• DocumentCode
    619759
  • Title

    General reactive power optimization of distribution network based on power loss sensitivity analysis

  • Author

    Zhan Mengmeng ; Shang Qunli ; Ling Long

  • Author_Institution
    Sch. of Autom., Hangzhou Dianzi Univ., Hangzhou, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    566
  • Lastpage
    570
  • Abstract
    A reactive power optimization method for distribution network based on power loss sensitivity analysis is proposed. Take the minimized sum of power loss and the investment of reactive power compensation devices as objective function to build the mathematical model for optimization. According to the features of distribution network, i.e., numerous nodes, complicated structures and generous amount of calculation, sensitivity analysis method is used and appropriate improvement is made on it. Both of the network structure and load distribution are considered and through matrix calculation to get the sensitivity indexes .The compensation capacity at the installation buses is decided by the Simple Genetic Algorithm (SGA). The test results on IEEE28-bus system demonstrate the validity with fast calculation, lower energy loss and higher voltages.
  • Keywords
    distribution networks; genetic algorithms; matrix algebra; reactive power; sensitivity analysis; IEEE28-bus system; SGA; compensation capacity; distribution network; general reactive power optimization; installation buses; investment; load distribution; mathematical model; matrix calculation; network structure; objective function; power loss sensitivity analysis; sensitivity indexes; simple genetic algorithm; Educational institutions; Electronic mail; Linear programming; Optimization; Power system stability; Reactive power; Sensitivity analysis; Distribution Network; Matrix; Reactive Power Optimization; SGA; Sensitivity Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6560988
  • Filename
    6560988