Integrating GIS and AHP for Photovoltaic Farm Site Selection: A Case Study of Ikorodu, Nigeria

Abstract

Large-scale renewable energy plants such as solar photovoltaic (PV) farms are vital to the global transition to a green energy economy. They reduce greenhouse gas emissions, mitigate climate change, and promote sustainable and resilient energy. However, large-scale solar PV farms need adequate planning and site selection for optimal performance. This study presents a geographic information system (GIS)-based multi-criteria decision-making (MCDM) framework utilizing the analytic hierarchy process (AHP) to identify optimal sites for utility-scale photovoltaic (PV) farms in Ikorodu, Lagos State, Nigeria. By integrating critical environmental, technical, economic, and social factors, the model evaluates land suitability for solar energy projects across the study area. The finding indicates that 68.77% of the land is unsuitable for development, with only 17.78% classified as highly suitable and 12.67% as moderately suitable. Marginally suitable and most appropriate areas are minimal, at 0.73% and 0.04%, respectively. This study provides a replicable approach for stakeholders and policymakers aiming to implement sustainable energy solutions, aligning with national renewable energy targets. Future research could integrate dynamic factors such as community engagement, land use changes, and evolving environmental policies to enhance decision-making models. This framework offers valuable insights into renewable energy planning and contributes to advancing Nigeria’s transition to sustainable energy systems.