Binary SVM Approach for Security Assessment and Classification in Power Systems

Power System Security is a major concern in real time operation. Conventional method of security evaluation consists of performing continuous load flow and transient stability studies by simulation program. This is highly time consuming and infeasible for on-line application. Pattern Recognition (PR) is a promising tool for on-line security evaluation. This paper proposes a Support Vector Machine (SVM) based binary classification for static and transient security evaluation. The proposed SVM based PR approach is tested on IEEE 57 Bus and 118 Bus systems. The simulation results of SVM classifier is compared with the conventional Method of Least Squares (MLS) classifiers.