IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i8p1907-d1377287.html
   My bibliography  Save this article

Analysis of Energy Efficiency Opportunities for a Public Transportation Maintenance Facility—A Case Study

Author

Listed:
  • Jordan Higgins

    (Smart and Small Thermal Systems Laboratory, Center for Environmental Energy Engineering, University of Maryland College Park, 8228 Paint Branch Drive, College Park, MD 20742, USA)

  • Aditya Ramnarayan

    (Smart and Small Thermal Systems Laboratory, Center for Environmental Energy Engineering, University of Maryland College Park, 8228 Paint Branch Drive, College Park, MD 20742, USA)

  • Roxana Family

    (Department of Materials Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA)

  • Michael Ohadi

    (Smart and Small Thermal Systems Laboratory, Center for Environmental Energy Engineering, University of Maryland College Park, 8228 Paint Branch Drive, College Park, MD 20742, USA)

Abstract

A comprehensive energy audit of a light rail maintenance facility was performed to assess its energy performance and identify potential scope for improvements. The facility’s energy use intensity (EUI) for 2022 was 404 kWh/m 2 —more than double the benchmark EUI for maintenance facilities (151 kWh/m 2 ) recommended by EnergyStar. Furthermore, the load factor was 0.22—significantly lower than the recommended minimum of 0.75 for an efficient building. The energy audit encompassed an in-depth evaluation of the facility’s structural and operational characteristics, comprising HVAC systems, lighting, the building envelope, and energy-intensive machinery. An energy model of the facility was developed to emulate the facility’s energy performance in 2022. Following the energy model’s validation, an analysis was conducted to identify opportunities for improving energy efficiency. Post-implementation of energy efficiency measures for the facility, the projected annual reductions are 1086 MWh of electricity, 5034 GJ of natural gas, utility savings of USD 162,402, and net GHG emissions reductions of 584 metric tons of CO 2e . A subsequent 30% reduction in EUI to 283.6 kWh/m 2 could be achieved with an 86% improvement in load factor, that is, increasing it from 0.22 to 0.41. This study emphasizes the need for energy audits and modeling for maintenance facilities to reduce Scope 1 and 2 emissions.

