Forecasting of HVAC energy consumption and thermal comfort in office buildings

Jan Kurzidim, Michael Schöny

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in Tagungsband

Abstract

In this contribution, we used machine learning to forecast both the HVAC energy consumption of an office building and the thermal comfort in its office spaces. To a limited extent, we used the forecasts to optimize control values of the building’s automation system for minimal HVAC energy consumption. Our investigation was based on data collected in an office building in Vienna, Austria. To structure the available data, we leveraged an existing semantic model of the building. We found that the forecasts for the HVAC energy consumption were more reliable than those for thermal comfort, and that the control value optimization has potential for real-life application. The results of this work are intended to support the facility management of the building in the operation of the building.
OriginalspracheEnglisch
TitelIntelligente Energie- und Klimastrategien
UntertitelEnergie – Gebäude – Umwelt
Redakteure/-innenHildegard Gremmel-Simon
ErscheinungsortWien
Seiten41-48
Seitenumfang8
ISBN (elektronisch)978-3-903207-89-9
DOIs
PublikationsstatusVeröffentlicht - Juni 2024
Veranstaltunge·nova: Intelligente Energie- und Klimastrategien - FH Burgenland, Pinkafeld, Österreich
Dauer: 12 Juni 202413 Juni 2024
https://www.fh-burgenland.at/bachelor-energie-und-umweltmanagement/enova/

Konferenz

Konferenze·nova
Kurztitele-nova 2024
Land/GebietÖsterreich
StadtPinkafeld
Zeitraum12/06/2413/06/24
Internetadresse

Research Field

  • Efficient Buildings and HVAC Technologies

Fingerprint

Untersuchen Sie die Forschungsthemen von „Forecasting of HVAC energy consumption and thermal comfort in office buildings“. Zusammen bilden sie einen einzigartigen Fingerprint.

Diese Publikation zitieren