An optimal scheduling strategy for peer-to-peer trading in interconnected microgrids based on RO and Nash bargaining

Chun Wei, Zhuzheng Shen, Dongliang Xiao, Licheng Wang, Xiaoqing Bai and Haoyong Chen

Applied Energy, 2021, vol. 295, issue C, No S0306261921004888

Abstract: Based on the peer-to-peer (P2P) trading framework of interconnected microgrids, this paper proposes an optimal scheduling strategy for interconnected microgrids considering the uncertainty of wind power, to minimize the operation cost of the individual microgrid and obtain profits through active energy trading with other microgrids. The proposed optimization model considers the grid structure of microgrids and uses the robust optimization (RO) method to express uncertainty. The incentive mechanism based on Nash bargaining is used to encourage the individual microgrid to trade energy actively and realize fair benefit sharing. In order to protect the privacy of the individual microgrid, the alternating direction method of multipliers (ADMM) is used to achieve the decentralized solution of the proposed model. Simulation analysis based on four interconnected microgrids shows that each microgrid can ultimately make profits in the trading, verifying the effectiveness and fairness of the proposed method.

Keywords: Alternating direction method of multipliers; Interconnected microgrid; Nash bargaining; Peer-to-peer trading; Robust optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (25)

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DOI: 10.1016/j.apenergy.2021.117024

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