Artificial neural network controlled battery energy storage system for enhancing power system stability

This paper describes an application of an adaptive Artificial Neural Network (ANN) controller to continuously control the charging and discharging of a Battery Energy Storage System (BESS) to improve the stability of an electric power system. The simulation studies have included a detailed model of the generator including its excitation controller and governor, as well as a comprehensive BESS model, including the DC battery model and the switch operation associated with the power converter. An on-line training Artificial Neural Network controller is continuously trained to directly control the BESS operation to damp power system oscillation in various power system operating conditions. Simulation results show that this ANN-controller can adaptively learn and update its control strategy to improve the system stability under different system operating conditions.