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Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance

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  • Lee, Sang Hoon
  • Hong, Tianzhen
  • Piette, Mary Ann
  • Sawaya, Geof
  • Chen, Yixing
  • Taylor-Lange, Sarah C.

Abstract

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback.

Suggested Citation

  • Lee, Sang Hoon & Hong, Tianzhen & Piette, Mary Ann & Sawaya, Geof & Chen, Yixing & Taylor-Lange, Sarah C., 2015. "Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance," Energy, Elsevier, vol. 90(P1), pages 738-747.
    • Handle: RePEc:eee:energy:v:90:y:2015:i:p1:p:738-747
    DOI: 10.1016/j.energy.2015.07.107
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Rachael Sherman & Hariharan Naganathan & Kristen Parrish, 2021. "Energy Savings Results from Small Commercial Building Retrofits in the US," Energies, MDPI, vol. 14(19), pages 1-16, September.
    2. Sun, Kaiyu & Hong, Tianzhen & Taylor-Lange, Sarah C. & Piette, Mary Ann, 2016. "A pattern-based automated approach to building energy model calibration," Applied Energy, Elsevier, vol. 165(C), pages 214-224.
    3. Wang, Yuhao & Qu, Ke & Chen, Xiangjie & Zhang, Xingxing & Riffat, Saffa, 2022. "Holistic electrification vs deep energy retrofits for optimal decarbonisation pathways of UK dwellings: A case study of the 1940s’ British post-war masonry house," Energy, Elsevier, vol. 241(C).
    4. Garg, Amit & Maheshwari, Jyoti & Shukla, P.R. & Rawal, Rajan, 2017. "Energy appliance transformation in commercial buildings in India under alternate policy scenarios," Energy, Elsevier, vol. 140(P1), pages 952-965.
    5. Wu, Wenbo & Dong, Bing & Wang, Qi (Ryan) & Kong, Meng & Yan, Da & An, Jingjing & Liu, Yapan, 2020. "A novel mobility-based approach to derive urban-scale building occupant profiles and analyze impacts on building energy consumption," Applied Energy, Elsevier, vol. 278(C).
    6. Chen, Yixing & Hong, Tianzhen & Piette, Mary Ann, 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis," Applied Energy, Elsevier, vol. 205(C), pages 323-335.
    7. Chen, Yixing & Hong, Tianzhen, 2018. "Impacts of building geometry modeling methods on the simulation results of urban building energy models," Applied Energy, Elsevier, vol. 215(C), pages 717-735.
    8. Li, Xiwang & Malkawi, Ali, 2016. "Multi-objective optimization for thermal mass model predictive control in small and medium size commercial buildings under summer weather conditions," Energy, Elsevier, vol. 112(C), pages 1194-1206.
    9. Ma, Dingyuan & Li, Xiaodong & Lin, Borong & Zhu, Yimin, 2023. "An intelligent retrofit decision-making model for building program planning considering tacit knowledge and multiple objectives," Energy, Elsevier, vol. 263(PB).
    10. Lu, Mengxue & Lai, Joseph, 2020. "Review on carbon emissions of commercial buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    11. Christopher Charles Seeley & Shobhakar Dhakal, 2021. "Energy Efficiency Retrofits in Commercial Buildings: An Environmental, Financial, and Technical Analysis of Case Studies in Thailand," Energies, MDPI, vol. 14(9), pages 1-17, April.
    12. Memon, Abdul Jabbar & Shaikh, Muhammad Mujtaba, 2016. "Confidence bounds for energy conservation in electric motors: An economical solution using statistical techniques," Energy, Elsevier, vol. 109(C), pages 592-601.
    13. Picallo-Perez, Ana & Sala-Lizarraga, José M. & Portillo-Valdes, Luis, 2022. "Development of a tool based on thermoeconomics for control and diagnosis building thermal facilities," Energy, Elsevier, vol. 239(PD).
    14. Paul Mathew & Cindy Regnier & Jordan Shackelford & Travis Walter, 2020. "Energy Efficiency Package for Tenant Fit-Out: Laboratory Testing and Validation of Energy Savings and Indoor Environmental Quality," Energies, MDPI, vol. 13(20), pages 1-22, October.
    15. Fernanda Cruz Rios & Sulaiman Al Sultan & Oswald Chong & Kristen Parrish, 2023. "Empowering Owner-Operators of Small and Medium Commercial Buildings to Identify Energy Retrofit Opportunities," Energies, MDPI, vol. 16(17), pages 1-20, August.
    16. Hou, Jing & Liu, Yisheng & Wu, Yong & Zhou, Nan & Feng, Wei, 2016. "Comparative study of commercial building energy-efficiency retrofit policies in four pilot cities in China," Energy Policy, Elsevier, vol. 88(C), pages 204-215.
    17. Liu, Xiaoyu & Cui, Qingbin, 2018. "Value of performance baseline in voluntary carbon trading under uncertainty," Energy, Elsevier, vol. 145(C), pages 468-476.
    18. Shen, Pengyuan & Braham, William & Yi, Yunkyu, 2019. "The feasibility and importance of considering climate change impacts in building retrofit analysis," Applied Energy, Elsevier, vol. 233, pages 254-270.
    19. Hong, Tianzhen & Piette, Mary Ann & Chen, Yixing & Lee, Sang Hoon & Taylor-Lange, Sarah C. & Zhang, Rongpeng & Sun, Kaiyu & Price, Phillip, 2015. "Commercial Building Energy Saver: An energy retrofit analysis toolkit," Applied Energy, Elsevier, vol. 159(C), pages 298-309.

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