基于动态规划的配微网安全防御策略

奚泽立; 陈聪; 杨新森; 詹细妹; 郭国伟; 张乾

doi:10.11930/j.issn.1004-9649.202507101

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基于动态规划的配微网安全防御策略

配微储协同新型电力系统多元资源协调优化调度与控制关键技术 | 更新时间：2026-02-03

- 基于动态规划的配微网安全防御策略
- Security defense strategy for distribution-microgrids based on dynamic programming
- 中国电力 2026年59卷第1期页码：97-104
- 作者机构：
  
  1. 广东电网有限责任公司佛山顺德供电局,广东,佛山,528300
  2. 武汉大学电气与自动化学院,湖北,武汉,430000
- 作者简介：
- 基金信息：
  
  国家重点研发计划资助项目（2024YFB2409303）;中国南方电网有限责任公司科技项目（GDKJXM20222480）。
- DOI：10.11930/j.issn.1004-9649.202507101
  中图分类号：
- 网络出版：2026-01-13，
  
  纸质出版：2026-01-13
- 稿件说明：
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奚泽立, 陈聪, 杨新森, 詹细妹, 郭国伟, 张乾. 基于动态规划的配微网安全防御策略[J]. 中国电力, 2026, 59(1): 97-104.

奚泽立, 陈聪, 杨新森, et al. Security defense strategy for distribution-microgrids based on dynamic programming[J]. 2026, 59(1): 97-104.
奚泽立, 陈聪, 杨新森, 詹细妹, 郭国伟, 张乾. 基于动态规划的配微网安全防御策略[J]. 中国电力, 2026, 59(1): 97-104. DOI： 10.11930/j.issn.1004-9649.202507101.

奚泽立, 陈聪, 杨新森, et al. Security defense strategy for distribution-microgrids based on dynamic programming[J]. 2026, 59(1): 97-104. DOI： 10.11930/j.issn.1004-9649.202507101.

摘要

基于信息物理融合结构的配微协同新型配电系统，为多能互补的能源优化调度提供了新的技术路径。然而，多种能源出力的强不确定性以及未知扰动导致发电难以精准调控，严重威胁系统的安全稳定运行。为应对这一挑战，提出了一种融合非对称结构建模的动态规划最优安全防御策略。将未知不确定性扰动与防御侧的非对称结构问题统一建模为非合作博弈框架，并利用自适应评判学习网络进行求解，实现防御资源的最优分配。仿真结果表明：所提策略能有效缓解非对称结构下的不确定性安全风险。

Abstract

The new distribution system based on the information-physical fusion structure provides a new technical path for the optimization and dispatch of multi-energy complementary energy

the strong uncertainty of multi-energy output and unknown disturbances make it difficult for power generation to be precisely regulated

which seriously threatens the safe and stable operation of the system. address this challenge

an optimal security defense strategy with dynamic programming is proposed by integrating asymmetric structure modeling. The unknown uncertainty disturbance and the asymmetric structure problem on the defense side are unified into non-cooperative game framework and are solved by using an adaptive evaluation learning network

which implements the optimal allocation of defense resources. Simulation results show that the proposed strategy can effectively the uncertainty security risk under asymmetric structure.

关键词

Keywords

references

1郭琦, 陈孟晓, 余佳微, 等. 考虑负荷灵活调节潜力的分布式能源系统能量管理策略[J]. 中国电力, 2025, 58 (8): 60- 68.

GUO Qi, CHEN Mengxiao, YU Jiawei, et al. Energy management strategy for distributed energy systems considering the regulation capability from flexible loads[J]. Electric Power, 2025, 58 (8): 60- 68.

2刘文军, 董伟杰, 陈远扬, 等. 新能源高渗透配电网柔性多状态开关的多目标优化控制策略[J]. 中国电力, 2025, 58 (1): 85- 92.

LIU Wenjun, DONG Weijie, CHEN Yuanyang, et al. Multi-objective optimization control strategy for soft open point in distribution network with high penetration of DG[J]. Electric Power, 2025, 58 (1): 85- 92.

3翟苏巍, 李银银, 杜凡, 等. 考虑海量分布式能源接入的配电网分布式无功控制策略[J]. 中国电力, 2024, 57 (8): 138- 144.

ZHAI Suwei, LI Yinyin, DU Fan, et al. Distributed reactive power control strategy of distribution network considering massive distributed energy access[J]. Electric Power, 2024, 57 (8): 138- 144.

4周洋, 黄德志, 李培栋, 等. 考虑平衡端点相位不对称及光伏接入的低压配电网三相潮流模型[J]. 中国电力, 2024, 57 (10): 190- 198.

