IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15307-d1267681.html
   My bibliography  Save this article

Study on the Influence of the Energy Intensity of Residential District Layout on Neighborhood Buildings

Author

Listed:
  • Junle Yan

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Hui Zhang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China
    College of Design and Engineering, National University of Singapore, Singapore 117566, Singapore)

  • Yunjiang Li

    (School of Civil Engineering and Architecture, China Three Gorges University, Yichang 443002, China)

  • Xiaoxi Huang

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Shiyu Jin

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Xueying Jia

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Zikang Ke

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

  • Haibo Yu

    (School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China)

Abstract

Numerous prior studies have substantiated the influence of residential layout on building energy consumption; however, their principal emphasis has predominantly been on urban and neighborhood contexts. Nevertheless, research conducted at the cluster scale has the potential to augment the well-being of neighboring communities and render the objective of a reduction in energy consumption more pertinent to residents’ daily lives. Furthermore, there is a shortage of more robust metrics capable of quantifying the degree of mutual shading among individual buildings within residential neighborhoods. This shading factor constitutes a pivotal element impacting the energy consumption of individual structures. This study utilizes the VirVil-HTB2 tool to calculate solar radiation intensity for individual buildings, serving as a shading metric. Correlation and linear regression analyses are employed to quantify the causal relationship, allowing us to investigate the impact of residential complex layouts on the energy efficiency of individual buildings. The findings of this study indicate that solar radiation serves as a precise metric for gauging shading intensity among buildings, and building energy consumption exhibits a distinct block-like distribution pattern within the residential complex. Furthermore, through an analysis of the level of inter-building shading and a judicious optimization of the layout, it is feasible to achieve a reduction of up to 4.03% in heating energy consumption and a maximum reduction of 4.39% in cooling energy consumption.

