ANN BASED NOVEL APPROACH FOR IMPROVEMENT OF POWER SYSTEM SECURITY
Assistant Professor Department of Electrical Engineering, Sanjaybhai Rajguru college of engineering, India
ABSTRACT
This paper describes what is power system security, how it can be carried out in large networks, and new improvement to the existing defense . Completely reliable system against contingency is an objective, however, not possible. There will always be vulnerable in the network. This paper describes briefly some to methods to make system security more powerful . We also describe limitations of existing method to detect and prevention of these contingency in power system networks. Feed Forward Back Propagation Neural Network is used to classify the security condition of test bus system. The input data of ANN are derived from offline Newton Raphson load flow analysis. The result obtained from the ANN method is compared with the Newton Raphson load flow analysis in terms of accuracy to predict the security level of test bus system. The accuracy of 14 hidden neurons feed forward back propagation neural network to predict the security level of test bus system is 99.99%. In conclusion, ANN is found to be reliable to evaluate the security level of test bus system.
