Renewable energy is the key to achieving energy transition and sustainable development. However, the intermittency, volatility, and uncertainty faced by the power system with a high share of renewable access are much higher than the current level, and the economic and stable operation of the power supply system encounters huge challenges. This paper combines the short-term power economic dispatch with the long-term capacity expansion and introduces the uncertainty of renewables through clustering and scenario tree technology. Furthermore, it establishes a power system stochastic optimization model with temporally and spatially high resolution, aiming to reveal how the power system can economically and efficiently absorb a high share of renewables through the coordinated optimization of power generation, transmission, and storage. The results show that there are significant differences in the main measures used to deal with intermittency and uncertainty in different regions. The power system needs to coordinately optimize the layout of the wind, solar, and coal industries, strengthen the ability of inter-regional peak regulation, and utilize the complementary advantages among generation, transmission, and storage while avoiding technology lock-in effects.