Real-time Scheduling of Virtual Power System Based on the Hidden Markov Model

With the large-scale grid connection of renewable energy, the grid operation gradually presents a new feature of high-order uncertainty, which poses a severe challenge to the security and stability of the system operation. At present, the intelligent degree of dispatching instruction operation is low, and the human-computer interaction is still in the stage of manual operation. In this paper, a virtual power system for real-time power grid scheduling is proposed. Firstly, a grid model is established based on graph theory. Secondly, a GES agent is designed for power grid scheduling decisions. The implementation effect of the strategy is verified by simulation, and the scheduling strategy is sent to the new energy station. The analysis results show that compared with the traditional manual scheduling method, the proposed man-machine scheduling scheme can effectively improve the execution time and accuracy of scheduling, effectively reduce the risk of overload in the power grid, and provide a solution for the man-machine interaction system in the environment of power scheduling.