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Model Predictive Control-Based Surface Condensation Prevention for Thermo-Active Building Systems (TABS) : = In Regard to the Partial Theoretical Model Approach.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Model Predictive Control-Based Surface Condensation Prevention for Thermo-Active Building Systems (TABS) :/
Reminder of title:	In Regard to the Partial Theoretical Model Approach.
Author:	Woo, Deokoh.
Description:	1 online resource (180 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 83-01, Section: B.
Contained By:	Dissertations Abstracts International83-01B.
Subject:	Architectural engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28667101click for full text (PQDT)
ISBN:	9798516087691

Model Predictive Control-Based Surface Condensation Prevention for Thermo-Active Building Systems (TABS) : = In Regard to the Partial Theoretical Model Approach.
Woo, Deokoh.

Model Predictive Control-Based Surface Condensation Prevention for Thermo-Active Building Systems (TABS) :In Regard to the Partial Theoretical Model Approach. - 1 online resource (180 pages)

Source: Dissertations Abstracts International, Volume: 83-01, Section: B.

Thesis (Ph.D.)--University of Michigan, 2021.

Includes bibliographical references

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 based on 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. Based on 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 proposed MPC-based surface condensation prevention framework reduced the surface condensation occurrence risk as well as the cooling energy even when the TABS is in operation under warm and humid climate regions. Given the growing demand for the TABS, the proposed MPC framework meets a critical need. By controlling the potential risk of surface condensation development, it can extend TABS use to an area in which climate conditions had made them infeasible.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798516087691Subjects--Topical Terms:

3174102
Architectural engineering.
Subjects--Index Terms:

Model predictive controlIndex Terms--Genre/Form:

542853
Electronic books.

Model Predictive Control-Based Surface Condensation Prevention for Thermo-Active Building Systems (TABS) : = In Regard to the Partial Theoretical Model Approach.
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504 $a Includes bibliographical references
520 $a 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 based on 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. Based on 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 proposed MPC-based surface condensation prevention framework reduced the surface condensation occurrence risk as well as the cooling energy even when the TABS is in operation under warm and humid climate regions. Given the growing demand for the TABS, the proposed MPC framework meets a critical need. By controlling the potential risk of surface condensation development, it can extend TABS use to an area in which climate conditions had made them infeasible.
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