Abstract: This paper makes a new energy hybrid power generation model,composed of wind power,photovoltaics,and concentrating solar power（CSP）. Considering the consumption of wind and solar resources,a two-tier optimal scheduling model that uses high-load energy loads as schedulable resources to participate in the new energy complementary power generation system has been established.The fast non-dominated sorting genetic algorithm（NSGA-Ⅱ）with elite strategy and binary particle swarm algorithm are used to solve the two-layer model. The upper-level optimization model uses the minimum output power fluctuation of the hybrid system and the maximum grid connection benefit as the optimization indicators to determine the output of each unit,to calculates the amount of wind and solar abandonment. On this basis,the lower-level optimization model selects the high-energy loads that can effectively absorb wind and light to participate in the grid dispatching according to the amount of wind and light abandonment caused by the upper-level optimization model. Finally,the actual data in Gansu district of China verifies the feasibility and effectiveness of the proposed method.The simulation results show that the participation of CSP stations increases the economic benefits by 44.3%,the output power fluctuations drops by 65.8%,and the participation of high-energy loads reduces the amount of wind and solar abandonment by 86.3%