Abstract
This paper describes a dataset of residential electricity household and heat pump load profiles, measured in 38 single-family houses in Northern Germany. We provide data per household of apparent, active and reactive power (W), voltage (V), current (A) and the power factor (no unit) in 10 seconds to 60 minutes temporal resolution from May 2018 to the end of 2020. We validated the dataset both in itself, comparing different measurements that should produce the same results, and externally to standard load profiles and found no major inconsistencies. We identified an average consumption per single-family house with 2.38 inhabitants of 2829 kWh for the household and an additional 4993 kWh for the heat pump. The dataset can support the understanding of patterns in electrical load curves and can help to estimate the additional load on distribution networks induced by heat pumps.
Highlights
Background & SummaryResidential buildings are a major contributor to energy consumption
In the European Union, the residential sector accounted for 26.1% of the final energy consumption in 2018, of which 78.4% are used for space and water heating and the remaining 21.6% are used for electric end-uses such as lighting[1] or appliances
The share of electricity consumption is expected to increase with the rising relevance of heat pumps
Summary
Residential buildings are a major contributor to energy consumption. In the European Union, the residential sector accounted for 26.1% of the final energy consumption in 2018, of which 78.4% are used for space and water heating and the remaining 21.6% are used for electric end-uses such as lighting[1] or appliances. Despite the large amount of datasets available, there is space for improvement in each of them: Most datasets are measured in a single-digit number of households[4,5,7,8,9] and some datasets only provide a temporal resolution of 15 or more minutes[3,6,9]. Measurements including electrical properties such as voltage, current or reactive power are missing[2,3,4,6] and some datasets only make available their data, but are not published in a scientific journal[3,4,6]. None of the datasets provides measurements of electrical household loads and heat pump loads with corresponding weather data. The WPuQ dataset[10] is able to fill the gaps left by the aforementioned datasets and provides a unique combination of a large sample size, high number of measured indicators, high temporal resolution and long measurement period
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