ZHOU Yang, HUANG Dezhi, LI Peidong, et al. A three-phase power flow model for low-voltage distribution networks considering balanced bus phase asymmetry and photovoltaic access[J]. Electric Power, 2024, 57 (10): 190- 198.

5张叶青, 陈文彬, 徐律军, 等. 面向多虚拟电厂的分层分区多层互补动态聚合调控策略[J]. 发电技术, 2024, 45 (1): 162- 169.

ZHANG Yeqing, CHEN Wenbin, XU Lüjun, et al. Multi-virtual power plant-oriented dynamic aggregation control strategy based on hierarchical partition and multi-layer complementation[J]. Power Generation Technology, 2024, 45 (1): 162- 169.

6刘海鹏, 杨晓静, 陆涛, 等. 考虑分布式新能源的电网运行风险评估指标体系构建方法[J]. 浙江电力, 2024, 43 (12): 1- 14.

LIU Haipeng, YANG Xiaojing, LU Tao, et al. A method for constructing a risk assessment indicator system for grid operation considering distributed new energy sources[J]. Zhejiang Electric Power, 2024, 43 (12): 1- 14.

7钟永洁, 汤成俊, 王紫东, 等. 我国虚拟电厂的发展演进和关键技术及难点分析[J]. 浙江电力, 2025, 44 (2): 13- 31.

8KHALAF M, AYAD A, TUSHAR M H K, et al. A survey on cyber-physical security of active distribution networks in smart grids[J]. IEEE Access, 2024, 12, 29414- 29444.

9WU S T, WANG Q, CHEN Q C, et al. Cyber-physical integrated planning of distribution networks considering spatial-temporal flexible resources[J]. Protection and Control of Modern Power Systems, 2024, 9 (3): 142- 156.

10YANG B, LIU S W, GAO H D. Energy e-commerce user portrait and multi-agent cooperative game price mechanism design[J]. Frontiers in Energy Research, 2024, 12, 1379612.

11DING X, WANG H, ZHANG X, et al. Dual nature of cyber–physical power systems and the mitigation strategies[J]. Reliability Engineering & System Safety, 2024, 244, 109958.

12ZANG T L, WANG S J, WANG Z A, et al. Integrated planning and operation dispatching of source–grid–load–storage in a new power system: a coupled socio–cyber–physical perspective[J]. Energies, 2024, 17 (12): 3013.

13曲朝阳, 范旭东, 于华涛, 等. 基于本体的智能电网文本知识获取模型[J]. 东北电力大学学报, 2014, 34 (5): 60- 68.

QU Zhaoyang, FAN Xudong, YU Huatao, et al. Smart grid text knowledge acquisition model based on ontology[J]. Journal of Northeast Dianli University, 2014, 34 (5): 60- 68.

14严康, 陆艺丹, 白晓清, 等. 电力信息物理系统需求操控攻击策略及防护分析[J]. 电力系统自动化, 2025, 49 (8): 178- 188.

YAN Kang, LU Yidan, BAI Xiaoqing, et al. Manipulation of demand attack strategy and analysis of its defence for cyber-physical power system[J]. Automation of Electric Power Systems, 2025, 49 (8): 178- 188.

15DONG S, ZANG T L, ZHOU B X, et al. Robust coordinated resilience enhancement strategy for communication networks of power and thermal cyber-physical systems considering decision-dependent uncertainty[J]. Applied Energy, 2024, 368, 123494.

16GOLPÎRA H, FRANCOIS B. Artificial intelligence-based approach for islanding detection in cyber-physical power systems[J]. Chaos, Solitons & Fractals, 2024, 185: 115165.

17YAN X H, LI R Z, LIU N. Non-cooperative game based energy management method for prosumers considering operation cost of integrated system under uncertainty[J]. CSEE Journal of Power and Energy Systems, 2024. DOI:10.17775/CSEEJPES.2022.08780.

18DAS A, WU D, AHMAD BHATTI B, et al. Approximate dynamic programming with enhanced off-policy learning for coordinating distributed energy resources[J]. IEEE Transactions on Sustainable Energy, 2024, 15 (3): 1614- 1626.

19CUI Y, XU Y, LI Y, et al. Deep reinforcement learning based optimal energy management of multi-energy microgrids with uncertainties[J]. CSEE Journal of Power and Energy Systems, 2024. DOI:10.17775/CSEEJPES.2023.05120.

20LU X Q, LAI J G. Distributed cluster cooperation for multiple DC MGs over two-layer switching topologies[J]. IEEE Transactions on Smart Grid, 2020, 11 (6): 4676- 4687.

