IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v159y2015icp298-309.html
   My bibliography  Save this article

Commercial Building Energy Saver: An energy retrofit analysis toolkit

Author

Listed:
  • Hong, Tianzhen
  • Piette, Mary Ann
  • Chen, Yixing
  • Lee, Sang Hoon
  • Taylor-Lange, Sarah C.
  • Zhang, Rongpeng
  • Sun, Kaiyu
  • Price, Phillip

Abstract

Small commercial buildings in the United States consume 47% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, which calculates the energy use of a building, identifies and evaluates retrofit measures in terms of energy savings, energy cost savings and payback. The CBES Toolkit includes a web app (APP) for end users and the CBES Application Programming Interface (API) for integrating CBES with other energy software tools. The toolkit provides a rich set of features including: (1) Energy Benchmarking providing an Energy Star score, (2) Load Shape Analysis to identify potential building operation improvements, (3) Preliminary Retrofit Analysis which uses a custom developed pre-simulated database and, (4) Detailed Retrofit Analysis which utilizes real-time EnergyPlus simulations. CBES includes 100 configurable energy conservation measures (ECMs) that encompass IAQ, technical performance and cost data, for assessing 7 different prototype buildings in 16 climate zones in California and 6 vintages. A case study of a small office building demonstrates the use of the toolkit for retrofit analysis. The development of CBES provides a new contribution to the field by providing a straightforward and uncomplicated decision making process for small and medium business owners, leveraging different levels of assessment dependent upon user background, preference and data availability.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:159:y:2015:i:c:p:298-309
    DOI: 10.1016/j.apenergy.2015.09.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915010703
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.09.002?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. Lee, Sang Hoon & Hong, Tianzhen & Piette, Mary Ann & Sawaya, Geof & Chen, Yixing & Taylor-Lange, Sarah C., 2015. "Accelerating the energy retrofit of commercial buildings using a database of energy efficiency performance," Energy, Elsevier, vol. 90(P1), pages 738-747.
    2. Zhao, Hai-xiang & Magoulès, Frédéric, 2012. "A review on the prediction of building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3586-3592.
    3. Chidiac, S.E. & Catania, E.J.C. & Morofsky, E. & Foo, S., 2011. "Effectiveness of single and multiple energy retrofit measures on the energy consumption of office buildings," Energy, Elsevier, vol. 36(8), pages 5037-5052.
    4. Nord, Natasa & Mathisen, Hans Martin & Cao, Guangyu, 2015. "Energy cost models for air supported sports hall in cold climates considering energy efficiency," Renewable Energy, Elsevier, vol. 84(C), pages 56-64.
    5. Chung, William, 2011. "Review of building energy-use performance benchmarking methodologies," Applied Energy, Elsevier, vol. 88(5), pages 1470-1479, May.
    6. 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.
    7. Cagno, E. & Worrell, E. & Trianni, A. & Pugliese, G., 2013. "A novel approach for barriers to industrial energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 290-308.
    8. Wang, Endong, 2015. "Benchmarking whole-building energy performance with multi-criteria technique for order preference by similarity to ideal solution using a selective objective-weighting approach," Applied Energy, Elsevier, vol. 146(C), pages 92-103.
    9. 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.
    10. Henze, Gregor P. & Pavlak, Gregory S. & Florita, Anthony R. & Dodier, Robert H. & Hirsch, Adam I., 2015. "An energy signal tool for decision support in building energy systems," Applied Energy, Elsevier, vol. 138(C), pages 51-70.
    11. Lee, Sang Hoon & Hong, Tianzhen & Piette, Mary Ann & Taylor-Lange, Sarah C., 2015. "Energy retrofit analysis toolkits for commercial buildings: A review," Energy, Elsevier, vol. 89(C), pages 1087-1100.
    12. 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.
    13. Gliedt, Travis & Hoicka, Christina E., 2015. "Energy upgrades as financial or strategic investment? Energy Star property owners and managers improving building energy performance," Applied Energy, Elsevier, vol. 147(C), pages 430-443.
    14. Roberts, Simon, 2008. "Altering existing buildings in the UK," Energy Policy, Elsevier, vol. 36(12), pages 4482-4486, December.
    15. 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.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Sun, Kaiyu & Hong, Tianzhen & Taylor-Lange, Sarah C. & Piette, Mary Ann, 2016. "A pattern-based automated approach to building energy model calibration," Applied Energy, Elsevier, vol. 165(C), pages 214-224.
    3. 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.
    4. Garg, Amit & Maheshwari, Jyoti & Shukla, P.R. & Rawal, Rajan, 2017. "Energy appliance transformation in commercial buildings in India under alternate policy scenarios," Energy, Elsevier, vol. 140(P1), pages 952-965.
    5. 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.
    6. 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.
    7. 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.
    8. Raatikainen, Mika & Skön, Jukka-Pekka & Leiviskä, Kauko & Kolehmainen, Mikko, 2016. "Intelligent analysis of energy consumption in school buildings," Applied Energy, Elsevier, vol. 165(C), pages 416-429.
    9. 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.
    10. 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.
    11. Grillone, Benedetto & Danov, Stoyan & Sumper, Andreas & Cipriano, Jordi & Mor, Gerard, 2020. "A review of deterministic and data-driven methods to quantify energy efficiency savings and to predict retrofitting scenarios in buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    12. Walter, Travis & Sohn, Michael D., 2016. "A regression-based approach to estimating retrofit savings using the Building Performance Database," Applied Energy, Elsevier, vol. 179(C), pages 996-1005.
    13. Roth, Jonathan & Rajagopal, Ram, 2018. "Benchmarking building energy efficiency using quantile regression," Energy, Elsevier, vol. 152(C), pages 866-876.
    14. 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.
    15. Park, Hyo Seon & Lee, Minhyun & Kang, Hyuna & Hong, Taehoon & Jeong, Jaewook, 2016. "Development of a new energy benchmark for improving the operational rating system of office buildings using various data-mining techniques," Applied Energy, Elsevier, vol. 173(C), pages 225-237.
    16. Lai, Yuan & Papadopoulos, Sokratis & Fuerst, Franz & Pivo, Gary & Sagi, Jacob & Kontokosta, Constantine E., 2022. "Building retrofit hurdle rates and risk aversion in energy efficiency investments," Applied Energy, Elsevier, vol. 306(PB).
    17. Amasyali, Kadir & El-Gohary, Nora M., 2018. "A review of data-driven building energy consumption prediction studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1192-1205.
    18. Lu, Zhijian & Shao, Shuai, 2016. "Impacts of government subsidies on pricing and performance level choice in Energy Performance Contracting: A two-step optimal decision model," Applied Energy, Elsevier, vol. 184(C), pages 1176-1183.
    19. Chul-Ho Kim & Seung-Eon Lee & Kang-Soo Kim, 2018. "Analysis of Energy Saving Potential in High-Performance Building Technologies under Korean Climatic Conditions," Energies, MDPI, vol. 11(4), pages 1-34, April.
    20. 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.

    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:159:y:2015:i:c:p:298-309. 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.