A decision support system for assessing the barriers and policies for wind energy deployment

Addressing Africa's energy infrastructure gap, including generation, distribution, and transmission, demands substantial investment, with a portion allocated to renewable energy technologies like wind energy. The significant scale-up of wind energy can yield substantial socioeconomic benefits for countries. However, there are barriers that, if not adequately addressed, can impede its adoption and expansion across the continent. For the first time, this study assessed these barriers and associated policies for its deployment using spherical fuzzy sets (SFSs), which enables modeling vagueness in evaluations while reducing bias. The study presents a decision support system incorporating the Best Worst Method (BWM), Criteria Importance Through Inter-criteria Correlation (CRITIC), and VIšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) within a spherical fuzzy (SF) framework. Five policy alternatives were considered, and to rank them, 23 barriers were identified and categorized into five main groups based on a literature review and expert opinions. Subsequently, the BWM and SF-CRITIC methods were utilized to establish both subjective and objective weights for these barriers. Finally, the SF-VIKOR method was employed to rank the five policy alternatives. While the most critical barriers include “Not in My Backyard” (NIMBY) concerns, limited subsidies compared to fossil fuels, the absence of institutions and mechanisms for information dissemination, non-liberalized market, and a shortage of critical human resources, the most appropriate policy remains the renewable obligations standard (ROS). Sensitivity analysis was applied to demonstrate the robustness of the proposed methodology.