A novel random optimal scheduling of virtual power plant with multiple wind farms

With the improvement of the reliability and security requirements of the power grid, more and more distributed power sources are integrated into the power grid. There is a huge impact on the power grid to the output of distributed. This paper proposed a random optimal scheduling mechanism for virtual power plants with multiple wind fields. Firstly, the optimal scheduling model of virtual power plant is proposed based on the maximum expected value of virtual power plant economic benefits. Secondly, in order to improve the efficiency of the virtual power plant stochastic optimal scheduling model, a particle swarm optimization algorithm based on ELM was proposed. Thirdly, a population evolution mechanism based on ELM is formed, which greatly improves the global convergence of the algorithm. Finally, the improved particle swarm optimization algorithm based on EIM is proved to have faster convergence speed and better global convergence than standard particle swarm optimization algorithm.