Data-Driven Occupancy Profile Identification and Application to the Ventilation Schedule in a School Building
Loading...
Access rights
openAccess
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
23
Series
Energies, Volume 17, issue 13
Abstract
Facing the current sustainability challenges requires reduction in building stock energy usage towards achieving the European Green Deal targets. This can be accomplished by adopting techniques such as fault detection and diagnosis and efficiency optimization. Taking an Estonian school as a case study, an occupancy-based algorithm for scheduling ventilation operations in buildings is here developed starting only from energy use data. The aim is optimizing the system’s operation according to occupancy profiles while maintaining a comfortable indoor climate. By relying only on electricity meters without using carbon dioxide or occupancy sensors, we use the historical data of a school to develop a DBSCAN-based clustering algorithm that generates consumption profiles. A novel occupancy estimation algorithm, based on threshold and time-series methods, then creates 12 occupancy schedules that are either based on classical detection with an on-off method or on occupancy estimation for demand-controlled ventilation. We find that the latter replaces the 60% capacity of current on-off schedules by 30% or even 0%, with energy savings ranging from 3.5% to 66.4%. The corresponding costs are reduced from 18.1% up to 62.6%, while still complying with current national regulations for indoor air quality. Remarkably, our method can immediately be extended to other countries, as it relies only on occupancy schedules that ignore weather and other location-specific factors.Description
Publisher Copyright: © 2024 by the authors. | openaire: EC/H2020/856602/EU//SOS.aquaterra
Keywords
Other note
Citation
Vassiljeva, K, Matson, M, Ferrantelli, A, Petlenkov, E, Thalfeldt, M & Belikov, J 2024, 'Data-Driven Occupancy Profile Identification and Application to the Ventilation Schedule in a School Building', Energies, vol. 17, no. 13, 3080. https://doi.org/10.3390/en17133080