POWER SYSTEM NETWORK TOPOLOGY PROCESSING BASED ON ARTIFICIAL NEURAL NETWORKS

摘要

In this paper, a new approach for the determination of power system network topology based on Artificial Neural Networks (ANN) has been suggested. For the determination of power system network topology, three models of ANN based on Multilayer perceptron using Backpropagation Algorithm (BPA), Functional Link Network (FLN) and Counterpropagation Network (CPN) have been utilized and tested for both noisy as well as noise free data sets. ANN models based on BPA, FLN and CPN have been tested on IEEE 14-bus, IEEE 57-bus and a 75-bus practical Indian system. It has been established that the CPN based model predicts network topology more accurately as compared to the FLN and BPA based models in all test cases. Further, the CPN model is able to determine the network topology even if the network is unobservable for which the conventional network topology algorithm fail to determine the topology.