IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v35y2010i1p50-54.html
   My bibliography  Save this article

Benchmarking the energy performance for cooling purposes in buildings using a novel index-total performance of energy for cooling purposes

Author

Listed:
  • Lee, Wen-Shing

Abstract

Benchmarking the energy performance for cooling purposes in buildings is an important tool for energy management. This paper proposes a novel index and develops a benchmarking process for energy performance for cooling purposes by means of data envelopment analysis and cooling degree hour method. The research begins by using climate data to calculate cooling degree hour and proceeds to build an index of total performance of energy for cooling purposes by linear regression method. Finally, data envelopment analysis is adopted to benchmark the energy performance for cooling purposes in buildings with the index of total performance of energy for cooling that has the effect of ventilation factors (floor area and number of occupants) removed. An application to office buildings in Taiwan is presented to illustrate the development and the use of the evaluating method.

Suggested Citation

  • Lee, Wen-Shing, 2010. "Benchmarking the energy performance for cooling purposes in buildings using a novel index-total performance of energy for cooling purposes," Energy, Elsevier, vol. 35(1), pages 50-54.
    • Handle: RePEc:eee:energy:v:35:y:2010:i:1:p:50-54
    DOI: 10.1016/j.energy.2009.08.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544209003661
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2009.08.026?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. Satman, A & Yalcinkaya, N, 1999. "Heating and cooling degree-hours for Turkey," Energy, Elsevier, vol. 24(10), pages 833-840.
    2. Büyükalaca, Orhan & Bulut, Hüsamettin & YIlmaz, Tuncay, 2001. "Analysis of variable-base heating and cooling degree-days for Turkey," Applied Energy, Elsevier, vol. 69(4), pages 269-283, August.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    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. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    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. Zhou, Guanghui & Chung, William & Zhang, Xiliang, 2013. "A study of carbon dioxide emissions performance of China's transport sector," Energy, Elsevier, vol. 50(C), pages 302-314.
    2. Vaninsky, Alexander, 2010. "Prospective national and regional environmental performance: Boundary estimations using a combined data envelopment – stochastic frontier analysis approach," Energy, Elsevier, vol. 35(9), pages 3657-3665.
    3. Geraldi, Matheus Soares & Ghisi, Enedir, 2022. "Data-driven framework towards realistic bottom-up energy benchmarking using an Artificial Neural Network," Applied Energy, Elsevier, vol. 306(PA).
    4. Livingston, Olga V. & Pulsipher, Trenton C. & Anderson, David M. & Vlachokostas, Alex & Wang, Na, 2018. "An analysis of utility meter data aggregation and tenant privacy to support energy use disclosure in commercial buildings," Energy, Elsevier, vol. 159(C), pages 302-309.
    5. Malmqvist, Tove & Glaumann, Mauritz & Svenfelt, Åsa & Carlson, Per-Olof & Erlandsson, Martin & Andersson, Johnny & Wintzell, Helene & Finnveden, Göran & Lindholm, Torbjörn & Malmström, Tor-Göran, 2011. "A Swedish environmental rating tool for buildings," Energy, Elsevier, vol. 36(4), pages 1893-1899.
    6. Wang, Yang & Zhao, Fu-Yun & Kuckelkorn, Jens & Liu, Di & Liu, Li-Qun & Pan, Xiao-Chuan, 2014. "Cooling energy efficiency and classroom air environment of a school building operated by the heat recovery air conditioning unit," Energy, Elsevier, vol. 64(C), pages 991-1001.
    7. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Mohammadi, Ali, 2011. "Optimization of energy consumption and input costs for apple production in Iran using data envelopment analysis," Energy, Elsevier, vol. 36(2), pages 909-916.
    8. Khoshroo, Alireza & Mulwa, Richard & Emrouznejad, Ali & Arabi, Behrouz, 2013. "A non-parametric Data Envelopment Analysis approach for improving energy efficiency of grape production," Energy, Elsevier, vol. 63(C), pages 189-194.
    9. Lee, Wen-Shing & Kung, Chung-Kuan, 2011. "Using climate classification to evaluate building energy performance," Energy, Elsevier, vol. 36(3), pages 1797-1801.
    10. Jeong, Jaewook & Hong, Taehoon & Ji, Changyoon & Kim, Jimin & Lee, Minhyun & Jeong, Kwangbok & Koo, Choongwan, 2017. "Improvements of the operational rating system for existing residential buildings," Applied Energy, Elsevier, vol. 193(C), pages 112-124.
    11. Goto, Mika & Otsuka, Akihiro & Sueyoshi, Toshiyuki, 2014. "DEA (Data Envelopment Analysis) assessment of operational and environmental efficiencies on Japanese regional industries," Energy, Elsevier, vol. 66(C), pages 535-549.

