Assessing renewable energy alternatives with multi-criteria decision-making techniques based on q-rung orthopair fuzzy sets

Abstract

In recent years, countries have prioritized the selection of viable renewable energy alternatives, driven by the urgent need for a transition to sustainable energy. Selecting appropriate energy sources requires careful consideration of social, political, economic, and technological factors. This study proposes a comprehensive framework for evaluating renewable energy alternatives using a combination of the CRITIC (Criteria Importance Through Intercriteria Correlation) and MABAC (Multi-Attributive Border Approximation area Comparison) methods, enhanced by quantum-Rung Fuzzy Sets. A detailed evaluation is performed using 22 sub-criteria, grouped into environmental, technological, economic, and sociopolitical dimensions, to assess renewable sources such as wind, solar, geothermal, biomass, wave, hydraulic, and hydrogen. Expert input and literature guide the criteria selection. The model is applied in a case study of the Turkish energy sector, revealing hydrogen as the most promising alternative. Sensitivity analysis confirms the robustness of the results, showing no significant changes in the ranking of energy alternatives. To the best of the authors’ knowledge, this is the first study to combine CRITIC and MABAC methods within the q-ROFS domain to solve the problem of selecting a renewable energy source. This framework provides valuable insights to policymakers, energy planners, and decision-makers, offering a reliable tool for navigating the complexities of renewable energy selection.