We develop a methodology for updating and regionalising Standard load profiles. For this purpose we analyse two approaches to separate the total load of a distribution network into commercial and household load. The decoupled time series are used to create improved load profiles for commercial and household consumers. We show that the updating and regionalisation of Standard load profiles reduces the forecast error significantly. This video is an overview to a paper which was presented at the 14th International Conference on the European Energy Market 2017 and appeared at IEEE Xplore: DOI: 10.1109/EEM.2017.7981939

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Author: Daniel Scholz, Chair of Energy Economics at BTU Cottbus-Senftenberg
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Abstract:
Currently, most distribution system operators in Germany estimate non-real-time metered consumption profiles based on “Standard Load Profiles” developed in the late 1990s by the German Association of Energy and Water Industries. However, as both consumption behaviour and consumer structure change over time, their predictive power may have deteriorated. In addition, they do not account for regional differences within Germany. Therefore, we compared their forecasting accuracy with two newly developed alternative standard load profiles, differentiating between households and commercial enterprises. We calculated the new profiles based on regional, more up-to-date aggregated consumption data and a limited set of smart meter data. Furthermore, we varied the number of seasons and day types included in the profiles. A comparison of our new load profiles with the existing Standard Load Profiles revealed significant improvements in forecasting accuracy. Improvements are mainly resulting from improved input data (regional and more recent data set), but the utilization of smart meter data as well as variations in day types and seasons also reduced forecast errors.

Keywords: Energy Economics, Load Forecasting, Load Profile, Smart Meter
Year of publication: 2017

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