基于电池老化评估与运行风险推演的配电网储能容量配置方法

刘乃胜; 王一; 马贵波; 李晓乐; 禇天舒; 王晓龙; 颜宁

doi:10.19799/j.cnki.2095-4239.2025.1170

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基于电池老化评估与运行风险推演的配电网储能容量配置方法

储能系统与工程 | 更新时间：2026-07-13

- 基于电池老化评估与运行风险推演的配电网储能容量配置方法
- The energy storage capacity allocation method for distribution networks based on battery aging assessment and operational risk simulation
- 储能科学与技术 2026年15卷第6期页码：2258-2268
- 作者机构：
  
  1.国网阜新供电公司，辽宁阜新 123000
  2.沈阳工业大学电气工程学院，辽宁沈阳 110870
- 作者简介：
  
  刘乃胜（1988—），男，硕士，高级工程师，研究方向为储能系统优化配置，E-mail：liunaisheng666666@126.com；
  颜宁，副教授，研究方向为电池状态估计、储能系统控制方法，E-mail：yanning@sut.edu.cn。
- 基金信息：
  
  国网科技部项目(2025YF-35)
- DOI：10.19799/j.cnki.2095-4239.2025.1170
  中图分类号： TM 734
- 收稿：2025-12-30，
  
  修回：2026-01-27，
  
  纸质出版：2026-06-28
- 稿件说明：
移动端阅览
刘乃胜, 王一, 马贵波, 等. 基于电池老化评估与运行风险推演的配电网储能容量配置方法[J]. 储能科学与技术, 2026, 15(6): 2258-2268.

LIU Naisheng, WANG Yi, MA Guibo, et al. The energy storage capacity allocation method for distribution networks based on battery aging assessment and operational risk simulation[J]. Energy Storage Science and Technology, 2026, 15(6): 2258-2268.
刘乃胜, 王一, 马贵波, 等. 基于电池老化评估与运行风险推演的配电网储能容量配置方法[J]. 储能科学与技术, 2026, 15(6): 2258-2268. DOI： 10.19799/j.cnki.2095-4239.2025.1170.

LIU Naisheng, WANG Yi, MA Guibo, et al. The energy storage capacity allocation method for distribution networks based on battery aging assessment and operational risk simulation[J]. Energy Storage Science and Technology, 2026, 15(6): 2258-2268. DOI： 10.19799/j.cnki.2095-4239.2025.1170.

摘要

为提升高比例可再生能源接入下配电网的运行韧性，延长储能系统服役寿命，本工作提出一种基于电池老化评估与运行风险推演的储能容量优化配置方法。首先，构建储能系统接入配电网的运行架构，基于电池健康状态（state of health，SOH）与容量衰减机制，建立描述不同运行阶段下电池寿命边界的多因素动态评估模型。其次，构建面向典型负荷变化、新能源波动与设备故障的多场景模拟体系，通过时序功率流计算与状态评估，推演节点电压越限、馈线过载与储能功率不足等关键运行风险的发生概率与空间分布特征。最后，考虑电池老化、电压越限概率、过充过放频率，构建电池寿命最大、系统风险最小与配电网运行成本最小的储能系统配置模型，通过多场景仿真，验证本工作配置方法，有效提高容量配置科学性、延长储能系统寿命及增强配电网运行可靠性。

Abstract

To enhance the operational resilience of distribution networks amid high penetration of renewable energy and extend the service life of energy storage systems (ESS)

we propose an optimal ESS capacity configuration method based on battery aging assessment and operational risk delineation. First

we construct the operational architecture of the ESS incorporated into a distribution network. Drawing on the battery state of health and capacity degradation mechanism

we establish a multifactor dynamic evaluation model that delineates the lifespan boundaries of batteries across different operational phases. Second

we develop a multiscenario simulation system accounting for typical load variations

renewable energy fluctuations

and equipment failures. Through time-series power flow calculation and state assessment

we delineate the occurrence probability and spatial distribution characteristics of key operational risk factors

including node voltage deviations

feeder overloads

and ESS power inadequacy. Finally

considering battery aging

voltage deviation probability

and overcharging frequency

we formulate an ESS configuration model to optimize battery lifespan

system risk

and distribution network operational cost. Multiscenario simulations verify that the proposed ESS configuration method effectively enhances the scientific rigor of capacity configuration

extends ESS lifespan

and strengthens the operational reliability of distribution networks.

关键词

Keywords

references

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