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Day-Ahead Bidding Strategy of a Virtual Power Plant with Multi-Level Electric Energy Interaction in China

Author

Listed:
  • Hui Sun

    (School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Yanan Dou

    (School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Shubo Hu

    (School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China
    State Grid Liaoning Electric Power Research Institute Co., Ltd., Shenyang 110055, China)

  • Zhengnan Gao

    (School of Electrical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Zhonghui Wang

    (Electric Power Dispatching and Control Center of State Grid Liaoning Electric Power Co., Ltd., Shenyang 110055, China)

  • Peng Yuan

    (State Grid Liaoning Electric Power Research Institute Co., Ltd., Shenyang 110055, China)

Abstract

Effective aggregation and rational allocation of flexible resources are the fundamental methods for solving the problem of an insufficient flexibility adjustment ability of a power system. The flexible scheduling resources of a distribution system are often small in scale and distributed mostly by different stakeholders. A virtual power plant (VPP) gathers small resources to participate in the day-ahead electricity market, but, due to the scale and characteristics of a VPP’s internal flexible resources, it cannot reach the access threshold of a peak shaving market in some periods due to small differences. In order to solve the market bidding problem of a VPP limited by capacity, and to achieve economic goals, a virtual power plant operator (VPPO) not only needs to interact with internal subjects but also needs to interact with other subjects with flexible resources in the distribution network. In this study, an electric vehicle (EV) cluster is taken as the interactive object, and a day-ahead bidding strategy of a VPP with multi-level electric energy interaction is proposed. The VPP not only makes full-time game pricing for internal participants but also makes time-sharing bargaining with an EV operator. The validity and the rationality of the proposed strategy are verified by an example.

Suggested Citation

  • Hui Sun & Yanan Dou & Shubo Hu & Zhengnan Gao & Zhonghui Wang & Peng Yuan, 2023. "Day-Ahead Bidding Strategy of a Virtual Power Plant with Multi-Level Electric Energy Interaction in China," Energies, MDPI, vol. 16(19), pages 1-27, September.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:19:p:6760-:d:1245339
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    References listed on IDEAS

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