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Framework for model predictive control (MPC)-based surface condensation prevention for thermo-active building systems (TABS)
Highlights Model predictive control-based surface condensation prevention method is presented. Dynamic model of construction layers and dynamic model of buildings were coupled. Surface relative humidity prediction accuracy was improved with curve fitting process. Control horizon was set as six hours and prediction horizon was set as 24 h. The cooling energy was reduced by extending the operable periods for TABS with MPC.
Abstract The potential risk of developing surface condensation keeps thermo-active building systems (TABS) from being applied in buildings located in partly warm and humid climate regions. This study presents a framework for model predictive control (MPC)-based surface condensation prevention that can avoid the surface condensation during the cooling periods when the TABS is in operation. Because MPC determines the input signal for the system not only on the basis of the current states but also on the impact that the actions will have on the future states, it is suitable for anticipatory surface condensation control that must respond to both dynamic indoor condition changes and the time-delay in hygrothermal transfer in advance. Heat and moisture transfer dynamic models were developed for prediction of future states and these dynamic models were calibrated with the measured data to improve the surface condensation prediction accuracy. On the basis of future states predicted by the calibrated dynamic models, the MPC-based condensation prevention framework adjusts the surface temperature for the TABS in ways that ensure indoor thermal comfort and energy efficiency without the development of surface condensation. The results demonstrated that the MPC-based TABS operation achieved 21.0 − 29.6% site cooling distribution energy savings compared to the conventional forced air-based cooling mode depending on the climatic regions; in comparison between the TABS governed by the MPC framework and by the on/off control, 2.5 − 10.0% more site cooling distribution energy savings were achieved through use of the MPC framework than through use of the on/off control.
Framework for model predictive control (MPC)-based surface condensation prevention for thermo-active building systems (TABS)
Highlights Model predictive control-based surface condensation prevention method is presented. Dynamic model of construction layers and dynamic model of buildings were coupled. Surface relative humidity prediction accuracy was improved with curve fitting process. Control horizon was set as six hours and prediction horizon was set as 24 h. The cooling energy was reduced by extending the operable periods for TABS with MPC.
Abstract The potential risk of developing surface condensation keeps thermo-active building systems (TABS) from being applied in buildings located in partly warm and humid climate regions. This study presents a framework for model predictive control (MPC)-based surface condensation prevention that can avoid the surface condensation during the cooling periods when the TABS is in operation. Because MPC determines the input signal for the system not only on the basis of the current states but also on the impact that the actions will have on the future states, it is suitable for anticipatory surface condensation control that must respond to both dynamic indoor condition changes and the time-delay in hygrothermal transfer in advance. Heat and moisture transfer dynamic models were developed for prediction of future states and these dynamic models were calibrated with the measured data to improve the surface condensation prediction accuracy. On the basis of future states predicted by the calibrated dynamic models, the MPC-based condensation prevention framework adjusts the surface temperature for the TABS in ways that ensure indoor thermal comfort and energy efficiency without the development of surface condensation. The results demonstrated that the MPC-based TABS operation achieved 21.0 − 29.6% site cooling distribution energy savings compared to the conventional forced air-based cooling mode depending on the climatic regions; in comparison between the TABS governed by the MPC framework and by the on/off control, 2.5 − 10.0% more site cooling distribution energy savings were achieved through use of the MPC framework than through use of the on/off control.
Framework for model predictive control (MPC)-based surface condensation prevention for thermo-active building systems (TABS)
Woo, Deok-Oh (author) / Junghans, Lars (author)
Energy and Buildings ; 215
2020-02-22
Article (Journal)
Electronic Resource
English