• DocumentCode
    3336222
  • Title

    Network reconfiguration using a genetic approach for loss and reliability optimization in distribution systems

  • Author

    Vitorino, Romeu M V ; Jorge, Humberto M M ; Neves, Luís M P

  • Author_Institution
    Dept. of Electr. Eng., Polytech. Inst. of Leiria, Leiria
  • fYear
    2009
  • fDate
    18-20 March 2009
  • Firstpage
    84
  • Lastpage
    89
  • Abstract
    This paper presents a new method to improve reliability and also minimize losses in radial distribution systems (RDS), trough a process of network reconfiguration, using a genetic algorithm approach. The methodology adopted to enhance reliability, uses the Monte Carlo simulation and an historical data of the network such as the level of reliability and the severity of potential contingencies in each branch. The method analyses the RDS in two perspectives. A first perspective of optimization considering no investment, therefore using only the switches presented in the network, and a second perspective of optimization where is given the possibility to place a limited number of tie-switches and thus get better results. Here, the number of tie-switches and the branches that can receive them are defined by a decision agent. The effectiveness of the proposed method is demonstrated through the analysis of a 69 bus RDS.
  • Keywords
    Monte Carlo methods; distribution networks; genetic algorithms; power system reliability; Monte Carlo simulation; genetic algorithm; genetic approach; loss optimization; network reconfiguration; radial distribution systems; reliability optimization; Computer network reliability; Computer networks; Distributed computing; Genetics; Load management; Optimization methods; Paper technology; Power system reliability; Simulated annealing; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, Energy and Electrical Drives, 2009. POWERENG '09. International Conference on
  • Conference_Location
    Lisbon
  • Print_ISBN
    978-1-4244-4611-7
  • Electronic_ISBN
    978-1-4244-2291-3
  • Type

    conf

  • DOI
    10.1109/POWERENG.2009.4915219
  • Filename
    4915219