A multifeature fusion approach for power system transient stability assessment using PMU data

TL;DR

This paper introduces a novel multifeature fusion method using VBpMKL and synchrophasor data to enhance transient stability assessment accuracy in power systems, validated on IEEE and real-world systems.

Contribution

It proposes a new multifeature fusion approach with VBpMKL for power system transient stability assessment using synchrophasor data, improving accuracy and reliability.

Findings

Enhanced classification accuracy in TSA

Effective application on IEEE 39-bus system

Validated on real-world power system

Abstract

Taking full advantage of synchrophasors provided by GPS-based wide-area measurement system (WAMS), a novel VBpMKL-based transient stability assessment (TSA) method through multifeature fusion is proposed in this paper. First, a group of classification features reflecting the transient stability characteristics of power systems are extracted from synchrophasors, and according to the different stages of the disturbance process they are broken into three nonoverlapped subsets; then a VBpMKL-based TSA model is built using multifeature fusion through combining feature spaces corresponding to each feature subset; and finally application of the proposed model to the IEEE 39-bus system and a real-world power system is demonstrated. The novelty of the proposed approach is that it improves the classification accuracy and reliability of TSA using multifeature fusion with synchrophasors. The application results on the test systems verify the effectiveness of the proposal.