• DocumentCode
    1683298
  • Title

    A neural approach for determination of global energetic efficiency indicator in groundwater wells

  • Author

    Saggioro, Nilton Jose ; Cagnon, Jose Angelo ; Silva, Ivan Nunes da

  • Author_Institution
    State Univ. of Sao Paulo, Brazil
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1258
  • Lastpage
    1262
  • Abstract
    In most of the cases, the systems of water distribution from groundwater wells use electrical submersible pumps. All electrical energy is applied to the pumps; however, other components (pipes, valves, etc.) of these systems are also responsible by the higher or lower consumption of electric energy. The supervisors and operators of the systems should thus have knowledge of the global energetic behavior of the process in order to administrate it properly. This work suggests a ´global energy efficiency indicator´ for groundwater wells by using mathematical equations and neural networks. Simulation results are presented in order to demonstrate the validity of the proposed approach
  • Keywords
    groundwater; multilayer perceptrons; power consumption; pumping plants; water supply; electrical submersible pumps; global energy efficiency indicator; groundwater wells; multilayer perceptron; neural networks; pumping system; underground aquifers; water distribution; water supply system; Energy consumption; Equations; Geology; Iron; Neural networks; Production; Testing; Underwater vehicles; Valves; Water resources;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
  • Conference_Location
    Honolulu, HI
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-7278-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.2002.1007675
  • Filename
    1007675