Finite Control Set Model Predictive Control with Model Parameter Correction for Power Conversion System in Battery Energy Storage Applications

Adding a Battery Energy Storage System (BESS) in the vicinity of renewable energy sources is a feasible solution to overcome the inherent negative impact caused by their random power fluctuating problems. Power conversion system performs as an interface between the battery packs and grid. The control method of power conversion system is essential to BESS. Finite Control Set Model Predictive Control (FCS-MPC) is favorable to be chosen as the core control method for grid-injected current regulation in such a system due to its outstanding benefactions, including fast dynamics, multiobjective optimization and simple implementations. Hence, this paper presents a FCS-MPC with active damping feature for an Inductor(L) Capacitor(C) Inductor(L) (LCL)-filter-based power conversion system first. However, it is also well known that the practical effect of model predictive control significantly relies on the accuracy of mathematical model embedded within the controller. Parametric mismatch of the model tends to generate a prediction error, leading to a deterioration of the power quality of power conversion system or even instability issues furthermore. Therefore, this paper proposes an additional model correction strategy based on a comprehensive on-line analysis on the difference between predictive and real value of respective voltage or current signals during the ever-lasting several grid cycles to eliminate the influence of parametric mismatch. Simulation of an LCL-filter-based power conversion system is carried out to verify the validity of the theoretical analysis and control method in this paper. Finally, experimental results obtained from a down-scaled prototype are provided to confirm the feasibility of the overall control strategy. (c) 2020 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.