4.8 Article

Peer-to-Peer Multienergy and Communication Resource Trading for Interconnected Microgrids

期刊

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 4, 页码 2522-2533

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3000906

关键词

Distributed optimization; energy hub; multimicrogrids; Nash bargaining solution; resource trading

资金

  1. National Natural Science Foundation of China [51877072]
  2. Huxiang Young Talents Programme of Hunan Province [2019RS2018]
  3. Open Fund of State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources

向作者/读者索取更多资源

This article proposes a peer-to-peer transactive multiresource trading framework for multiple multienergy microgrids, addressing the optimization problem of multiple resources and independent decision-makings. The methodology developed can optimize communication and energy flows through Nash bargaining problem and decomposition, showing superiority in system operational economy and resource utilization.
This article proposes a peer-to-peer transactive multiresource trading framework for multiple multienergy microgrids. In this framework, the interconnected microgrids not only fulfil the multienergy demands of with local hybrid biogas-solar-wind renewables, but also proactively trade their available multienergy and communication resources with each other for delivering secured and high quality of services. The multimicrogrid multienergy and communication trading is an intractable optimization problem because of their inherent strong couplings of multiple resources and independent decision-makings. The original problem is thus formulated as a Nash bargaining problem and further decomposed into the subsequent social multiresource allocation subproblem and payoff allocation subproblem. Furthermore, fully-distributed alternating direction method of multipliers approaches with only limited trading information shared are developed to co-optimize the communication and energy flows while taking into account the local resource-autonomy of heterogeneous microgrids. The proposed methodology is implemented and benchmarked on a three-microgrid system over a 24-h scheduling periods. Numerical results show the superiority of the proposed scheme in system operational economy and resource utilization, and also demonstrate the effectiveness of the proposed distributed approach.

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