基于数据驱动响应约束的配电网可靠性评估方法

张帅; 刘文霞; 刘佳怡; 王雅姝; 成锐

doi:10.19725/j.cnki.1007-2322.2024.0042

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基于数据驱动响应约束的配电网可靠性评估方法

智能电网 | 更新时间：2026-06-02

- 基于数据驱动响应约束的配电网可靠性评估方法
- A Data-driven Response Constraint-based Reliability Assessment Method for Distribution Networks
- 现代电力 2026年43卷第3期页码：401-412
- 作者机构：
  
  新能源电力系统国家重点实验室 (华北电力大学) , 北京市昌平区,102206
- 作者简介：
  
  张帅(1994)，男，博士研究生，研究方向为电力系统可靠性评估、深度学习等，E-mail：zsrfkl@ncepu.edu.cn
  刘文霞(1967)，女，通信作者，教授，博士生导师，研究方向为电力系统规划与可靠性、电力系统风险评估等，E-mail：liuwenxia001@163.com
  刘佳怡(2001)，女，硕士研究生，研究方向为电力系统风险评估，E-mail：ljy15632324445@163.com
- 基金信息：
  
  中国博士后科学基金资助项目(GZC20230785)。
- DOI：10.19725/j.cnki.1007-2322.2024.0042
  中图分类号： 3
- 纸质出版：2026
- 稿件说明：
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张帅, 刘文霞, 刘佳怡, 等. 基于数据驱动响应约束的配电网可靠性评估方法[J]. 现代电力, 2026,43(3):401-412.

ZHANG Shuai, LIU Wenxia, LIU Jiayi, et al. A Data-driven Response Constraint-based Reliability Assessment Method for Distribution Networks[J]. 2026, 43(3): 401-412.
张帅, 刘文霞, 刘佳怡, 等. 基于数据驱动响应约束的配电网可靠性评估方法[J]. 现代电力, 2026,43(3):401-412. DOI： 10.19725/j.cnki.1007-2322.2024.0042.

ZHANG Shuai, LIU Wenxia, LIU Jiayi, et al. A Data-driven Response Constraint-based Reliability Assessment Method for Distribution Networks[J]. 2026, 43(3): 401-412. DOI： 10.19725/j.cnki.1007-2322.2024.0042.

摘要

为量化具有能流互济的综合能源系统（integrated energy system，IES）接入对配电网可靠性的影响，提出一种基于数据驱动响应约束的配电网-综合能源系统可靠性评估方法。首先，分析综合能源系统接入对配电网可靠性的影响，提出配电网–综合能源系统可靠性评估框架；建立基于数据驱动的IES优化运行模型，采用深度确定性策略梯度（deep deterministic policy gradient

DDPG）算法实现综合能源系统最优经济调度；基于大M法和分段线性化法将训练好的DDPG模型线性化，构建数据驱动响应约束；最后结合数据驱动响应约束，以配电网失负荷量最少为目标函数，建立混合整数线性规划的配电网最优切负荷模型，通过IEEE RBTS-BUS6算法验证其有效性。算例表明，所提模型能够实现不完全信息下配电网的可靠性评估，IES通过能流互补为配电网提供可靠性支撑。

Abstract

To quantify the impact of IES access with interconnected energy flows on the reliability of distribution networks

a data-driven response constraint-based reliability assessment method is proposed for distribution networks and IES. Firstly

the impact of IES access on the reliability of distribution networks is analyzed

and a reliability assessment framework is proposed for distribution networks and IES. A data-driven optimization operation model for IES is developed

and a deep deterministic policy gradient (DDPG) algorithm is utilized to achieve the optimal economic dispatch of the IES. Subsequently

the trained DDPG model is linearized using the large M method and segmented linearization method to construct data-driven response constraints. Finally

with minimizing load loss in the distribution network as the objective

the data-driven response constraints are combined to establish the optimal load-slicing model of the distribution network with mixed-integer linear programming

and its validity is verified through IEEE RBTS-BUS6 system. Examples demonstrate that the proposed model can realize the reliability assessment for distribution networks under the condition of incomplete information

while IES provides reliability support for distribution networks through interconnected energy flow.

关键词

Keywords

references

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