Applicability Evaluation of Retired Battery Echelon Utilization Scenarios Based on Game Theory and Multi-Attribute Decision Making

The rapid growth of electric vehicles has led to a surge in retired power batteries, yet scientific methods for selecting their echelon utilization scenarios remain lacking. This paper proposes an applicability evaluation method for echelon battery grid energy storage applications. First, an applicability evaluation index system for echelon battery grid energy storage scenarios is established from three dimensions: technical performance, economic performance, and safety performance. It comprehensively considers battery operating conditions, economic benefits of energy storage configuration, and safety risks of echelon utilization. Second, game theory and multi-attribute group decision-making are employed to optimize the weights of evaluation dimensions. A combination weighting method based on AEW and LBWA is used to assign weights to evaluation indicators, and a scenario applicability evaluation algorithm is developed using the DQGRA-MARCOS approach. Finally, the applicability of three typical grid energy storage scenarios—peak-valley arbitrage, renewable output smoothing, and frequency regulation—is quantitatively assessed based on the given state of retired power batteries.