Abstract: The implementation of medium and long-term electricity contract with load curves is beneficial for the energy management on both sides. In this paper, a multi-energy complementary power system including wind power, photovoltaic, thermal power, storage battery, electrolytic hydrogen production, and fuel cells is constructed to optimize the capacity configuration of system components. The model considers the load curve constraints, introduces the horizontal, vertical and consistency indexes to assess the load consistency rate, and affects the power system income through the curve assessment benefits. The objective function of the model is to maximize the cumulative net present value, at the same time, considering the operation stability and load satisfaction rate of the multi energy complementary system, the quantum particle swarm optimization (QPSO) algorithm is used to solve the model. The simulation results show that the optimized multi energy complementary power system has better economy and load curve consistency rate performance.