Comprehensive performance assessment of energy storage systems for various application scenarios based on fuzzy group multi criteria decision making considering risk preferences

Abstract

The energy storage (ES) is an indispensable flexible resource for green and low-carbon transformation of energy system. However, ES application scenarios are complex. Therefore, scientifically assessing the applicability of different energy storage systems in various scenarios is prominent for the development of ES industry. This paper proposes an integrated fuzzy-GMCDM (group multi criteria decision making) method for achieving the above objective. In the proposed method, the comprehensive performance assessment index system consists of 10 indicators from the perspectives of technology, economy, efficiency and environment based on fuzzy Delphi model. The optimal aggregation weights can reflect the total judgments of all experts are determined by Bayesian Best-Worst method. Fuzzy cumulative prospect theory is employed to maximize the use of objective data, and prioritize the rankings of alternatives under various scenarios considering risk preferences of decision-makers. The results show that this method can provide decision-makers with the optimal solutions for ES selection in various scenarios such as renewable energy consumption and ancillary services. Furthermore, risk preferences with respect to the 4 aspects, affect the optimal choice and the rankings of ES systems, especially for the flywheel ES, sodium‑sulfur battery and vanadium redox flow battery.