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

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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, revised Jul 2020.
    • Handle: RePEc:arx:papers:1903.10965
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    References listed on IDEAS

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    1. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    2. Zhou, Yue & Wu, Jianzhong & Long, Chao, 2018. "Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework," Applied Energy, Elsevier, vol. 222(C), pages 993-1022.
    3. 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.
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