Realizing the potential of renewable hydrogen production requires flexible operation of electrolysis systems to integrate with intermittent power sources. This work develops an optimization model to assess flexible operational strategies for alkaline and proton exchange membrane (PEM) electrolysers powered by wind energy. The model quantitatively analyses trade-offs between electrolyser shutdown strategies, overloading capacities, and battery integration to identify optimal regimes balancing efficiency, flexibility, and economics. The results reveal a mixed-integer linear programming approach can optimize system configurations and control strategies to minimize the levelized cost of hydrogen production. Optimal near-minimum load operation is achieved by independently optimizing the load of each electrolyser block, while avoiding shutdowns above a critical load level. Strategic electrolyser overloading can provide economic benefits by reducing installed capital costs, if technical feasibility and accelerated degradation are addressed. Battery energy storage integration significantly improves economics by enhancing asset utilization, provided excess renewable energy is available. The model provides novel insights on integrating alkaline and PEM electrolysis with intermittent wind power to advance renewable hydrogen production. Quantifying trade-offs between operational flexibility and economics will help guide flexible design and control strategies for cost-optimal renewable electrolysis systems
