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An insight into actual energy use and its drivers in high-performance buildings

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  • Li, Cheng
  • Hong, Tianzhen
  • Yan, Da

Abstract

Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. These findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

Suggested Citation

  • Li, Cheng & Hong, Tianzhen & Yan, Da, 2014. "An insight into actual energy use and its drivers in high-performance buildings," Applied Energy, Elsevier, vol. 131(C), pages 394-410.
    • Handle: RePEc:eee:appene:v:131:y:2014:i:c:p:394-410
    DOI: 10.1016/j.apenergy.2014.06.032
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    References listed on IDEAS

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    1. Li, Danny H.W. & Yang, Liu & Lam, Joseph C., 2013. "Zero energy buildings and sustainable development implications – A review," Energy, Elsevier, vol. 54(C), pages 1-10.
    2. Hong, Tianzhen & Chang, Wen-Kuei & Lin, Hung-Wen, 2013. "A fresh look at weather impact on peak electricity demand and energy use of buildings using 30-year actual weather data," Applied Energy, Elsevier, vol. 111(C), pages 333-350.
    3. Peterman, Andrew & Kourula, Arno & Levitt, Raymond, 2012. "A roadmap for navigating voluntary and mandated programs for building energy efficiency," Energy Policy, Elsevier, vol. 43(C), pages 415-426.
    4. Hong, Tianzhen & Yang, Le & Hill, David & Feng, Wei, 2014. "Data and analytics to inform energy retrofit of high performance buildings," Applied Energy, Elsevier, vol. 126(C), pages 90-106.
    5. Brown, Richard E. & Koomey, Jonathan G., 2003. "Electricity use in California: past trends and present usage patterns," Energy Policy, Elsevier, vol. 31(9), pages 849-864, July.
    6. Lin, Hung-Wen & Hong, Tianzhen, 2013. "On variations of space-heating energy use in office buildings," Applied Energy, Elsevier, vol. 111(C), pages 515-528.
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