Controller design and optimal sizing of battery energy storage system for frequency regulation in a multi machine power system

Frequency regulation is one of the key components needed to keep the power grid stable and reliable in the case of an imbalance between generation and load. This study looks at several control techniques for Battery Energy Storage Systems (BESSs) to keep the frequency stable in the power system during generation/load disruptions. This research aims to build several BESS controllers, including the proportional-integral (PI), proportional integral derivative (PID), and Tilt-Integral Derivative (TID) controllers. Also, the BESS controller parameters are optimized and compared by using metaheuristics based particle swarm optimization (PSO) and the BAT algorithm. However, for practical power systems with high MVA ratings, the size of the battery energy storage systems has to be increased considerably to offset frequency deviations. Additionally, by utilizing PSO to reduce the frequency deviations within prescribed limits, this work presents the optimal BESS sizing for multimachine power systems. Furthermore, the research study examines the impact of BESS connected to various voltage levels, such as LV, MV, and HV subgrids. It also examines BESS's role in frequency management, which is an area of expertise that needs further investigation and is anticipated to have a big influence on the frequency stability of the system. Time domain simulations are carried out, which shows that the PSO based controller design is capable of stabilizing the system frequency with superior performance as well as the BESS's capability to participate effectively in frequency regulation. Additionally, this paper also implements the experimental verification through Hardware-in-the-Loop (HIL) simulations to validate the performance and robustness of the proposed control system. The WSCC 9-bus test system is used to demonstrate the BESS's efficacy. The system is modelled and simulated using the DIgSILENT PowerFactory software. © 2024 The Authors