To address the impact of large-scale renewable energy integration on the operation of electro-hydrogen coupling systems, and to resolve the subjectivity in uncertainty set selection and insufficient utilization of renewable energy probability information in traditional twostage robust optimization, a two-stage risk-robust scheduling method tailored for renewable power systems is proposed. First, an integrated model for renewable power system that encompasses dynamic hydrogen production, storage, and utilization is established. A multi-physics aware electrolyzer model that couples the thermodynamics and bubble dynamics is proposed to precisely characterize the dynamic variation of electrolytic efficiency. Second, a two-stage risk-robust generation-reserve coordination scheduling method for the renewable power system is developed based on robust optimization and conditional value at risk（CVaR）. In the first stage, the output baselines and reserve capacities for energy storage, controllable units, and hydrogen production systems are determined based on renewable energy forecasts, and wind curtailment and load shedding risks are quantified. In the second stage, operations are rescheduled based on actual renewable energy output and reserved reserves to meet all scenario demands within the acceptable range. Finally, the column-and-constraint generation（C&CG）algorithm is adopted to solve the optimization model, and the optimal uncertainty set is determined through collaborative two-stage solution. Case studies validate the effectiveness of the proposed model.