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In the conversion toward a clear and sustainable energy system, theflexibility of power-to-hydrogen (P2H) production enables the admittance ofvolatile renewable energies on a utility scale and provides the connectedelectrical power system with ancillary services. To extend the load flexibilityand thus improve the profitability of green hydrogen production, this paperpresents an optimal production scheduling approach for utility-scale P2H plantscomposed of multiple alkaline electrolyzers. Unlike existing works, this workdiscards the conservative constant steady-state constraints and first leveragesthe dynamic thermal and hydrogen-to-oxygen (HTO) impurity crossover processesof electrolyzers. Doing this optimizes their effects on the loading range andenergy conversion efficiency, therefore improving the load flexibility of P2Hproduction. The proposed multiphysics-aware scheduling model is formulated asmixed-integer linear programming (MILP). It coordinates the electrolyzers'operation state transitions and load allocation subject to comprehensivethermodynamic and mass transfer constraints. A decomposition-based solutionmethod, SDM-GS-ALM, is followingly adopted to address the scalability issue forscheduling large-scale P2H plants composed of tens of electrolyzers. With anexperiment-verified dynamic electrolyzer model, case studies up to 22electrolyzers show that the proposed method remarkably improves the hydrogenoutput and profit of P2H production powered by either solar or wind energycompared to the existing scheduling approach.

Extended Load Flexibility of Utility-Scale P2H Plants: Optimal Production Scheduling Considering Dynamic Thermal and HTO Impurity Effects