GT-CFS: A game theoretic coalition formulation strategy for reducing power loss in micro grids

Chao Wei, Zubair M. Fadlullah, Nei Kato, Akira Takeuchi

Research output: Contribution to journalArticlepeer-review

81 Citations (Scopus)

Abstract

In recent years, research attention on smart grid comprising distributed power generators has increased. To produce electricity in the smart grid, many micro grids (MGs) may exploit various renewable energy resources. Because the production capacity of renewable resources cannot be controlled, the MGs often require the power plants to provide power for them. However, the power loss between each MG and the power plant is larger than that among the MGs. To alleviate this power loss, we propose a game theoretic coalition formulation strategy for the MGs dubbed GT-CFS. Our proposed GT-CFS allows the MGs (belonging to the same macro station (MS)) to autonomously cooperate and self-organize into a partition composed of disjoint MG coalitions. Also, GT-CFS enables the MGs, in a distributed manner, to decide whether they will remain in the coalitions or not upon environmental changes, e.g., the variation of the power demand of the MGs. Within every coalition, MGs coordinate the power transfer among themselves as well as with the MS, in a fashion to optimize a utility function, which captures the total losses over the power distribution lines. MGs in the same coalition will distribute the extra profits (i.e., payoff) produced from forming coalitions by their 'Shapley value.' Through computer simulations, we demonstrate that the proposed GT-CFS reduces the average power loss per MG significantly in contrast with the conventional noncooperative approach.

Original languageEnglish
Article number6565982
Pages (from-to)2307-2317
Number of pages11
JournalIEEE Transactions on Parallel and Distributed Systems
Volume25
Issue number9
DOIs
Publication statusPublished - 2014 Sep

Keywords

  • Coalition game
  • Shapley value
  • cooperative game
  • micro grid

ASJC Scopus subject areas

  • Signal Processing
  • Hardware and Architecture
  • Computational Theory and Mathematics

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