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Energy optimization of high-rise commercial buildings integrated with photovoltaic facades in urban context

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  • Chen, Xi
  • Yang, Hongxing
  • Peng, Jinqing

Abstract

This research thoroughly explored the impact of archetypes and confounding factors on a proposed holistic design optimization approach for high-rise office buildings with integrated photovoltaic (PV) facades. The design optimization adopts the hybrid generalized pattern search particle swarm optimization (HGPSPSO) algorithm, which is incorporated with qualitative and quantitative sensitivity analyses for factor prioritizing and fixing. Different archetypes are modelled by changing floor plan sizes and shapes, while diverse urban contexts and internal load (heat gain) levels are investigated as major confounding factors beyond designers' control. Variation of these four simulation scenarios are then used to examine the uncertainty of sensitivity indices and optimization potential for passive architectural design parameters. The window geometry, thermal and optical properties are proved to be most important to the reference PV envelope design. The building plan shape is found to have little impact on the weighting of different design parameters, while the shape coefficient (SC) is determined to be almost linearly correlated with the HVAC (heating, ventilation and air-conditioning) demand. The office design with the highest shape coefficient can therefore achieve a net energy demand reduction up to 48.77%. The floor plan size also has minor impact on the sensitivity index for each design factor, but the energy-saving potential grows with decreasing floor sizes. On the contrary, confounding factors can greatly change the sensitivity analysis (SA) result. The window U-value becomes more important with an increasing internal load level and urban context density whereas the impact of the window light-to-solar gain ratio is reduced by peripheral shading. Furthermore, varying confounding factors can even change the dimension of optimization problems based on different factor fixing results. This research can provide early-stage design guidance for energy efficient buildings with a comprehensive analysis of pragmatic building archetypes, background contexts and operation scenarios.

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  • 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.
    • Handle: RePEc:eee:energy:v:172:y:2019:i:c:p:1-17
    DOI: 10.1016/j.energy.2019.01.112
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    3. Skandalos, Nikolaos & Karamanis, Dimitris, 2021. "An optimization approach to photovoltaic building integration towards low energy buildings in different climate zones," Applied Energy, Elsevier, vol. 295(C).
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    5. Ferahtia, Seydali & Djeroui, Ali & Rezk, Hegazy & Houari, Azeddine & Zeghlache, Samir & Machmoum, Mohamed, 2022. "Optimal control and implementation of energy management strategy for a DC microgrid," Energy, Elsevier, vol. 238(PB).
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    7. Ascione, Fabrizio & Bianco, Nicola & Maria Mauro, Gerardo & Napolitano, Davide Ferdinando, 2019. "Building envelope design: Multi-objective optimization to minimize energy consumption, global cost and thermal discomfort. Application to different Italian climatic zones," Energy, Elsevier, vol. 174(C), pages 359-374.
    8. Yorgos Spanodimitriou & Giovanni Ciampi & Michelangelo Scorpio & Niloufar Mokhtari & Ainoor Teimoorzadeh & Roberta Laffi & Sergio Sibilio, 2022. "Passive Strategies for Building Retrofitting: Performances Analysis and Incentive Policies for the Iranian Scenario," Energies, MDPI, vol. 15(5), pages 1-22, February.
    9. Yu, Guoqing & Yang, Hongxing & Luo, Daina & Cheng, Xu & Ansah, Mark Kyeredey, 2021. "A review on developments and researches of building integrated photovoltaic (BIPV) windows and shading blinds," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    10. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).
    11. Gauch, H.L. & Dunant, C.F. & Hawkins, W. & Cabrera Serrenho, A., 2023. "What really matters in multi-storey building design? A simultaneous sensitivity study of embodied carbon, construction cost, and operational energy," Applied Energy, Elsevier, vol. 333(C).
    12. Stevović, Ivan & Mirjanić, Dragoljub & Stevović, Svetlana, 2019. "Possibilities for wider investment in solar energy implementation," Energy, Elsevier, vol. 180(C), pages 495-510.
    13. Hong, Taehoon & Kim, Jimin & Lee, Minhyun, 2019. "A multi-objective optimization model for determining the building design and occupant behaviors based on energy, economic, and environmental performance," Energy, Elsevier, vol. 174(C), pages 823-834.
    14. Balali, Amirhossein & Yunusa-Kaltungo, Akilu & Edwards, Rodger, 2023. "A systematic review of passive energy consumption optimisation strategy selection for buildings through multiple criteria decision-making techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    15. Shen, Pengyuan & Wang, Huilong, 2024. "Archetype building energy modeling approaches and applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).

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