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A new trading mechanism for prosumers based on flexible reliability preferences in active distribution network

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  • Chen, Xi
  • Liu, Boxuan
  • Qiu, Jing
  • Shen, Wei
  • Reedman, Luke
  • Dong, Zhao Yang

Abstract

Due to the rapid development of distributed renewable generation, emerging prosumers are encouraged to participate in the energy market. Meanwhile, blackout events, planned and unplanned outages due to weather, component failures and other causes, can also impact users’ experience. To maintain reliability and improve users’ experience under outage conditions, it is possible to transform the service reliability from a public good (compulsory and uniform) to a private good (self-selection). In this paper, a new restore mechanism based on private reliability service is proposed, the reliability service is no longer uniform. Customers with a higher reliability requirement are willing to pay to maintain their desired consumption in outage conditions. The customers are classified by dynamic elasticity considering historical data and real-time customer preferences. Then the advised unit price, trading amount and reliability level are provided to customer. Once they submit this information to market operator, the price and transaction amount is matched in each group, and floated average clearing price is applied to obtain the bidding results. The trading mechanism is proved to satisfy incentive compatibility, and the transaction process for a specific area in Australia is analyzed in a case study to verify the proposed model.

Suggested Citation

  • Chen, Xi & Liu, Boxuan & Qiu, Jing & Shen, Wei & Reedman, Luke & Dong, Zhao Yang, 2021. "A new trading mechanism for prosumers based on flexible reliability preferences in active distribution network," Applied Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:appene:v:283:y:2021:i:c:s0306261920316627
    DOI: 10.1016/j.apenergy.2020.116272
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    References listed on IDEAS

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    Cited by:

    1. Piotr Zuk & Pawel Zuk, 2022. "Prosumers in Action: The Analysis of Social Determinants of Photovoltaic Development and Prosumer Strategies in Poland," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 294-306, July.
    2. Hua, Weiqi & Jiang, Jing & Sun, Hongjian & Tonello, Andrea M. & Qadrdan, Meysam & Wu, Jianzhong, 2022. "Data-driven prosumer-centric energy scheduling using convolutional neural networks," Applied Energy, Elsevier, vol. 308(C).

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