A Spatial Analysis for Optimal Wind Site Selection from a Sustainable Supply-Chain-Management Perspective

Finding optimal locations for wind farms requires a delicate balance between maximizing energy generation potential and addressing the socio-economic implications for local communities, particularly in regions facing socio-economic challenges. While existing research often focuses on technical and economic aspects of wind farm siting, this study addresses a crucial research gap by integrating sustainable supply-chain-management principles into a comprehensive site-selection framework. We present a novel approach that combines Geographic-Information-System-based spatial analysis, the Fuzzy Analytic Hierarchy Process, and multi-criteria decision-making techniques to identify and prioritize optimal wind farm locations in Tunisia. Our framework considers not only traditional factors, like wind speed, terrain slope, and road and grid infrastructure, but also crucial socio-economic indicators, such as unemployment rates, population density, skilled workforce availability, and land cost. Based on the spatial analysis, it was revealed that 33,138 km 2 was appropriate for deploying large-scale wind systems, of which 6912 km 2 (4.39% of the total available area) was categorized as “most suitable”. Considering the SSCM evaluation criteria, despite the minor variations, the ARAS, COPRAS, EDAS, MOORA, VIKOR, and WASPAS techniques showcased that Kasserine, Kebili, and Bizerte stood as ideal locations for hosting large-scale wind systems. These rankings were further validated by the Averaging, Borda, and Copeland methods. By incorporating this framework, the study identifies locations where wind energy development can be a catalyst for economic growth, social upliftment, and improved livelihoods. This holistic approach facilitates informed decision making for policymakers and investors, thus ensuring that wind energy projects contribute to a more sustainable and equitable future for all stakeholders.