Multi-Time-Scale Rolling Optimal Scheduling of Virtual Power Plants in Energy and Flexible Ramping Product Markets

Abstract

Virtual power plants (VPPs) offer a feasible solution for integrating various types of distributed energy resources (DERs) into the power grid in the electricity market. This paper proposes a multi-time-scale rolling optimal scheduling for VPPs, enabling optimal self-scheduling plans across intra-week rolling scheduling, intra-day rolling dispatch, and real-time dispatch. The proposed method facilitates participation in energy and flexible ramping product (FRP) markets while considering the specific characteristics with complementary advantages for the aggregated renewable resources, gas turbines, energy storages, and flexible demands of each time scale. The flexible ramping products within the VPP framework are established, while the energy storage systems address fluctuations during dispatch periods. Case studies are conducted to verify the efficiency of the proposed method. The results show that the proposed method can obtain optimal self-scheduling plans within the multi-time framework and has better performance in economy and security operation in comparisons among cases.