Research on multi-objective optimal scheduling of virtual power plant based on self-supplied coal-fired power plants

With the development of renewable energy, improving the absorption capacity of power grid has become a difficult problem. It is very important to establish virtual power plants based on self-supplied coal-fired power plant to coordinate renewable energy consumption, especially in Xinjiang Province, China. This paper studied the optimal scheduling of a virtual power plant including wind turbines, photovoltaic units, and energy storage equipment based on the self-supplied power plant. First, a mathematical model of the power and power generation cost of each unit inside the virtual power plant was established, and the demand response mechanism was introduced. Secondly, a multi-objective optimization model is established by considering the maximization of net income of virtual power plants, the minimization of system coal consumption and the maximization of user interruption load benefits, and the use of analytic hierarchy process to determine the weights of three objective functions, of which user interruption load benefits are used to reflect the enthusiasm of users to interrupt the load. Finally, the particle swarm algorithm is used to solve the model. The optimization results show that when the coal price rises, the net income of the system decreases, and even a loss occurs, however, the change in coal price has little effect on the Interrupted load of user. In addition, multi-objective optimization can improve the enthusiasm of users while ensuring the net income of the system, it proves that the model has a good optimization effect.