GIS-BASED FUZZY AHP APPROACH FOR SOLAR FARM SITE SUITABILITY ANALYSIS IN EGOR, BENIN CITY, NIGERIA

  • S. O. Oladosu University of Benin
  • S. F. Obayuana University of Benin
  • G. E. Okoeka University of Benin
  • E. O. Aizesogie University of Benin
Keywords: Solar Farm Siting, Fuzzy AHP, Terrain Analysis, Suitability Analysis, Benin City

Abstract

The increasing demand for sustainable energy solutions in Nigeria has necessitated the exploration of alternative energy sources, particularly solar power. This study presents a cost-effective suitability analysis for siting a solar photovoltaic (PV) farm in Egor Local Government Area of Edo State, Nigeria, using an integrated Geospatial Information System (GIS) and Fuzzy Analytical Hierarchy Process (FAHP) framework. Eight critical factors were evaluated: solar radiation, elevation, slope, temperature, relative humidity, land use/land cover, distance to roads, and distance to residential areas. Each factor was standardized using fuzzy membership functions, weighted using the AHP pairwise comparison method, and overlaid using fuzzy summation to generate a final suitability map. Validation was performed by cross-checking spatial outputs with existing physical features and confirming consistency with known land use characteristics. The results reveal that solar radiation and elevation are the most influential criteria, with weighted sums of 5.802 and 3.204, respectively. The analysis identifies Evbuotubu and surrounding zones as highly suitable for solar farm development. This study demonstrates that the combination of GIS and FAHP provides a robust decision-support tool for identifying optimal locations for solar energy infrastructure in urbanizing environments. The findings offer practical insights for policymakers, planners, and energy developers aiming to expand renewable energy infrastructure in Nigeria.

References

Aliyu AS, Ramli AT, Saleh MA. (2015) Nigeria electricity crisis: Power generation capacity expansion and environmental ramifications. Energy. 93: 10461056. https://doi.org/10.1016/j.energy.2015.09.017 DOI: https://doi.org/10.1016/j.energy.2015.09.017

Asakereh A, Soleymani M, Sheikhdavoodi MJ. (2017) A GIS-based Fuzzy-AHP method for the evaluation of solar farms locations: Case study in Khuzestan Province, Iran. Environmental Energy and Economic Research. 1 (3): 247256. https://doi.org/10.22097/eeer.2017.47236 DOI: https://doi.org/10.1016/j.solener.2017.05.075

Babakatcha H, Yusuf A, Salihu A, Abdulrahman S. (2020) Solar energy planning and development in Sub-Saharan Africa: A case for Nigeria. Renewable and Sustainable Energy Reviews. 119: 109576. https://doi.org/10.1016/j.rser.2019.109576 DOI: https://doi.org/10.1016/j.rser.2019.109576

Chaves J, Bahil M. (2019) A decision-making framework using GIS for solar power plant location selection. Renewable Energy. 139: 11131124. https://doi.org/10.1016/j.renene.2019.03.004 DOI: https://doi.org/10.1016/j.renene.2019.03.004

Gerbo, A., Suryabhagavan, KV., Raghuvanshi, TK. (2022). GIS-based approach for modeling grid-connected solar power potential sites: a case study of East Shewa Zone, Ethiopia. Geology, Ecology, and Landscapes, 6(3), 159173. https://doi.org/10.1080/24749508.2020.1809059 DOI: https://doi.org/10.1080/24749508.2020.1809059

Giwa, A., Alabi, A., Yusuf, A., & Olukan, T. (2017). A Comprehensive Review on Biomass and Solar Energy for Sustainable Energy Generation in Nigeria. Renewable and Sustainable Energy Reviews, 69, 620-641. https://doi.org/10.1016/j.rser.2016.11.160 DOI: https://doi.org/10.1016/j.rser.2016.11.160

