OPTIMAL CAPACITOR SWITCHING IN A POWER DISTRIBUTION SYSTEM USING ANN

Abstract

In this thesis, an artificial neural network based algorithm for determining optimal capacitor switching pattern for a given loading condition in a radial distribution system has been developed. Traditionally, combinatorial methods have been used to decide the optimal switching patterns. However, these combinatorial methods take significant amount of time for a practical size power distribution system involving thousands of feeders. Hence, these algorithms may not be very suitable for on-line application in a modern distribution automation system. Functional Link Network (FLN) architecture has been used to determine the optimal capacitor-switching pattern. Here a new modified form of perceptron learning rule has been developed for training the FLN. It has been found that the time taken by ANN based method is quite less compared to the time taken by the traditional combinatorial methods