Dataset of smart heat and water meter data with accompanying building characteristics

Markus Schaffer; Martin Veit; Anna Marszal-Pomianowska; Martin Frandsen; Michal Zbigniew Pomianowski; Emil Dichmann; Christian Grau Sørensen; Jesper Kragh

doi:10.1016/j.dib.2023.109964

Dataset of smart heat and water meter data with accompanying building characteristics

Markus Schaffer, Martin Veit, Anna Marszal-Pomianowska^*, Martin Frandsen, Michal Zbigniew Pomianowski, Emil Dichmann, Christian Grau Sørensen, Jesper Kragh

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

5 Citations (Scopus)

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Abstract

The data presented were sourced from 34,884 commercial smart heat meters and 10,765 commercial smart water meters, spanning a timeframe of up to 5 years (2018–2022). All data primarily originated from single-family houses in Aalborg Municipality, Denmark. Furthermore, comprehensive building characteristics were collected for each building, where available, from the Danish Building and Dwelling Register (BBR) and Energy Performance Certificate (EPC) input data. This effort yielded an extensive pool of up to 86 distinct characteristics per building. All smart meter data were processed employing a well-established methodology, resulting in equidistant hourly data without any erroneous or missing values. The building characteristics derived from the EPCs were additionally filtered using rule sets to improve the data quality. This dataset holds substantial value for researchers involved in the domains of the built environment, district heating, and water sectors.

Original language	English
Article number	109964
Journal	Data in Brief
Volume	52
Number of pages	16
ISSN	2352-3409
DOIs	https://doi.org/10.1016/j.dib.2023.109964
Publication status	Published - Feb 2024

Bibliographical note

Keywords

District heating
Energy use data
Potable water data
Building information

Access to Document

10.1016/j.dib.2023.109964Licence: CC BY 4.0

Open Access ArticleFinal published version, 671 KBLicence: CC BY 4.0

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Cite this

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title = "Dataset of smart heat and water meter data with accompanying building characteristics",

abstract = "The data presented were sourced from 34,884 commercial smart heat meters and 10,765 commercial smart water meters, spanning a timeframe of up to 5 years (2018–2022). All data primarily originated from single-family houses in Aalborg Municipality, Denmark. Furthermore, comprehensive building characteristics were collected for each building, where available, from the Danish Building and Dwelling Register (BBR) and Energy Performance Certificate (EPC) input data. This effort yielded an extensive pool of up to 86 distinct characteristics per building. All smart meter data were processed employing a well-established methodology, resulting in equidistant hourly data without any erroneous or missing values. The building characteristics derived from the EPCs were additionally filtered using rule sets to improve the data quality. This dataset holds substantial value for researchers involved in the domains of the built environment, district heating, and water sectors.",

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AU - Schaffer, Markus

AU - Veit, Martin

AU - Marszal-Pomianowska, Anna

AU - Frandsen, Martin

AU - Pomianowski, Michal Zbigniew

AU - Dichmann, Emil

AU - Sørensen, Christian Grau

AU - Kragh, Jesper

PY - 2024/2

Y1 - 2024/2

N2 - The data presented were sourced from 34,884 commercial smart heat meters and 10,765 commercial smart water meters, spanning a timeframe of up to 5 years (2018–2022). All data primarily originated from single-family houses in Aalborg Municipality, Denmark. Furthermore, comprehensive building characteristics were collected for each building, where available, from the Danish Building and Dwelling Register (BBR) and Energy Performance Certificate (EPC) input data. This effort yielded an extensive pool of up to 86 distinct characteristics per building. All smart meter data were processed employing a well-established methodology, resulting in equidistant hourly data without any erroneous or missing values. The building characteristics derived from the EPCs were additionally filtered using rule sets to improve the data quality. This dataset holds substantial value for researchers involved in the domains of the built environment, district heating, and water sectors.

AB - The data presented were sourced from 34,884 commercial smart heat meters and 10,765 commercial smart water meters, spanning a timeframe of up to 5 years (2018–2022). All data primarily originated from single-family houses in Aalborg Municipality, Denmark. Furthermore, comprehensive building characteristics were collected for each building, where available, from the Danish Building and Dwelling Register (BBR) and Energy Performance Certificate (EPC) input data. This effort yielded an extensive pool of up to 86 distinct characteristics per building. All smart meter data were processed employing a well-established methodology, resulting in equidistant hourly data without any erroneous or missing values. The building characteristics derived from the EPCs were additionally filtered using rule sets to improve the data quality. This dataset holds substantial value for researchers involved in the domains of the built environment, district heating, and water sectors.

KW - District heating

KW - Energy use data

KW - Potable water data

KW - Building information

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DO - 10.1016/j.dib.2023.109964

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SN - 2352-3409

VL - 52

JO - Data in Brief

JF - Data in Brief

M1 - 109964

ER -

Dataset of smart heat and water meter data with accompanying building characteristics

Abstract

Bibliographical note

Keywords

Access to Document

AUB Link

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FOREFRONT: From conventional towards energy optimized and smart building – framing a new paradigm in utilisation of smart heat data

PRELUDE: Prescient building Operation utilizing Real Time data for Energy Dynamic Optimization

EDYCE: Energy Flexible Dynamic Building Certification