Hydrogen production from renewable energy is a promising solution for clean and efficient hydrogen generation. The hybrid electrolyzers system (HES) consists of alkaline (ALK) and proton exchange mem-brane (PEM) electrolyzers. It balances PEM’s economic benefits and ALK’s hydrogen production capabil-ities. To enhance hydrogen production efficiency and ensure the operational stability of HES, this study proposes a novel multi-timescale rolling optimization strategy considering flexible hydrogen demand. A joint wind-photovoltaic power prediction model is used to provide accurate forecast data for schedul-ing optimization. The operating characteristics of the electrolyzers, including various operating states, start-stop behaviors, load variations, and hydrogen production features of ALK and PEM, are modeled in detail. Multi-timescale modeling is employed for rolling optimization to obtain the optimal scheduling solution. Finally, the validity of the proposed method is verified under varying weather types in Macheng, Hubei, China. The results show that HES significantly improves hydrogen production capacity and eco-nomics compared to ALK-only production, with a 25% increase in net revenue under extreme weather. Flexible hydrogen load demand response synchronizes fluctuations on both the supply and demand sides, multiplying grid trading benefits. The multi-timescale scheduling strategy enabled each electrolyzer to achieve over 96% execution of the day-ahead schedule across various weather conditions. The system’s economy achieves 98% of the ideal maximum benefit and 80% under extreme weather. This demonstrates that the proposed scheme holds promise for providing effective solutions for the optimal design and scheduling of renewable energy hydrogen production systems.