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author:

Chen, X. (Chen, X..) [1] | Zhang, Y. (Zhang, Y..) [2] (Scholars:张亚超) | Huang, Z. (Huang, Z..) [3] | Xie, S. (Xie, S..) [4] (Scholars:谢仕炜)

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EI Scopus PKU CSCD

Abstract:

The uncertainty of renewable energy output brings challenge to the market pricing mechanism,it becomes a key problem to realize balanced benefit distribution among market participants. A market clearing mechanism for locational marginal price considering the uncertainty of wind power output is proposed. A bi-level model for coordinated optimal dispatch between distribution network and multiple microgrids is established. The upper level model is a data-driven robust economic dispatch model of the distribution network considering the uncertainty of wind power output and power interaction,and the lower level model is a data-driven robust economic dispatch model of the microgrids considering price-based demand response. The upper and lower level models are iteratively solved through the information transmission of power interaction and electricity price between the distribution network and microgrids,which realizes balanced benefit distribution among different market participants. The simulative results of a test system verify the effectiveness of the proposed model and the solving approach. © 2023 Electric Power Automation Equipment Press. All rights reserved.

Keyword:

bi-level optimization distribution network market pricing mechanism multiple microgrids price-based demand response

Community:

  • [ 1 ] [Chen X.]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Zhang Y.]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Huang Z.]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Xie S.]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, 350108, China

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Source :

Electric Power Automation Equipment

ISSN: 1006-6047

CN: 32-1318/TM

Year: 2023

Issue: 11

Volume: 43

Page: 51-58

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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