A fast-partitioning decision method for demand side resources based on grid resilience assessment

Yueping Kong, Shihai Yang, Meimei Duan, Yuqi Zhou, Zecheng Ding, Tingquan Zhang, Ju Sheng
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Abstract

With the large-scale renewable energy integrated into the distribution grid, the grid’s regulating ability and disturbance tolerance are weakening. When partitioning demand-side resources, it is necessary to enhance resilience to ensure the reliability of electric power. This paper proposes a fast-partitioning method that considers resilience, structure, and functionality to adapt to the evolving requirements of the distribution system. Specifically, the comprehensive partition index system is constructed with the resilience assessment index reflecting the ability of partitions to withstand and mitigate the effects of faults, the modularity index based on electrical distance, and regional power balance indexes. Meanwhile, a modified genetic algorithm is proposed to calculate the comprehensive partition index. The modified algorithm first uses a sensitivity matrix to perform initial partitions and construct initial populations. Then, it utilizes a triangular network adjacency matrix for chromosome encoding, significantly reducing the algorithm’s search space and enhancing partitioning efficiency. Finally, the applicability and effectiveness of the proposed method are verified through simulation analysis of the IEEE 28-node system.
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基于电网恢复能力评估的需求侧资源快速分区决策方法
随着大规模可再生能源并入配电网,电网的调节能力和抗干扰能力不断减弱。在对需求侧资源进行分区时,有必要提高其弹性,以确保电力的可靠性。本文提出了一种兼顾弹性、结构和功能的快速分区方法,以适应配电系统不断发展的要求。具体而言,通过反映分区抵御和减轻故障影响能力的复原力评估指标、基于电气距离的模块化指标和区域电力平衡指标,构建了综合分区指标体系。同时,提出了一种改进的遗传算法来计算综合分区指数。改进后的算法首先使用灵敏度矩阵进行初始分区并构建初始种群。然后,利用三角形网络邻接矩阵进行染色体编码,大大缩小了算法的搜索空间,提高了分区效率。最后,通过对 IEEE 28 节点系统的仿真分析,验证了所提方法的适用性和有效性。
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