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Performance-rating-based approach to formulate a new envelope index for commercial buildings in perspective of energy efficiency and thermal comfort

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  • Hwang, Ruey-Lung
  • Shih, Wen-Mei
  • Huang, Kuo-Tsang

Abstract

Taiwan's building envelope thermal performance assessment method (ENVLOAD) was implemented in 1995. The lack of regard for thermal comfort in ENVLOAD has caused ENVLOAD certified buildings to have indoor areas that cause thermal discomfort, which leads to an increase in the energy end-use of the building during actual operation stage. This study aims to develop a new building envelop energy performance index by simultaneously analyzing the influence of energy consumption and thermal comfort. Latin hypercube sampling method is adopted to generate various building envelope samples for building energy simulation to construct the evaluation equations. By comparing to each sample’s annual sensible cooling energy against its own baseline case, indices of performance ratings (PR) based on the dry-bulb temperature and the operative temperature control are proposed. Another aim is to establish an algorithm to convert the proposed index to the previous ENVLOAD benchmark so that the new index can be directly applied to the existing building energy conservation regulations. The study found that the standard regression coefficient of the glazing's thermal insulation property rises from 0.11 to 0.20 when the control scheme switches from dry-bulb control to operative temperature control. Suggesting that the thermal performance requirements for the openings of building envelopes are more important for the new index based on thermal comfort, and that designers need to pay more attention to the control of indoor solar radiation heat gain.

Suggested Citation

  • Hwang, Ruey-Lung & Shih, Wen-Mei & Huang, Kuo-Tsang, 2020. "Performance-rating-based approach to formulate a new envelope index for commercial buildings in perspective of energy efficiency and thermal comfort," Applied Energy, Elsevier, vol. 264(C).
    • Handle: RePEc:eee:appene:v:264:y:2020:i:c:s0306261920302373
    DOI: 10.1016/j.apenergy.2020.114725
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    References listed on IDEAS

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    1. Mao, Ning & Hao, Jingyu & He, Tianbiao & Song, Mengjie & Xu, Yingjie & Deng, Shiming, 2019. "PMV-based dynamic optimization of energy consumption for a residential task/ambient air conditioning system in different climate zones," Renewable Energy, Elsevier, vol. 142(C), pages 41-54.
    2. Mao, Ning & Song, Mengjie & Deng, Shiming, 2016. "Application of TOPSIS method in evaluating the effects of supply vane angle of a task/ambient air conditioning system on energy utilization and thermal comfort," Applied Energy, Elsevier, vol. 180(C), pages 536-545.
    3. Hwang, Ruey-Lung & Shih, Wen-Mei & Lin, Tzu-Ping & Huang, Kuo-Tsang, 2018. "Simplification and adjustment of the energy consumption indices of office building envelopes in response to climate change," Applied Energy, Elsevier, vol. 230(C), pages 460-470.
    4. Mao, Ning & Pan, Dongmei & Li, Zhao & Xu, Yingjie & Song, Mengjie & Deng, Shiming, 2017. "A numerical study on influences of building envelope heat gain on operating performances of a bed-based task/ambient air conditioning (TAC) system in energy saving and thermal comfort," Applied Energy, Elsevier, vol. 192(C), pages 213-221.
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    Cited by:

    1. Nishant Raj Kapoor & Ashok Kumar & Tabish Alam & Anuj Kumar & Kishor S. Kulkarni & Paolo Blecich, 2021. "A Review on Indoor Environment Quality of Indian School Classrooms," Sustainability, MDPI, vol. 13(21), pages 1-43, October.
    2. Reindl, K. & Palm, J., 2021. "Installing PV: Barriers and enablers experienced by non-residential property owners," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    3. Martínez-de-Alegría, Itziar & Río, Rosa-María & Zarrabeitia, Enara & Álvarez, Izaskun, 2021. "Heating demand as an energy performance indicator: A case study of buildings built under the passive house standard in Spain," Energy Policy, Elsevier, vol. 159(C).
    4. Wu, Xianguo & Feng, Zongbao & Chen, Hongyu & Qin, Yawei & Zheng, Shiyi & Wang, Lei & Liu, Yang & Skibniewski, Miroslaw J., 2022. "Intelligent optimization framework of near zero energy consumption building performance based on a hybrid machine learning algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    5. Yuang Guo & Dewancker Bart, 2020. "Optimization of Design Parameters for Office Buildings with Climatic Adaptability Based on Energy Demand and Thermal Comfort," Sustainability, MDPI, vol. 12(9), pages 1-23, April.

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