Analysis of precooling optimization for residential buildings

Wang, Junke; Tang, Choon Yik; Song, Li

doi:10.1016/j.apenergy.2022.119574

Analysis of precooling optimization for residential buildings

Journal Article · Sat Jul 09 00:00:00 EDT 2022 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2022.119574· OSTI ID:2204487

Wang, Junke ^[1]; Tang, Choon Yik ^[2]; Song, Li ^[2]

University of Oklahoma, Norman, OK (United States); University of Oklahoma
University of Oklahoma, Norman, OK (United States)

To reduce peak demand and/or energy cost for residential buildings, optimal precooling strategies are becoming important as an alternative to rule-based precooling strategies that are intuitive but may not be optimal. Since precooling optimization is heavily dependent on a variety of factors such as the home thermal properties, HVAC system, weather, thermal comfort criteria, and utility rate structure, the individual and collective impact of these factors on precooling performance needs to be analyzed. In addition, since the indoor air temperature is affected by heat transfer to and from the interior wall surface, performance analysis in view of the interior wall surface temperature is also essential. Therefore, in this paper, an optimal precooling strategy that accounts for the aforementioned factors and utilizes a second-order thermal network model, is proposed. With this strategy, the HVAC on/off control signal that minimizes 24-hour energy cost while maintaining thermal comfort, is determined. Through extensive simulations, it is found that the proposed optimal precooling strategy is able to adapt to changing conditions and that having a sufficiently low interior wall surface temperature during precooling is critical for avoiding expensive on-peak operation. Here, the reason for the latter is that such a temperature indicates that enough “cooling energy” has been stored. It is also found that weather has the most dominant impact on the precooling performance, followed by home thermal condition, with the rated cooling capacity and utility rate structure having the least impact.

View Accepted Manuscript (DOE)

Research Organization:: University of Oklahoma, Norman, OK (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: EE0008697

OSTI ID:: 2204487

Alternate ID(s):: OSTI ID: 1876504

Journal Information:: Applied Energy, Journal Name: Applied Energy Journal Issue: 1 Vol. 323; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Home thermal condition
Precooling optimization
Rated cooling capacity
Thermal network model
Utility rate structure
Weather

Analysis of precooling optimization for residential buildings

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References (18)

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