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Data for Optimizing Heat Supply Systems in Existing Districts

Estevam Schmiedt, Jacob und Blanco Bohorquez, Luis Armando und Diel, Markus und Groesdonk, Philip (2025) Data for Optimizing Heat Supply Systems in Existing Districts. 11th International Conference on Smart Energy Systems, 2025-09-16 - 2025-09-17, Kopenhagen, Dänemark.

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Kurzfassung

The planning and modernization of heat supply systems in existing districts rely heavily on high-quality data about the building stock. Heat demand densities are a minimum requirement for designing heat networks. Moreover, knowledge of the efficiency status of individual buildings is crucial for determining required supply temperatures, potential reductions in heat demand through future retrofits, and the likely connection rate of buildings to a heat network. To address this, we combine data from various sources to obtain this information with high accuracy and minimal investment of time and resources. Our harmonization process integrates 3D data from public surveying offices, OpenStreetMap, the federal census, regional cadastres, and earth observation data – all of which are freely available in many European countries. Machine learning models are employed to fill data gaps and disaggregate information that is only available in aggregated form. This chain of data cleaning, harmonization, and building classification generates the input for heat demand calculations without the need for on-site inspections. In this contribution, we treat this purely remote analysis as a baseline and explore how it can be extended by data from thermographic drive-through assessments. A car-mounted multi-sensor system equipped with a thermography camera captures a series of images, location and time stamps, and potentially additional data. An automated processing pipeline evaluates the recorded data and estimates the insulation quality of all building facades visible from the streets. This approach enables the estimation of the efficiency and retrofit status of each building for entire districts or towns using real on-site data with minimal human labor. By combining these datasets, we can provide the high-quality information required for district energy concepts and heat network planning, ultimately supporting the development of more efficient and sustainable heat supply systems.

elib-URL des Eintrags:https://elib.dlr.de/218923/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Data for Optimizing Heat Supply Systems in Existing Districts
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Estevam Schmiedt, JacobJacob.EstevamSchmiedt (at) dlr.dehttps://orcid.org/0000-0002-0794-6769NICHT SPEZIFIZIERT
Blanco Bohorquez, Luis Armandoluis.blancobohorquez (at) dlr.dehttps://orcid.org/0000-0002-2300-8385NICHT SPEZIFIZIERT
Diel, Markusmarkus.diel (at) dlr.dehttps://orcid.org/0009-0000-2157-954XNICHT SPEZIFIZIERT
Groesdonk, PhilipPhilip.Groesdonk (at) dlr.dehttps://orcid.org/0000-0002-1274-0378NICHT SPEZIFIZIERT
Datum:September 2025
Referierte Publikation:Nein
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:heat network design, open data, thermographic survey, machine learning, heat demand, retrofit status, efficiency
Veranstaltungstitel:11th International Conference on Smart Energy Systems
Veranstaltungsort:Kopenhagen, Dänemark
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:16 September 2025
Veranstaltungsende:17 September 2025
Veranstalter :Aalborg University und Energy Cluster Denmark
HGF - Forschungsbereich:Energie
HGF - Programm:Energiesystemdesign
HGF - Programmthema:Digitalisierung und Systemtechnologie
DLR - Schwerpunkt:Energie
DLR - Forschungsgebiet:E SY - Energiesystemtechnologie und -analyse
DLR - Teilgebiet (Projekt, Vorhaben):E - Energiesystemtechnologie, E - Condition Monitoring
Standort: Jülich
Institute & Einrichtungen:Institut für Solarforschung
Institut für Solarforschung > Nachhaltige Systemverfahrenstechnik
Hinterlegt von: Estevam Schmiedt, Dr. Jacob
Hinterlegt am:13 Nov 2025 09:26
Letzte Änderung:13 Nov 2025 09:26

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