Establishing energy consumption quota for residential buildings using regression analysis and energy simulation

被引:0
作者
Zhou Z. [1 ]
Zhou L. [1 ]
Zhu C. [1 ]
Ebert A. [2 ]
机构
[1] Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming
[2] Armstrong Fluid Technology, 23 Bertrand Avenue, Toronto
关键词
Annual energy consumption quota; Building energy efficiency; Residential buildings;
D O I
10.25103/jestr.096.14
中图分类号
学科分类号
摘要
The regulation of the design and construction of new buildings is insufficient; controlling the energy consumption of buildings in the service stage is the key to realizing the goal of energy saving of buildings by tiered pricing for electricity consumption based on quota. Fifty families in Kunming, China were investigated through questionnaire survey and spot test; regression analysis and energy simulation were conducted to obtain the annual energy consumption of a nuclear family. The quota was finally established based on the correction of the two results according to the actual situation; annual energy consumption per capita was used as the unit, which was more reasonable than the annual energy consumption per floor area that was used by numerous scholars. The study demonstrates that the annual per capita energy consumption is significantly related with per capita floor area and annual per capita income. With the popularity of solar hot water system, natural ventilation is the main way for cooling in summer and the requirement of indoor comfort cannot be met during winter in residential buildings in Kunming. Thus, the value of energy simulation is higher than that of regression analysis. Finally, the corrected value of energy simulation was determined to be the final quota, which was 7.7% lower than the value of regression analysis, to meet the requirements of energy efficiency and indoor comfort. To sum up, both the value of regression analysis and the adjusted value of energy simulation could be determined as the quota. The study has a reference value to the prediction of the energy consumption of buildings, which also offers a guideline for the local government to establish relevant policies. © 2016 Eastern Macedonia and Thrace Institute of Technology. All rights reserved.
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页码:103 / 107
页数:4
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