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Refined multi-state modeling based battery energy storage system reliability indicators and evaluation

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  • Yan, Xiaohe
  • Li, Jialiang
  • Liu, Nian

Abstract

Accurate reliability evaluation of the battery energy storage system (BESS) has great significance for enhancing BESS operational efficiency, extending service life, and reducing maintenance costs. The reliability indicators are the key link to realizing the reliability evaluation of BESS. However, current reliability indicators are mostly set up from the overall perspective of BESS, ignoring the internal battery performance degradation. These indicators do not apply to the large-capacity, multi-unit, and complex topology BESS. Therefore, this paper proposes a reliability indicator system and comprehensive evaluation method based on the refined multi-state model of BESS. Firstly, considering the performance decay of the battery cell, a multi-state model based on the state of health (SOH) of the battery cell is established. This model is expanded into a multi-state model of the BESS by combining the recursive Universal Generating Function (UGF) process of operator splitting. Then, a reliability indicator system for portraying BESS is proposed in terms of the basic dimension, temporal dimension, and spatial dimension. Finally, a comprehensive assessment of the BESS is carried out based on the extension cloud model with prospective weights, and a five-state classification of “Good-Decay-Risk-Defect-Failure” for BESS is proposed. The case study is based on the actual BESS in an energy storage power station in the Inner Mongolia. The results show that the proposed reliability indicators and methods can reflect the reliability performance variations of BESSs with different topologies efficiently.

Suggested Citation

  • Yan, Xiaohe & Li, Jialiang & Liu, Nian, 2025. "Refined multi-state modeling based battery energy storage system reliability indicators and evaluation," Applied Energy, Elsevier, vol. 393(C).
    • Handle: RePEc:eee:appene:v:393:y:2025:i:c:s0306261925007688
    DOI: 10.1016/j.apenergy.2025.126038
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