  Google Scholar 

  10. Doorga JR, Rughooputh SD, Boojhawon R (2019) Multi-criteria GIS-based modelling technique for identifying potential solar farm sites: a case study in Mauritius. Renewable Energy 133:1201–1219. https://doi.org/10.1016/j.renene.2018.08.105

    Article  Google Scholar 

  11. General Directorate of Renewable Energy (2019) Solar energy potential atlas. https://www.enerjiatlasi.com/gunes-enerjisi-haritasi/turkiye. Accessed date: 05 Jan 2020

  12. Georgiou A, Skarlatos D (2016) Optimal site selection for sitting a solar park using multi-criteria decision analysis and geographical information systems. Geosci Instr, Methods Data Syst 5(2):321–332. https://doi.org/10.5194/gi-5-321-2016

    Article  Google Scholar 

  13. Giamalaki M, Tsoutsos T (2019) Sustainable siting of solar power installations in Mediterranean using a GIS/AHP approach. Renew Energy 141:64–75. https://doi.org/10.1016/j.renene.2019.03.100

    Article  Google Scholar 

  14. Hoffmann AA, Rymer PD, Byrne M, Ruthrof KX, Whinam J, McGeoch M, Hill SJ (2019) Impacts of recent climate change on terrestrial flora and fauna: some emerging Australian examples. Austral Ecol 44:3–27. https://doi.org/10.1111/aec.12674

    Article  Google Scholar 

  15. IRENA (2020) International Renewable Energy Agency official web site, Country ranking, https://www.irena.org/Statistics/View-Data-by-Topic/Capacity-and-Generation/Country-Rankings. Accessed 11 Aug 2020

  16. Kaygusuz K, Avci AC (2018) Renewable energy potential, utilization and policies in Turkey for environmental friendly sustainable development. J Eng Res Appl Sci 7:902–909

    Google Scholar 

  17. Kellogg W, Schware R (2019) Climate Change and society: consequences of increasing atmospheric carbon dioxide. Routledge, New York

    Google Scholar 

  18. Khan J, Arsalan MH (2016) Solar power technologies for sustainable electricity generation–a review. Renew Sustain Energy Rev 55:414–425. https://doi.org/10.1016/j.rser.2015.10.135

    Article  Google Scholar 

  19. Koc A, Turk S, Şahin G (2019) Multi-criteria of wind-solar site selection problem using a GIS-AHP-based approach with an application in Igdir Province/Turkey. Environ Sci Pollut Res 26(31):32298–32310. https://doi.org/10.1007/s11356-019-06260-1

    CAS  Article  Google Scholar 

  20. Kum G, Sönmez ME, Karabaş M (2019) Determination of Solar Energy Potential in GazÏ̇antep Province by Analytical Hierarchy Process Method (AHP). Journal of Geography 39:61–72. https://doi.org/10.26650/JGEOG2019-0031

    Article  Google Scholar 

  21. Lau LC, Lee KT, Mohamed AR (2012) Global warming mitigation and renewable energy policy development from the Kyoto Protocol to the Copenhagen Accord—A comment. Renew Sustain Energy Rev 16:5280–5284. https://doi.org/10.1016/j.rser.2012.04.006

    Article  Google Scholar 

  22. Li Y, Ren T, Kinney PL, Joyner A, Zhang W (2018) Projecting future climate change impacts on heat-related mortality in large urban areas in China. Environ Res 163:171–185. https://doi.org/10.1016/j.envres.2018.01.047

    CAS  Article  Google Scholar 

  23. Løken E (2007) Use of multicriteria decision analysis methods for energy planning problems. Renew Sustain Energy Rev 11:1584–1595. https://doi.org/10.1016/j.rser.2005.11.005

    Article  Google Scholar 

  24. Merrouni AA, Elalaoui FE, Mezrhab A, Mezrhab A, Ghennioui A (2017) Large scale PV sites selection by combining GIS and Analytical Hierarchy Process. Case study: Eastern Morocco. Renew Energy 119:1–17. https://doi.org/10.1016/j.renene.2017.10.044

    Article  Google Scholar 

  25. Nguyen KH, Kakinaka M (2019) Renewable energy consumption, carbon emissions, and development stages: some evidence from panel cointegration analysis. Renew Energy 132:1049–1057. https://doi.org/10.1016/j.renene.2018.08.069

