Sustainable Component-Level Prioritization of PV Panels, Batteries, and Converters for Solar Technologies in Hybrid Renewable Energy Systems Using Objective-Weighted MCDM Models

Swapandeep Kaur (), Raman Kumar () and Kanwardeep Singh
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Swapandeep Kaur: Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, Punjab, India
Raman Kumar: Department of Mechanical and Production Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, Punjab, India
Kanwardeep Singh: Department of Electrical Engineering, Guru Nanak Dev Engineering College, Ludhiana 141006, Punjab, India

Energies, 2025, vol. 18, issue 20, 1-43

Abstract: Data-driven prioritization of photovoltaic (PV), battery, and converter technologies is crucial for achieving sustainability, efficiency, and cost-effectiveness in the increasingly complex domain of hybrid renewable energy systems (HRES). Conducting an in-depth and systematic ranking of these components for solar-based HRESs necessitates a comprehensive multi-criteria decision-making (MCDM) framework. This study develops as the most recent and integrated approach available in the literature. To ensure balanced and objective weighting, five quantitative weighting techniques, Entropy, Standard Deviation, CRITIC, MEREC, and CILOS, were aggregated through the Bonferroni operator, thereby minimizing subjective bias while preserving robustness. The final ranking was executed using the measurement of alternatives and ranking according to compromise solution method (MARCOS). Subsequently, comparative validation was conducted across eight additional MCDM methods, supplemented by correlation and sensitivity analysis to evaluate the consistency and reliability of the obtained results. The results revealed that thin-film PV modules (0.7108), hybrid supercapacitor batteries (0.6990), and modular converters (1.1812) emerged as the top-performing technologies, reflecting optimal trade-offs among technical, economic, and environmental performance criteria. Correlation analysis (ρ > 0.9 across nine MCDM methods) confirmed the stability of the rankings. The results establish a reproducible decision-support framework for designing sustainable hybrid systems. These technologies demonstrated superior thermal stability, cycling endurance, and system scalability, respectively, thus laying a foundation for more sustainable and resilient hybrid energy system deployments. The proposed framework provides a reproducible, transparent, and resilient decision-support tool designed to assist engineers, researchers, and policy-makers in developing reliable low-carbon components for the realization of future carbon-neutral energy infrastructures.

Keywords: hybrid renewable energy systems (HRES); multi-criteria decision-making (MCDM); MARCOS method; photovoltaic (PV) technologies; battery storage technologies; converter topologies; Bonferroni operator; sustainability assessment; correlation analysis; sensitivity analysis (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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