A Support Vector Machine (SVM) Based Voltage Stability Classifier

R.D. Dosano, H. Song, and B. Lee (Korea)


Classification, local phasor measurement, power system voltage stability, real-time monitoring, support vector machine


This paper proposes a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. The excellent performance of the SVM in the classification related to time-series prediction matches the real-time data of local measurement for system responses by short term and long-term dynamics. The methodology for automatic monitoring of the system is initiated locally, which aims to leave sufficient time to perform immediate corrective actions to stop system degradation by the effect of major disturbances. This paper explains the procedure for fast classification of long-term voltage stability using the SVM algorithm.

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