Abstract
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. © 2025 IEEE.
| Original language | English |
|---|---|
| Title of host publication | 2025 IEEE International Conference on Power and Integrated Energy Systems (ICPIES 2025) |
| Publisher | IEEE |
| Pages | 505-510 |
| ISBN (Electronic) | 9798331511852, 979-8-3315-1184-5 |
| ISBN (Print) | 979-8-3315-1186-9 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 2025 IEEE International Conference on Power and Integrated Energy Systems (ICPIES 2025) - Haikou, China Duration: 7 Apr 2025 → 9 Apr 2025 |
Publication series
| Name | IEEE International Conference on Power and Integrated Energy Systems, ICPIES |
|---|
Conference
| Conference | 2025 IEEE International Conference on Power and Integrated Energy Systems (ICPIES 2025) |
|---|---|
| Place | China |
| City | Haikou |
| Period | 7/04/25 → 9/04/25 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Research Keywords
- bidding strategy
- distributed energy resources
- energy system
- Virtual power plant
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