居住行为与模式:对东南地区高层住宅能耗的影响

IF 5.4 Q2 ENERGY & FUELS Smart Energy Pub Date : 2022-05-01 DOI:10.1016/j.segy.2022.100072
Wuxia Zhang , John Calautit
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引用次数: 7

摘要

随着中国城市化的快速发展,住宅建筑的能耗和相应的碳排放也在不断增加。由于居住者的行为在建筑能源性能和居住者舒适度方面起着重要作用,因此了解居住者的生活方式和能源使用之间的关键联系是关键。大多数关于使用行为与能源使用之间关系的研究都是在公共或商业建筑中进行的。由于数据难以获取,又需要现有房屋的关键信息,对高层住宅的研究受到限制。为了了解居民的热满意度、住宅设备拥有量和使用习惯以及对智能电表的态度,本文对112个生活在典型新兴城市的大都市家庭进行了全面调查。以高层住宅楼为例,利用建筑能耗仿真工具进行建模。结果将与住户或智能电表提供的实际能源账单进行比较,以更好地了解该地区的能源使用情况。调查结果显示,不同住户的能源使用情况可能存在较大差异,这受住户模式和习惯等因素的影响。与此同时,它显示了预测这种建筑的能源使用的挑战,因为不同家庭的内部热量增益、设定点和开窗行为不同。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Occupancy behaviour and patterns: Impact on energy consumption of high-rise households in southeast China

With the rapid urbanization in China, energy consumption and corresponding carbon emissions in residential buildings are growing. Because occupant behaviour plays a significant role in building energy performance and occupant comfort, understanding the crucial links between occupant lifestyles and energy use is the key. Most studies on the relationship between occupancy behaviour and energy usage have been conducted in public or commercial buildings. Because data is difficult to obtain and key information about existing houses is required, research on high rise residential buildings is limited. To acquire information on thermal satisfaction, residential equipment ownership and usage habits and attitude to smart meters, this paper conducted a comprehensive survey of 112 metropolitan families living in a typical booming city. A case study high-rise residential building is modelled in a building energy simulation tool. The results are compared with the actual energy bills acquired from occupants or smart meters to better understand the energy usage in this area. The results showed that a large variation in energy use could exist in different households, which is influenced by several factors such as occupancy patterns and habits, as observed in the survey. At the same time, it shows the challenge of predicting the energy use of such a building with varying internal heat gains, set points and window opening behaviours across the different households.

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来源期刊
Smart Energy
Smart Energy Engineering-Mechanical Engineering
CiteScore
9.20
自引率
0.00%
发文量
29
审稿时长
73 days
期刊最新文献
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