A Novel Approach to Neighborhood Fair Energy Trading in a Distribution Network of Multiple Microgrid Clusters

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Abstract

Microgrids (MGs) have emerged as an ideal platform to integrate distributed energy resources (DERs) in a distribution network. However, the intermittent nature of DERs poses a new challenge of energy balance within a MG. Trading energy among the MGs has emerged as a well-suited solution. Therefore, we have proposed a novel method for fair and stable energy sharing among MG clusters with minimum information overhead. The novelty of the proposed method lies within the seller level game and introduction of a new pricing mechanism. The concept of an aggregator is used as a mediator between the trading parties. Depending on the priority factor, each buyer MG decides its strategy for energy demand from the surplus using a noncooperative game theory-based algorithm. The interests of seller MGs are protected by allowing them to decide the amount of energy they want to share out of their total surplus. To avoid the selfish behavior of any buyer MG, an algorithm is used by the energy market operator which verifies the strategies submitted by buyer MGs before releasing set points to the generators. Apart from fairness and stability, the extensive numerical study confirms the ascendancy of the proposed method.

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Microgrids (MGs) have emerged as an ideal platform to integrate distributed energy resources (DERs) in a distribution network. However, the intermittent nature of DERs poses a new challenge of energy balance within a MG. Trading energy among the MGs has emerged as a well-suited solution. Therefore, we have proposed a novel method for fair and stable energy sharing among MG clusters with minimum information overhead. The novelty of the proposed method lies within the seller level game and introduction of a new pricing mechanism. The concept of an aggregator is used as a mediator between the trading parties. Depending on the priority factor, each buyer MG decides its strategy for energy demand from the surplus using a noncooperative game theory-based algorithm. The interests of seller MGs are protected by allowing them to decide the amount of energy they want to share out of their total surplus. To avoid the selfish behavior of any buyer MG, an algorithm is used by the energy market operator which verifies the strategies submitted by buyer MGs before releasing set points to the generators. Apart from fairness and stability, the extensive numerical study confirms the ascendancy of the proposed method.

Original languageEnglish
Article number8316917
JournalIEEE Transactions on Industrial Electronics
Volume66
Issue number2
Pages (from-to)1520-1531
Number of pages12
ISSN0278-0046
DOI
Publication statusPublished - 1 Feb 2019
Publication categoryResearch
Peer-reviewedYes

    Research areas

  • Distributed energy resources (DERs), energy trading, game theory, microgrids (MGs), multiple microgrid clusters

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