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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Jun Zhan & Mei Huang & Xiaojia Sun & Zuowei Chen & Yubo Zhang & Xuejing Xie & Yilin Chen & Yining Qiao & Qian Ai, 2025. "Aggregation Method and Bidding Strategy for Virtual Power Plants in Energy and Frequency Regulation Markets Using Zonotopes," Energies, MDPI, vol. 18(10), pages 1-24, May.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2458-:d:1653144
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