IDEAS home Printed from https://ideas.repec.org/a/eee/juipol/v41y2016icp57-66.html
   My bibliography  Save this article

Establishing target-oriented energy consumption quotas for buildings

Author

Listed:
  • Yang, Le
  • Xia, Jianjun
  • Shen, Qi

Abstract

The energy assessment of public buildings is currently emerging as an imperative of the Chinese government. However, in setting the overall control targets for entire regions, effective and specific energy consumption quotas (ECQs) for individual buildings are not specified. In this paper, in an effort to meet the energy conservation targets of the 12th Five-Year Plan, new methods for establishing target-oriented and equitable ECQs are proposed and applied in the assessment of a particular group of government office buildings in Beijing. The respective annual ECQs for electricity and gas were established for each building, and a corresponding year-end assessment was conducted. The core concept of the methods could be applied to other types of buildings and this concept could therefore provide important guidance for future policymaking.

Suggested Citation

  • Yang, Le & Xia, Jianjun & Shen, Qi, 2016. "Establishing target-oriented energy consumption quotas for buildings," Utilities Policy, Elsevier, vol. 41(C), pages 57-66.
    • Handle: RePEc:eee:juipol:v:41:y:2016:i:c:p:57-66
    DOI: 10.1016/j.jup.2016.06.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0957178716301394
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jup.2016.06.001?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. 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.
    2. 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.
    3. 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.
    4. Zhao, Jing & Xin, Yajuan & Tong, Dingding, 2012. "Energy consumption quota of public buildings based on statistical analysis," Energy Policy, Elsevier, vol. 43(C), pages 362-370.
    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. 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.

    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. Ruparathna, Rajeev & Hewage, Kasun & Sadiq, Rehan, 2016. "Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1032-1045.
    2. 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.
    3. 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.
    4. Thomas Wu & Bo Wang & Dongdong Zhang & Ziwei Zhao & Hongyu Zhu, 2023. "Benchmarking Evaluation of Building Energy Consumption Based on Data Mining," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    5. Mingfang Tang & Xiao Fu & Huiming Cao & Yuan Shen & Hongbing Deng & Gang Wu, 2016. "Energy Performance of Hotel Buildings in Lijiang, China," Sustainability, MDPI, vol. 8(8), pages 1-12, August.
    6. Capozzoli, Alfonso & Piscitelli, Marco Savino & Neri, Francesco & Grassi, Daniele & Serale, Gianluca, 2016. "A novel methodology for energy performance benchmarking of buildings by means of Linear Mixed Effect Model: The case of space and DHW heating of out-patient Healthcare Centres," Applied Energy, Elsevier, vol. 171(C), pages 592-607.
    7. Jiang, Feifeng & Ma, Jun & Li, Zheng & Ding, Yuexiong, 2022. "Prediction of energy use intensity of urban buildings using the semi-supervised deep learning model," Energy, Elsevier, vol. 249(C).
    8. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    9. Yan, Chengchu & Wang, Shengwei & Xiao, Fu & Gao, Dian-ce, 2015. "A multi-level energy performance diagnosis method for energy information poor buildings," Energy, Elsevier, vol. 83(C), pages 189-203.
    10. Roth, Jonathan & Rajagopal, Ram, 2018. "Benchmarking building energy efficiency using quantile regression," Energy, Elsevier, vol. 152(C), pages 866-876.
    11. 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.
    12. Chung, William & Yeung, Iris M.H., 2017. "Benchmarking by convex non-parametric least squares with application on the energy performance of office buildings," Applied Energy, Elsevier, vol. 203(C), pages 454-462.
    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. 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.
    16. Ferreira, Ana & Pinheiro, Manuel Duarte & de Brito, Jorge & Mateus, Ricardo, 2018. "Combined carbon and energy intensity benchmarks for sustainable retail stores," Energy, Elsevier, vol. 165(PB), pages 877-889.
    17. Xavier Serrano-Guerrero & Guillermo Escrivá-Escrivá & Santiago Luna-Romero & Jean-Michel Clairand, 2020. "A Time-Series Treatment Method to Obtain Electrical Consumption Patterns for Anomalies Detection Improvement in Electrical Consumption Profiles," Energies, MDPI, vol. 13(5), pages 1-23, February.
    18. Lee, Wen-Shing & Kung, Chung-Kuan, 2011. "Using climate classification to evaluate building energy performance," Energy, Elsevier, vol. 36(3), pages 1797-1801.
    19. Tian, Wei & Song, Jitian & Li, Zhanyong & de Wilde, Pieter, 2014. "Bootstrap techniques for sensitivity analysis and model selection in building thermal performance analysis," Applied Energy, Elsevier, vol. 135(C), pages 320-328.
    20. 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.

    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:juipol:v:41:y:2016:i:c:p:57-66. 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: https://www.sciencedirect.com/journal/utilities-policy .

    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.