An interval-valued spherical fuzzy framework for strategic renewable energy selection

Abstract

Many countries are prioritizing renewable energy sources in response to fossil fuel depletion, environmental concerns, and the need for energy resilience. This study evaluates five renewable energy alternatives: Biomass, Wind, Solar, Geothermal, and Hydro, with the aim of reducing foreign energy dependency and enhancing flexibility under potential geopolitical disruptions. A three-stage hybrid decision-making framework is proposed, integrating Modified Preference Selection Index (MPSI) and Multi-Attributive Border Approximation Area Comparison (MABAC) methods within an Interval-Valued Spherical Fuzzy (IVSF) environment. In the first stage, expert input is collected. The second stage applies IVSF-MPSI to determine the criteria weights under uncertainty. The third stage employs IVSF-MABAC to rank the alternatives based on these weights. The results indicate that Solar Energy, with a distance value of 0.2783, is the most suitable renewable energy, followed by Wind, Hydro, Geothermal, and Biomass. The proposed IVSF-MPSI-MABAC model equips decision-makers with a mathematically rigorous, uncertainty-resilient evaluation framework that supports quantitative trade-off analysis, prioritization of capital-intensive projects, and alignment of renewable energy portfolios with long-term energy security and sustainability objectives, while the integrated sensitivity analysis ensures ranking stability and robustness against variations in decision parameters.