Suggested Citation

  • Jordan Higgins & Aditya Ramnarayan & Roxana Family & Michael Ohadi, 2024. "Analysis of Energy Efficiency Opportunities for a Public Transportation Maintenance Facility—A Case Study," Energies, MDPI, vol. 17(8), pages 1-20, April.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:8:p:1907-:d:1377287
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/8/1907/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/8/1907/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Wenliang & Zhou, Yuyu & Cetin, Kristen & Eom, Jiyong & Wang, Yu & Chen, Gang & Zhang, Xuesong, 2017. "Modeling urban building energy use: A review of modeling approaches and procedures," Energy, Elsevier, vol. 141(C), pages 2445-2457.
    2. Gao, Hao & Koch, Christian & Wu, Yupeng, 2019. "Building information modelling based building energy modelling: A review," Applied Energy, Elsevier, vol. 238(C), pages 320-343.
    3. Sezgen, Osman & Koomey, Jonathan G, 2000. "Interactions between lighting and space conditioning energy use in US commercial buildings," Energy, Elsevier, vol. 25(8), pages 793-805.
    4. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    5. Perez-Lombard, Luis & Ortiz, Jose & Maestre, Ismael R., 2011. "The map of energy flow in HVAC systems," Applied Energy, Elsevier, vol. 88(12), pages 5020-5031.
    6. Mustafaraj, Giorgio & Marini, Dashamir & Costa, Andrea & Keane, Marcus, 2014. "Model calibration for building energy efficiency simulation," Applied Energy, Elsevier, vol. 130(C), pages 72-85.
    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. Si Chen & Daniel Friedrich & Zhibin Yu & James Yu, 2019. "District Heating Network Demand Prediction Using a Physics-Based Energy Model with a Bayesian Approach for Parameter Calibration," Energies, MDPI, vol. 12(18), pages 1-19, September.
    2. Shimoda, Yoshiyuki & Yamaguchi, Yohei & Iwafune, Yumiko & Hidaka, Kazuyoshi & Meier, Alan & Yagita, Yoshie & Kawamoto, Hisaki & Nishikiori, Soichi, 2020. "Energy demand science for a decarbonized society in the context of the residential sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    3. Schito, Eva & Conti, Paolo & Testi, Daniele, 2018. "Multi-objective optimization of microclimate in museums for concurrent reduction of energy needs, visitors’ discomfort and artwork preservation risks," Applied Energy, Elsevier, vol. 224(C), pages 147-159.
    4. Solène Goy & François Maréchal & Donal Finn, 2020. "Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges," Energies, MDPI, vol. 13(16), pages 1-23, August.
    5. Mihail Mateev, 2024. "Digital Twins Concept For Energy-Efficient Smart Buildings," Yearbook of the Faculty of Economics and Business Administration, Sofia University, Faculty of Economics and Business Administration, Sofia University St Kliment Ohridski - Bulgaria, vol. 23(1), pages 187-198, June.
    6. 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.
    7. Boonekamp, Piet G.M., 2006. "Actual interaction effects between policy measures for energy efficiency—A qualitative matrix method and quantitative simulation results for households," Energy, Elsevier, vol. 31(14), pages 2848-2873.
    8. Tian, Shen & Shao, Shuangquan & Liu, Bin, 2019. "Investigation on transient energy consumption of cold storages: Modeling and a case study," Energy, Elsevier, vol. 180(C), pages 1-9.
    9. Langevin, J. & Reyna, J.L. & Ebrahimigharehbaghi, S. & Sandberg, N. & Fennell, P. & Nägeli, C. & Laverge, J. & Delghust, M. & Mata, É. & Van Hove, M. & Webster, J. & Federico, F. & Jakob, M. & Camaras, 2020. "Developing a common approach for classifying building stock energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    10. Younghun Choi & Takuro Kobashi & Yoshiki Yamagata & Akito Murayama, 2021. "Assessment of waterfront office redevelopment plan on optimal building energy demand and rooftop photovoltaics for urban decarbonization," Papers 2108.09029, arXiv.org.
    11. Dujuan Yang & Harry Timmermans & Aloys Borgers, 2016. "The prevalence of context-dependent adjustment of activity-travel patterns in energy conservation strategies: results from a mixture-amount stated adaptation experiment," Transportation, Springer, vol. 43(1), pages 79-100, January.
    12. 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.
    13. Sila Kiliccote & Daniel Olsen & Michael D. Sohn & Mary Ann Piette, 2016. "Characterization of demand response in the commercial, industrial, and residential sectors in the United States," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(3), pages 288-304, May.
    14. Lin, Yu-Hao & Tsai, Kang-Ting & Lin, Min-Der & Yang, Ming-Der, 2016. "Design optimization of office building envelope configurations for energy conservation," Applied Energy, Elsevier, vol. 171(C), pages 336-346.
    15. Moore, David & Webb, Amanda L., 2022. "Evaluating energy burden at the urban scale: A spatial regression approach in Cincinnati, Ohio," Energy Policy, Elsevier, vol. 160(C).
    16. Glasgo, Brock & Hendrickson, Chris & Azevedo, Inês Lima, 2017. "Assessing the value of information in residential building simulation: Comparing simulated and actual building loads at the circuit level," Applied Energy, Elsevier, vol. 203(C), pages 348-363.
    17. Alaia Sola & Cristina Corchero & Jaume Salom & Manel Sanmarti, 2018. "Simulation Tools to Build Urban-Scale Energy Models: A Review," Energies, MDPI, vol. 11(12), pages 1-24, November.
    18. Christoph Sejkora & Lisa Kühberger & Fabian Radner & Alexander Trattner & Thomas Kienberger, 2020. "Exergy as Criteria for Efficient Energy Systems—A Spatially Resolved Comparison of the Current Exergy Consumption, the Current Useful Exergy Demand and Renewable Exergy Potential," Energies, MDPI, vol. 13(4), pages 1-51, February.
    19. 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.
    20. Lešnik, Maja & Kravanja, Stojan & Premrov, Miroslav & Žegarac Leskovar, Vesna, 2020. "Optimal design of timber-glass upgrade modules for vertical building extension from the viewpoints of energy efficiency and visual comfort," Applied Energy, Elsevier, vol. 270(C).

    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:gam:jeners:v:17:y:2024:i:8:p:1907-:d:1377287. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.