Power distribution network reconstruction method based on adaptive fuzzy C-means clustering scene division

The invention discloses a power distribution network reconstruction method based on adaptive fuzzy C-means clustering scene division. The method comprises the steps of 1, obtaining a typical scene ofthe operation of a power distribution network through adaptive fuzzy C-means clustering according to the prediction data of DG output and load, 2, establishing a power distribution network reconstruction model based on the typical scene, and 3, solving the power distribution network reconstruction model through a particle swarm algorithm to obtain an optimized topological structure. The inventionprovides the power distribution network reconstruction method which considers various operation scenes and is simple in calculation method, and the operation network loss of the power distribution network after structure optimization is reduced. 本发明公开了一种基于自适应模糊C均值聚类场景划分的配电网重构方法，其步骤包括：1.根据DG出力和负荷的预测数据，通过自适应模糊C均值聚类得到配电网运行的典型场景；2.基于典型场景建立配电网重构模型；3.通过粒子群算法对配电网重构模型进行求解，得到优化后的拓扑结构。本发明提供了一种考虑多种运行场景的同时计算方法简单的配电网重构方法，结构优化后的配电网运行网损得