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储能系统技术 储能系统 可靠性分析 ★ 5.0

基于精细化多状态建模的电池储能系统可靠性指标与评估

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

作者 Xiaohe Yan · Jialiang Li · Nian Liu
期刊 Applied Energy
出版日期 2025年1月
卷/期 第 393 卷
技术分类 储能系统技术
技术标签 储能系统 可靠性分析
相关度评分 ★★★★★ 5.0 / 5.0
关键词 Multi-dimensional indicators (basic temporal spatial) reflect BESS reliability identify weaknesses guide maintenance.
语言:

中文摘要

准确评估电池储能系统(BESS)的可靠性对于提高其运行效率、延长使用寿命以及降低维护成本具有重要意义。可靠性指标是实现BESS可靠性评估的关键环节。然而,当前的可靠性指标大多从BESS的整体角度出发进行设定,忽略了内部电池性能的退化过程,难以适用于大容量、多单元、拓扑结构复杂的BESS。因此,本文提出了一种基于BESS精细化多状态模型的可靠性指标体系及综合评价方法。首先,考虑电池单体的性能衰减,建立了基于电池单体健康状态(SOH)的多状态模型,并通过算子分裂的递归通用生成函数(UGF)方法将其扩展为BESS的多状态模型。然后,从基本维度、时间维度和空间维度三个方面提出了刻画BESS的可靠性指标体系。最后,基于带前景权重的云模型对BESS进行综合评估,并提出了BESS“优良—衰退—风险—缺陷—故障”的五状态分类方法。案例研究基于内蒙古某储能电站的实际BESS数据,结果表明,所提出的可靠性指标与方法能够有效反映不同拓扑结构BESS的可靠性性能变化特征。

English Abstract

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.
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SunView 深度解读

该电池储能系统多状态可靠性建模技术对阳光电源ST系列PCS及PowerTitan储能解决方案具有重要应用价值。论文提出的基于电芯SOH的精细化多状态模型和'良好-衰减-风险-缺陷-故障'五级分类体系,可直接应用于阳光电源大容量储能系统的健康管理。结合iSolarCloud平台的预测性维护功能,该可靠性指标体系能够从基础维度、时间维度和空间维度全面评估储能电站性能衰减,优化运维策略,延长系统寿命并降低维护成本,提升阳光电源储能产品的市场竞争力。