IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v43y2012icp362-370.html
   My bibliography  Save this article

Energy consumption quota of public buildings based on statistical analysis

Author

Listed:
  • Zhao, Jing
  • Xin, Yajuan
  • Tong, Dingding

Abstract

The establishment of building energy consumption quota as a comprehensive indicator used to evaluate the actual energy consumption level is an important measure for promoting the development of building energy efficiency. This paper focused on the determination method of the quota, and firstly introduced the procedure of establishing energy consumption quota of public buildings including four important parts: collecting data, classifying and calculating EUIs, standardizing EUIs, determining the measure method of central tendency. The paper also illustrated the standardization process of EUI by actual calculation based on the samples of 10 commercial buildings and 19 hotel buildings. According to the analysis of the frequency distribution of standardized EUIs of sample buildings and combining the characteristics of each measure method of central tendency, comprehensive application of mode and percentage rank is selected to be the best method for determining the energy consumption quota of public buildings. Finally the paper gave some policy proposals on energy consumption quota to help achieve the goal of further energy conservation.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:enepol:v:43:y:2012:i:c:p:362-370
    DOI: 10.1016/j.enpol.2012.01.015
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421512000183
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2012.01.015?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. 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.
    2. Zhao, Jing & Wu, Yong & Zhu, Neng, 2009. "Implementing effect of energy efficiency supervision system for government office buildings and large-scale public buildings in China," Energy Policy, Elsevier, vol. 37(6), pages 2079-2086, June.
    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. Supapradit Marsong & Yuttana Kongjeen & Boonyang Plangklang, 2022. "Vertical Transportation System Power Usage: Behavioural Case Study of Regulated Buildings in Bangkok," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    2. Tian, Wei, 2013. "A review of sensitivity analysis methods in building energy analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 411-419.
    3. El Asri, Najat & Nouira, Youness & Maaroufi, Ibtissam & Marfak, Abdelghafour & Saleh, Nour & Mharzi, Mohammed, 2022. "The policy of energy management in public buildings procurements through the study of the process of delegated project management - Case of Morocco," Energy Policy, Elsevier, vol. 165(C).
    4. 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.
    5. Yang, Le & Xia, Jianjun & Shen, Qi, 2016. "Establishing target-oriented energy consumption quotas for buildings," Utilities Policy, Elsevier, vol. 41(C), pages 57-66.
    6. Chen, Yibo & Wu, Jianzhong, 2018. "Distribution patterns of energy consumed in classified public buildings through the data mining process," Applied Energy, Elsevier, vol. 226(C), pages 240-251.
    7. Wang, Chao & Du, Yuyan & Li, Hailong & Wallin, Fredrik & Min, Geyong, 2019. "New methods for clustering district heating users based on consumption patterns," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. 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.
    9. Jong Hwan Suh, 2018. "Generating Future-Oriented Energy Policies and Technologies from the Multidisciplinary Group Discussions by Text-Mining-Based Identification of Topics and Experts," Sustainability, MDPI, vol. 10(10), pages 1-33, October.
    10. 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).
    11. Cai, Wei & Liu, Fei & Zhou, XiaoNa & Xie, Jun, 2016. "Fine energy consumption allowance of workpieces in the mechanical manufacturing industry," Energy, Elsevier, vol. 114(C), pages 623-633.
    12. Najat El Asri & Nawal Abdou & Mohammed Mharzi & Abdelmajid Maghnouj, 2023. "Moroccan Public Buildings and the RTCM: Insights into Compliance, Energy Performance, and Regulation Improvement," Energies, MDPI, vol. 16(18), pages 1-20, September.
    13. 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.
    14. 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.
    15. 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. 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. 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.
    3. Lee, Wen-Shing & Kung, Chung-Kuan, 2011. "Using climate classification to evaluate building energy performance," Energy, Elsevier, vol. 36(3), pages 1797-1801.
    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. Aapo Huovila & Pekka Tuominen & Miimu Airaksinen, 2017. "Effects of Building Occupancy on Indicators of Energy Efficiency," Energies, MDPI, vol. 10(5), pages 1-19, May.
    6. 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.
    7. 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.
    8. Antonio Attanasio & Marco Savino Piscitelli & Silvia Chiusano & Alfonso Capozzoli & Tania Cerquitelli, 2019. "Towards an Automated, Fast and Interpretable Estimation Model of Heating Energy Demand: A Data-Driven Approach Exploiting Building Energy Certificates," Energies, MDPI, vol. 12(7), pages 1-25, April.
    9. 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.
    10. Long Li & Zhongfu Li & Lei Jiang & Guangdong Wu & Daojin Cheng, 2018. "Enhanced Cooperation among Stakeholders in PPP Mega-Infrastructure Projects: A China Study," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    11. Zhang, Jiefeng & Bai, Zhipeng & Chang, Victor W.C. & Ding, Xiao, 2011. "Balancing BEC and IAQ in civil buildings during rapid urbanization in China: Regulation, interplay and collaboration," Energy Policy, Elsevier, vol. 39(10), pages 5778-5790, October.
    12. Wang, Zhaohua & Liu, Qiang & Zhang, Bin, 2022. "What kinds of building energy-saving retrofit projects should be preferred? Efficiency evaluation with three-stage data envelopment analysis (DEA)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    13. 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.
    14. Gao, Dian-ce & Wang, Shengwei & Shan, Kui, 2016. "In-situ implementation and evaluation of an online robust pump speed control strategy for avoiding low delta-T syndrome in complex chilled water systems of high-rise buildings," Applied Energy, Elsevier, vol. 171(C), pages 541-554.
    15. Li, Kai & Ma, Minda & Xiang, Xiwang & Feng, Wei & Ma, Zhili & Cai, Weiguang & Ma, Xin, 2022. "Carbon reduction in commercial building operations: A provincial retrospection in China," Applied Energy, Elsevier, vol. 306(PB).
    16. Yang, Le & Xia, Jianjun & Shen, Qi, 2016. "Establishing target-oriented energy consumption quotas for buildings," Utilities Policy, Elsevier, vol. 41(C), pages 57-66.
    17. Wang, H. & Zhou, D.Q. & Zhou, P. & Zha, D.L., 2012. "Direct rebound effect for passenger transport: Empirical evidence from Hong Kong," Applied Energy, Elsevier, vol. 92(C), pages 162-167.
    18. Karmellos, M. & Kiprakis, A. & Mavrotas, G., 2015. "A multi-objective approach for optimal prioritization of energy efficiency measures in buildings: Model, software and case studies," Applied Energy, Elsevier, vol. 139(C), pages 131-150.
    19. Juaidi, Adel & AlFaris, Fadi & Montoya, Francisco G. & Manzano-Agugliaro, Francisco, 2016. "Energy benchmarking for shopping centers in Gulf Coast region," Energy Policy, Elsevier, vol. 91(C), pages 247-255.
    20. Braun, M.R. & Altan, H. & Beck, S.B.M., 2014. "Using regression analysis to predict the future energy consumption of a supermarket in the UK," Applied Energy, Elsevier, vol. 130(C), pages 305-313.

    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:enepol:v:43:y:2012:i:c:p:362-370. 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/locate/enpol .

    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.