A design methodology based on three dimensional spherical fuzzy linguistic variables for solar energy potential and penetration

Nigeria faces critical socio-economic challenges due to its dependence on fossil fuels and rapid population growth, leading to economic instability, environmental harm, health crises, and political unrest. These issues have widened the energy demand-supply gap, necessitating a shift to clean energy. Photovoltaic (PV) technology shows significant promises for addressing this gap and achieving Sustainable Development Goal-7 (SDG-7). However, localized challenges in Nigeria hinder PV adoption beyond global efficiency concerns. This study presents a decision methodology in Spherical Fuzzy (SF) environment to address uncertainty and minimize bias in evaluating solar energy (SE) challenges and policies. The approach integrates SF-Stepwise Weight Assessment Ratio Analysis (SWARA), SF-Criteria Importance Through Inter-criteria Correlation (CRITIC), and SF-COmbinative Distance-based Assessment (CODAS) techniques to assess challenges and rank policy alternatives. Based on expert opinions and literature, 12 challenges were identified and categorized, with subjective and objective weights determined using SF-SWARA and SF-CRITIC. The SF-CODAS ranked eight alternative policies to enhance SE potential and penetration. Key challenges include energy company debt, high generation costs, and affordability issues. Prioritized policies involve Research & Development supplementary funding, preventing sub-standard renewable products, and enabling research on PV maintenance. Sensitivity analysis confirms the robustness of the proposed methodology, offering structured solutions to Nigeria's energy challenges.