• DocumentCode
    2762133
  • Title

    Research on the Forecast of Electricity Consumption Based on Autoregressive Model

  • Author

    Baosen, Wang ; Dawei, Hu ; Yi, Cheng ; Yizhe, Zhou

  • Author_Institution
    Sch. of Econ. & Manage., Hebei Univ. of Eng., Handan, China
  • Volume
    2
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    166
  • Lastpage
    169
  • Abstract
    With the rapid growth of the national economy, the electricity supply presents severe shortage, which directly affects the economic development and the normal life of people. Electricity supply has become a restricting factor on sustainable development of national economy. According to the recent situation of electricity demand, this paper uses time series analysis on its consumer to do scientific prediction, and put forward to prevent future electricity shortages, we should establish power early warning system, adopt time-of-use electricity price for a short term, and adjust the industrial structure, especially the internal structure of industrial products. Then we can promote economic growth mode to transform from extensive to intensive, which can improve the quality and efficiency of economic growth. Energy saving will be a long-term strategy policy of national economic development from the point of view of the long-term development of the electricity industry.
  • Keywords
    Alarm systems; Economic forecasting; Energy consumption; Forward contracts; Industrial economics; Power generation economics; Power system economics; Predictive models; Sustainable development; Time series analysis; AM; Autoregressive Models; Eviews; electricity consumption; time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Challenges in Environmental Science and Computer Engineering (CESCE), 2010 International Conference on
  • Conference_Location
    Wuhan, China
  • Print_ISBN
    978-0-7695-3972-0
  • Electronic_ISBN
    978-1-4244-5924-7
  • Type

    conf

  • DOI
    10.1109/CESCE.2010.120
  • Filename
    5493252