为解决风光可再生能源出力波动性强导致电解制氢系统运行稳定性不足、单位制氢成本偏高的问题，针对风光耦合制氢应用场景，开展双通道混合制氢系统的优化控制方法研究。提出一种基于集合经验模态分解(ensemble empirical mode decomposition, EEMD)与Petri网启停修正的双通道电解槽优化控制策略，通过对风电与光伏功率信号进行EEMD分解，将不同频段功率分量分别分配至碱性与质子交换膜电解槽，并利用Petri网模型构建电解槽启停逻辑以抑制低负载频繁启停行为，同时建立以系统能量转换效率最大化和单位制氢成本最小化为目标的多目标优化模型，采用多目标粒子群优化算法进行求解。基于张北地区风光实测出力数据的仿真结果表明，优化后混合制氢系统的能量转换效率提升至58.64%，单位氢气生产成本降至2.3958美元/kg，相较于传统单一制氢方案，分别提升15.25%与降低1.7384美元/kg，且电解槽启停次数显著减少。研究表明，所提出的控制方法在提升系统稳定性、降低经济成本方面具有良好效果，为风光制氢系统的高效运行提供了一种切实可行的优化路径。

To address the poor operational stability and high unit hydrogen production cost caused by strong power fluctuations of wind and photovoltaic (PV) renewable energy, this study investigates an optimal control strategy for a dual-channel hybrid hydrogen production system under wind-PV coupled application scenarios. An optimal control strategy for a dual-channel electrolytic cell system based on ensemble empirical mode decomposition (EEMD) and Petri net-based start-stop correction is proposed. Wind and PV power signals are decomposed using EEMD, and power components at different frequency bands are allocated to alkaline and proton exchange membrane (PEM) electrolytic cells according to their dynamic response characteristics. Meanwhile, a Petri net model is employed to construct start-stop logic for electrolytic cells, effectively suppressing frequent switching under low-load conditions. Furthermore, a multi-objective optimization model is established with the objectives of maximizing system energy conversion efficiency and minimizing the unit hydrogen production cost, which is solved using a multi-objective particle swarm optimization algorithm. Simulation results based on measured wind-PV power output data from the Zhangbei region indicate that the optimized hybrid hydrogen production system achieves an energy conversion efficiency of 58.64% and a unit hydrogen production cost of 2.3958 USD/kg. Compared with conventional single-type hydrogen production schemes, the proposed method improves efficiency by 15.25% and reduces cost by 1.7384 USD/kg, while significantly decreasing the number of start-stop events of electrolytic cells. The results demonstrate that the proposed control strategy effectively enhances system stability and reduces economic cost, providing a practical and feasible optimization approach for the efficient operation of wind-PV hydrogen production systems.