夏热冬冷地区办公建筑能耗模拟与预测研究
发布时间：2018-08-17 17:01
【摘要】：公共建筑作为我国建筑的主要组成部分,其能源消耗是住宅类建筑能耗的十倍以上；而办公建筑作为公共建筑的主体部分,其建筑面积近年来也随着城市建设的快速发展而迅猛增长,同时也标志着我国经济水平迅猛发展。本研究对夏热冬冷地区的典型办公建筑的能耗情况进行了研究,得出了适用于该地区典型办公建筑能耗的预测回归方程,为典型办公建筑的能耗分析和节能设计提供了一定的参考。首先,根据相关的建筑节能设计标准,并参阅有关参考文献,建立了夏热冬冷地区典型办公建筑模型,并使用EQUEST软件对所建立的典型办公建筑模型的能耗水平进行了模拟,分析了典型办公建筑模型的合理性。其次,使用典型办公建筑模型,利用单因素敏感性法计算了各因素对空调系统能耗的敏感度。结果表明办公建筑能耗受各个因素影响的程度,由大到小分别为空调系统形式、人员密度、外窗遮阳系数、水系统是否变频、相对湿度控制范围、风机单位风量耗功率、平均窗墙比、人均新风量、水泵效率、制冷COP、夏季室内设计温度、热回收效率、冬季室内设计温度、设备功率密度、锅炉效率、照明功率密度、外墙传热系数、外窗传热系数、屋顶传热系数、太阳辐射吸收系数、建筑朝向、地面传热系数。再次,根据分析得到的能耗影响因素,设计了20因素4水平的能耗模拟正交试验方案,以最少的试验次数获得了合理的试验数据。根据正交试验方案,对于采用变风量、定风量、风机盘管加新风三种不同空调系统的办公建筑分别进行了64次模拟,得到了回归分析所需要的原始数据。最后,在大量的模拟数据基础上,应用SPSS统计软件分别对变风量、定风量、风机盘管加新风三种空调系统的能耗模拟结果进行了多元非线性预测回归分析。对各回归模型的合理性和正确性进行了理论分析,并选取了上海某办公大楼作为实测对象,对回归预测模型的可靠性进行了检验。本研究着重考虑了影响建筑能耗的20个设计参数,根据正交试验设计方案,使用EQUEST能耗模拟软件得到大量合理的模拟数据,并利用统计软件SPSS对试验数据进行了多元非线性回归分析,得到了适用于夏热冬冷地区典型办公建筑的能耗预测模型。该模型能较为准确的预测采用变风量、定风量、风机盘管加新风空调系统形式的典型办公建筑能耗,只需通过输入相关的建筑围护结构和空调系统设计参数,即可简单快速地计算出此设计参数下的典型办公建筑能耗,为建筑设计师提供了一种便捷的能耗计算和节能设计方法。
[Abstract]:As the main part of Chinese buildings, public buildings consume more than ten times as much energy as residential buildings, while office buildings are the main parts of public buildings. With the rapid development of urban construction in recent years, its building area has been growing rapidly, and it also marks the rapid development of our country's economic level. In this study, the energy consumption of typical office buildings in hot summer and cold winter area is studied, and the regression equation of energy consumption for typical office buildings in this area is obtained. It provides a certain reference for energy consumption analysis and energy saving design of typical office buildings. Firstly, according to the related building energy saving design standards and referring to the relevant references, the typical office building model in hot summer and cold winter area is established, and the energy consumption level of the typical office building model is simulated by using EQUEST software. The rationality of typical office building model is analyzed. Secondly, using the typical office building model, single factor sensitivity method is used to calculate the sensitivity of each factor to air conditioning system energy consumption. The results show that the energy consumption of office buildings is affected by various factors, from large to small air conditioning system form, personnel density, window shade coefficient, water system frequency conversion, relative humidity control range, fan unit air consumption power, Average window / wall ratio, per capita fresh air volume, pump efficiency, cooling COP, summer indoor design temperature, heat recovery efficiency, winter indoor design temperature, equipment power density, boiler efficiency, lighting power density, external wall heat transfer coefficient, external window heat transfer coefficient, Heat transfer coefficient of roof, absorption coefficient of solar radiation, building orientation, heat transfer coefficient of ground. Thirdly, according to the influence factors of energy consumption, 20 factors and 4 levels of energy consumption simulation orthogonal test scheme is designed, and reasonable test data are obtained at the least number of times. According to the orthogonal test scheme, the office buildings with variable air volume, fixed air volume, fan coil unit plus fresh air were simulated for 64 times respectively, and the original data needed for regression analysis were obtained. Finally, on the basis of a large number of simulation data, the simulation results of energy consumption of VAV, VAV, Fan-Coil Unit and fresh Air conditioning system are analyzed by using SPSS statistical software, respectively, and multivariate nonlinear predictive regression analysis is carried out for the energy consumption simulation results of three kinds of air conditioning systems. The rationality and correctness of each regression model are theoretically analyzed, and the reliability of the regression prediction model is tested by selecting a certain office building in Shanghai as the measured object. This study focuses on 20 design parameters that affect building energy consumption. According to the orthogonal design scheme, a large number of reasonable simulation data are obtained by using EQUEST energy consumption simulation software. The multivariate nonlinear regression analysis of the test data is carried out by using the statistical software SPSS, and the energy consumption prediction model suitable for typical office buildings in hot summer and cold winter area is obtained. The model can accurately predict the energy consumption of a typical office building in the form of variable air volume, constant air volume, fan coil unit plus fresh air conditioning system, and only need to input relevant building envelope structure and air conditioning system design parameters. The energy consumption of typical office buildings under this design parameter can be calculated simply and quickly, which provides a convenient energy consumption calculation and energy saving design method for architectural designers.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU111.195
