[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v179y2016icp488-496.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261916308406
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2016.06.065?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. A.M. Fogheri, 2015. "Energy Efficiency in Public Buildings," Rivista economica del Mezzogiorno, Società editrice il Mulino, issue 3-4, pages 763-784.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nam, KiJeon & Heo, SungKu & Li, Qian & Loy-Benitez, Jorge & Kim, MinJeong & Park, DuckShin & Yoo, ChangKyoo, 2020. "A proactive energy-efficient optimal ventilation system using artificial intelligent techniques under outdoor air quality conditions," Applied Energy, Elsevier, vol. 266(C).
    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. 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.
    5. 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.
    6. 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.
    7. 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).
    8. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Østergård, Torben & Jensen, Rasmus L. & Maagaard, Steffen E., 2016. "Building simulations supporting decision making in early design – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 187-201.
    2. 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.
    3. Mehrabi, Hamed & Coviello, Nicole & Ranaweera, Chatura, 2021. "When is top management team heterogeneity beneficial for product exploration? Understanding the role of institutional pressures," Journal of Business Research, Elsevier, vol. 132(C), pages 775-786.
    4. Zhou, Yuren & Lork, Clement & Li, Wen-Tai & Yuen, Chau & Keow, Yeong Ming, 2019. "Benchmarking air-conditioning energy performance of residential rooms based on regression and clustering techniques," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Qi-Gan Shao & James J. H. Liou & Sung-Shun Weng & Yen-Ching Chuang, 2018. "Improving the Green Building Evaluation System in China Based on the DANP Method," Sustainability, MDPI, vol. 10(4), pages 1-20, April.
    6. Li, Xinyi & Yao, Runming & Li, Qin & Ding, Yong & Li, Baizhan, 2018. "An object-oriented energy benchmark for the evaluation of the office building stock," Utilities Policy, Elsevier, vol. 51(C), pages 1-11.
    7. Yang, Le & Xia, Jianjun & Shen, Qi, 2016. "Establishing target-oriented energy consumption quotas for buildings," Utilities Policy, Elsevier, vol. 41(C), pages 57-66.
    8. Jeffrey D. Spitler & Signhild Gehlin, 2019. "Measured Performance of a Mixed-Use Commercial-Building Ground Source Heat Pump System in Sweden," Energies, MDPI, vol. 12(10), pages 1-34, May.
    9. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    10. Roth, Jonathan & Rajagopal, Ram, 2018. "Benchmarking building energy efficiency using quantile regression," Energy, Elsevier, vol. 152(C), pages 866-876.
    11. 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.
    12. Hye Gi Kim & Sun Sook Kim, 2020. "Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database," Energies, MDPI, vol. 13(4), pages 1-18, February.
    13. Andrews, Abigail & Jain, Rishee K., 2022. "Beyond Energy Efficiency: A clustering approach to embed demand flexibility into building energy benchmarking," Applied Energy, Elsevier, vol. 327(C).
    14. 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.
    15. Eggimann, Sven & Hall, Jim W. & Eyre, Nick, 2019. "A high-resolution spatio-temporal energy demand simulation to explore the potential of heating demand side management with large-scale heat pump diffusion," Applied Energy, Elsevier, vol. 236(C), pages 997-1010.
    16. Luo, Xuan & Hong, Tianzhen & Chen, Yixing & Piette, Mary Ann, 2017. "Electric load shape benchmarking for small- and medium-sized commercial buildings," Applied Energy, Elsevier, vol. 204(C), pages 715-725.
    17. Wang, Endong, 2017. "Decomposing core energy factor structure of U.S. residential buildings through principal component analysis with variable clustering on high-dimensional mixed data," Applied Energy, Elsevier, vol. 203(C), pages 858-873.
    18. 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.
    19. Shen, Yuxuan & Pan, Yue, 2023. "BIM-supported automatic energy performance analysis for green building design using explainable machine learning and multi-objective optimization," Applied Energy, Elsevier, vol. 333(C).
    20. Yu Dong & Tongyu Qin & Siyuan Zhou & Lu Huang & Rui Bo & Haibo Guo & Xunzhi Yin, 2020. "Comparative Whole Building Life Cycle Assessment of Energy Saving and Carbon Reduction Performance of Reinforced Concrete and Timber Stadiums—A Case Study in China," Sustainability, MDPI, vol. 12(4), pages 1-24, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:179:y:2016:i:c:p:488-496. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.