Assessing Renewable Energy Alternatives with Multi-Criteria Decision-Making Techniques Based on Q-Rung Orthopair Fuzzy Sets

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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 socio-political 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. This framework provides valuable insights to policymakers, energy planners, and decision-makers, offering a reliable tool for navigating the complexities of renewable energy selection.
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Assessing Renewable Energy Alternatives with Multi-Criteria Decision-Making Techniques Based on Q-Rung Orthopair Fuzzy Sets | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Assessing Renewable Energy Alternatives with Multi-Criteria Decision-Making Techniques Based on Q-Rung Orthopair Fuzzy Sets Berk Ayvaz, Emine Elif Nebati, Ali Osman Kusakci, Selin Oral, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5507107/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 Feb, 2026 Read the published version in Soft Computing → Version 1 posted 6 You are reading this latest preprint version 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 socio-political 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. This framework provides valuable insights to policymakers, energy planners, and decision-makers, offering a reliable tool for navigating the complexities of renewable energy selection. Renewable Energy Energy Sources Fuzzy Sets Q-Rung Orthopair Multi-Criteria Decision-Making Full Text Cite Share Download PDF Status: Published Journal Publication published 07 Feb, 2026 Read the published version in Soft Computing → Version 1 posted Editorial decision: Major Revision 14 Aug, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers invited by journal 01 Apr, 2025 Editor invited by journal 21 Jan, 2025 Editor assigned by journal 16 Jan, 2025 First submitted to journal 25 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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