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

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。

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.