Aggregation Method and Bidding Strategy for Virtual Power Plants in Energy and Frequency Regulation Markets Using Zonotopes

Jun Zhan, Mei Huang, Xiaojia Sun, Zuowei Chen, Yubo Zhang, Xuejing Xie, Yilin Chen, Yining Qiao () and Qian Ai
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Jun Zhan: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Mei Huang: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Xiaojia Sun: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Zuowei Chen: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Yubo Zhang: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Xuejing Xie: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Yilin Chen: Shenzhen Power Supply Bureau Co., Ltd., Shenzhen 518001, China
Yining Qiao: School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Qian Ai: School of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Energies, 2025, vol. 18, issue 10, 1-24

Abstract: Aggregating and scheduling flexible resources through virtual power plants (VPPs) is a key measure used to improve the flexibility of new power systems. To maximize the regulation potential of flexible resources and achieve the efficient, unified scheduling of flexible resource clusters by VPPs, this study proposed a flexible resource aggregation method for VPPs and a bidding strategy for participation in the electricity and frequency regulation markets. First, considering the differences in the grid frequency regulation demand across periods, an improved zonotope approximation method was adopted to internally approximate the feasible region of flexible resources, thereby achieving the efficient aggregation of feasible regions. On this basis, the aggregation model was applied to the optimization model for VPPs, and a day-ahead double-layer bidding model of VPPs participating in the electricity and frequency regulation markets was proposed. The upper layer optimizes the bidding strategies to maximize the VPP revenue, while the lower layer achieves joint market clearing with the goal of maximizing social welfare. Finally, case studies were undertaken to validate the effectiveness of the proposed method.

Keywords: bidding strategy; feasible region aggregation; flexible resources; frequency regulation ancillary service; virtual power plant (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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