Evaluation Algorithm for Discrimination between Fault and Power Swing Using Independent Component Analysis

Abstract

The analysis of faults and disturbances in power systems is a basic requirement for a secure and reliable electrical power supply. Independent component analysis (ICA) is an efficient computational method used to find out hidden components in a set of sampled data. The basic target of ICA is to find a linear representation and relation between nongaussian data captured during disturbance, so that the components are statistically independent, or as independent as possible. This paper explains the application of ICA as an abrupt change detection technology to detect the abrupt changes in segmented current and voltage signals, which are recorded during fault or disturbance. Also show how the detected abrupt change in signal segment is discriminated in fault and power swing.

Keywords: Distance protection, Abrupt change detection, Power Swing, Disturbance analysis, Relay performance

Cite this Article

Upadhyay VJ, Pandya AS. Evaluation Algorithm for Discrimination between Fault and Power Swing Using Independent Component Analysis. Journal of Power Electronics and Power Systems. 2016; 6(3): 53–59p.