Hybrid Operation Of New Energy And Optimal Reserve Dispatch

The energy problem in the world is becoming more and more important, which is becoming one of the major limiting factors in economic development. So how to use wind, solar, hydro and other clean renewable energy effectively attracts people’s more attention. Wind, solar and hydro complementary system can make the output power more smooth by utilizing the complementary characteristic of the above three energy. In addition, energy storage can effectively overcome the renewable energy system uncertainty.First of all, this paper puts forward the scheduling strategy of wind, solar and hydro complementary system, making contribution to the system stability and economic operation. In considering the factors of investment cost, operation cost, environmental governance, as well as the isolated, connected operation mode, this paper establishes the optimization model of the lowest cost. On this basis, further proposes the scheduling strategy of wind, solar and hydro complementary system, realizing the best dispatch of three kinds of new energy. Optimal operation and scheduling strategy can economic performance evaluation system in different operation modes, improve the reliability and flexibility of the proposed complementary system.Secondly, this paper presents a model of scenario-based optimal reserve dispatch and security-constrained unit commitment. The objective of the model is to minimize the cost of the energy and reserve and the constraints include network security constraints, reserve scheduled and deployed constraints. The wind speed fluctuation is generated by Monte Carlo simulation, and a computationally available mixed-integer linear programming algorithm has been applied to solve the model efficiently. The results for the six-bus system and the New England39-bus system show the effectiveness of the proposed model for achieving the optimal reserve capacity, economic dispatch and unit commitment.Finally, the complementary optimization operation of new energy and storage optimization scheduling are summarized and prospected.