PMU Signals Responses-Based RAS for Instability Mitigation Through On-The Fly Identification and Shedding of the Run-Away Generators

Abstract

This paper presents a new method of instability detection and subsequent stabilization of the power system network using a proposed multi-shot remedial action scheme (RAS) that can extemporaneously detect critical generators based on the dynamic states of generator computed from the terminal phasor measurement units. The instability detector is a moving window classifier that predicts impending instability using rate of change of individual generator transient energy indices evaluated from the d-q axis voltage as well as conventional severity indices based on generator angle and frequency. A comparative performance analysis of a spectral feature based ensemble decision tree classifier with a multivariate long short-term memory network is also presented. The proposed RAS identifies critical generators through individual machine transient energy formulation and recursive coherency matrix, evaluated solely from system-wide generator dynamic states, and maintains stability by tripping adaptively the run-away generators. Performance evaluation of the proposed scheme has been made on IEEE 39-bus network and it has been demonstrated that the proposed RAS is robust with regards to instability prediction and it can effectively identify critical generators and stabilize the network by tripping the same.