Abstract: A parameter adaptive stochastic model prediction control(PASMPC) power regulation strategy was proposed based on scenario analysis method, aiming at the impact of uncertainty on the power balance of the wind-solar-hydrogen coupling system on both the source and load sides. A linear discrete state-space model was established to describe its dynamic characteristics, based on the energy supply architecture of the wind-solar-hydrogen coupling system. Then, the scenario analysis method was used to describe the uncertainty of the system as input for the PASMPC.Under the framework of the designed PASMPC, the goal of extending the life cycle of the system equipment was taken into consideration for optimization. To compensate for the defects of fixed time domain prediction and control time domain instochastic model prediction control during optimization process, a parameter adaptive method was proposed to obtain better optimization control effect. Results show that the PASMPC strategy improves the system power balance by 6.25 percentage compared with the stochastic model prediction control. Compared with the conventional model predictive control, the high-power operation of the system-controllable equipment is reduced by 60%, which verifies that the proposed strategy can effectively solve the uncertainty on both sides of the source and load of the wind-solar-hydrogen coupling system.