    Article  Google Scholar 

  26. Rediske G, Siluk JCM, Gastaldo N, Rigo PD, Rosa CB (2019) Determinant factors in site selection for photovoltaic projects: a systematic review. Int J Energy Res 43(5):1689–1701. https://doi.org/10.1002/er.4321

    CAS  Article  Google Scholar 

  27. Republic of Turkey Ministry of Agriculture and Forestry General Directorate of Meteorology (2018) Radyasyon. https://www.mgm.gov.tr/kurumici/radyasyon_iller.aspx. Accessed 05 Jan 2019

  28. Republic of Turkey Ministry of Energy and Natural Resources (2020) Turkey's National Renewable Energy Action Plan. https://www.enerjiatlasi.com/gunes-enerjisi-haritasi/turkiye. Accessed 04 Jan 2020

  29. Saaty TL (1980) The Analytic Hierarchy Process Mcgraw Hill, New York. Agricultural Economics Review, 70.

  30. Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26. https://doi.org/10.1016/0377-2217(90)90057-I

    Article  Google Scholar 

  31. Saaty TL (2008) Decision making with the analytic hierarchy process. Intern J Serv Sci 1:83–98

    Google Scholar 

  32. Sen S, Ganguly S (2017) Opportunities, barriers and issues with renewable energy development–a discussion. Renew Sustain Energy Rev 69:1170–1181. https://doi.org/10.1016/j.rser.2016.09.137

    Article  Google Scholar 

  33. Shorabeh SN, Firozjaei MK, Nematollah O, Firozjaei HK, Jelokhani-Niaraki M (2019) A risk-based multi-criteria spatial decision analysis for solar power plant site selection in different climates: a case study in Iran. Renew Energy 143:958–973. https://doi.org/10.1016/j.renene.2019.05.063

    Article  Google Scholar 

  34. Solangi YA, Shah SA, Zameer H, Ikram M, Saracoglu BO (2019) Assessing the solar PV power project site selection in Pakistan: based on AHP-fuzzy VIKOR approach. Environ Sci Pollut Res 26(29):30286–30302. https://doi.org/10.1007/s11356-019-06172-0

    Article  Google Scholar 

  35. Uyan M (2017) Optimal site selection for solar power plants using multi-criteria evaluation: a case study from the Ayranci region in Karaman, Turkey. Clean Technol Environ Policy 19(9):2231–2244. https://doi.org/10.1007/s10098-017-1405-2

    CAS  Article  Google Scholar 

  36. Western Mediterranean Development Agency (2011) Solar energy sector report. http://baka.gov.tr/uploads/1303486512GUNES-TURKCE-KATALOG.pdf. Accessed 05 Jan 2020

  37. WHO (2014) Quantitative risk assessment of the effects of climate change on selected causes of death, 2030s and 2050s. World Health Organization. https://apps.who.int/iris/handle/10665/134014. Accessed 04 Jan 2020

  38. WMDA (2011) West Mediterranean Development Agency Report, https://www.baka.gov.tr/assets/upload/dosyalar/1303486512GUNES-TURKCE-KATALOG.pdf. Accessed 11 Aug 2020

  39. Yimen N, Dagbasi M (2019) Multi-Attribute decision-making: applying a modified brown-gibson model and RETScreen software to the optimal location process of utility-scale photovoltaic plants. Processes 7(8):505. https://doi.org/10.3390/pr7080505

    Article  Google Scholar 

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Acknowledgements

This study was produced from the Master’s Thesis of Urban Planner Şura Kırcalı under the supervision of Assoc. Prof. Dr. Serdar Selim.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors

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Correspondence to Serdar Selim.

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Kırcalı, Ş., Selim, S. Site suitability analysis for solar farms using the geographic information system and multi-criteria decision analysis: the case of Antalya, Turkey. Clean Techn Environ Policy (2021). https://doi.org/10.1007/s10098-020-02018-3

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Keywords

  • Geographic information systems (GIS)
  • Multi-criteria decision analysis (MCDA)
  • Site selection
  • Solar farms
  • Sustainable energy
  • Analytic hierarchy process (AHP)