Development of Ann based System for Stable and Efficient Power Distribution System

Abstract

The electric power system consists of large number of interconnected components that work together to generate and deliver electrical power to many load points scattered over a wide geographical area. In order to satisfy the modem age power needs, it is very much essential to plan ahead for higher power generation and design of efficient transmission and distribution systems. The increasing demand for high power quality has increased the demand for power quality monitoring tools.

The distribution systems are normally configured radially for effective coordination of their protection scheme. Most networks are sectionalized by using switches.

The objective of this study is to develop ANN based system for Evaluation of Stability of Electrical Power Distribution Systems. The will input the parameters of the network branches and train itself whether system is stable and then apply to check stability of other branches of network. Artificial Neural Networks have emerged as a major paradigm for Data Mining applications. Neural nets have gone through two major development periods -the early 60’s and the mid 80’s. They were a key development in the field of machine learning. Artificial Neural Networks were inspired by biological findings relating to the behavior of the brain as a network of units called neurons.

Attempt is made to build a classifier that can identify the stability of a particular electrical distribution system from its characteristics. Six voltage characteristics of the distribution system will be considered. Neural networks have proved themselves as proficient classifiers and are particularly well suited for addressing non-linear problems. This is achieved by presenting previously recorded inputs to a neural network and then tuning it to produce the desired target outputs.

The results are presented for the above using trained ANN.