Abstract: In the hydropower enrichment network, the tight time-space coupling relationship of hypower and electricity between cascade hydropower stations and the policy requirements of clean energy consumption has greatly increased the challenge of power grid optimization and dispatching in the spot market environment.Based on the market characteristics and real demand for the hydropower-dominated power grid, the day-ahead spot market trading mechanism of the hydropower enrichment grid was discussed to guarantee the absorption of renewable energy.On this basis, a day-ahead optimization scheduling model aiming at minimizing the comprehensive power purchase cost of the power system was established.The nonlinear factors in the model such as the relationship between water level and storage capacity of hydropower stations, and the relationship between water level and water-consumption rate were linearized through multiple linearization techniques.Therefore the original nonlinear model was transformed into a Mixed Integer Linear Programming(MILP) model, and the developed model was verified by 10 thermal power stations and 22 hydropower stations in Yunnan Power Grid.The calculation time was 183.6s, the comprehensive power purchase cost of the system was 155.35 million CNY,and there was no water abandonment in the three river basins.The simulation results showed that the proposed model had high solution accuracy and efficiency, and maximized the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost.The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grid.