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Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case

Authors: Leiria, Daniel; Johra, Hicham; Marszal-Pomianowska, Anna; Pomianowski, Michal Zbigniew; Kvols Heiselberg, Per;

Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case

Abstract

In Europe, one of the most sustainable solutions to supply heat to buildings is district heating. It has good acceptance in the Northern countries, a low-carbon footprint, and can easily integrate intermittent renewable energy sources when coupled to the electrical grid. Even though district heating is seen as a vital element for a sustainable future, it requires extensive planning and long-term investments. To increase the understanding of the district heating network performance and the demand-side dynamics of the connected buildings, several countries, including Denmark, have installed smart heat meters in different cities. In that context, this paper presents several methodologies to analyze the datasets from the smart heat meters installed in a small Danish town. The first method is concerning data curation to remove the anomalies and missing data points. The second method analyses measured variables (heat consumption, outdoor temperature, wind speed, and global radiation) to acquire new knowledge on the building characteristics. These results were compared with the values given by the energy performance certificates of a smaller sample of 41 households. Finally, to communicate and visualize the analysis outputs in a user-friendly way, an interactive web interface tool has been created.

Country
Denmark
Keywords

Building characterization, Smart energy meters, Energy performance certificates, /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy, /dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action, District Heating, Big data mining, Linear regression analysis

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Top 10%
Top 10%
Green
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