Optimal reconfiguration of distribution network based on deep fuzzy c-means clustering algorithm

Abstract

Abstract This study examines the best distribution network reconfiguration to enhance distribution network safety and reduce active power loss. Distribution networks can be reconfigured using a deep fuzzy C-means (FCM) clustering method with the objective of the least amount of active power loss. By creating a novel framework, the size of the neural network is lowered by modifying the number of neurons in input layer. With the simulations tested on IEEE 33-bus distribution network, the outcomes of traditional approaches, such as the Branch-and-Cut and the switching algorithms, are contrasted with the simulation results. The comparative results clearly show advantages to employing the suggested framework for distribution network reconfiguration, such as a quick turnaround time far quicker than the alternatives. These characteristics demonstrate how well the suggested paradigm may be applied to distribution network real-time reconfiguration.