Novel control approach for integrating water electrolyzers to renewable energy sources

Abstract Green hydrogen can be produced by integrating water electrolyzers to renewable energy sources. The integration confronts the problem of renewable power volatility that requires advanced control strategies. There are three main electrolyzer control approaches, which are: battery hysteresis cycle, model‐based scheduling, and frequency response. These approaches do not fully solve the problem of electrolyzer operation under power fluctuating conditions. This study introduces a novel integration and control approach for water electrolyzers based on model predictive control algorithm. The algorithm controls electrolyzer load so that steering the system into a breakeven energy balance across the main DC busbar that links generation and demand sides. However, the energy balance is subject to power conditioning losses and capacity constraints of electrolyzer. The novel approach uses simplified prediction models for the generation and demand and introduces a compensator for model uncertainty based on a novel role to the battery as a sensor of energy imbalance. The approach is tested on a 5 kW polymer electrolyte membrane electrolyzer and showed that fully automated energy balancing is achievable for grid connected and stand‐alone systems. Also, the electrolyzer can operate at partial capacity with improved efficiency and hydrogen yield, and it is applicable to any mix of renewables.