Electrolyzer modeling and real-time control for optimized production of hydrogen gas?

We present a method that operates an electrolyzer to meet the demand of a hydrogen refueling station in a cost-effective manner by solving a model-based optimal control problem. To formulate the underlying problem, we first conduct an experimental characterization of a Siemens SILYZER 100 polymer electrolyte membrane electrolyzer with 100 kW of rated power. We run experiments to determine the electrolyzer's conversion efficiency and thermal dynamics as well as the overload-limiting algorithm used in the electrolyzer. The resulting detailed nonlinear models are used to design a real-time optimal controller, which is then implemented on the actual system. Each minute, the controller solves a deterministic, receding-horizon problem which seeks to minimize the cost of satisfying a given hydrogen demand, while using a storage tank to take advantage of time-varying electricity prices and photovoltaic inflow. We illustrate in simulation the significant cost reduction achieved by our method compared to others in the literature, and then validate our method by demonstrating it in real-time operation on the actual system.

Automated summary

The study presents a method to operate an electrolyzer in a cost-effective manner by solving a model-based optimal control problem. Experimental characterization of the electrolyzer is conducted to formulate nonlinear models and design a real-time optimal controller, then implemented on the actual system. Simulation results show significant cost reduction compared to existing methods, with validation demonstrated in real-time operation.