Unlock city-scale energy saving and peak load shaving potential of green roofs by GIS-informed urban building energy modelling

被引:12
|
作者
Wang, Meng [1 ]
Yu, Hang [1 ]
Liu, Yupeng [2 ,3 ]
Lin, Jianyi [2 ,4 ]
Zhong, Xianzhun [1 ]
Tang, Yin [1 ]
Guo, Haijin [1 ]
Jing, Rui [5 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai, Peoples R China
[2] Chinese Acad Sci, Inst Urban Environm, Key Lab Urban Environm & Hlth, Xiamen, Fujian, Peoples R China
[3] Xiamen Key Lab Smart Management Urban Environm, Xiamen, Fujian, Peoples R China
[4] Xiamen Key Lab Urban Metab, Xiamen, Fujian, Peoples R China
[5] Xiamen Univ, Coll Energy, Xiamen, Peoples R China
基金
中国国家自然科学基金;
关键词
GIS; City-scale energy demands; Prototype buildings; City-scale energy savings; City-scale peak load shaving; CHINA;
D O I
10.1016/j.apenergy.2024.123315
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Urban green roofs have emerged as a significant trend in urban architecture worldwide, offering numerous benefits, including enhanced energy performance, improved urban microclimate, and public health. This study proposes a holistic framework for assessing the green roofs' energy-saving potential at the city scale, achieved by scaling up building-scale energy simulations to city-scale energy demands. Firstly, massive building information is collected using Geometric Information System (GIS) technologies. Subsequently, prototype buildings are generated to accurately represent the geometric characteristics of buildings at the city scale. Building performance simulation is further conducted considering three types of plants on roofs. A case study in Xiamen, China, demonstrates the effectiveness of the proposed framework to efficiently quantify the city-scale energy-saving potential of green roofs. By implementing green roofs in Xiamen, energy savings of 1.62-1.83% and peak load shaving of 1.10-1.63% can be achieved for the whole city. Overall, the proposed framework has the potential for widespread application in other cities with minor adjustments to accommodate variations in climate and building parameters.
引用
收藏
页数:15
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