Optimization model for operation of VPP cluster participating in peak load ancillary service

Under the "dual carbon" goals, the large-scale integration of new energy into the grid has led to a surge in the demand for regulation in the new power system. Fully leveraging the adjustable capacity of demand-side flexibility resources is of great significance for peak shaving and valley filling of the grid. Virtual power plants (VPPs), as an advanced technology for aggregating and controlling massive distributed demand-side resources, face significant market trading risks in the process of resource aggregation and bidding due to the complexity of demand-side resources. Therefore, this paper proposes a bidding method for virtual power plant clusters participating in peak-valley regulation ancillary services. First, the operating model of the virtual power plant cluster is proposed, and a quantitative model of its regulation capacity is established. Then, to ens ure that the VPP resources can successfully bid in the peak-valley market, a peak-valley service bidding framework is introduced, and a conventional aggregated load bidding model is constructed. Finally, the validity and applicability of the proposed model are verified through a case study.