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

Frits Møller Andersen, Helge V. Larsen, R.B. Gaardestrup

    Research output: Contribution to journalJournal articleResearchpeer-review


    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:. •consumption profiles differ between local areas,•consumption by categories of customers contribute differently to the aggregated consumption profile,•the weight of categories of customers differ between local areas.In this 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.The model 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. © 2013 Elsevier Ltd.
    Original languageEnglish
    JournalApplied Energy
    Pages (from-to)147-162
    Publication statusPublished - 2013


    • Aggregates
    • Computer simulation
    • Sales
    • Electric load forecasting
    • Long term electricity consumption
    • Forecasting load profiles
    • Local areas
    • Econometric modelling


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