As the integration of renewable energy such as wind and solar power greatly increases, the challenges such as wind and solar power curtailment, voltage out-of-limit, and reverse power flow are becoming increasingly prominent in power systems. Pumped storage stands out as the most mature and cost-effective large-scale energy storage solution, which can be combined with renewable energy to help mitigate the fluctuation of renewable energy, improve the system operation flexibility, and enhance the reliability of power supply. The conventional wind-solar power storage and control methods have low efficiency in solving complex scenarios such as uncertain wind and solar power output, and the solving time is not adjustable. To address these issues, an adaptive two-stage robust scheduling method for wind-solar power storage based on an inexact column-and-constraint generation (i?C&CG) algorithm is proposed. Firstly, a model considering the operating condition conversion and power transition of pumped storage units is established. Secondly, an adaptive two-stage robust scheduling model for wind-solar power storage is developed based on polyhedral interval uncertain sets. Subsequently, the model is decomposed into master and sub-problems, and the i?C&CG algorithm is employed to derive the optimization decisions that balance the accuracy and efficiency. Finally, through case simulation, the comparison and analysis of the model solving time and error using the i?C&CG algorithm and the traditional column-and-constraint generation algorithm are conducted. It is demonstrated that the proposed two-stage scheduling method can effectively balance the robustness and economy of system operation and ensure the model solving efficiency within the allowable error range.