Real-Time Transient Stability Assessment Based on Genetic Algorithm-Extreme Learning Machine

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 1390-1393
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.1390
• Online since: September 2013
• Authors: Bo Wang*, Ke Wang, Da Hai You, Wei Hua Chen, Gang Wang
• Keywords: Extreme Learning Machine, Genetic Algorithm (GA), Power System, Transient Stability Assessment

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