The power generation of renewable energy sources is directly related to meteorological conditions like wind speed and sunlight. Integrating large-scale unstable power sources into the power system generates a need for adjustment and introduces operational risks. To improve the system’s adjustment performance and address the impact of uncertainties, this paper analyzes the operational characteristics and adjustment differences of various flexible resources and proposes a collaborative robust scheduling model for multi-flexible resources of source, grid, load, and storage, considering multiple uncertainties. The model aims to minimize system operation costs, including technical modifications, fuel consumption, start-up and shutdown, and energy curtailment, while satisfying constraints such as real-time supply-demand balance, system adjustment margin, and unit operation. An improved robust optimization theory is introduced to handle the uncertainties in renewable energy, transforming the model into an easier-to-solve problem. Finally, the case study results show that various flexible resources of source-grid-load-storage have different adjustment performances, and all types of resources are indispensable for a power system with a high proportion of renewable energy. Applying the proposed collaborative robust scheduling model can achieve a balanced decision-making process between risk and economy, ensuring complementary advantages and optimal allocation of various source-grid-loadstorage resources.