IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v228y2018icp2140-2152.html
   My bibliography  Save this article

Building retrofit optimization models using notch test data considering energy performance certificate compliance

Author

Listed:
  • Fan, Yuling
  • Xia, Xiaohua

Abstract

Determining a systematic whole-building retrofit plan for envelope components and indoor appliances to achieve targets such as cost savings and policy compliance is a challenging task. To be specific, the systematic whole-building retrofit problem, when solved by an optimization approach, is highly complicated. It is sometimes even impossible to find a solution with given computation resources and algorithms. In addition, a costly comprehensive bottom-up audit is required to establish the parameters of the problem. This study presents two models to reduce the complexity of the systematic whole-building retrofit optimization problem. Firstly, the proposed models use the grouping concept to optimize the retrofit of subsystems in a building instead of individual components/appliances, which reduces the dimension of the problem effectively. Secondly, the models use so-called ‘notch test’ data, which are sampled and verified savings of an intervention, to eliminate the need for bottom-up energy audits. This further simplifies the retrofit optimization problem and reduces the retrofit cost. The models are based on our previous work and aim at energy savings maximization and payback period minimization, considering the green building policy and tax incentive initiatives. A case study shows that about 2530 MWh energy savings and an A rating from the energy performance certificate standard can be obtained with a payback period of 59 months, which verifies the feasibility and effectiveness of the models proposed.

Suggested Citation

  • Fan, Yuling & Xia, Xiaohua, 2018. "Building retrofit optimization models using notch test data considering energy performance certificate compliance," Applied Energy, Elsevier, vol. 228(C), pages 2140-2152.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:2140-2152
    DOI: 10.1016/j.apenergy.2018.07.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918310729
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.07.043?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. Kang, Lixia & Liu, Yongzhong, 2015. "Multi-objective optimization on a heat exchanger network retrofit with a heat pump and analysis of CO2 emissions control," Applied Energy, Elsevier, vol. 154(C), pages 696-708.
    2. Carstens, Herman & Xia, Xiaohua & Ye, Xianming, 2014. "Improvements to longitudinal Clean Development Mechanism sampling designs for lighting retrofit projects," Applied Energy, Elsevier, vol. 126(C), pages 256-265.
    3. Ye, Xianming & Xia, Xiaohua & Zhang, Jiangfeng, 2013. "Optimal sampling plan for clean development mechanism energy efficiency lighting projects," Applied Energy, Elsevier, vol. 112(C), pages 1006-1015.
    4. Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard Barry & Tong, Zheming, 2016. "Energy Saving Potential of Natural Ventilation in China: The Impact of Ambient Air Pollution," Scholarly Articles 27733689, Harvard University Department of Economics.
    5. Huang, Yu & Niu, Jian-lei & Chung, Tse-ming, 2013. "Study on performance of energy-efficient retrofitting measures on commercial building external walls in cooling-dominant cities," Applied Energy, Elsevier, vol. 103(C), pages 97-108.
    6. Xia, Xiaohua & Zhang, Jiangfeng, 2013. "Mathematical description for the measurement and verification of energy efficiency improvement," Applied Energy, Elsevier, vol. 111(C), pages 247-256.
    7. Ye, Xianming & Xia, Xiaohua, 2016. "Optimal metering plan for measurement and verification on a lighting case study," Energy, Elsevier, vol. 95(C), pages 580-592.
    8. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    9. Tronchin, Lamberto & Fabbri, Kristian, 2012. "Energy Performance Certificate of building and confidence interval in assessment: An Italian case study," Energy Policy, Elsevier, vol. 48(C), pages 176-184.
    10. Tong, Zheming & Chen, Yujiao & Malkawi, Ali & Liu, Zhu & Freeman, Richard B., 2016. "Energy saving potential of natural ventilation in China: The impact of ambient air pollution," Applied Energy, Elsevier, vol. 179(C), pages 660-668.
    11. Qian, Dong & Guo, Ju’e, 2014. "Research on the energy-saving and revenue sharing strategy of ESCOs under the uncertainty of the value of Energy Performance Contracting Projects," Energy Policy, Elsevier, vol. 73(C), pages 710-721.
    12. Carstens, Herman & Xia, Xiaohua & Yadavalli, Sarma, 2018. "Measurement uncertainty in energy monitoring: Present state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2791-2805.
    13. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2016. "Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design," Applied Energy, Elsevier, vol. 182(C), pages 625-633.
    14. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2017. "Estimating natural ventilation potential for high-rise buildings considering boundary layer meteorology," Applied Energy, Elsevier, vol. 193(C), pages 276-286.
    15. Fan, Yuling & Xia, Xiaohua, 2017. "A multi-objective optimization model for energy-efficiency building envelope retrofitting plan with rooftop PV system installation and maintenance," Applied Energy, Elsevier, vol. 189(C), pages 327-335.
    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. Ünal, Berat Berkan & Onaygil, Sermin & Acuner, Ebru & Cin, Rabia, 2022. "Application of energy efficiency obligation scheme for electricity distribution companies in Turkey," Energy Policy, Elsevier, vol. 163(C).
    2. Zhu, Chuanqi & Tian, Wei & Yin, Baoquan & Li, Zhanyong & Shi, Jiaxin, 2020. "Uncertainty calibration of building energy models by combining approximate Bayesian computation and machine learning algorithms," Applied Energy, Elsevier, vol. 268(C).
    3. Deb, C. & Schlueter, A., 2021. "Review of data-driven energy modelling techniques for building retrofit," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Shadram, Farshid & Bhattacharjee, Shimantika & Lidelöw, Sofia & Mukkavaara, Jani & Olofsson, Thomas, 2020. "Exploring the trade-off in life cycle energy of building retrofit through optimization," Applied Energy, Elsevier, vol. 269(C).

