Model Predictive Control of Small-Scale Electrified Hydrogen Electrolyzer Systems

This paper presents a model predictive control framework for a power conversion system consisting of an active front end (AFE) rectifier cascaded with a dual active bridge (DAB) converter for hydrogen electrolysis applications. To meet the grid power quality requirements, an AFE rectifier with finite control set model predictive control (FCS-MPC) is employed. A moving discretized control set model predictive control (MDCS-MPC) strategy is employed for the DAB converter to improve the dynamic performance while lowering the computational burden. In traditional PI-based control, cascading of dual loops used in the AFE rectifier and voltage loop of the DAB converter leads to slow dynamic response and complex modeling. The proposed dual predictive control method ensures stable voltage with low current ripple on the electrolyzer side and better dynamic performance while ensuring the power quality of the grid. The effectiveness of the proposed framework is validated using MATLAB simulations and results demonstrate electrolyzer current ripple is within limits while maintaining the grid side power quality.