Real-Time Transient Stability Assessment Based on Genetic Algorithm-Extreme Learning Machine
Bo Yuan Wang, Ke Wang, Da Hai You, Weihua Chen, Gang Wang · Applied Mechanics and Materials · 2013
In this paper an genetic algorithm-extreme learning machine (ELM) based real-time transient stability assessment method is proposed. This method uses genetic algorithm (GA) to search optimal input weights and hidden biases in the principle of cross validation to establish GA-ELM classifier. In order to do real-time transient stability assessment, generator trajectories of rotor angle, rotor speed, voltage magnitude, electromagnetic power and imbalance power in-and post-disturbance are chosen as original features for the quick access based synchronously sampled values. Simulation results of New-England 39-bus system show that this method has good performance in power system transient stability assessment.