Study On Scheduling Model Of Power System Considering Demand Response’s Participation In Large-Scale Wind Power Consumption

With the rapid development of global economy, the consumption of non-renewable energy such as coal, oil and so on continues to grow. The excessive exploitation and utilization of non-renewable energy sources bring many problems, such as energy crisis, air pollution and global warming. In order to solve the above problems, exploitation and utilization of renewable energy have become a pressing matter of the moment. Wind power is a kind of renewable and clean energy, which has an important role in energy saving and emission reduction. But output of wind power is random, volatile and anti-peaking, and these characteristics bring certain risks to the power grid dispatching. In addition, with the further construction of smart grid, demand response as a flexible resource attracts more and more attention. How to make arrangements for the wind power grid connected system scheduling and how to use the demand response resources to improve the absorptive capacity of wind power have become the focus of the study. In this paper, we studied the related scheduling models and methods, mainly including the following parts.Firstly, this thesis analyzed the uncertainty factors in the modern power system and proposed models for wind power plants, traditional units, demand response resources and other uncertain factors, which laid the foundation for the follow-up study.Secondly, this thesis presented a robust optimal scheduling model of wind power grid connected system. Based on the traditional robust optimization and introducing uncertainty set concept, this thesis proposed an adjustable robust optimization scheduling model. Research showed that the robustness of the model is very high.Then, taking advantages of stochastic optimization and adjustable robust optimization, this thesis presented a stochastic & adjustable robust hybrid scheduling model. In the model, the stochastic programming and the adjustable robust optimization were effectively integrated together and realized the coordinated optimization of the power supply side resources and demand response resources.Finally, in view of the characteristics of wind power prediction accuracy gradually increasing with the time scale and multiple-time-scale of demand response resources, this thesis proposed a multi-time-scale rolling scheduling model for large scale wind power access system. The model provided a basis for the arrangement of scheduling plan and reserve capacity in power system with large scale new energy sources.