文章基本信息

标题：Research on Load Recovery Optimization Strategy Based on Power Grid Partition
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作者：Yingzhe Huo ; Ting Wang ; Qun Wang 等
期刊名称：IOP Conference Series: Earth and Environmental Science
印刷版ISSN：1755-1307
电子版ISSN：1755-1315
出版年度：2019
卷号：300
期号：4
页码：1-9
DOI：10.1088/1755-1315/300/4/042111
出版社：IOP Publishing
摘要：Aiming at the problem of fast load recovery after power system blackout, an intelligent optimization strategy of load recovery based on grid partition is proposed. An optimal regionalization strategy for system recovery after major blackouts is proposed. In the optimization model, factors such as charging reactive power of overhead lines for generator recovery and closing times of lines for load recovery are taken into account. After optimizing the large-scale system partition, a unified load recovery optimization model considering network reconfiguration factors is established for each partition to realize the parallel load recovery of each partition. Aiming at the optimization model proposed above, the load recovery optimization problem based on power grid partition is solved by combining traditional graph theory and genetic algorithm. In the solution, the genetic algorithm is improved, and aiming at a large number of infeasible problems arising from the application of genetic algorithm, a method of random load rejection and shortest path repair strategy is proposed, which further improves the optimization efficiency and global optimization ability of the algorithm. The correctness and effectiveness of the proposed model and method are verified by simulation analysis of IEEE30-bus system.