Intelligent control scheme for participation of aggregated energy storage in grid frequency regulation

Battery Energy Storage Systems (BESSs) have proved to be efficient in frequency regulation by providing flexible charging/discharging powers. This paper proposes an artificial neural network (ANN)-based intelligent control scheme to provide the aggregated BESS with control signals to be efficiently involved in the frequency regulation in a power system. The ANN is proposed to provide online correction for the controller's gains embedded in the control loop of aggregated BESS, passing the control system's reliance on operating point conditions. Then, the steady state power distributions are evaluated, showing that BESSs can facilitate a fast contribution to frequency regulation and smooth removal from the regulation process. Eventually, the OPAL-RT real-time digital simulator is used to perform real-time verifications on the simulated power grid to demonstrate the proposed control scheme's effectiveness.