Suggested Citation

  • Junle Yan & Hui Zhang & Yunjiang Li & Xiaoxi Huang & Shiyu Jin & Xueying Jia & Zikang Ke & Haibo Yu, 2023. "Study on the Influence of the Energy Intensity of Residential District Layout on Neighborhood Buildings," Sustainability, MDPI, vol. 15(21), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15307-:d:1267681
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15307/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/21/15307/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Han, Yilong & Taylor, John E. & Pisello, Anna Laura, 2017. "Exploring mutual shading and mutual reflection inter-building effects on building energy performance," Applied Energy, Elsevier, vol. 185(P2), pages 1556-1564.
    2. Junle Yan & Hui Zhang & Xiaoxin Liu & Ling Ning & Wong Nyuk Hien, 2023. "The Impact of Residential Cluster Layout on Building Energy Consumption and Carbon Emissions in Regions with Hot Summers and Cold Winters in China," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
    3. Javanroodi, Kavan & Mahdavinejad, Mohammadjavad & Nik, Vahid M., 2018. "Impacts of urban morphology on reducing cooling load and increasing ventilation potential in hot-arid climate," Applied Energy, Elsevier, vol. 231(C), pages 714-746.
    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. 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.
    2. Pigliautile, I. & Pisello, A.L. & Bou-Zeid, E., 2020. "Humans in the city: Representing outdoor thermal comfort in urban canopy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    3. Rodrigues, Eugénio & Fernandes, Marco S. & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Costa, José J., 2019. "Performance-based design of multi-story buildings for a sustainable urban environment: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    4. Wei Feng & Wei Ding & Yingdi Yin & Qixian Lin & Meng Zheng & Miaomiao Fei, 2021. "Optimization Strategy of Traditional Block Form Based on Field Investigation—A Case Study of Xi’an Baxian’an, China," IJERPH, MDPI, vol. 18(20), pages 1-25, October.
    5. Battini, Federico & Pernigotto, Giovanni & Gasparella, Andrea, 2023. "District-level validation of a shoeboxing simplification algorithm to speed-up Urban Building Energy Modeling simulations," Applied Energy, Elsevier, vol. 349(C).
    6. Yi Song Liu & Tan Yigitcanlar & Mirko Guaralda & Kenan Degirmenci & Aaron Liu & Michael Kane, 2022. "Leveraging the Opportunities of Wind for Cities through Urban Planning and Design: A PRISMA Review," Sustainability, MDPI, vol. 14(18), pages 1-78, September.
    7. Huimin Ji & Yifan Li & Juan Li & Wowo Ding, 2023. "A Novel Quantitative Approach to the Spatial Configuration of Urban Streets Based on Local Wind Environment," Land, MDPI, vol. 12(12), pages 1-25, November.
    8. Zhao, Bin & Wang, Chuyao & Hu, Mingke & Ao, Xianze & Liu, Jie & Xuan, Qingdong & Pei, Gang, 2022. "Light and thermal management of the semi-transparent radiative cooling glass for buildings," Energy, Elsevier, vol. 238(PA).
    9. Natanian, Jonathan & Aleksandrowicz, Or & Auer, Thomas, 2019. "A parametric approach to optimizing urban form, energy balance and environmental quality: The case of Mediterranean districts," Applied Energy, Elsevier, vol. 254(C).
    10. Chen, Xi & Yang, Hongxing & Peng, Jinqing, 2019. "Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context," Energy, Elsevier, vol. 172(C), pages 1-17.
    11. Chen, Yixing & Hong, Tianzhen, 2018. "Impacts of building geometry modeling methods on the simulation results of urban building energy models," Applied Energy, Elsevier, vol. 215(C), pages 717-735.
    12. Osawa Hisato & Taro Mori & Kouichi Shinagawa & Satoshi Nakayama & Hayato Hosobuchi & Emad Mushtaha, 2022. "Analysis of Requirements for Achieving Carbon Neutrality in a Cold Dense City Using GIS," Energies, MDPI, vol. 15(19), pages 1-24, September.
    13. Juan, Yu-Hsuan & Wen, Chih-Yung & Li, Zhengtong & Yang, An-Shik, 2021. "Impacts of urban morphology on improving urban wind energy potential for generic high-rise building arrays," Applied Energy, Elsevier, vol. 299(C).
    14. Salah Vaisi & Saleh Mohammadi & Benedetto Nastasi & Kavan Javanroodi, 2020. "A New Generation of Thermal Energy Benchmarks for University Buildings," Energies, MDPI, vol. 13(24), pages 1-18, December.
    15. Liao, Xuan & Zhu, Rui & Wong, Man Sing & Heo, Joon & Chan, P.W. & Kwok, Coco Yin Tung, 2023. "Fast and accurate estimation of solar irradiation on building rooftops in Hong Kong: A machine learning-based parameterization approach," Renewable Energy, Elsevier, vol. 216(C).
    16. Ritesh Wankhade & Giovanni Pernigotto & Michele Larcher, 2023. "A Literature Review on Methods and Metrics for the Analysis of Outdoor Air Displacement Conditions in the Urban Environment," Energies, MDPI, vol. 16(6), pages 1-31, March.
    17. Quan, Steven Jige & Li, Chaosu, 2021. "Urban form and building energy use: A systematic review of measures, mechanisms, and methodologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    18. Chen, Xi & Yang, Hongxing & Sun, Ke, 2017. "Developing a meta-model for sensitivity analyses and prediction of building performance for passively designed high-rise residential buildings," Applied Energy, Elsevier, vol. 194(C), pages 422-439.
    19. Kohler, M. & Blond, N. & Clappier, A., 2016. "A city scale degree-day method to assess building space heating energy demands in Strasbourg Eurometropolis (France)," Applied Energy, Elsevier, vol. 184(C), pages 40-54.
    20. Yang, Yuchen & Javanroodi, Kavan & Nik, Vahid M., 2021. "Climate change and energy performance of European residential building stocks – A comprehensive impact assessment using climate big data from the coordinated regional climate downscaling experiment," Applied Energy, Elsevier, vol. 298(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:jsusta:v:15:y:2023:i:21:p:15307-:d:1267681. 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.