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- W4376472199 abstract "The cascade utilization of retired lithium batteries to build an energy storage system is an effective means to achieve my country's dual-carbon goal, but safety issues restrict large-scale promotion and application. Accurately assessing the operational risk of cascade batteries in an energy storage system can ensure the safe operation of the system. This paper defines the risk of retired power batteries in the energy storage system, and establishes the risk with the remaining useful life (RUL), state of charge (SOC)and temperature rise rate of the echelon battery as the evaluation factors. Evaluate the model. In this paper, the BP (back propagation) neural network algorithm is used to estimate the RUL of the echelon battery, and the nonlinear model of the echelon battery is used to estimate the SOC and the temperature rise rate. Combined with the AHP (analytic hierarchy process) method and K-means mean aggregation. The class method estimates the subjective and objective weights of the evaluation indicators. This method can complete the risk assessment and determine the warning threshold value, and finally realize the real-time operation risk estimation during the operation of the echelon battery. The calculation example shows that the method can realize the operation risk assessment of the cascade battery energy storage system, improve the safety of the system, and promote the large-scale popularization and application of the cascade battery energy storage system." @default.
- W4376472199 created "2023-05-14" @default.
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- W4376472199 date "2023-01-01" @default.
- W4376472199 modified "2023-10-16" @default.
- W4376472199 title "Risk Assessment of Retired Power Battery Energy Storage System" @default.
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- W4376472199 doi "https://doi.org/10.1007/978-981-99-1027-4_74" @default.
- W4376472199 hasPublicationYear "2023" @default.
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