TY  - JOUR
U1  - Zeitschriftenartikel, wissenschaftlich - begutachtet (reviewed)
A1  - Schmelas, Martin
A1  - Bollin, Elmar
A1  - Feldmann, Thomas
T1  - Savings through the use of adaptive predictive control of thermo-active building systems (TABS): A case study
JF  - Applied Energy
N2  - 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 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.
KW  - Thermo-activate building system (TABS)
KW  - Adaptive predictive control
KW  - Multiple regression
KW  - Thermal comfort
Y1  - 2017
UR  - https://www.sciencedirect.com/science/article/pii/S0306261917305408
SN  - 0306-2619
SS  - 0306-2619
U6  - https://doi.org/10.1016/j.apenergy.2017.05.032
DO  - https://doi.org/10.1016/j.apenergy.2017.05.032
VL  - 199
SP  - 294
EP  - 309
PB  - Elsevier B.V.
ER  -