For multi-source joint systems containing wind solar storage, the output of wind and photovoltaic power generation is characterized by uncertainty. When the actual output of wind turbines and photovoltaic power generation does not match the power arranged in the actual scheduling plan, it will lead to a significant decrease in the economic benefits of the system. In response to the above issues, this article first establishes wind power generation models, photovoltaic power generation models, and user electricity consumption models, which have the commonality of uncertainty. Then, an energy storage model for the storage end is established, and the Seagull Optimization Algorithm is used to solve the model and obtain the optimal power storage parameters. This paper establishes a power scheduling model for the power supply side, and then optimizes the power scheduling using robust optimization strategies. Finally, to verify the feasibility of the algorithm, an IEEE 14 node model is used for validation.