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Affected by extreme hot and dry weather events, the power supplied by hydropower is seriously insufficient in Sichuan province during the summer of 2022, causing severe power shortage and incalculable economic losses for the society. Therefore, a novel multi-objective scheduling model based on grid-connected hydro-wind-solar-battery energy resources combining flexible reserves is proposed to collaboratively guarantee the power supply reliability of both the contracted long-distance power transmission and the local electricity demand under extreme hot and dry weather. The intermittent nature of water inflow, wind speed, solar irradiance, and load is considered, and the multi-scenarios are produced using Latin Hypercube Sampling method. In this work, thermal plants are regarded as flexible reserves for easing the load shedding level of local load. The McCormick's Envelope method is implemented to linearize the power production model of the hydropower station. A multi-objective model, including minimum penalty cost of load shedding and carbon dioxide emission, is proposed to achieve the economic-environmental equilibrium of the power system. The proposed multi-objective optimal hybrid energy complementary strategy is transformed into a single objective model via ε -constraint method, and the fuzzy satisfying method is introduced to select the best compromise solution in the Pareto Front. The meteorological information of the summer of 2022 is collected to verify the effectiveness of this proposed mixed-integer-linear-programming energy complementary model based on a hydropower station on the Jinsha River in Sichuan province, China. Numerical experiments demonstrate that the proposed model is efficient and can enhance the reliability of real-world power systems under extreme hot and dry weather. A set of policy suggestions have been provided for Sichuan province to develop the power grid to face the extreme weather effect. [ABSTRACT FROM AUTHOR]