Huld T, Friesen G, Skoczek A, Kenny R, Sample T, Dunlop E. (2015) Estimating PV module performance using satellite data. Solar Energy. 112: 196204. https://doi.org/10.1016/j.solener.2014.11.005 DOI: https://doi.org/10.1016/j.solener.2014.11.005

Kalogirou SA. (2004) Solar thermal collectors and applications. Progress in Energy and Combustion Science. 30 (3): 231295. https://doi.org/10.1016/j.pecs.2004.02.001 DOI: https://doi.org/10.1016/j.pecs.2004.02.001

Masud AA, Yahaya TI, Ojoye S, Muhammed SY. (2017) An assessment of renewable energy readiness in Nigeria. Renewable and Sustainable Energy Reviews. 75: 818828. https://doi.org/10.1016/j.rser.2016.11.078 DOI: https://doi.org/10.1016/j.rser.2016.11.078

Noorollahi Y, Fadai D, Shirazi MA, Ghodsipour SH. (2016) GIS-based site selection for solar farms using fuzzy AHP and TOPSIS: A case study of Iran. Environmental Earth Sciences. 75: 669. https://doi.org/10.1007/s12665-016-5370-2

NPC. (2006) National Population Census. National Bureau of Statistics, Nigeria. Available from: http://www.population.gov.ng/factssand figures2006.

Ohunakin OS, Akinnawonu OO, Adaramola MS. (2014) Solar energy applications and development in Nigeria: Drivers and barriers. Renewable and Sustainable Energy Reviews. 32: 294301. https://doi.org/10.1016/j.rser.2014.01.014 DOI: https://doi.org/10.1016/j.rser.2014.01.014

Oladosu SO, Alademomi AS, Odonye SE. (2025) Optimal Membership Function Selection for A Co-Active Adaptive Neuro-Fuzzy Inference System Modelling of Reservoir Sedimentation in Nigeria. Matrix Science Mathematic (MSMK), 9(1), 1925. https://doi.org/10.26480/msmk.01.2025.19.25

Ozuegwu MO, Ugwu HH, Oparaku OU. (2017) The status, challenges, and prospects of renewable energy in Nigeria. Renewable and Sustainable Energy Reviews. 70: 257272. https://doi.org/10.1016/j.rser.2016.11.220 DOI: https://doi.org/10.1016/j.rser.2016.11.224

Sanjeevi S. (2014) Geospatial decision support system for solar energy site selection. Journal of Cleaner Production. 85: 380392. https://doi.org/10.1016/j.jclepro.2014.05.072 DOI: https://doi.org/10.1016/j.jclepro.2014.05.072

Saaty TL. (1980) The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill. New York.

Ulu AR, Aigbayboa CO. (2019) Evaluating solar potential in Nigeria: An urban planning approach. Energy Reports. 5: 293302. https://doi.org/10.1016/j.egyr.2019.02.063

Uyan M. (2013) GIS-based solar farms site selection using Analytic Hierarchy Process (AHP): A case study in Konya, Turkey. Renewable and Sustainable Energy Reviews. 28: 1117. https://doi.org/10.1016/j.rser.2013.07.042 DOI: https://doi.org/10.1016/j.rser.2013.07.042

Wheatbelt Development Commission. (2010) Solar energy opportunities in the Wheatbelt. Government of Western Australia.

Zadeh LA. (1965) Fuzzy sets. Information and Control. 8 (3): 338353. https://doi.org/10.1016/S0019-9958(65)90241-X DOI: https://doi.org/10.1016/S0019-9958(65)90241-X

Published
2025-06-30
How to Cite
Oladosu, S. O., Obayuana, S. F., Okoeka, G. E., & Aizesogie, E. O. (2025). GIS-BASED FUZZY AHP APPROACH FOR SOLAR FARM SITE SUITABILITY ANALYSIS IN EGOR, BENIN CITY, NIGERIA. FUDMA JOURNAL OF SCIENCES, 9(6), 208 - 221. https://doi.org/10.33003/fjs-2025-0906-3725