【作者】 谢艳群；

【导师】 李念平；

【作者基本信息】 湖南大学 ， 供热、供燃气、通风及空调工程， 2007， 硕士

【摘要】 随着经济的增长,人们生活水平的不断提高,人们对舒适健康建筑环境的要求日益迫切,从而导致建筑能耗的增长,建筑能耗的统计和节能工作引起业内人士的广泛关注。住宅建筑是建筑的一个重要组成部分,它和商业建筑同属于民用建筑。与商业建筑相比,住宅建筑虽然功能单一,但更受室内居住人员行为的影响,因此具有更大的不确定性,详细计算的工作量和难度都很大,而实际调查则是一种比较直接、相对简单、比较可靠的方法。因此本文采用调查实测的方法对长沙市住宅建筑能耗进行研究。为了掌握长沙市住宅建筑能源消耗现状及其影响因素,本文于2005年11月至2006年10月对长沙市70户住宅进行了相关的问卷调查和为期一年的逐月用电量和用气量的收集,并于2006年12月至2007年9月对两典型住户冬、夏季的各终端能耗进行了调查实测。在此数据基础上利用应用统计软件SPSS中的偏相关分析和多元线性回归分析对长沙市住宅总能耗(包括用电量和用气量)和单位面积能耗的影响因素进行了分析。通过问卷调查,了解到长沙市住宅室内环境及家庭能源消耗情况。统计分析结果表明:长沙市住宅户均能耗量具有明显的季节性,不同住户由于住宅围护结构、生活方式、年收入、能源消耗观念等的不同存在很大的差异。通过对两典型住户的冬、夏季能耗进行逐时实测,将总能耗分解为照明、采暖空调、炊事热水、其他用电器四项终端能耗,进一步了解住宅能耗的比例分布。实测结果表明,不管是冬季还是夏季,采暖空调能耗和炊事热水能耗是住宅能耗的主要部分,特别是采暖空调能耗具有明显的季节性,这与住宅能耗随季节变化的统计结果相符合。在进行问卷调查和逐月能耗数据采集的基础上,采用应用统计软件SPSS对长沙市住宅能耗的影响因素进行了偏相关分析和多元线性回归分析。偏相关分析表明,年总能耗、单位面积能耗与家庭年收入、采暖形式显著相关,与家庭人口数、建筑面积、降温形式、建筑朝向、住户所在楼层和建筑总层数不显著相关。多元线性回归分析得出了影响总能耗和单位面积能耗因素的回归模型。最后在调查实测与统计分析的基础上,本文从减少围护结构传热、改变降温采暖方式、改变居民的生活方式方面提出一些住宅建筑节能措施。更多还原

【Abstract】 With increasing of economy and improving of standard of living, people’s demand to comfortable and healthy building environment is more and more urgent, and then it leads to sharp increase of building energy consumption. Professional men focus on the job of building energy consumption statistics and energy efficiency. Residential building is an important component of building, which belongs to civil architecture with public building. Compare to public building, although the function is unitary, residential building profoundly influenced by the action of residenter and takes on randomicity, so it’s hard to calculate detailed and field investigates is a relatively direct, simple and reliable method. So this paper study energy consumption of residential building in Changsha by investigation and filed measure. To find out the situation and influence factors of energy consumption of residential building in Changsha, this paper had selected 70 representative urban households in Changsha city and carried out a questionnaire survey on indoor thermal environment and energy consumption from November 2005 to October 2006. At the meantime, the monthly energy consumption quantity (including electricity and gas) of households had been tracked for one year. Two representative households were selected and the total energy consumption and various terminal energy consumptions were measured in the field from December 2006 to September 2007. Using partial correlations and multi linear regression analysis in SPSS (Statistical Package for the Social Sciences) software, this paper analyzed the influencing factors of energy consumption of residential building.By the questionnaire survey, it finds out the situation of indoor thermal comfort environment and domestic energy consumption. The results show monthly mean energy consumption quantity in Changsha revealed seasonal observed variations and there were difference among different households for different outer envelope, life style, annual income and the concept of energy consumption.The total energy consumption was divided into four terminal consumption including lighting, heating and air conditioning, cooking and heating water, and other electrical appliances, the result of field measure of the two representative households reveal that the heating and air conditioning, cooking and heating water were principal in winter and summe. Especially, heating and air conditioning show seasonal observed variations, it consistent with the result of the questionnaire survey.Using partial correlations and multi linear regression analysis in SPSS software, this paper analyzed the influencing factors of energy consumption of residential building base on the result of questionnaire and monthly energy consumption quantity. Partial correlations analysis reveals that the closest correlation between energy consumption and annual income, the style of heating, and it also reveals the nonsignificant correlation between energy consumption and domestic population, floor area, the style of air conditioning, building orientation, building total storey and households’storey. Through multi linear regression, the regression equation models of influence factors on residential building total energy consumption and unit area energy consumption were founded.Finally, basing on the result of field measure and statistical analysis, this paper probes the methods and approaches that can improve the indoor thermal environment and meet the requirement of building energy efficiency from the aspects of reducing energy loss of the building, changing the style of cooling and heating and changing occupants’life style.更多还原