A Cross-Country Model for End-Use Specific Aggregated Household Load Profiles

Marlon Schlemminger, Raphael Niepelt and Rolf Brendel
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Marlon Schlemminger: Department Solar Energy, Leibniz University Hannover, Appelstr. 2, 30167 Hannover, Germany
Raphael Niepelt: Department Solar Energy, Leibniz University Hannover, Appelstr. 2, 30167 Hannover, Germany
Rolf Brendel: Department Solar Energy, Leibniz University Hannover, Appelstr. 2, 30167 Hannover, Germany

Energies, 2021, vol. 14, issue 8, 1-24

Abstract: End-use specific residential electricity load profiles are of interest for energy system modelling that requires future load curves or demand-side management. We present a model that is applicable across countries to predict consumption on a regional and national scale, using openly available data. The model uses neural networks (NNs) to correlate measured consumption from one country (United Kingdom) with weather data and daily profiles of a mix of human activity and device specific power profiles. We then use region-specific weather data and time-use surveys as input for the trained NNs to predict unscaled electric load profiles. The total power profile consists of the end-use household load profiles scaled with real consumption. We compare the model’s results with measured and independently simulated profiles of various European countries. The NNs achieve a mean absolute error compared with the average load of 6.5 to 33% for the test set. For Germany, the standard deviation between the simulation, the standard load profile H0, and measurements from the University of Applied Sciences Berlin is 26.5%. Our approach reduces the amount of input data required compared with existing models for modelling region-specific electricity load profiles considering end-uses and seasonality based on weather parameters. Hourly load profiles for 29 European countries based on four historical weather years are distributed under an open license.

Keywords: energy system modelling; household load profile; neural network; end-uses; consumer behavior; cross-country; open data (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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