TY - JFULL AU - S Kalyani and K Shanti Swarup PY - 2009/5/ TI - Power System Security Assessment using Binary SVM Based Pattern Recognition T2 - International Journal of Electrical and Computer Engineering SP - 745 EP - 752 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/10828 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 28, 2009 N2 - 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 implemented on New England 39 Bus and IEEE 57 Bus systems. The simulation results of SVM classifier is compared with the other classifier algorithms like Method of Least Squares (MLS), Multi- Layer Perceptron (MLP) and Linear Discriminant Analysis (LDA) classifiers. ER -