• DocumentCode
    2542051
  • Title

    Evolutionary heuristic to determine future land use

  • Author

    Carreno, E.M. ; Padilha-Feltrin, A.

  • Author_Institution
    Univ. Estadual Paulista (UNESP), Ilha Solteira
  • fYear
    2008
  • fDate
    20-24 July 2008
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In the spatial electric load forecasting, the future land use determination is one of the most important tasks, and one of the most difficult, because of the stochastic nature of the city growth. This paper proposes a fast and efficient algorithm to find out the future land use for the vacant land in the utility service area, using ideas from knowledge extraction and evolutionary algorithms. The methodology was implemented into a full simulation software for spatial electric load forecasting, showing a high rate of success when the results are compared to information gathered from specialists. The importance of this methodology lies in the reduced set of data needed to perform the task and the simplicity for implementation, which is a great plus for most of the electric utilities without specialized tools for this planning activity.
  • Keywords
    evolutionary computation; knowledge acquisition; load forecasting; power engineering computing; power system planning; evolutionary algorithms; evolutionary heuristic; knowledge extraction; land use; planning activity; spatial electric load forecasting; utility service area; Cities and towns; Data mining; Evolutionary computation; Fuzzy logic; Land use planning; Load forecasting; Power industry; Spatial databases; Stochastic processes; Substations; Spatial electric load forecasting; distribution planning; knowledge extraction; land use;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE
  • Conference_Location
    Pittsburgh, PA
  • ISSN
    1932-5517
  • Print_ISBN
    978-1-4244-1905-0
  • Electronic_ISBN
    1932-5517
  • Type

    conf

  • DOI
    10.1109/PES.2008.4596675
  • Filename
    4596675