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author:

Liu, Yan (Liu, Yan.) [1] | Zhang, Yachao (Zhang, Yachao.) [2] | Zhu, Shu (Zhu, Shu.) [3] | Xie, Shiwei (Xie, Shiwei.) [4]

Indexed by:

EI PKU CSCD

Abstract:

The large-scale access of EVsElectric Vehicles and distributed energy has posed great challenges to the safe and economic operation of distribution networks. Considering that HADDNHybrid ACDC Distribution Network has the characteristics of high flexibility and controllability and significant partitioning featuresa distributed cooperative optimization method of HADDN active and reactive power considering the dual uncertainties of source side and load side is proposed. Firstlythe EV charging load-wind power scenario generation method is proposedwhich comprehensively considers the traffic topology structurethe residents’travel behavior and the interval difference of wind power prediction error. The optimal scenario reduction algorithm based on Wasserstein distance is used to generate typical probability scenarios. Secondlythe stochastic optimization model of HADDN is established to minimize the network loss and node voltage deviation. Thenthe objective decomposition and region decoupling of the proposed multi-objective optimization model are performedand the alternating direction method of multipliers based on the objective value exchange principle is used to solve the above model. Finallythe effectiveness of the proposed method is verified by a numerical example. © 2022 Electric Power Automation Equipment Press. All rights reserved.

Keyword:

Electric vehicles Multiobjective optimization Numerical methods Stochastic models Stochastic systems Wind power

Community:

  • [ 1 ] [Liu, Yan]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 2 ] [Zhang, Yachao]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China
  • [ 3 ] [Zhu, Shu]Dispatching and Control Center, State Grid Hunan Electric Power Co.Ltd., Changsha; 410004, China
  • [ 4 ] [Xie, Shiwei]School of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350108, China

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Source :

Electric Power Automation Equipment

ISSN: 1006-6047

Year: 2022

Issue: 10

Volume: 42

Page: 218-226,272

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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