Two-stage optimization of a virtual power plant incorporating with demand response and energy complementation

Abstract

The virtual power plant (VPP) breaks the geographical restrictions of environment and resource types by virtue of aggregating the distributed energy resources and dispatchable loads. In view of the impact of large-scale energy consumption by users on the operational safety of VPP, based on the existing demand response (DR) researches, this paper adds a penalty mechanism for the reasonable management of loads. For the difference of resources in multiple VPPs, the current researches ignore the energy interaction between different VPPs, and the external operator is introduced innovatively in this paper to coordinate the real-time complementation of regional energy. Considering the uncertainty from renewable energy and load, a two-stage scheduling strategy for VPP with multi-time scale optimization is proposed, including a long-time scale day-ahead scheduling and a short-time scale real-time scheduling. On the basis of DR and unit constraints, the resource scheduling plan is formulated in the day-ahead stage. In the real-time stage, the energy complementation between VPPs is considered under the framework of rolling optimization for the correction of the previous plan. The scheduling of both stages is aimed at the economic operation of the VPP. Simulation results show that the DR flexibly optimizes the load distribution while bringing economic benefits, and the total profit can be increased by up to 6.65%. Moreover, the results show that the energy interaction under the external operator coordination significantly reduces the total correction cost by up to 8.23%, and the correction cost is decreased with the extension of the rolling optimization scheduling period.