• DocumentCode
    2440948
  • Title

    Analysis of Electricity Demand Forecasting in Inner Mongolia Based on Gray Markov Model

  • Author

    Dongxiao Niu ; Yanan Wei ; Jianqing Li ; Cong Xu ; Junfang Wu

  • Author_Institution
    Sch. of Bus. Manage., Univ. of North China Electr. Power, Beijing, China
  • fYear
    2010
  • fDate
    7-9 May 2010
  • Firstpage
    5082
  • Lastpage
    5085
  • Abstract
    Accurate electricity demand forecasting is the foundation of power system operation and planning, the basic of placing development plans, business strategy and tactics of the power companies. Electricity consumption is a gray system which is impacted by economic development, industrial structure, income levels and national policies. The paper counted Inner Mongolia electricity data from four factors, used the gray model GM (1, n) to predict, established Markov model from the percentage of relative deviation δ of the fitted value and actual value, and revised forecast values obtained from gray model. At last, the paper predicted the demand for electric power industry in Inner Mongolia by gray Markov model.
  • Keywords
    Gaussian processes; Markov processes; load forecasting; power consumption; power system economics; power system planning; Gaussian model; business strategy; development plans; economic development; electric power industry; electricity consumption; electricity demand forecasting; gray Markov model; income levels; industrial structure; inner Mongolia electricity data; national policies; power companies; power system operation; power system planning; Biological system modeling; Electricity; Industries; Markov processes; Mathematical model; Power systems; Predictive models; Markov prediction model; consumption of electricity in Inner Mongolia; gray model; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    E-Business and E-Government (ICEE), 2010 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3997-3
  • Type

    conf

  • DOI
    10.1109/ICEE.2010.1275
  • Filename
    5592892