Bidding Strategies for Virtual Power Plants in Multi-Energy Systems: A Comparative Study of Model-Based and AI-Based Approaches

Due to the increasing proportion of distributed energy resources (DERs), such as PVs, battery energy storage systems (BESS), electric vehicles (EVs) and multiple controllable loads in the overall power systems, the virtual power plant (VPP), as a technology capable of effectively aggregating these resources, has attracted growing attention. In addition, artificial intelligence (AI) technology has experienced rapid development, which has profoundly changed the landscape of energy systems. To this end, this paper summarizes existing research on the optimal bidding strategy for VPP integration of DERs. The research on traditional mathematical method-based bidding strategies is first reviewed. Then, this paper demonstrates the application of AI techniques in bidding strategies. Compared with traditional methods, AI-based approaches can effectively improve efficiency and reduce reliance on forecasting. Finally, the research prospects for bidding strategies of VPP are outlined.