Due to the inherent volatility and randomness, the He County power system is facing increasing pressure on peak, and the current regulation capacity of the system is no longer sufficient to meet actual needs. This article constructs a multi-objective optimization scheduling model based on the complementary characteristics of multiple energy sources such as wind energy, solar energy, hydro energy, and thermal storage. This model covers two key levels. One of them is the optimization scheduling layer of the wind solar water storage combined power generation system. The core goal of this layer is to achieve the optimal output effect of the system by minimizing the net load variance and maximizing the clean energy generation. The second is the optimization scheduling layer of thermal power units, which mainly focuses on minimizing the operating costs of the system and optimizing and adjusting the output of thermal power units in various time periods. Then, the artificial fish swarm algorithm is introduced and dynamic growth and reduction strategies are designed for solving. Select the He County power system to construct a simulation system, and conduct a case study on the summer solstice as a typical load day. Case analysis shows that considering the optimal consumption rate of new energy has multiple impacts on the operating costs of wind solar water thermal storage multi energy complementary systems. Overall, it is conducive to reducing the total operating costs of the system, bringing positive cost-effectiveness in thermal power unit peak shaving, clean energy operation, energy storage system operation, and environmental protection, and providing useful reference for the economic and efficient operation of the power system.
