基于提升韧性的输电网灾后应急维修策略优化

doi:10.11930/j.issn.1004-9649.202009052

中国电力 ›› 2022, Vol. 55 ›› Issue (3): 142-151.DOI: 10.11930/j.issn.1004-9649.202009052

基于提升韧性的输电网灾后应急维修策略优化

梁海平¹, 石皓岩¹, 王岩¹, 刘英培¹, 王鑫明²

1. 华北电力大学（保定）电力工程系，河北保定 071003;
2. 国网河北省电力有限公司，河北石家庄 050021

收稿日期:2020-09-07 修回日期:2021-10-25 出版日期:2022-03-28 发布日期:2022-03-29
作者简介:梁海平(1979—)，男，博士，讲师，从事现代电网评估、电力系统韧性提升、电力系统安全防御与恢复控制研究，E-mail：lianghaiping@aliyun.com;石皓岩(1996—)，男，硕士研究生，从事电力系统检修计划优化、电力系统韧性提升策略研究，E-mail：499261364@qq.com
基金资助:
国家自然科学基金资助项目(51607069)，国家电网有限公司科技项目(基于多源异构时空信息的电网运行方式智能互动决策关键技术研究，SGTYHT/17-JS-199)

Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks

LIANG Haiping¹, SHI Haoyan¹, WANG Yan¹, LIU Yingpei¹, WANG Xinming²

1. Department of Electrical Engineering, North China Electric Power University (Baoding), Baoding 071003, China;
2. State Grid Hebei Electric Power Co., Ltd., Shijiazhuang 050021, China

Received:2020-09-07 Revised:2021-10-25 Online:2022-03-28 Published:2022-03-29
Supported by:
This work is supported by National Natural Science Foundation of China (No.51607069), Science and Technology Project of SGCC (No.SGTYHT/17-JS-199)

摘要/Abstract

摘要： 极端自然灾害等事件易使输电网发生大范围故障。为减少经济损失，提升输电网灾后恢复能力，对输电网灾后应急维修策略优化进行研究。首先根据输电网韧性内涵，提出期望系统负荷恢复效率作为韧性评价指标；其次分析输电网灾后应急维修的过程，建立基于时间不确定的输电网灾后应急维修策略协同优化模型。该模型既考虑了输电网的韧性提升带来的经济性，又考虑灾后维修过程中的资源、路径规划等约束。针对该优化模型提出了改进的粒子群优化算法，采用多维不定长编码、子群协同优化、基于蒙特卡洛模拟的适应度评价等方法对标准粒子群算法进行改进。通过IEEE RTS-79算例对建立的协同优化模型进行了仿真验证，算例结果表明，改进粒子群算法能够有效求解所提优化模型，且输电网灾后应急维修策略协同优化模型的结果能够有效提升输电网韧性指标，提升灾后输电网应急维修的经济性。

关键词: 输电网韧性, 输电网灾后应急维修, 输电网韧性评价指标, 改进粒子群算法, 路径规划

Abstract: Extreme natural disasters and other events are likely to cause large-scale failures of the transmission networks. In order to minimize the economic losses and improve the post-disaster resilience of transmission networks, firstly, according to the connotation of transmission network resilience, the expected system load recovery efficiency is proposed as the resilience evaluation index; secondly, the post-disaster emergency maintenance process of transmission networks is analyzed, and a collaborative optimization model of time-uncertainty based post-disaster emergency maintenance strategy is established for transmission networks, which not only considers the resilience-improving economy of transmission networks, but also the constraints such as resources and path planning in the process of post-disaster maintenance. An improved particle swarm optimization (PSO) algorithm is proposed for the optimization model, which uses such methods as the multi-dimensional indefinite length coding, sub-group collaborative optimization, and Monte-Carlo-simulation-based fitness evaluation to improve the standard PSO algorithm. The simulation results of an IEEE RTS-79 case show that the improved particle swarm optimization algorithm can effectively solve the proposed optimization model, and the results of the collaborative optimization model can effectively improve the transmission network resilience index and the economy of post-disaster emergency maintenance.

Key words: transmission network resilience, post-disaster transmission network emergency maintenance, transmission network resilience evaluation index, improved particle swarm optimization algorithm, path planning

梁海平, 石皓岩, 王岩, 刘英培, 王鑫明. 基于提升韧性的输电网灾后应急维修策略优化[J]. 中国电力, 2022, 55(3): 142-151.

LIANG Haiping, SHI Haoyan, WANG Yan, LIU Yingpei, WANG Xinming. Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks[J]. Electric Power, 2022, 55(3): 142-151.

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基于提升韧性的输电网灾后应急维修策略优化

Resilience-Improving Based Optimization of Post-Disaster Emergency Maintenance Strategy for Transmission Networks

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