• DocumentCode
    1942137
  • Title

    Short term load forecast based on time series analysis: A case study

  • Author

    Dodamani, S.N. ; Shetty, V.J. ; Magadum, R.B.

  • Author_Institution
    Gogte Inst. of Technol., Belagavi, India
  • fYear
    2015
  • fDate
    24-26 June 2015
  • Firstpage
    299
  • Lastpage
    303
  • Abstract
    Short term load forecasting plays a vital role in the daily generation, efficient power system planning, unit maintenance, determining unit commitment and secured power system operation. There are number of approaches for short term load forecasting but it is observed that time series approach is most feasible and provides more reasonable accurate forecast. The present paper discuses the Autoregressive (AR) approach of time series analysis for short term load forecast for Tamilnadu (India) load data. The time series Autoregressive gives better forecasting results for 4 to 6 Hours ahead.
  • Keywords
    autoregressive processes; load forecasting; power generation dispatch; power generation economics; power generation planning; power generation scheduling; power system security; time series; AR approach; India; Tamilnadu; autoregressive approach; efficient power system planning; power system operation security; short-term load forecasting; time series analysis; unit commitment; unit maintenance; Biomass; Forecasting; Hydroelectric power generation; Load forecasting; Load modeling; Mathematical model; Wind; Autoregressive (AR) models; Load data; Root Mean Square Error (RMSE); Short term load forecast; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advancements in Power and Energy (TAP Energy), 2015 International Conference on
  • Conference_Location
    Kollam
  • Type

    conf

  • DOI
    10.1109/TAPENERGY.2015.7229635
  • Filename
    7229635