To address the limitations of existing energy storage technology evaluations—specifically the lack of horizontal comparisons under unified scenarios and inadequate research on adaptability under extreme conditions. This paper constructs a comprehensive utility evaluation system for new energy storage based on Grey Fuzzy Theory. This system comprises four core criterion layers, namely technical performance, economy, reliability and environmental impact, and scenario adaptability, along with 11 quantitative indicators. To enhance the objectivity of the evaluation, a combined weighting method integrating Grey Relational Analysis (GRA) and the Entropy Weight Method (EWM) is adopted to determine the indicator weights. To adapt to complex practical operating conditions, a dynamic update mechanism for energy storage evaluation factors is established, which considers both the service demand structure and physical operating environment; correspondingly, a scenario correction coefficient matrix and an extreme environmental risk correction matrix are constructed. Taking four mainstream energy storage technologies—Electrochemical Energy Storage (EES), Compressed Air Energy Storage (CAES), Gravity Energy Storage (GES), and Flywheel Energy Storage (FES) as research objects, case studies are carried out under multiple typical scenarios. The results indicate that in balanced service scenarios, EES achieves the highest comprehensive score of 0.7912; in high-ramping scenarios, GES attains the highest comprehensive score of 0.8457; and in extreme high-temperature and high-frequency regulation scenarios, FES achieves the highest comprehensive score of 0.7372. The research findings provide a solid theoretical basis for energy storage technology selection, safety management, and policy formulation in new power systems.
安海云 et al. (Thu,) studied this question.