Issue |
E3S Web of Conf.
Volume 396, 2023
The 11th International Conference on Indoor Air Quality, Ventilation & Energy Conservation in Buildings (IAQVEC2023)
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Article Number | 05010 | |
Number of page(s) | 8 | |
Section | Outdoor Thermal Environments and Impacts of Heat Island Phenomena | |
DOI | https://doi.org/10.1051/e3sconf/202339605010 | |
Published online | 16 June 2023 |
Effect of existing residential renovation strategies on heating and cooling load in Shanghai
1 School of Design, Shanghai Jiao Tong University, 200240 Shanghai, China
2 Shanghai Municipal Housing and Urban-Rural Construction Administration Commission, 200011 Shanghai, China
* Corresponding author: zhanghuibo@sjtu.edu.cn
To provide a reference for the renovation of Shanghai’s existing residential districts, this study quantifies and compares the relationships between common renovation strategies, microclimate, heating and cooling loads. These common strategies include improving the greening rate (G), improving the reflectivity of pavement (P), improving the reflectivity of wall materials (W), and improving the reflectivity of roof materials or applying green roof (R). These strategies are applied to a typical model extracted from existing residential areas in Shanghai, China. ENVI-met and EnergyPlus are combined to simulate the microclimate represented by the average meteorological parameters in front of building surfaces and the building heating and cooling load on a typical meteorological day in winter and summer. The results show that applying microclimate data around target building contributes to a significant difference in air conditioning load in both summer and winter. For summer, G, W, and R reduced their total cooling load, whereas P increased this parameter. R contributed the most significant decrease in the total cooling load, followed by W, and G contributed the least. G3P1W3R3 and G1P3W1R1 were the scenarios with the lowest and highest cooling load. The total cooling load under G3P1W3R3 was 136 kWh (12.7%) less than that under G1P3W1R1. For winter, P and applying green roof (R4) reduced the heating load of the target building, whereas G, W and improving roof reflectivity (R2, R3) increased it. G1P3W1R4 and G3P1W3R3 were the scenarios with the lowest and highest heating load. The heating load under G1P3W1R4 was 145 kWh (14.5%) less than that under G3P1W3R3.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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