Design and Preliminary Implementation of Simulation Framework for Virtual Power Plant Participation in Power Market

With the deep participation of Virtual Power Plants (VPPs) in the electricity market, the complexity of their bidding strategies and the coordination issues with Distribution System Operators (DSOs) have become increasingly prominent. To address this challenge, this paper first establishes a multi-agent bidding model within the VPP, and based on this, proposes a bi-level optimization framework founded on Stackelberg game theory. At the upper level, DSO maximizes operational profits through dynamic pricing strategies; at the lower level, VPP minimizes operational costs through optimal configuration of distributed energy resources. To effectively handle system uncertainties, this paper introduces Latin hypercube sampling method and designs a particle swarm optimization-based solution algorithm. Simulation results demonstrate that the proposed dynamic pricing mechanism not only effectively guides VPPs to participate rationally in market transactions but also achieves synergistic benefits enhancement for both DSO and VPP.