    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. Chen, Yujiao & Tong, Zheming & Wu, Wentao & Samuelson, Holly & Malkawi, Ali & Norford, Leslie, 2019. "Achieving natural ventilation potential in practice: Control schemes and levels of automation," Applied Energy, Elsevier, vol. 235(C), pages 1141-1152.
    2. Sakiyama, N.R.M. & Carlo, J.C. & Frick, J. & Garrecht, H., 2020. "Perspectives of naturally ventilated buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    3. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2017. "Estimating natural ventilation potential for high-rise buildings considering boundary layer meteorology," Applied Energy, Elsevier, vol. 193(C), pages 276-286.
    4. Nutkiewicz, Alex & Jain, Rishee K. & Bardhan, Ronita, 2018. "Energy modeling of urban informal settlement redevelopment: Exploring design parameters for optimal thermal comfort in Dharavi, Mumbai, India," Applied Energy, Elsevier, vol. 231(C), pages 433-445.
    5. Tong, Shuiguang & Cheng, Zhewu & Cong, Feiyun & Tong, Zheming & Zhang, Yidong, 2018. "Developing a grid-connected power optimization strategy for the integration of wind power with low-temperature adiabatic compressed air energy storage," Renewable Energy, Elsevier, vol. 125(C), pages 73-86.
    6. Olinga, Zadok & Xia, Xiaohua & Ye, Xianming, 2017. "A cost-effective approach to handle measurement and verification uncertainties of energy savings," Energy, Elsevier, vol. 141(C), pages 1600-1609.
    7. Payam Nejat & Fatemeh Jomehzadeh & Hasanen Mohammed Hussen & John Kaiser Calautit & Muhd Zaimi Abd Majid, 2018. "Application of Wind as a Renewable Energy Source for Passive Cooling through Windcatchers Integrated with Wing Walls," Energies, MDPI, vol. 11(10), pages 1-23, September.
    8. Ye, Xianming & Xia, Xiaohua, 2016. "Optimal metering plan for measurement and verification on a lighting case study," Energy, Elsevier, vol. 95(C), pages 580-592.
    9. Carstens, Herman & Xia, Xiaohua & Yadavalli, Sarma, 2017. "Low-cost energy meter calibration method for measurement and verification," Applied Energy, Elsevier, vol. 188(C), pages 563-575.
    10. Alberto Meiss & Miguel A. Padilla-Marcos & Jesús Feijó-Muñoz, 2017. "Methodology Applied to the Evaluation of Natural Ventilation in Residential Building Retrofits: A Case Study," Energies, MDPI, vol. 10(4), pages 1-19, April.
    11. Ye, Xianming & Xia, Xiaohua & Zhang, Jiangfeng, 2014. "Optimal sampling plan for clean development mechanism lighting projects with lamp population decay," Applied Energy, Elsevier, vol. 136(C), pages 1184-1192.
    12. Tong, Zheming & Chen, Yujiao & Malkawi, Ali, 2016. "Defining the Influence Region in neighborhood-scale CFD simulations for natural ventilation design," Applied Energy, Elsevier, vol. 182(C), pages 625-633.
    13. Bienvenido-Huertas, David & Sánchez-García, Daniel & Rubio-Bellido, Carlos, 2020. "Analysing natural ventilation to reduce the cooling energy consumption and the fuel poverty of social dwellings in coastal zones," Applied Energy, Elsevier, vol. 279(C).
    14. Ikuzwe, Alice & Xia, Xiaohua & Ye, Xianming, 2020. "Maintenance optimization incorporating lumen degradation failure for energy-efficient lighting retrofit projects," Applied Energy, Elsevier, vol. 267(C).
    15. Cui, X. & Mohan, B. & Islam, M.R. & Chou, S.K. & Chua, K.J., 2017. "Energy performance evaluation and application of an air treatment system for conditioning building spaces in tropics," Applied Energy, Elsevier, vol. 204(C), pages 1500-1512.
    16. Carstens, Herman & Xia, Xiaohua & Yadavalli, Sarma, 2018. "Measurement uncertainty in energy monitoring: Present state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2791-2805.
    17. Zhang, Chaobo & Xue, Xue & Zhao, Yang & Zhang, Xuejun & Li, Tingting, 2019. "An improved association rule mining-based method for revealing operational problems of building heating, ventilation and air conditioning (HVAC) systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    18. Peter Rafaj & Markus Amann, 2018. "Decomposing Air Pollutant Emissions in Asia: Determinants and Projections," Energies, MDPI, vol. 11(5), pages 1-14, May.
    19. Zhang, Shaohui & Guo, Qinxin & Smyth, Russell & Yao, Yao, 2022. "Extreme temperatures and residential electricity consumption: Evidence from Chinese households," Energy Economics, Elsevier, vol. 107(C).
    20. Costanzo, Vincenzo & Yao, Runming & Xu, Tiantian & Xiong, Jie & Zhang, Qiulei & Li, Baizhan, 2019. "Natural ventilation potential for residential buildings in a densely built-up and highly polluted environment. A case study," Renewable Energy, Elsevier, vol. 138(C), pages 340-353.

    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:228:y:2018:i:c:p:2140-2152. 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.