Power system reduced model by artificial neural networks

This paper is aimed to the application of artificial neural networks (ANN) for constructing a power system reduced model, also termed dynamic equivalent. ANN are trained to help in constructing dynamic equivalents, which is considered a hard task in the context of electrical power systems. The main objective is to reproduce the complex voltage at some relevant nodes. The simulation results prove the applicability and robustness of this innovative approach.