2026-09-19T18:09:51Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/615082022-01-13T07:54:12Zcom_1721.1_97716com_1721.1_7749com_1721.1_7582com_1721.1_7581col_1721.1_97717col_1721.1_131022

Leslie K. Norford. Gayeski, Nicholas (Nicholas Thomas) Massachusetts Institute of Technology. Dept. of Architecture. Massachusetts Institute of Technology. Department of Architecture 2011-03-07T14:36:53Z 2011-03-07T14:36:53Z 2010 2010 http://hdl.handle.net/1721.1/61508 703152790 Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2010. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student-submitted PDF version of thesis. Includes bibliographical references (p. 143-159). Low lift cooling systems (LLCS) hold the potential for significant energy savings relative to conventional cooling systems. An LLCS is a cooling system which leverages existing HVAC technologies to provide low energy cooling by operating a chiller at low pressure ratios more of the time. An LLCS combines variable capacity chillers, hydronic distribution, radiant cooling, thermal energy storage and predictive control to achieve lower condensing temperatures, higher evaporating temperatures, and reductions in instantaneous cooling loads by spreading the daily cooling load over time. The LLCS studied in this research is composed of a variable speed chiller and a concrete-core radiant floor, which acts as thermal energy storage. The operation of the chiller is optimized to minimize daily energy consumption while meeting thermal comfort requirements. This is achieved through predictive pre-cooling of the thermally massive concrete floor. The predictive pre-cooling control optimization uses measured data from a test chamber, forecasts of controlled climate conditions and internal loads, empirical models of chiller performance, and data-driven models of the temperature response of the zone being controlled. These data and models are used to determine a near-optimal operational strategy for the chiller over a 24-hour horizon. At each hour, this optimization is updated with measured data from the previous hour and new forecasts for the next 24 hours. The novel contributions of this research include the following: experimental validation of the sensible cooling energy savings of the LLCS relative to a high efficiency split system air conditioner - savings measured in a full size test chamber were 25 percent for a typical summer week in Atlanta subject to standard efficiency internal loads; development of a methodology for incorporating real building thermal mass, chiller performance models, and room temperature response models into a predictive pre-cooling control optimization for LLCS; and detailed experimental data on the performance of a rolling-piston compressor chiller to support this and future research. by Nicholas Thomas Gayeski. Ph.D. 219 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Architecture. Predictive pre-cooling control for low lift radiant cooling using building thermal mass Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="7ba664a2-1704-47c4-a4cd-21eb07e9db78"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Predictive pre-cooling control for low lift radiant cooling using building thermal mass</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2010</PublicationDate> <Authors> <Author> <DisplayName>Gayeski, Nicholas (Nicholas Thomas)</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Architecture.</Keyword> <Abstract>Low lift cooling systems (LLCS) hold the potential for significant energy savings relative to conventional cooling systems. An LLCS is a cooling system which leverages existing HVAC technologies to provide low energy cooling by operating a chiller at low pressure ratios more of the time. An LLCS combines variable capacity chillers, hydronic distribution, radiant cooling, thermal energy storage and predictive control to achieve lower condensing temperatures, higher evaporating temperatures, and reductions in instantaneous cooling loads by spreading the daily cooling load over time. The LLCS studied in this research is composed of a variable speed chiller and a concrete-core radiant floor, which acts as thermal energy storage. The operation of the chiller is optimized to minimize daily energy consumption while meeting thermal comfort requirements. This is achieved through predictive pre-cooling of the thermally massive concrete floor. The predictive pre-cooling control optimization uses measured data from a test chamber, forecasts of controlled climate conditions and internal loads, empirical models of chiller performance, and data-driven models of the temperature response of the zone being controlled. These data and models are used to determine a near-optimal operational strategy for the chiller over a 24-hour horizon. At each hour, this optimization is updated with measured data from the previous hour and new forecasts for the next 24 hours. The novel contributions of this research include the following: experimental validation of the sensible cooling energy savings of the LLCS relative to a high efficiency split system air conditioner - savings measured in a full size test chamber were 25 percent for a typical summer week in Atlanta subject to standard efficiency internal loads; development of a methodology for incorporating real building thermal mass, chiller performance models, and room temperature response models into a predictive pre-cooling control optimization for LLCS; and detailed experimental data on the performance of a rolling-piston compressor chiller to support this and future research.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>