• DocumentCode
    648054
  • Title

    Specialized genetic algorithm to solve the electrical distribution system expansion planning

  • Author

    Camargo, V. ; Lavorato, Marina ; Romero, Ruben

  • Author_Institution
    Dept. of Math. of Sinop, Mato Grosso State Univ., Sinop, Brazil
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A specialized genetic algorithm with a adaptation of Chu-Beasley algorithm is presented in this paper to solve the electrical distribution distribution system expansion planning (DSP) problem modeled by a mixed integer nonlinear programming problem. The specialized genetic algorithm proposed in this paper starting from a initial population where all elements have a radial topology found using a heuristic algorithm and after the selection and mutation operations must also go through a local improvement in order to make the proposed solution in a feasible solution, if necessary, with respect to operational constraints. The DSP problem presented in this paper consider the circuit construction/recondutoring for different types of conductors and the substation construct/reinforcement. To evaluate the quality of the proposed methodology were used three different test systems found in the literature, 23, 54 and 136 buses systems.
  • Keywords
    genetic algorithms; integer programming; nonlinear programming; power distribution planning; 136 buses system; 23 buses system; 54 buses system; Chu-Beasley algorithm; DSP problem; circuit construction; circuit recondutoring; electrical distribution system expansion planning; heuristic algorithm; mixed integer nonlinear programming problem; radial topology; specialized genetic algorithm; Digital signal processing; Genetic algorithms; Planning; Proposals; Sociology; Statistics; Substations; Distribution network planning; genetic algorithm; mixed integer nonlinear programming; power systems optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672615
  • Filename
    6672615