• DocumentCode
    1688567
  • Title

    Calculation of transmission system losses for the Taiwan Power Company by the artificial neural network with time decayed weight

  • Author

    Chu, Wen-Chen ; Chen, Bin-Kwie ; Mo, Pao-Chang

  • Author_Institution
    Tatung Inst. of Technol., Taipei, Taiwan
  • Volume
    1
  • fYear
    1995
  • Firstpage
    80
  • Abstract
    For energy conservation and improvement of power system operation efficiency, how to reduce the transmission system losses becomes an important topic of grave concern. To understand the cause, and to evaluate the amount, of the losses are the prior steps to diminish them. To simplify the evaluation procedure without losing too much accuracy, this paper adopts the artificial neural network, which is a model free network, to analyze the transmission system losses. As the artificial neural network with time decayed weight has the capability of learning, memorizing, and forgetting, it is more suitable for a power system with gradually changing characteristics. By using this artificial neural network, the estimation of transmission system losses will be more precise. In this paper, comparison is made between the results of artificial neural network analysis and polynomial loss equations analysis
  • Keywords
    losses; neural nets; polynomials; power system analysis computing; power transmission; Taiwan Power Company; artificial neural network; forgetting capability; learning capability; memorizing capability; model free network; polynomial loss equations analysis; power system operation efficiency; time decayed weight; transmission system losses; Artificial neural networks; Energy conservation; Equations; IEEE members; Polynomials; Power system analysis computing; Power system modeling; Power systems; Propagation losses; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Energy Management and Power Delivery, 1995. Proceedings of EMPD '95., 1995 International Conference on
  • Print_ISBN
    0-7803-2981-3
  • Type

    conf

  • DOI
    10.1109/EMPD.1995.500704
  • Filename
    500704