• DocumentCode
    1335925
  • Title

    Application of Grey Correlation Analysis in Evolutionary Programming for Distribution System Feeder Reconfiguration

  • Author

    Tsai, Men-Shen ; Hsu, Fu-Yuan

  • Author_Institution
    Grad. Inst. of Autom. Technol., Nat. Taipei Univ. of Technol., Taipei, Taiwan
  • Volume
    25
  • Issue
    2
  • fYear
    2010
  • fDate
    5/1/2010 12:00:00 AM
  • Firstpage
    1126
  • Lastpage
    1133
  • Abstract
    Feeder reconfiguration is a common technique that is used by distribution system operators during normal or emergency operational planning. By changing the status of switches on the distribution systems, the feeders can be reconfigured. During a feeder reconfiguration, more than one objective is considered by the distribution system operators. Due to the complexity of the reconfiguration problems, the system operators are looking for assistance from computer program that can provide adequate switching plans to reconfigure the feeders such that the desired goal can be achieved. Thus, the feeder reconfiguration is a type of discrete multi-objective optimization problems. Evolutionary programming (EP) technique is a method that can be applied to identify an optimal switching plan for feeder reconfiguration. A fitness function is required in EP for chromosome selection during reproduction process. The fitness function needs to integrate the objectives to provide a measure for each chromosome. Normalizing the objectives is a typical method for multi-objective optimizations such that these objectives are comparable. In this paper, Gray CoRrelation Analysis (GCRA) method is proposed. The proposed method is used to integrate the objectives and provide a relative measure to a particular switching plan associated with a chromosome without any prior knowledge of the system under reconfiguration. Two different distribution systems are used in this paper to demonstrate how the proposed GCRA is applied during the selection process of EP. Several simulations show that the EP can identify the solution more accurately when GCRA is applied than other methods.
  • Keywords
    correlation methods; distribution networks; evolutionary computation; grey systems; power distribution planning; switching; discrete multiobjective optimization; distribution system feeder reconfiguration; evolutionary programming; grey correlation analysis; operational planning; optimal switching plan; Evolutionary programming; grey correlation analysis; power distribution planning;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2009.2032325
  • Filename
    5337944