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A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations

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  • Hu, Qian
  • Zhu, Ziqing
  • Bu, Siqi
  • Wing Chan, Ka
  • Li, Fangxing

Abstract

In the presence of geographically dispersed distributed energy resources (DERs), the microgrid (MG) can be organized into a number of nanogrids (NGs) which provides an efficient approach to aggregating DERs for the participation of ancillary service with a high level of efficiency and controllability. In this regard, this paper presents a multi-market NG trading paradigm for simultaneous real-time imbalance elimination and frequency regulation procurement, based on the architecture of peer-to-peer (P2P) trading and communication. It comprises three consecutive markets: P2P bilateral energy market, balancing market and ancillary service market. Optimal offering strategies are designed to maximize the profits of producer NGs and meanwhile to tackle the capacity allocation tradeoffs among three markets. When it is approaching to real-time, the market will be closed with completion of balancing, and selected NGs with reserved capacity for the ancillary service will provide the real-time frequency regulation in a fully distributed manner. A parameter so-called engagement factor is designed based on the market clearing results to determine the deployment of frequency regulation service of each participated NGs. Subsequently, the pinning-based distributed secondary control upon P2P information sharing among NGs is implemented to regulate the frequency and ensuring the power sharing. The results of case studies indicate the feasibility of the proposed paradigm and its good performance, while different remuneration mechanisms are compared for discussion of their pros and cons.

Suggested Citation

  • Hu, Qian & Zhu, Ziqing & Bu, Siqi & Wing Chan, Ka & Li, Fangxing, 2021. "A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations," Applied Energy, Elsevier, vol. 293(C).
  • Handle: RePEc:eee:appene:v:293:y:2021:i:c:s0306261921004177
    DOI: 10.1016/j.apenergy.2021.116938
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    Cited by:

    1. Zhu, Ziqing & Hu, Ze & Chan, Ka Wing & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2023. "Reinforcement learning in deregulated energy market: A comprehensive review," Applied Energy, Elsevier, vol. 329(C).
    2. Zhu, Ziqing & Wing Chan, Ka & Bu, Siqi & Zhou, Bin & Xia, Shiwei, 2021. "Real-Time interaction of active distribution network and virtual microgrids: Market paradigm and data-driven stakeholder behavior analysis," Applied Energy, Elsevier, vol. 297(C).
    3. Younes Zahraoui & Tarmo Korõtko & Argo Rosin & Hannes Agabus, 2023. "Market Mechanisms and Trading in Microgrid Local Electricity Markets: A Comprehensive Review," Energies, MDPI, vol. 16(5), pages 1-52, February.
    4. Spiliopoulos, Nikolas & Sarantakos, Ilias & Nikkhah, Saman & Gkizas, George & Giaouris, Damian & Taylor, Phil & Rajarathnam, Uma & Wade, Neal, 2022. "Peer-to-peer energy trading for improving economic and resilient operation of microgrids," Renewable Energy, Elsevier, vol. 199(C), pages 517-535.
    5. Zhang, Bidan & Du, Yang & Chen, Xiaoyang & Lim, Eng Gee & Jiang, Lin & Yan, Ke, 2022. "A novel adaptive penalty mechanism for Peer-to-Peer energy trading," Applied Energy, Elsevier, vol. 327(C).
    6. Jun Dong & Dongran Liu & Xihao Dou & Bo Li & Shiyao Lv & Yuzheng Jiang & Tongtao Ma, 2021. "Key Issues and Technical Applications in the Study of Power Markets as the System Adapts to the New Power System in China," Sustainability, MDPI, vol. 13(23), pages 1-29, December.

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