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Impact of neighbourhood-scale climate characteristics on building heating demand and night ventilation cooling potential

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  • Xie, Xiaoxiong
  • Sahin, Ozge
  • Luo, Zhiwen
  • Yao, Runming

Abstract

As buildings are main contributor to greenhouse gas emissions, it is important to assess the performance of existing buildings and assist the design of new sustainable buildings through building energy simulation. It is well known that by using local climate measurements for building energy simulation would provide more accurate result than by using other typical weather data, i.e. typical meteorological year (TMY). However, as different built forms/architectural layouts would also have impacts on neighbourhood-scale microclimate, it is worthy to quantify the difference it would make. In this study, we performed a year-long measurement with four weather stations surrounding a campus building in 2009 and 2010. Each station was placed in a typical type of built form, including a street canyon, a courtyard, a semi-closed courtyard and a relatively larger open area. Besides, two typical weather data files, typical meteorological year (TMY) and actual meteorological year (AMY) were taken as reference. Annual heating demand and natural ventilation cooling potential were calculated based on all 6 weather files. Our simulation results show that the variation in annual heating demand of different built forms could be between 1.1 and 7.3%, where the large open area has the highest heating demand and it of the courtyard is the lowest. The difference between on-site measurement and TMY in annual heating load is as high as 10.8%. While in summer, night ventilation cooling potential of the courtyard and the semi-closed form are the highest, and it of the street canyon is the lowest. Using TMY could underestimate the night ventilation cooling potential by 26–31% and using AMY could overestimate it by 9–14% in total. Overall speaking, the courtyard form shows good performance in reducing heating demand and enhancing night ventilation cooling, while the street canyon shows relatively poor performance in both aspects. These findings highlight the importance to understand the impact of neighbourhood-scale microclimate on building energy performance.

Suggested Citation

  • Xie, Xiaoxiong & Sahin, Ozge & Luo, Zhiwen & Yao, Runming, 2020. "Impact of neighbourhood-scale climate characteristics on building heating demand and night ventilation cooling potential," Renewable Energy, Elsevier, vol. 150(C), pages 943-956.
  • Handle: RePEc:eee:renene:v:150:y:2020:i:c:p:943-956
    DOI: 10.1016/j.renene.2019.11.148
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    Cited by:

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    2. Beilei Qin & Xi Xu & Takashi Asawa & Lulu Zhang, 2022. "Experimental and Numerical Analysis on Effect of Passive Cooling Methods on an Indoor Thermal Environment Having Floor-Level Windows," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    3. Jingtao Li & Zhixin Li & Yao Wang & Hong Zhang, 2023. "Energy Utilization and Carbon Reduction Potential of Solar Energy in Residential Blocks: A Case Study on a Tropical High-Density City in China," Sustainability, MDPI, vol. 15(17), pages 1-25, August.
    4. Wang, Wei & Liu, Ke & Zhang, Muxing & Shen, Yuchi & Jing, Rui & Xu, Xiaodong, 2021. "From simulation to data-driven approach: A framework of integrating urban morphology to low-energy urban design," Renewable Energy, Elsevier, vol. 179(C), pages 2016-2035.
    5. 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.
    6. Guo, Rui & Hu, Yue & Heiselberg, Per & Johra, Hicham & Zhang, Chen & Peng, Pei, 2021. "Simulation and optimization of night cooling with diffuse ceiling ventilation and mixing ventilation in a cold climate," Renewable Energy, Elsevier, vol. 179(C), pages 488-501.
    7. Shiyi Song & Hong Leng & Han Xu & Ran Guo & Yan Zhao, 2020. "Impact of Urban Morphology and Climate on Heating Energy Consumption of Buildings in Severe Cold Regions," IJERPH, MDPI, vol. 17(22), pages 1-24, November.

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