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author:

Gao, Jin (Gao, Jin.) [1] | Shao, Zhenguo (Shao, Zhenguo.) [2] | Chen, Feixiong (Chen, Feixiong.) [3] | Chen, Yuchao (Chen, Yuchao.) [4] | Lin, Yongqi (Lin, Yongqi.) [5] | Deng, Hongjie (Deng, Hongjie.) [6]

Indexed by:

EI ESCI Scopus

Abstract:

In microgrid (MG) systems, traditional centralised energy trading models can lead to issues such as low energy efficiency due to unstable energy supply and lack of flexibility. Peer-to-peer (P2P) trading models have been widely used due to their advantages in promoting the sustainable development of renewable energy and reducing energy trading costs. However, P2P multi-energy trading requires mutual agreements between two microgrids (MGs), and the uncertainties of renewable energy and load affects energy supply security. To address these issues, this article proposed a distributed robust operation strategy based on P2P multi-energy trading for multi-microgrid (MMG) systems. Firstly, a two-stage robust optimisation (TRO) method was adopted to consider the uncertainties of P2P multi-energy trading between MGs, which reduced the conservatism of robust optimisation (RO). Secondly, a TRO model for P2P multi-energy trading among MGs was established based on the Nash bargaining theory, where each MG negotiates with others based on their energy contributions in the cooperation. Additionally, a distributed algorithm was used to protect the privacy of each MG. Finally, the simulation results based on three MGs showed that the proposed approach can achieve a fair distribution of cooperative interests and effectively promote cooperation among MGs. © 2023 The Authors. IET Energy Systems Integration published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology and Tianjin University.

Keyword:

Energy efficiency Energy management Energy management systems Energy utilization Microgrids Optimization Power markets

Community:

  • [ 1 ] [Gao, Jin]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Shao, Zhenguo]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 3 ] [Chen, Feixiong]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Chen, Yuchao]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 5 ] [Lin, Yongqi]Fujian Smart Electrical Engineering Technology Research Center, College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 6 ] [Deng, Hongjie]Guangzhou Power Supply Bureau Co., Ltd., Guangzhou, China

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Source :

IET Energy Systems Integration

Year: 2023

Issue: 4

Volume: 5

Page: 376-392

1 . 6

JCR@2023

1 . 6 0 0

JCR@2023

JCR Journal Grade:3

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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