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Building stock energy modeling considering building system composition and long-term change for climate change mitigation of commercial building stocks

Author

Listed:
  • Yamaguchi, Yohei
  • Kim, Bumjoon
  • Kitamura, Takuya
  • Akizawa, Kotone
  • Chen, Hemiao
  • Shimoda, Yoshiyuki

Abstract

A significant improvement in the building stock energy efficiency is imperative to mitigate climate change. Building stock energy models (BSEMs) that employ reference building models are useful for mitigation analysis. However, most existing BSEMs developed for commercial building stock focus on limited building systems and energy conservation measures, and technology deployments are suggested based on simple vintage-driven scenarios. These approaches are insufficient, particularly for regions where improvements to building insulation performances can have a modest impact. This study aims to establish a BSEM framework to overcome this issue and to validate the framework via its application to the Japanese commercial building stock. The framework develops statistical models for estimating the selection probabilities of system alternatives and utilizes them to disaggregate building stocks. A reference building model is developed for each stock segment. The results show that this approach facilitates the use of multiple technological options considering various factors that affect technological deployments, and it also helps estimate the baseline development of building stocks. Furthermore, the developed model well represents the observed distributions in energy use intensity and estimates the aggregated energy consumption of building stocks with a reasonable accuracy. The baseline development was estimated to reduce the CO2 emission by 18% by 2030 from 2013. Efficiency measures can help avoid the increase in electricity demand caused by electrifying the heat source of heating, ventilating, and air-conditioning and water heating systems. The framework could help extend the scope of BSEM application because BSEM development is not information intensive.

Suggested Citation

  • Yamaguchi, Yohei & Kim, Bumjoon & Kitamura, Takuya & Akizawa, Kotone & Chen, Hemiao & Shimoda, Yoshiyuki, 2022. "Building stock energy modeling considering building system composition and long-term change for climate change mitigation of commercial building stocks," Applied Energy, Elsevier, vol. 306(PA).
  • Handle: RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921012204
    DOI: 10.1016/j.apenergy.2021.117907
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    References listed on IDEAS

    as
    1. Corgnati, Stefano Paolo & Fabrizio, Enrico & Filippi, Marco & Monetti, Valentina, 2013. "Reference buildings for cost optimal analysis: Method of definition and application," Applied Energy, Elsevier, vol. 102(C), pages 983-993.
    2. Andrews, Clinton J. & Krogmann, Uta, 2009. "Technology diffusion and energy intensity in US commercial buildings," Energy Policy, Elsevier, vol. 37(2), pages 541-553, February.
    3. Ó Broin, Eoin & Mata, Érika & Göransson, Anders & Johnsson, Filip, 2013. "The effect of improved efficiency on energy savings in EU-27 buildings," Energy, Elsevier, vol. 57(C), pages 134-148.
    4. Swan, Lukas G. & Ugursal, V. Ismet, 2009. "Modeling of end-use energy consumption in the residential sector: A review of modeling techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1819-1835, October.
    5. Wang, Huan & Chen, Wenying & Shi, Jingcheng, 2018. "Low carbon transition of global building sector under 2- and 1.5-degree targets," Applied Energy, Elsevier, vol. 222(C), pages 148-157.
    6. Ciulla, Giuseppina & Lo Brano, Valerio & D’Amico, Antonino, 2016. "Modelling relationship among energy demand, climate and office building features: A cluster analysis at European level," Applied Energy, Elsevier, vol. 183(C), pages 1021-1034.
    7. Napp, T.A. & Few, S. & Sood, A. & Bernie, D. & Hawkes, A. & Gambhir, A., 2019. "The role of advanced demand-sector technologies and energy demand reduction in achieving ambitious carbon budgets," Applied Energy, Elsevier, vol. 238(C), pages 351-367.
    8. Sandberg, Nina Holck & Næss, Jan Sandstad & Brattebø, Helge & Andresen, Inger & Gustavsen, Arild, 2021. "Large potentials for energy saving and greenhouse gas emission reductions from large-scale deployment of zero emission building technologies in a national building stock," Energy Policy, Elsevier, vol. 152(C).
    9. 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.
    10. Sandels, C. & Brodén, D. & Widén, J. & Nordström, L. & Andersson, E., 2016. "Modeling office building consumer load with a combined physical and behavioral approach: Simulation and validation," Applied Energy, Elsevier, vol. 162(C), pages 472-485.
    11. Boßmann, T. & Staffell, I., 2015. "The shape of future electricity demand: Exploring load curves in 2050s Germany and Britain," Energy, Elsevier, vol. 90(P2), pages 1317-1333.
    12. Azar, Elie & Menassa, Carol C., 2014. "A comprehensive framework to quantify energy savings potential from improved operations of commercial building stocks," Energy Policy, Elsevier, vol. 67(C), pages 459-472.
    13. McNeil, Michael A. & Feng, Wei & de la Rue du Can, Stephane & Khanna, Nina Zheng & Ke, Jing & Zhou, Nan, 2016. "Energy efficiency outlook in China’s urban buildings sector through 2030," Energy Policy, Elsevier, vol. 97(C), pages 532-539.
    14. Brugger, Heike & Eichhammer, Wolfgang & Mikova, Nadezhda & Dönitz, Ewa, 2021. "Energy Efficiency Vision 2050: How will new societal trends influence future energy demand in the European countries?," Energy Policy, Elsevier, vol. 152(C).
    15. Crespi, Giulia & Becchio, Cristina & Corgnati, Stefano Paolo, 2021. "Towards Post-Carbon Cities: Which retrofit scenarios for hotels in Italy?," Renewable Energy, Elsevier, vol. 163(C), pages 950-963.
    16. Buso, Tiziana & Corgnati, Stefano Paolo, 2017. "A customized modelling approach for multi-functional buildings – Application to an Italian Reference Hotel," Applied Energy, Elsevier, vol. 190(C), pages 1302-1315.
    17. Higgins, Andrew & Syme, Mike & McGregor, James & Marquez, Leorey & Seo, Seongwon, 2014. "Forecasting uptake of retrofit packages in office building stock under government incentives," Energy Policy, Elsevier, vol. 65(C), pages 501-511.
    18. 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).
    19. Pang, Zhihong & Chen, Yan & Zhang, Jian & O'Neill, Zheng & Cheng, Hwakong & Dong, Bing, 2020. "Nationwide HVAC energy-saving potential quantification for office buildings with occupant-centric controls in various climates," Applied Energy, Elsevier, vol. 279(C).
    20. Nan Zhou & Nina Khanna & Wei Feng & Jing Ke & Mark Levine, 2018. "Scenarios of energy efficiency and CO2 emissions reduction potential in the buildings sector in China to year 2050," Nature Energy, Nature, vol. 3(11), pages 978-984, November.
    21. Yang, Tao & Pan, Yiqun & Yang, Yikun & Lin, Meishun & Qin, Bingyue & Xu, Peng & Huang, Zhizhong, 2017. "CO2 emissions in China's building sector through 2050: A scenario analysis based on a bottom-up model," Energy, Elsevier, vol. 128(C), pages 208-223.
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    Cited by:

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    5. Couraud, Benoit & Andoni, Merlinda & Robu, Valentin & Norbu, Sonam & Chen, Si & Flynn, David, 2023. "Responsive FLEXibility: A smart local energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).

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