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Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day
The window-to-wall ratio (WWR) significantly affects the indoor thermal environment, causing changes in buildings’ energy demands. This research couples the “Envi-met” model and the “TRNSYS” model to predict the impact of the window-to-wall ratio on indoor cooling energy demands in south Hunan. With...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8393238/ https://www.ncbi.nlm.nih.gov/pubmed/34444161 http://dx.doi.org/10.3390/ijerph18168411 |
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author | Li, Jiayu Zheng, Bohong Bedra, Komi Bernard Li, Zhe Chen, Xiao |
author_facet | Li, Jiayu Zheng, Bohong Bedra, Komi Bernard Li, Zhe Chen, Xiao |
author_sort | Li, Jiayu |
collection | PubMed |
description | The window-to-wall ratio (WWR) significantly affects the indoor thermal environment, causing changes in buildings’ energy demands. This research couples the “Envi-met” model and the “TRNSYS” model to predict the impact of the window-to-wall ratio on indoor cooling energy demands in south Hunan. With the coupled model, “Envi-met + TRNSYS”, fixed meteorological parameters around the exterior walls are replaced by varied data provided by Envi-met. This makes TRNSYS predictions more accurate. Six window-to-wall ratios are considered in this research, and in each scenario, the electricity demand for cooling is predicted using “Envi-met + TRNSYS”. Based on the classification of thermal perception in south Hunan, the TRNSYS predictions of the electricity demand start with 30 °C as the threshold of refrigeration. The analytical results reveal that in a 6-storey residential building with 24 households, in order to maintain the air temperature below 30 °C, the electricity required for cooling buildings with 0% WWR, 20% WWR, 40% WWR, 60% WWR, 80% WWR, and 100% WWR are respectively 0 KW·h, 19.6 KW·h, 133.7 KW·h, 273.1 KW·h, 374.5 KW·h, and 461.9 KW·h. This method considers the influence of microclimate on the exterior wall and improves the accuracy of TRNSYS in predicting the energy demand for indoor cooling. |
format | Online Article Text |
id | pubmed-8393238 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83932382021-08-28 Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day Li, Jiayu Zheng, Bohong Bedra, Komi Bernard Li, Zhe Chen, Xiao Int J Environ Res Public Health Article The window-to-wall ratio (WWR) significantly affects the indoor thermal environment, causing changes in buildings’ energy demands. This research couples the “Envi-met” model and the “TRNSYS” model to predict the impact of the window-to-wall ratio on indoor cooling energy demands in south Hunan. With the coupled model, “Envi-met + TRNSYS”, fixed meteorological parameters around the exterior walls are replaced by varied data provided by Envi-met. This makes TRNSYS predictions more accurate. Six window-to-wall ratios are considered in this research, and in each scenario, the electricity demand for cooling is predicted using “Envi-met + TRNSYS”. Based on the classification of thermal perception in south Hunan, the TRNSYS predictions of the electricity demand start with 30 °C as the threshold of refrigeration. The analytical results reveal that in a 6-storey residential building with 24 households, in order to maintain the air temperature below 30 °C, the electricity required for cooling buildings with 0% WWR, 20% WWR, 40% WWR, 60% WWR, 80% WWR, and 100% WWR are respectively 0 KW·h, 19.6 KW·h, 133.7 KW·h, 273.1 KW·h, 374.5 KW·h, and 461.9 KW·h. This method considers the influence of microclimate on the exterior wall and improves the accuracy of TRNSYS in predicting the energy demand for indoor cooling. MDPI 2021-08-09 /pmc/articles/PMC8393238/ /pubmed/34444161 http://dx.doi.org/10.3390/ijerph18168411 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Jiayu Zheng, Bohong Bedra, Komi Bernard Li, Zhe Chen, Xiao Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title | Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title_full | Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title_fullStr | Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title_full_unstemmed | Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title_short | Evaluating the Effect of Window-to-Wall Ratios on Cooling-Energy Demand on a Typical Summer Day |
title_sort | evaluating the effect of window-to-wall ratios on cooling-energy demand on a typical summer day |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8393238/ https://www.ncbi.nlm.nih.gov/pubmed/34444161 http://dx.doi.org/10.3390/ijerph18168411 |
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