• Title of article

    Long term forecasting of hourly electricity consumption in local areas in Denmark

  • Author/Authors

    Andersen، نويسنده , , F.M. and Larsen، نويسنده , , H.V. and Gaardestrup، نويسنده , , R.B.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2013
  • Pages
    16
  • From page
    147
  • To page
    162
  • Abstract
    Long term projections of hourly electricity consumption in local areas are important for planning of the transmission grid. In Denmark, at present the method used for grid planning is based on statistical analysis of the hour of maximum load and for each local area the maximum load is projected to change proportional to changes in the aggregated national electricity consumption. That is, specific local conditions are not considered. Yet, from measurements of local consumption we know that: ption profiles differ between local areas, ption by categories of customers contribute differently to the aggregated consumption profile, ight of categories of customers differ between local areas. s paper we present a model calculating local consumption as composed of consumption by categories of customers with specific consumption profiles and different weights in local areas. The model describes the entire profile of hourly consumption and is a first step towards differentiated local predictions of electricity consumption. del is based on metering of aggregated hourly consumption at transformer stations covering selected local areas and on national statistics of hourly consumption by categories of customers. The model is estimated on data for the years 2009–2011 (in total 26,280 hourly observations). To evaluate how the model describes present consumption in local areas, observed and simulated hourly load duration curves for 2011 are compared. Using national projections of annual consumption by categories of customers, the model is used to project hourly consumption profiles for selected local areas and results are compared to projections using the existing methodology.
  • Keywords
    Long term electricity consumption , Local areas , Econometric modelling , Forecasting load profiles
  • Journal title
    Applied Energy
  • Serial Year
    2013
  • Journal title
    Applied Energy
  • Record number

    1606409