A dual-layer capacity optimization configuration method for direct coupled photovoltaic hydrogen (PVE) systems is proposed based on an improved genetic algorithm-traversal search method to address the inaccuracy in expected system revenue characterization due to static electrolyzer-array modeling. By establishing a PVE direct coupling system model that includes photovoltaic cells and proton exchange membrane (PEM) electrolytic cells

the impact of dynamic series-parallel reconfiguration of electrolyzers on system performance is analyzed. Based on a double-layer capacity optimization configuration model

the dynamic adjustment mechanism of the series-parallel structure of the electrolytic cell array is considered in the inner layer. With the goal of maximizing hydrogen production

the hourly series-parallel structure of the electrolytic cell on the typical day is optimized. The outer layer is designed with the goal of maximizing the cycle revenue

and the capacity configuration results are obtained. Based on the irradiance data from the three northeastern provinces of China

the results show that the proposed method can improve system revenue and reduce hydrogen production costs. This paper can provide some technical support for the construction of photovoltaic hydrogen production system.