Abstract: Characterized by randomness and volatility, there is always a gap between the day-ahead forecast value of photovoltaic power generation and its actual output. To improve the consumption of clean and renewable resources such as hydropower and PV under the carbon peaking and carbon neutrality background, a distributionally robust optimal scheduling method of power system considering hydro- photovoltaic-pumped storage complementarity and DC transmission is proposed. Firstly, an optimal scheduling model of power system considering hydropower-photovoltaic-pumped storage complementary and DC transmission is proposed with the objective of minimizing system operating cost and penalty for solar curtailment, in which the rapid regulation ability of cascade hydropower cooperative pumped storage units is adopted to improve the utilization of hydropower and solar, the optimal regulation of DC transmission is modeled, and the AC power flow method is used to take into account the active and reactive power losses of converter stations. Then, a two-stage distributionally robust optimization model based on generalized moment information fuzzy set is proposed, considering the uncertainty of solar. The first stage optimized the power system scheduling decision for the basic scenario, and the second stage minimized the penalty expectation for solar curtailment in the worst uncertain scenario. Finally, the effectiveness of the proposed model is verified by examples.