    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. Lee, Wen-Shing & Kung, Chung-Kuan, 2011. "Using climate classification to evaluate building energy performance," Energy, Elsevier, vol. 36(3), pages 1797-1801.
    2. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    3. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    4. Alperovych, Yan & Hübner, Georges & Lobet, Fabrice, 2015. "How does governmental versus private venture capital backing affect a firm's efficiency? Evidence from Belgium," Journal of Business Venturing, Elsevier, vol. 30(4), pages 508-525.
    5. Wang, Zhao-Hua & Zeng, Hua-Lin & Wei, Yi-Ming & Zhang, Yi-Xiang, 2012. "Regional total factor energy efficiency: An empirical analysis of industrial sector in China," Applied Energy, Elsevier, vol. 97(C), pages 115-123.
    6. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    7. Ruiqing Yuan & Xiangyang Xu & Yanli Wang & Jiayi Lu & Ying Long, 2024. "Evaluating Carbon-Emission Efficiency in China’s Construction Industry: An SBM-Model Analysis of Interprovincial Building Heating," Sustainability, MDPI, vol. 16(6), pages 1-16, March.
    8. Costa, Marcelo Azevedo & Lopes, Ana Lúcia Miranda & de Pinho Matos, Giordano Bruno Braz, 2015. "Statistical evaluation of Data Envelopment Analysis versus COLS Cobb–Douglas benchmarking models for the 2011 Brazilian tariff revision," Socio-Economic Planning Sciences, Elsevier, vol. 49(C), pages 47-60.
    9. Ahmad, Usman, 2011. "Financial Reforms and Banking Efficiency: Case of Pakistan," MPRA Paper 34220, University Library of Munich, Germany.
    10. Ashrafi, Ali & Seow, Hsin-Vonn & Lee, Lai Soon & Lee, Chew Ging, 2013. "The efficiency of the hotel industry in Singapore," Tourism Management, Elsevier, vol. 37(C), pages 31-34.
    11. Büschken, Joachim, 2009. "When does data envelopment analysis outperform a naïve efficiency measurement model?," European Journal of Operational Research, Elsevier, vol. 192(2), pages 647-657, January.
    12. António Afonso & Ana Patricia Montes & José M. Domínguez, 2024. "Measuring Tax Burden Efficiency in OECD Countries: An International Comparison," CESifo Working Paper Series 11333, CESifo.
    13. Jahangoshai Rezaee, Mustafa & Jozmaleki, Mehrdad & Valipour, Mahsa, 2018. "Integrating dynamic fuzzy C-means, data envelopment analysis and artificial neural network to online prediction performance of companies in stock exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 78-93.
    14. Suhyeon Han & Shinyoung Park & Sejin An & Wonjun Choi & Mina Lee, 2023. "Research on Analyzing the Efficiency of R&D Projects for Climate Change Response Using DEA–Malmquist," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    15. Chenini Hajer & Jarboui Anis, 2018. "Analysis of the Impact of Governance on Bank Performance: Case of Commercial Tunisian Banks," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 9(3), pages 871-895, September.
    16. Chai, Naijie & Zhou, Wenliang & Hu, Xinlei, 2022. "Safety evaluation of urban rail transit operation considering uncertainty and risk preference: A case study in China," Transport Policy, Elsevier, vol. 125(C), pages 267-288.
    17. Zanella, Andreia & Camanho, Ana S. & Dias, Teresa G., 2015. "Undesirable outputs and weighting schemes in composite indicators based on data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 245(2), pages 517-530.
    18. Ravelojaona, Paola, 2019. "On constant elasticity of substitution – Constant elasticity of transformation Directional Distance Functions," European Journal of Operational Research, Elsevier, vol. 272(2), pages 780-791.
    19. Hu, Jin-Li & Wang, Shih-Chuan & Yeh, Fang-Yu, 2006. "Total-factor water efficiency of regions in China," Resources Policy, Elsevier, vol. 31(4), pages 217-230, December.
    20. Adler, Nicole & Friedman, Lea & Sinuany-Stern, Zilla, 2002. "Review of ranking methods in the data envelopment analysis context," European Journal of Operational Research, Elsevier, vol. 140(2), pages 249-265, July.

    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:energy:v:35:y:2010:i:1:p:50-54. 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.journals.elsevier.com/energy .

    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.