The integrated wind-solar-hydrogen storage coupling system is one of the important means to improve the consumption of new energy and promote the development of hydrogen economy, but the high randomness of wind-solar-hydrogen load and the slow solution speed of the system model bring difficulties to the optimal scheduling of the system. Firstly, in order to analyze the uncertainty factors in the wind and solar load more accurately, the variational mode decomposition （VMD） technology is adopted, and the dynamic time warping （DTW） algorithm is combined with the K-medoids clustering method to obtain the uncertainty of the wind and solar load and the system operation scenario. Then, a wind-solar-hydrogen storage coupling system model and a multi-time-scale optimal scheduling model based on robust MPC-PSO are constructed. Then, the combination of robust MPC and PSO algorithm is used to realize the fast decoupling solution of rolling optimization of system operation. Finally, a simulation example of wind-solar-hydrogen-storage coupling system is established for analysis. The results show that the proposed method improves the economy of hydrogen production and the wind and solar absorption rate, and improves the solution efficiency compared with a single robust MPC.