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Development of a statistical analysis model to benchmark the energy use intensity of subway stations

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  • Ahn, Jonghoon
  • Cho, Soolyeon
  • Chung, Dae Hun

Abstract

This paper presents an Energy Use Intensity (EUI) indicator model for energy benchmarking subway stations.

Suggested Citation

  • Ahn, Jonghoon & Cho, Soolyeon & Chung, Dae Hun, 2016. "Development of a statistical analysis model to benchmark the energy use intensity of subway stations," Applied Energy, Elsevier, vol. 179(C), pages 488-496.
    • Handle: RePEc:eee:appene:v:179:y:2016:i:c:p:488-496
    DOI: 10.1016/j.apenergy.2016.06.065
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    References listed on IDEAS

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    1. Ye, Ling & Cheng, Zhijun & Wang, Qingqin & Lin, Haiyan & Lin, Changqing & Liu, Bin, 2015. "Developments of Green Building Standards in China," Renewable Energy, Elsevier, vol. 73(C), pages 115-122.
    2. Cheng, Yung-Hsiang & Chang, Yu-Hern & Lu, I.J., 2015. "Urban transportation energy and carbon dioxide emission reduction strategies," Applied Energy, Elsevier, vol. 157(C), pages 953-973.
    3. Wustari L. H. Mangundjaya, 2015. "People or Trust in Building Commitment to Change?," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(5), pages 67-78, Special I.
    4. Mathew, Paul A. & Dunn, Laurel N. & Sohn, Michael D. & Mercado, Andrea & Custudio, Claudine & Walter, Travis, 2015. "Big-data for building energy performance: Lessons from assembling a very large national database of building energy use," Applied Energy, Elsevier, vol. 140(C), pages 85-93.
    5. Huebner, Gesche M. & Hamilton, Ian & Chalabi, Zaid & Shipworth, David & Oreszczyn, Tadj, 2015. "Explaining domestic energy consumption – The comparative contribution of building factors, socio-demographics, behaviours and attitudes," Applied Energy, Elsevier, vol. 159(C), pages 589-600.
    6. A.M. Fogheri, 2015. "Energy Efficiency in Public Buildings," Rivista economica del Mezzogiorno, Società editrice il Mulino, issue 3-4, pages 763-784.
    7. Marquis, Chris & Jackson, Susan E. & Li, Yuan, 2015. "Building Sustainable Organizations in China," Management and Organization Review, Cambridge University Press, vol. 11(3), pages 427-440, September.
    8. Thompson, J.A. & Maidment, G.G. & Missenden, J.F., 2006. "Modelling low-energy cooling strategies for underground railways," Applied Energy, Elsevier, vol. 83(10), pages 1152-1162, October.
    9. Monts, J.Kenneth & Blissett, Marlan, 1982. "Assessing energy efficiency and energy conservation potential among commercial buildings: A statistical approach," Energy, Elsevier, vol. 7(10), pages 861-869.
    10. Chung, William & Hui, Y.V. & Lam, Y. Miu, 2006. "Benchmarking the energy efficiency of commercial buildings," Applied Energy, Elsevier, vol. 83(1), pages 1-14, January.
    11. 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.
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    Cited by:

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    2. Zhang, Yue-Jun & Liu, Zhao & Zhou, Si-Ming & Qin, Chang-Xiong & Zhang, Huan, 2018. "The impact of China's Central Rise Policy on carbon emissions at the stage of operation in road sector," Economic Modelling, Elsevier, vol. 71(C), pages 159-173.
    3. Yu, Yanzhe & You, Shijun & Zhang, Huan & Ye, Tianzhen & Wang, Yaran & Wei, Shen, 2021. "A review on available energy saving strategies for heating, ventilation and air conditioning in underground metro stations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    4. Benedetti, Miriam & Bonfa', Francesca & Bertini, Ilaria & Introna, Vito & Ubertini, Stefano, 2018. "Explorative study on Compressed Air Systems’ energy efficiency in production and use: First steps towards the creation of a benchmarking system for large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 227(C), pages 436-448.
    5. Kim, Sang-Chul & Shin, Hyun-Ik & Ahn, Jonghoon, 2020. "Energy performance analysis of airport terminal buildings by use of architectural, operational information and benchmark metrics," Journal of Air Transport Management, Elsevier, vol. 83(C).
    6. Salvatori, Simone & Benedetti, Miriam & Bonfà, Francesca & Introna, Vito & Ubertini, Stefano, 2018. "Inter-sectorial benchmarking of compressed air generation energy performance: Methodology based on real data gathering in large and energy-intensive industrial firms," Applied Energy, Elsevier, vol. 217(C), pages 266-280.
    7. Longo, S. & Mauricio-Iglesias, M. & Soares, A. & Campo, P. & Fatone, F. & Eusebi, A.L. & Akkersdijk, E. & Stefani, L. & Hospido, A., 2019. "ENERWATER – A standard method for assessing and improving the energy efficiency of wastewater treatment plants," Applied Energy, Elsevier, vol. 242(C), pages 897-910.
    8. Yanzhe Yu & Shijun You & Shen Wei & Huan Zhang & Tianzhen Ye & Yaran Wang & Yanling Na, 2022. "Exploring the Applicability of Building Energy Performance Certification Systems in Underground Stations in China," Sustainability, MDPI, vol. 14(6), pages 1-18, March.

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