Online Frequency Regulation Optimization Strategy for Energy Storage Clusters Considering Degradation Cost and State of Charge Balancing

SUN Yong; LUO Renjie; WANG Jie; ZHUANG Yuxuan; LI Zhiyi

doi:10.7500/AEPS20250831006

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Online Frequency Regulation Optimization Strategy for Energy Storage Clusters Considering Degradation Cost and State of Charge Balancing

Basic Research | 更新时间：2026-09-01

- Online Frequency Regulation Optimization Strategy for Energy Storage Clusters Considering Degradation Cost and State of Charge Balancing
- Automation of Electric Power Systems Vol. 50, Issue 17, Pages: 153-163(2026)
- 作者机构：
  
  1.国网吉林省电力有限公司延边供电公司，吉林省延边朝鲜族自治州 133000
  2.浙江大学电气工程学院，浙江省杭州市 310027
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2022YFB2404002)
- DOI：10.7500/AEPS20250831006
  CLC：
- Received：31 August 2025，
  
  Revised：2026-03-17，
  
  Online First：31 July 2026，
  
  Published：10 September 2026
- 稿件说明：
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孙勇,罗仁杰,王洁等.考虑退化成本与荷电状态均衡的储能集群在线调频优化策略[J].电力系统自动化,2026,50(17):153-163.

SUN Yong,LUO Renjie,WANG Jie,et al.Online Frequency Regulation Optimization Strategy for Energy Storage Clusters Considering Degradation Cost and State of Charge Balancing[J].Automation of Electric Power Systems,2026,50(17):153-163.
孙勇,罗仁杰,王洁等.考虑退化成本与荷电状态均衡的储能集群在线调频优化策略[J].电力系统自动化,2026,50(17):153-163. DOI： 10.7500/AEPS20250831006.

SUN Yong,LUO Renjie,WANG Jie,et al.Online Frequency Regulation Optimization Strategy for Energy Storage Clusters Considering Degradation Cost and State of Charge Balancing[J].Automation of Electric Power Systems,2026,50(17):153-163. DOI： 10.7500/AEPS20250831006.

摘要

随着可再生能源并网规模的不断扩大，传统电网调频能力不足的问题日益凸显。新型储能凭借其灵活的响应特性，已成为二次调频的重要支撑。然而，单一类型储能在自动发电控制（AGC）调频能力上存在局限性，且储能电站的状态耦合特性使得当前调频决策对后续技术经济影响的评估变得复杂难辨。因此，文中提出一种考虑退化成本与荷电状态（SOC）均衡的储能集群在线调频优化策略。上层模型首先基于邻近传播算法对储能电站进行集群划分，得到具有分布特性的储能集群；然后，基于李雅普诺夫优化方法，在无需储能显式能量约束和电网负荷预测信息的前提下，建立储能集群的在线AGC调频响应模型。下层模型基于容量感知注水算法，构建兼顾储能电站退化成本与SOC均衡特性的在线分配策略。通过算例分析验证了所提模型的有效性。该双层模型能够在不需要预测信息的前提下，准确响应调频信号，并有效提升储能集群的调频收益，扩展聚合功率可调节域。所提策略不仅能够兼顾调频过程中的鲁棒性与非预期性，且通过储能集群划分与功率合理分配显著提升了调频效率。

Abstract

With the continuous expansion of grid-connected scale of renewable energy

the insufficient frequency regulation capability of traditional power grids has become increasingly prominent. Relying on its flexible response characteristics

the new energy storage has become a critical support for secondary frequency regulation. Nevertheless

the single-type energy storage has limitations in automatic generation control (AGC) frequency regulation capability. Moreover

the state coupling characteristics of energy storage stations complicate the evaluation of the technical and economic impacts of current frequency regulation decisions on subsequent operation. Therefore

this paper proposes an online frequency regulation optimization strategy for energy storage clusters considering the degradation cost and state of charge (SOC) balancing. In the upper-layer model

energy storage stations are clustered based on the affinity propagation algorithm to obtain energy storage clusters with distributed characteristics. Subsequently

an online AGC frequency regulation response model for energy storage clusters is established using the Lyapunov optimization method

without requiring explicit energy constraints of energy storage devices or grid load forecasting information. The lower-layer model constructs an online power allocation strategy considering both the degradation cost and SOC balancing characteristics of energy storage stations via the capacity-aware water-filling algorithm. Case studies verify the effectiveness of the proposed model. This two-layer model can accurately track frequency regulation signals without forecasting data

effectively improve the frequency regulation revenue of energy storage clusters

and expand the adjustable range of aggregated power. The proposed strategy not only balances robustness and unpredictability during frequency regulation

but also significantly boosts frequency regulation efficiency through energy storage cluster partitioning and rational power allocation.

关键词

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references

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