本文编号：2188306
[Abstract]:As the main part of Chinese buildings, public buildings consume more than ten times as much energy as residential buildings, while office buildings are the main parts of public buildings. With the rapid development of urban construction in recent years, its building area has been growing rapidly, and it also marks the rapid development of our country's economic level. In this study, the energy consumption of typical office buildings in hot summer and cold winter area is studied, and the regression equation of energy consumption for typical office buildings in this area is obtained. It provides a certain reference for energy consumption analysis and energy saving design of typical office buildings. Firstly, according to the related building energy saving design standards and referring to the relevant references, the typical office building model in hot summer and cold winter area is established, and the energy consumption level of the typical office building model is simulated by using EQUEST software. The rationality of typical office building model is analyzed. Secondly, using the typical office building model, single factor sensitivity method is used to calculate the sensitivity of each factor to air conditioning system energy consumption. The results show that the energy consumption of office buildings is affected by various factors, from large to small air conditioning system form, personnel density, window shade coefficient, water system frequency conversion, relative humidity control range, fan unit air consumption power, Average window / wall ratio, per capita fresh air volume, pump efficiency, cooling COP, summer indoor design temperature, heat recovery efficiency, winter indoor design temperature, equipment power density, boiler efficiency, lighting power density, external wall heat transfer coefficient, external window heat transfer coefficient, Heat transfer coefficient of roof, absorption coefficient of solar radiation, building orientation, heat transfer coefficient of ground. Thirdly, according to the influence factors of energy consumption, 20 factors and 4 levels of energy consumption simulation orthogonal test scheme is designed, and reasonable test data are obtained at the least number of times. According to the orthogonal test scheme, the office buildings with variable air volume, fixed air volume, fan coil unit plus fresh air were simulated for 64 times respectively, and the original data needed for regression analysis were obtained. Finally, on the basis of a large number of simulation data, the simulation results of energy consumption of VAV, VAV, Fan-Coil Unit and fresh Air conditioning system are analyzed by using SPSS statistical software, respectively, and multivariate nonlinear predictive regression analysis is carried out for the energy consumption simulation results of three kinds of air conditioning systems. The rationality and correctness of each regression model are theoretically analyzed, and the reliability of the regression prediction model is tested by selecting a certain office building in Shanghai as the measured object. This study focuses on 20 design parameters that affect building energy consumption. According to the orthogonal design scheme, a large number of reasonable simulation data are obtained by using EQUEST energy consumption simulation software. The multivariate nonlinear regression analysis of the test data is carried out by using the statistical software SPSS, and the energy consumption prediction model suitable for typical office buildings in hot summer and cold winter area is obtained. The model can accurately predict the energy consumption of a typical office building in the form of variable air volume, constant air volume, fan coil unit plus fresh air conditioning system, and only need to input relevant building envelope structure and air conditioning system design parameters. The energy consumption of typical office buildings under this design parameter can be calculated simply and quickly, which provides a convenient energy consumption calculation and energy saving design method for architectural designers.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TU111.195
【参考文献】
相关硕士学位论文 前1条
1 陈会标;重庆市建筑节能政策研究[D];重庆大学;2012年
，本文编号：2188306
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