Optimizing proton exchange membrane electrolyzer performance through dynamic pressure and temperature control: A mixed-integer linear programming approach

Abstract

Hydrogen is a key energy carrier for decarbonizing multiple sectors, particularly when produced via water electrolysis powered by renewable energy. Proton exchange membrane (PEM) electrolyzers are well suited for this application due to their ability to rapidly adjust to fluctuating power inputs. Despite being conventionally operated at high temperatures and pressures to reduce heating and compression needs, recent studies suggest that under partial loads, lower operating conditions may enhance efficiency. This study introduces a novel optimization framework for dynamically adjusting pressure and temperature in PEM electrolyzers. The model integrates an efficiency map within a Mixed-Integer Linear Programming (MILP) formulation and applies McCormick tightening to address nonlinearities. A one-week case study demonstrates operational cost reductions of up to 12.5 % through optimal control, favoring lower temperatures and pressures at low current densities and higher temperatures near rated load, while maintaining moderate pressures. The results show improved efficiency and reduced hydrogen crossover, enhancing safety and enabling scalable application over extended time horizons. These insights are valuable for long-term planning and evaluation of hydrogen production and storage systems.