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Factors Affecting Energy Performance of Large-Scale Office Buildings: Analysis of Benchmarking Data from New York City and Chicago

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  • ChungYeon Won

    (Department of Architecture, School of Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea)

  • SangTae No

    (Department of Architecture, Korea National University of Transportation, 50 Daehak-ro, Geomdan-ri, Daesowon-myeon, Chungju-si, Chungcheongbuk-do 27469, Korea)

  • Qamar Alhadidi

    (Department of Architecture, School of Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Korea)

Abstract

Buildings in high-income, industrialized cities are responsible for more than 50% of global energy consumption; consequently, many developed cities have legislated energy benchmarking and disclosure policies to understand their buildings’ energy-use dynamics better. By utilizing these benchmarking data and additional information taken from 3D models, this paper presents a comprehensive analysis of large-scale office buildings located in New York and Chicago, with respect to their energy use intensity (EUI). To identify the primary factors affecting the EUI, Spearman’s correlation analysis and multiple variate regression tests were performed on office buildings over 500,000 ft 2 (46,452 m 2 ) gross floor area. The results showed the number of floors, construction year, window-to-wall ratio (WWR), and source-to-site ratio statistically significant, while morphological factors such as the relative compactness and surface-to-volume ratio showed limited relation to EUI. In New York City, the smallest EUI median was found in the buildings with 20 to 30 floors, and in Chicago, the buildings with 60 floors or more. A higher source-to-site ratio generally had lower overall EUI in both cities. Despite the high correlation, different kinds of dependency were found for window-to-wall ratio (WWR) and construction year between NYC and Chicago. These findings highlight the relative role that each building’s characteristics play concerning the EUI, depending on the particular building’s typology, scale, and the urban context.

Suggested Citation

  • ChungYeon Won & SangTae No & Qamar Alhadidi, 2019. "Factors Affecting Energy Performance of Large-Scale Office Buildings: Analysis of Benchmarking Data from New York City and Chicago," Energies, MDPI, vol. 12(24), pages 1-17, December.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:24:p:4783-:d:298258
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    References listed on IDEAS

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    1. Michael-Allan Millar & Neil M. Burnside & Zhibin Yu, 2019. "District Heating Challenges for the UK," Energies, MDPI, vol. 12(2), pages 1-21, January.
    2. Constantine Kontokosta, 2015. "A Market-Specific Methodology for a Commercial Building Energy Performance Index," The Journal of Real Estate Finance and Economics, Springer, vol. 51(2), pages 288-316, August.
    3. Papadopoulos, Sokratis & Bonczak, Bartosz & Kontokosta, Constantine E., 2018. "Pattern recognition in building energy performance over time using energy benchmarking data," Applied Energy, Elsevier, vol. 221(C), pages 576-586.
    4. Meng, Ting & Hsu, David & Han, Albert, 2017. "Estimating energy savings from benchmarking policies in New York City," Energy, Elsevier, vol. 133(C), pages 415-423.
    5. Babak Raji & Martin J. Tenpierik & Andy Van den Dobbelsteen, 2017. "Early-Stage Design Considerations for the Energy-Efficiency of High-Rise Office Buildings," Sustainability, MDPI, vol. 9(4), pages 1-28, April.
    6. Ilaria Ballarini & Giovanna De Luca & Argun Paragamyan & Anna Pellegrino & Vincenzo Corrado, 2019. "Transformation of an Office Building into a Nearly Zero Energy Building (nZEB): Implications for Thermal and Visual Comfort and Energy Performance," Energies, MDPI, vol. 12(5), pages 1-18, March.
    7. Giacomo Chiesa & Andrea Acquaviva & Mario Grosso & Lorenzo Bottaccioli & Maurizio Floridia & Edoardo Pristeri & Edoardo Maria Sanna, 2019. "Parametric Optimization of Window-to-Wall Ratio for Passive Buildings Adopting A Scripting Methodology to Dynamic-Energy Simulation," Sustainability, MDPI, vol. 11(11), pages 1-30, May.
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    Cited by:

    1. Vaisi, Salah & Varmazyari, Pouya & Esfandiari, Masoud & Sharbaf, Sara A., 2023. "Developing a multi-level energy benchmarking and certification system for office buildings in a cold climate region," Applied Energy, Elsevier, vol. 336(C).
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    3. Sangtae No & Chungyeon Won, 2020. "Comparative Analysis of Energy Consumption between Green Building Certified and Non-Certified Buildings in Korea," Energies, MDPI, vol. 13(5), pages 1-16, February.

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