Multi-time Scale Simulation of Optimal Scheduling Strategy for Virtual Power Plant Considering Load Response

The conventional scheduling models of the virtual power plant(VPP) only consider the electricity trading in the day-ahead market. In this paper, a multi-time scale model covering the day-ahead plan decomposition and the intraday forecast is proposed. At the same time, the load response is considered a resource that can participate in scheduling with traditional generators. Firstly, the power models of VPP has been established, VPP realizes the output tracking plan in each period by simulating the power flow between DG, grid, energy storage and the controllable load. Then, the highest profit and the lowest power generation costs, controllable load compensation and penalty costs is used as a target. By setting parameters and calculating, the economical and environmental protection of the VPP can be reflected. In order to ensure economic and environmental protection, the emission target is converted into economic penalty cost, and genetic algorithm optimization is adopted. The case study verifies the effectiveness of proposed method in the end.