• DocumentCode
    3764692
  • Title

    ANN based electric load forecasting applied to real time data

  • Author

    Shahida Khatoon; Ibraheem;Arunesh Kr. Singh; Priti

  • Author_Institution
    Department of Electrical Engg., Jamia Miilia Islamia, New Delhi, India
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The accuracy of electric load forecasts significantly affects the overall performance of power system. Some time due to complicated load pattern, forecasting becomes difficult. The object of this study is to develop more effective forecasting models, among others. This paper compares the electric load forecasting accuracy of ANN based techniques. This study investigates the time series techniques used to forecasts electric load, e.g. MA, linear trend, the exponential and parabolic trend. In the present study ANN based time series forecasting model has been developed, on hourly electric load consumption data. Data used to forecast is acquired from a distribution company located in Noida, Uttar Pradesh. These ANN based techniques are evaluated for the forecasting errors.
  • Keywords
    "Artificial neural networks","Power systems","Market research","Load modeling","Predictive models"
  • Publisher
    ieee
  • Conference_Titel
    India Conference (INDICON), 2015 Annual IEEE
  • Electronic_ISBN
    2325-9418
  • Type

    conf

  • DOI
    10.1109/INDICON.2015.7443392
  • Filename
    7443392