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This is a Quantitative Study study.

October 17, 2025Open Access

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

Key Points

The study reveals thin-film PV modules, hybrid supercapacitor batteries, and modular converters as the top technologies for hybrid energy.
The ranking achieved robustness through the use of multiple weighted MCDM techniques and comparative validation across methods.
Results indicate a strong correlation across MCDM methods, enhancing the reliability of the proposed ranking outcomes.
This framework serves as a decision-support tool for engineers and policymakers, promoting sustainable energy infrastructure development.

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.

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Cite This Study

Kaur et al. (Tue,) studied this question.

synapsesocial.com/papers/68f199b7de32064e504dc828 https://doi.org/https://doi.org/10.3390/en18205410

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