Research on a Multi-Level Reliability Assessment Method for Energy Storage Systems Based on Task Profiles

Energy storage system is a key component of modern power system, and its reliability directly affects the security and stability of grid operation. Traditional methods usually ignore the performance differences of energy storage system under different task load conditions, which makes it difficult to comprehensively reflect its operational characteristics. In this paper, a reliability assessment method of energy storage system based on task profile is proposed. First, the task profile of the energy storage system is obtained to extract key parameters such as the SOC curve, active output and ambient temperature of the energy storage battery, and to establish a correlation model with the operating state of the system; then, the rainfall counting method is used to extract the thermal load information of the key components and to construct a multilevel life model; finally, the reliability of the energy storage system under multi-task scenarios is obtained by combining Monte Carlo simulation with a Weibull distribution fitting distribution and operation curves under multi-task scenarios, and evaluate the failure probability and reliability performance of the system. Through simulation analysis, the results show that the proposed method can accurately portray the reliability characteristics of the energy storage system under complex operating conditions, which provides an important theoretical basis for the design optimization, operation and maintenance, and life prediction of the energy storage system.