Ensemble adaptive neuro fuzzy support vector machine for prediction of transient stability

Abstract

A new method which achieves high accuracy in predicting the transient stability of power systems is presented. This study examines the application of Weighted Support Vector Machine (WSVM), ensemble WSVM and Adaptive Neuro Fuzzy Inference System (ANFIS) for prediction of post-fault transient stability condition. The performance of the ensemble classifier is compared with other methods for accuracy of prediction. The method is tested on the IEEE 39-bus test system. Results show that the ensemble method achieves the highest accuracy using both rotor angles of generators and bus voltage magnitudes after fault clearance. Additionally, the proposed method is investigated under different contingencies and topology alterations to evaluate its performance in determining the stability.