A multi-time scale optimization scheduling strategy of virtual power plant with responsive loads

摘要

From the perspective of virtual power plant (VPP) with electric vehicles, a multi-time scale scheduling strategy based on response time margin (RTM) and state of charge margin (SOCM) is proposed. Firstly, the VPP is grouped according to its output in a given scheduling period. Then, the RTM and SOCM indexes are defined on the basis of the power system scheduling target and the electric vehicles (EVs) users' travel demand, which were calculated and sorted to generate a priority queue of responsive EVs. With the progression of scheduling period and rolling iteration, the scheduling schemes of VPP for multiple time periods are determined. Finally, the VPP multi-time scale optimization scheduling strategy is validated by taking an EV aggregator containing three different traffic uses as an example.