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A parametric method using vernacular urban block typologies for investigating interactions between solar energy use and urban design

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  • Shi, Zhongming
  • Fonseca, Jimeno A.
  • Schlueter, Arno

Abstract

Building geometries strongly constrain the on-site solar energy use. In this work, solar energy use is measured by solar energy penetration and capital costs for the photovoltaic panel installations. This work provides a novel typological method for investigating interactions between solar energy use and urban design. Compared to other studies using typological methods, this work uses a typological method that highlights both computational efficiency and relevance to the vernacular contexts. Typical vernacular block typologies are formulated using a case study of built urban form featuring various combinations of block dimensions, building patterns, floor area ratios, and site coverage. We develop the Urban Block Generator, a tool to parametrically model such block typologies in Rhino/Grasshopper. We assess the solar energy penetration and the capital costs for these block typologies using the Urban Block Generator and the City Energy Analyst, an urban energy modeling and simulation program. We demonstrate this workflow on a case study in Singapore formulating 18 vernacular block typologies. The results are discussed and interpreted into urban design options and suggestions on various urban design parameters for different main driving forces, either maximizing the solar energy use or achieving a certain floor area ratio.

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  • Shi, Zhongming & Fonseca, Jimeno A. & Schlueter, Arno, 2021. "A parametric method using vernacular urban block typologies for investigating interactions between solar energy use and urban design," Renewable Energy, Elsevier, vol. 165(P1), pages 823-841.
    • Handle: RePEc:eee:renene:v:165:y:2021:i:p1:p:823-841
    DOI: 10.1016/j.renene.2020.10.067
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    2. Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
    3. Yanxue Li & Dawei Wang & Shanshan Li & Weijun Gao, 2021. "Impact Analysis of Urban Morphology on Residential District Heat Energy Demand and Microclimate Based on Field Measurement Data," Sustainability, MDPI, vol. 13(4), pages 1-17, February.
    4. Zhongming Shi & Heidi Silvennoinen & Arkadiusz Chadzynski & Aurel von Richthofen & Markus Kraft & Stephen Cairns & Pieter Herthogs, 2023. "Defining archetypes of mixed-use developments using Google Maps API data," Environment and Planning B, , vol. 50(6), pages 1607-1623, July.
    5. Zhang, Chunxiao & Shen, Chao & Zhang, Yingbo & Sun, Cheng & Chwieduk, Dorota & Kalogirou, Soteris A., 2021. "Optimization of the electricity/heat production of a PV/T system based on spectral splitting with Ag nanofluid," Renewable Energy, Elsevier, vol. 180(C), pages 30-39.
    6. Bushra, Nayab, 2022. "A comprehensive analysis of parametric design approaches for solar integration with buildings: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. 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.
    8. 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).
    9. Bushra, Nayab & Hartmann, Timo & Constantin Ungureanu, Lucian, 2022. "A method for global potential assessment of roof integrated two-stage solar concentrators (TSSCs) at district scale," Applied Energy, Elsevier, vol. 326(C).

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