A novel fault diagnosis method for battery energy storage station based on differential current

Chao Li, Kaidi Zeng, Guanzheng Li, Peiyu Chen and Bin Li

Applied Energy, 2023, vol. 352, issue C, No S030626192301334X

Abstract: Nowadays, an increasing number of battery energy storage station (BESS) is constructed to support the power grid with high penetration of renewable energy sources. However, many accidents occurred in BESSs threaten the development of the BESS, so it is important to develop a protection method for the BESS. In this work, a novel fault diagnosis method based on differential current is proposed, which can identify the short circuit fault rapidly and effectively. Firstly, in order to simulate the short circuit fault characteristic of a BESS, a linear varying parameter battery equivalent circuit model (ECM) which can demonstrate the short circuit current are established based on the manta ray foraging optimization (MRFO) algorithm. Secondly, the fault diagnosis method based on differential current is proposed and analyzed through the calculation of short circuit current (SCC) in BESS. Finally, different working state data of battery are used to verify the fault diagnosis method. The results show that the proposed method can effectively diagnose the short circuit fault. In summary, the proposed fault diagnosis method based on differential current is efficient in protecting the BESS.

Keywords: Fault diagnose; Battery energy storage station; Differential current; Battery modelling; Fault characteristics (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2023.121970

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