Volume 3: Innovative Solutions for Energy Transitions: Part II

Perceptron Learning Model Based Reliability Evaluation Method of Medium Voltage Electrical Distribution Networks Yuxiong Huang, Gengfeng Li, Jinshi Wang

Abstract

This paper deals with the feasibility of using perceptron learning model to build an empirical model for the reliability evaluation of medium voltage electrical distribution networks. The main idea is to develop a novel reliability evaluation algorithm, by training the perceptron on a restricted sample set, and replace the conventional system state evaluation methods by a simpler calculation, which can quantitatively analyze the reliability and component importance of distribution networks. The proposed approach is illustrated by case studies.

Keywords electrical distribution networks, perceptron, reliability evaluation