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Abstract Considering that the benefits of hydropower stations from regulating and consuming new energy are restricted during the dry season due to the inadequate regulation capacity, this paper focuses on the accommodation capacity evaluation of hydropower for wind‐ photovoltaic (PV, for short) power generation in different supply‐grid‐load conditions. First, the factors that influence hydropower stations' accommodation capacity were initially examined in this study, in terms of power supply, power grid, and load. Then, two new indices, namely the regulatory factor of installed capacity and the regulatory factor of electric quantity, were put forward to evaluate the capacity of hydropower for accommodating wind‐PV. To reduce the peak regulation burden on the power grid and encourage the consumption of clean energy, a two‐objective optimization model with maximum source‐load matching and clean energy consumption was devised. And a two‐tier binary algorithm and progressive optimization coupled strategy was proposed to solve the model. Finally, the cascade hydropower stations in the north Panxi section of the Yalong River and the surrounding wind farm and PV power stations were taken as examples to examine the sensitivity of the factors. The results show that with each 5% increase in the regulatory electric quantity, the regulatable installed wind‐PV capacity and consumable wind‐PV electric quantity were increased by 7.57% and 8.21%, respectively, rank only second to transmission capacity. Considering the large investment required for transmission channel expansion, this result reveals that the most effective and economical way to promote wind‐PV consumption is to increase the regulated electric quantity of hydropower stations in the river basin.

Establishing a wind-solar-hydro hybrid generation system is an effective way of ensuring the smooth passage of clean energy into the grid, and its related scheduling research is a complex and real-time optimization problem. Compared with the traditional scheduling method, this research investigates and improves the accuracy of the scheduling model and the flexibility of the scheduling strategy. The paper innovatively introduces a sand-table deduction model and designs a real-time adaptive scheduling algorithm to evaluate the source-load matching capability of the hybrid wind-solar-hydro system at ultra-short-term scales, and verifies it through arithmetic examples. The results show that the proposed adaptive sand-table scheduling model can reflect the actual output characteristics of the hybrid wind-solar-hydro system, track the load curve, and suppress the fluctuation of wind and solar energy, with good source-load matching capability.