居民生活用电特征与影响机理

Characteristics and Impact Mechanism of Residential Electricity Consumption

近年来我国居民家庭生活中碳排放量增长迅速,其中电力消费增长是导致家庭碳排放增加的重要原因。本文利用上海市居民生活碳消费调查的居住用电数据,分析了上海市常住居民家庭用电的特征和影响机理。回归模型显示上海居民生活用电受到人口规模、收入水平、居住面积、低碳态度和用能习惯的显著影响,且不同用电量家庭的用电影响因素种类和作用效果都不同:低用电家庭的生活用电受人口规模、低碳态度和用能行为的影响,中等用电家庭生活用电的显著影响因素为人口规模、收入水平、低碳态度和用能行为,高用电家庭的生活用电受到人口规模、用能习惯和居住面积的影响;并且随着用电分布从低向高移动,各影响因素的作用效果或增高或降低,呈现不同的变化趋势。

The electricity consumption plays a vital role in the rapid growth of residential carbon emissions recently in China. Based on data from 2013 Carbon Consumption Survey in Shanghai, this paper analyzes the characteristics and impact mechanism of residential electricity consumption in Shanghai. The results show that the average annual electricity use per household is 2184. 6 kWh with a standard deviation of 1398.5 kWh, and Gini Coefficient is O. 32. Power consumed during summer and winter is more and has a higher dispersion than that in spring and autumn. Besides, this paper analyzes determinants of residential electricity use and applies quantile regression to examine effects of impact factors on power consumption at different levels. The results show that household sizes, dwelling sizes, incomes, environmental attitudes and behaviors all have significant impacts on household electricity consumption in Shanghai. We also find households with varying levels of energy use have different impact factors. Meanwhile, the effects of these impact factors vary when the electricity consumption moves from low to the high end of the spectrum. Our analysis based on quantile regression provides more information and help to further understand impact factors of residential electricity consumption for different families, which helps policymakers and researchers identify potential energy conservation opportunities.