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Multiple Virtual Power Plants Transaction Matching Strategy Based on Alliance Blockchain

Author

Listed:
  • Tianfeng Chu

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
    Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China)

  • Xingchen An

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

  • Wuyang Zhang

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
    Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China)

  • Yan Lu

    (Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China)

  • Jiaqi Tian

    (College of Information Science and Engineering, Northeastern University, Shenyang 110819, China)

Abstract

Virtual power plants can aggregate distributed energy resources and interruptible loads in a region for coordinated regulation and unified transaction. However, with the diversification of competition in the electricity market, the distributed operation mechanism between multiple virtual power plants (multi-VPPs) has gradually become a research focus. Based on this, this paper proposes a new type of distributed transactions strategy between multi-VPPs, i.e., the transaction matching mechanism. A two-stage transaction model based on the transaction matching is constructed for multi-VPPs to participate in the day-ahead and intraday electricity trading markets. In the first stage, each VPP optimizes its own internal units’ output and external interaction power through a cooperative game; in the second stage, it is the transaction matching among multi-VPPs that can match the most suitable counterpart by flexible price setting to increase the benefits of all the VPPs. Considering the efficiency and security of blockchain technology, we choose to complete the transaction matching between multi-VPPs with the support of alliance blockchain technology to improve the speed of system solution.

Suggested Citation

  • Tianfeng Chu & Xingchen An & Wuyang Zhang & Yan Lu & Jiaqi Tian, 2023. "Multiple Virtual Power Plants Transaction Matching Strategy Based on Alliance Blockchain," Sustainability, MDPI, vol. 15(8), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6939-:d:1128321
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    References listed on IDEAS

    as
    1. Uyikumhe Damisa & Nnamdi I. Nwulu & Pierluigi Siano, 2022. "Towards Blockchain-Based Energy Trading: A Smart Contract Implementation of Energy Double Auction and Spinning Reserve Trading," Energies, MDPI, vol. 15(11), pages 1-16, June.
    2. Yantao Wang & Yinhan Zhang & Xuesong Qi & Meiqi Wang & Xinyue Wang, 2023. "A Bi-Level Optimization Model for Virtual Power Plant Membership Selection Considering Load Time Series," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
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    Cited by:

    1. Yan Gao & Long Gao & Pei Zhang & Qiang Wang, 2023. "Two-Stage Optimization Scheduling of Virtual Power Plants Considering a User-Virtual Power Plant-Equipment Alliance Game," Sustainability, MDPI, vol. 15(18), pages 1-28, September.

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