Regression tree for stability margin prediction using synchrophasor measurements

A regression tree-based approach to predicting the power system stability margin and detecting impending system event is proposed. The input features of the regression tree (RT) include the synchronized voltage and current phasors. Modal analysis and continuation power flow are the tools used to build the knowledge base for offline RT training. Corresponding metrics include the damping ratio of the critical oscillation mode and MW-distance to the voltage collapse point. The robustness of the proposed predictor to measurement errors and system topology variation is analyzed. The optimal placement for the phasor measurement units (PMUs) based on the importance of RT variables is suggested.