• DocumentCode
    330496
  • Title

    Short-term load forecasting based on weather information

  • Author

    Feng, Wang ; Keng, Yu Er ; Qi, Liu Yong ; Jun, Liu ; Shan, Yan Chen

  • Author_Institution
    Electr. Power Res. Inst., Beijing, China
  • Volume
    1
  • fYear
    1998
  • fDate
    18-21 Aug 1998
  • Firstpage
    572
  • Abstract
    This paper addresses electric power short-term load forecasting (the next day 24 or 96 time point load) based on weather forecasting information. It describes a load forecasting system that is running in North China Electric Power Network. The system can consider the effect of temperature. Relative humidity and weather condition on the load. The forecasting result is improved. The ANN´s techniques and a simplified pattern recognition are adopted to deal with the complex relation between the load and weather variables
  • Keywords
    load forecasting; neural nets; pattern recognition; power system analysis computing; ANN techniques; North China Electric Power Network; pattern recognition; relative humidity; short-term load forecasting; temperature effect; weather condition; weather information; weather variables; Artificial neural networks; Erbium; Humidity; Load forecasting; Load modeling; Predictive models; Rain; Snow; Temperature; Weather forecasting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power System Technology, 1998. Proceedings. POWERCON '98. 1998 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7803-4754-4
  • Type

    conf

  • DOI
    10.1109/ICPST.1998.729029
  • Filename
    729029