Intelligent computing based scheme for evolving fault events location in series compensated power networks

Abstract

This paper describes an intelligent computing based scheme for evolving fault events location in interconnected series compensated power networks. An evolving fault event is usually actuated with one phase and spread to other phases within few cycles. The varying characteristics and magnitudes of evolving event make it much more complicated than the commonly occurring shunt events in the network. The location of evolving events in the power network is very challenging mainly because it involves the quick transition of phases. An integrated scheme based on signal processing and intelligent computing is presented in this paper for location of the evolving shunt abnormalities in an interconnected series compensated transmission network. The prominent features pattern set corresponding to different evolving events in the network has been realized in proposed scheme using signal processing mechanism. Afterward, it has been fed to designed intelligent computing-based network model for identifying the site of evolving events in power network. A cascade forward back propagation neural network model has been utilized for ascertaining the distance of events in the network. The competency of the proposed integrated events tracing scheme has been evaluated for different evolving faults scenario on a simulated interconnected compensated power test network. The results acquired under all considered test cases have reasserted that the proposed integrated scheme is very effective and precise in ascertaining the location of evolving abnormality events in the compensated power transmission network.