Abstract: In order to reduce the output uncertainty of wind and photovoltaic power generation and make the wind-solar-battery hybrid power system schedule,the outputs of wind and photovoltaic power generation are processed into certainty variables and fuzzy error sum.An energy storage model is built for wind-solar-battery hybrid power system,in which the maximum matching degree between the planning output curve and the scheduling output curve,the most smoothness of charge and discharge power in energy storage battery and the most optimal sustainable work ability of the energy storage battery are taken as objectives using the dependent-chance goal programming method.By combining fuzzy simulation,neural networks with improved particle swarm optimization algorithm,a new hybrid intelligent algorithm is proposed to solve the model,and its recently day schedule is given.Finally,numerical examples verify the effectiveness of the proposed method in solving highdimensional uncertain programming problems with fast convergence speed and satisfactory global and local searching ability.