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

Abstract

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