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.
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.
The energy storage capacity allocation method for distribution networks based on battery aging assessment and operational risk simulation
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.
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