Journal of Electrical Engineering and Technology

  • 제13권5호
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  • Pages.1778-1790
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  • 2018
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  • 1975-0102(pISSN)
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  • 2093-7423(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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Fully Distributed Economic Dispatching Methods Based on Alternating Direction Multiplier Method

  • Yang, Linfeng (School of Computer Electronics and Information, Guangxi University) ;
  • Zhang, Tingting (School of Computer Electronics and Information, Guangxi University) ;
  • Chen, Guo (School of Electrical Engineering and Telecommunications, University of New South Wales) ;
  • Zhang, Zhenrong (School of Computer Electronics and Information, Guangxi University) ;
  • Luo, Jiangyao (School of Computer Electronics and Information, Guangxi University) ;
  • Pan, Shanshan (College of Electrical Engineering, Guangxi University)
  • 투고 : 2017.11.10
  • 심사 : 2018.02.02
  • 발행 : 2018.09.01
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초록

Based on the requirements and characteristics of multi-zone autonomous decision-making in modern power system, fully distributed computing methods are needed to optimize the economic dispatch (ED) problem coordination of multi-regional power system on the basis of constructing decomposition and interaction mechanism. In this paper, four fully distributed methods based on alternating direction method of multipliers (ADMM) are used for solving the ED problem in distributed manner. By duplicating variables, the 2-block classical ADMM can be directly used to solve ED problem fully distributed. The second method is employing ADMM to solve the dual problem of ED in fully distributed manner. N-block methods based on ADMM including Alternating Direction Method with Gaussian back substitution (ADM_G) and Exchange ADMM (E_ADMM) are employed also. These two methods all can solve ED problem in distributed manner. However, the former one cannot be carried out in parallel. In this paper, four fully distributed methods solve the ED problem in distributed collaborative manner. And we also discussed the difference of four algorithms from the aspects of algorithm convergence, calculation speed and parameter change. Some simulation results are reported to test the performance of these distributed algorithms in serial and parallel.

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