IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1903.10965.html
   My bibliography  Save this paper

Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering

Author

Listed:
  • Liyang Han
  • Thomas Morstyn
  • Constance Crozier
  • Malcolm McCulloch

Abstract

Among the various market structures under peer-to-peer energy sharing, one model based on cooperative game theory provides clear incentives for prosumers to collaboratively schedule their energy resources. The computational complexity of this model, however, increases exponentially with the number of participants. To address this issue, this paper proposes the application of K-means clustering to the energy profiles following the grand coalition optimization. The cooperative model is run with the "clustered players" to compute their payoff allocations, which are then further distributed among the prosumers within each cluster. Case studies show that the proposed method can significantly improve the scalability of the cooperative scheme while maintaining a high level of financial incentives for the prosumers.

Suggested Citation

  • Liyang Han & Thomas Morstyn & Constance Crozier & Malcolm McCulloch, 2019. "Improving the Scalability of a Prosumer Cooperative Game with K-Means Clustering," Papers 1903.10965, arXiv.org.
  • Handle: RePEc:arx:papers:1903.10965
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1903.10965
    File Function: Latest version
    Download Restriction: no

    References listed on IDEAS

    as
    1. Sankaran, Jayaram K, 1991. "On Finding the Nucleolus of an N-Person Cooperative Game," International Journal of Game Theory, Springer;Game Theory Society, vol. 19(4), pages 329-338.
    Full references (including those not matched with items on IDEAS)

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1903.10965. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.