21NING B D, HAN Q L, DING L. A brief overview of recent advances in distributed accelerated secondary control for islanded AC microgrids[J]. IEEE Transactions on Industrial Informatics, 2025, 21 (9): 6605- 6614.

22李忠凡, 陈曦, 黄海涛. 基于多智能体分层强化学习的多园区综合能源系统优化运行[J]. 浙江电力, 2025, 44 (9): 46- 57.

LI Zhongfan, CHEN Xi, HUANG Haitao. Optimal operation of MPIESs based on hierarchical multi-agent reinforcement learning[J]. Zhejiang Electric Power, 2025, 44 (9): 46- 57.

23YANG X, HE H B. Event-driven H∞-constrained control using adaptive critic learning[J]. IEEE Transactions on Cybernetics, 2021, 51 (10): 4860- 4872.

24SUN J L, LIU C S. Distributed fuzzy adaptive backstepping optimal control for nonlinear multimissile guidance systems with input saturation[J]. IEEE Transactions on Fuzzy Systems, 2019, 27 (3): 447- 461.

25HUO X, KARIMI H R, ZHAO X D, et al. Adaptive-critic design for decentralized event-triggered control of constrained nonlinear interconnected systems within an identifier-critic framework[J]. IEEE Transactions on Cybernetics, 2022, 52 (8): 7478- 7491.

26WANG T, ZHANG L, XU N, et al. Adaptive critic learning for approximate optimal event-triggeredtracking control of nonlinear systems with prescribed performances[J]. International Journal of Control, 2024, 97 (9): 2009- 2023.

27LIU N, ZHANG K, XIE X P. Optimal control of unknown nonlinear system under event-triggered mechanism and identifier-critic-actor architecture[J]. International Journal of Robust and Nonlinear Control, 2024, 34 (1): 530- 550.

28马刚, 马健, 颜云松, 等. 基于多智能体强化学习的配电网电压分散控制[J]. 综合智慧能源, 2024, 46 (10): 32- 39.

MA Gang, MA Jian, YAN Yunsong, et al. Decentralized voltage control of distribution network based on multi-agent reinforcement learning[J]. Integrated Intelligent Energy, 2024, 46 (10): 32- 39.

30孙健浩, 初壮. 考虑碳交易和无功补偿的分布式电源优化配置[J]. 发电技术, 2024, 45 (1): 142- 150.

SUN Jianhao, CHU Zhuang. Optimal configuration of distributed generation considering carbon trading and reactive power compensation[J]. Power Generation Technology, 2024, 45 (1): 142- 150.

31王宣元, 李奇, 王泽森, 等. 考虑新能源消纳和电压偏差的配电网拓扑结构重构方法研究[J]. 湖南电力, 2025, 45 (3): 9- 17.

WANG Xuanyuan, LI Qi, WANG Zesen, et al. Research on distribution network topology reconfiguration method considering new energy consumption and voltage deviation[J]. Hunan Electric Power, 2025, 45 (3): 9- 17.

32娄征, 刘梅招, 景栋盛, 等. 基于改进证据理论的配电网多源数据融合方法[J]. 电测与仪表, 2025, 62 (5): 76- 81.

LOU Zheng, LIU Meizhao, JING Dongsheng, et al. A multi-source data fusion method for distribution network based on improved evidence theory[J]. Electrical Measurement & Instrumentation, 2025, 62 (5): 76- 81.

33黄海泉, 黄晓巍, 姜望, 等. 新型配电网分布式储能系统方案及配置研究综述[J]. 南方能源建设, 2024, 11 (4): 42- 53.

HUANG Haiquan, HUANG Xiaowei, JIANG Wang, et al. A review of distributed energy storage system solutions and configurations for new distribution grids[J]. Southern Energy Construction, 2024, 11 (4): 42- 53.

34姚军, 陆俊, 廖一璞, 等. 考虑配电网状态的共享储能优化运行方法[J]. 湖南电力, 2024, 44 (1): 67- 76.

YAO Jun, LU Jun, LIAO Yipu, et al. Optimal operation method of shared energy storage considering distribution network state[J]. Hunan Electric Power, 2024, 44 (1): 67- 76.

35杜龙, 沙建秀, 樊贝, 等. 基于信息物理双侧数据的配电网CPS窃电检测方法[J]. 综合智慧能源, 2024, 46 (5): 20- 29.

DU Long, SHA Jianxiu, FAN Bei, et al. Electricity theft detection method for distribution network CPS based on cyber and physical data[J]. Integrated Intelligent Energy, 2024, 46 (5): 20- 29.

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