Evaluating batteries for renewable energy storage: A hybrid MCDM framework based on combined objective weights and uncertainty-preserved COPRAS

Battery technologies offer promising solutions for renewable energy storage. However, selecting the most suitable battery requires proper investigation. This study introduces a multi-criteria decision-making framework assessing batteries based on various criteria and uncertain data, by using combined objective weighting method an uncertainty-preserved complex proportional assessment (UP-COPRAS). The proposed ensures objectivity fairness in result integrating interval entropy gray relational coefficient-supported trial evaluation laboratory to capture variation correlation degrees among criteria. After incorporating numbers with compensatory ranking method, UP-COPRAS prioritizes simple yet rigorous way data. To test feasibility of framework, illustrative case was employed assess four alternatives five-dimensional system. Through results comparison, two mathematical contributions are confirmed. First, uses features numerical data determine weights, which prevents subjective manipulation eliminates bias statistical analysis. Second, preserves uncertainties throughout evaluation, resulting rational decision output eliminating interference original