Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case
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.
Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case
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.
Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case
Pereira, Daniel Henrique Leiria E (Autor:in) / Johra, Hicham (Autor:in) / Marszal-Pomianowska, Anna (Autor:in) / Pomianowski, Michal Zbigniew (Autor:in) / Heiselberg, Per (Autor:in)
12.06.2021
Pereira , D H L E , Johra , H , Marszal-Pomianowska , A , Pomianowski , M Z & Heiselberg , P 2021 , ' Using data from smart energy meters to gain knowledge about households connected to the district heating network: A Danish case ' , Smart Energy , vol. 3 , 100035 . https://doi.org/10.1016/j.segy.2021.100035
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Linear regression analysis , /dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy , /dk/atira/pure/sustainabledevelopmentgoals/climate_action , Building characterization , name=SDG 13 - Climate Action , District Heating , Smart energy meters , Energy performance certificates , name=SDG 7 - Affordable and Clean Energy , Big data mining
DDC:
690
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