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Savings through the use of adaptive predictive control of thermo-active building systems (TABS): A case study

  • The building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linearThe building sector is one of the main consumers of energy. Therefore, heating and cooling concepts for renewable energy sources become increasingly important. For this purpose, low-temperature systems such as thermo-active building systems (TABS) are particularly suitable. This paper presents results of the use of a novel adaptive and predictive computation method, based on multiple linear regression (AMLR) for the control of TABS in a passive seminar building. Detailed comparisons are shown between the standard TABS and AMLR strategies over a period of nine months each. In addition to the reduction of thermal energy use by approx. 26% and a significant reduction of the TABS pump operation time, this paper focuses on investment savings in a passive seminar building through the use of the AMLR strategy. This includes the reduction of peak power of the chilled beams (auxiliary system) as well as a simplification of the TABS hydronic circuit and the saving of an external temperature sensor. The AMLR proves its practicality by learning from the historical building operation, by dealing with forecasting errors and it is easy to integrate into a building automation system.show moreshow less

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Metadaten
Document Type:Article (reviewed)
Zitierlink: https://opus.hs-offenburg.de/2709
Bibliografische Angaben
Title (English):Savings through the use of adaptive predictive control of thermo-active building systems (TABS): A case study
Author:Martin SchmelasStaff MemberORCiDGND, Elmar BollinStaff MemberGND, Thomas FeldmannStaff Member
Year of Publication:2017
Date of first Publication:2017/08/01
Publisher:Elsevier B.V.
First Page:294
Last Page:309
Parent Title (English):Applied Energy
Volume:199
ISSN:0306-2619
DOI:https://doi.org/10.1016/j.apenergy.2017.05.032
URL:https://www.sciencedirect.com/science/article/pii/S0306261917305408
Language:English
Inhaltliche Informationen
Institutes:Forschung / INES - Institut für nachhaltige Energiesysteme
Zentrale Einrichtungen
Institutes:Bibliografie
DDC classes:600 Technik, Medizin, angewandte Wissenschaften
GND Keyword:Adaptive predictive control; Multiple regression; Thermal comfort; Thermo-activate building system (TABS)
Formale Angaben
Open Access: Closed Access 
Licence (German):License LogoUrheberrechtlich geschützt