• DocumentCode
    3440290
  • Title

    An ice-coating predict system of transmission lines based on the improved neural network

  • Author

    Zhou, Jing ; Gu, Longfei ; Lai, Zhengtian ; Teng, Jing

  • Author_Institution
    Sch. of Control & Comput. Eng., North China Electr. Power Univ., Beijing, China
  • Volume
    3
  • fYear
    2010
  • fDate
    29-31 Oct. 2010
  • Firstpage
    831
  • Lastpage
    834
  • Abstract
    Due to the various weather conditions and the diverse geographical environments, ice disaster is unavoidable in many regions of China. The phenomena of ice-coating lead to quick and massive increment of the weight of transmission lines, resulting in wire breakage, tower toppling, flashover and other accidents. Therefore, it is of great significance to improve the capability of predicting and combating these serious disasters. This paper proposes to predict the thickness of ice-coating using an improved neural network. Based on analysis of the near-term meteorological parameters, including temperature, humidity and wind velocity, etc., problems in electricity transmission are effectively predicted and prevented.
  • Keywords
    disasters; ice; meteorology; neural nets; power engineering computing; power transmission lines; prediction theory; electricity transmission lines; ice disaster; ice-coating predict system; neural network; tower toppling; wire breakage; Indium tin oxide; Presses; Ice disaster; Ice-coating predict; Neural network; Transmission lines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-6582-8
  • Type

    conf

  • DOI
    10.1109/ICICISYS.2010.5658332
  • Filename
    5658332