重庆市公共建筑能耗定额方法研究
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摘要
全球气候变化是人类迄今面临的最重大环境问题，随着科学发展观在我国的深入贯彻，节约资源和保护环境成为我国的基本国策，如何加快转变城乡建设模式和建筑业发展方式，提高人民生活质量，成为一项亟待解决的问题。目前，建筑已经与工业、交通并列为能源消耗的三大领域，也是温室气体排放的重要来源。建筑领域能耗高、比重大，长期增长趋势明显，同时具备较大的节能潜力，减排成本相对较低。
为有效提高公共建筑能源利用效率，建立促进公共建筑节能的长效机制，中国政府建立了国家机关办公建筑和大型公共建筑节能监管体系。该政策体系的工作目标是逐步建立起全国联网的国家机关办公建筑和大型公共建筑能耗监测平台，对全国重点城市重点建筑能耗进行实时监测，并通过能耗统计、能源审计、用能定额和超定额加价等制度，促使国家机关办公建筑和大型公共建筑提高节能运行管理水平，培育建筑节能服务市场，为高能耗建筑的进一步节能改造准备条件。在“十一五”期间，全国共完成国家机关办公建筑和大型公共建筑能耗统计33000栋，完成能源审计4850栋，公示了近6000栋建筑的能耗状况，已对1500余栋建筑的能耗进行了动态监测。同时，北京、天津、深圳、江苏、重庆、内蒙古、上海、浙江、贵州等九个省市已开展能耗动态监测平台建设试点工作，部分省市也已出台了试运行的公共建筑用能定额。用能定额是整个公共建筑节能监管体系当中的一个重要环节，它为制定超定额加价和确定节能改造标准提供依据。但是，由于各地气候、建筑用电特点以及经济发展水平等差异，选取何种能耗定额分析方法存在较大争议，致使能耗定额政策迟迟未能得到推广。为了给住房和城乡建设部制定用能定额和超定额加价政策提供参考，本文以重庆地区为例，通过调查研究重庆市公共建筑的能耗现状和用能水平，从建筑运行阶段的负荷率变化来进行分类，探索制定了一种较为科学合理的用能定额方法。
首先，通过调研随机抽取重庆市公共建筑监测平台的207栋公共建筑的基本信息，以及它们在2012年全年各小时的用电数据。通过对用电数据进行整理，对主要存在的三种类型错误数据（突发错误、数据延迟和数据中断）进行处理，最终筛选出145栋公共建筑进行详细研究。通过对145栋公共建筑的总体用电现状进行统计分析，发现不同使用功能建筑的用电水平差异很大，相同功能的公共建筑之间年能耗的差异也很大。再分别对重庆市的政府办公建筑、商场建筑、一般办公建筑、酒店建筑这四类公共建筑的用电分布进行统计分析，得到其用电水平、电耗特征和电耗分布情况，发现建筑电耗分布规律服从对数正态分布。
而后对不同功能公共建筑的月、周用电变化进行研究。通过对样本建筑的周用电变化、月用电变化进行分析，获得不同建筑的用电特征。研究发现，总能耗的波动主要是受到空调系统用电的影响，全年月能耗有两个波峰和两个波谷。由于不同功能建筑的运行时间不同，导致各类建筑逐时负荷率存在很大差异。负荷率变化导致了用电变化。不同功能建筑的日用电变化在一定程度上表征该类建筑的用电特点。论证了从建筑运行阶段的负荷率变化出发建立公共建筑分类方法的合理性。
本文筛选了影响公共建筑用电的各主要因素，对影响因素与建筑能耗之间进行相关性分析和影响权重排序。分析发现，在α=0.01显著性水平上，单位面积的照明插座能耗、单位面积空调能耗、单位面积动力能耗和单位面积特殊系统能耗与单位面积年能耗显著性正相关；空调形式与单位面积空调能耗显著性正相关。通过实际能耗监测得到某一政府办公样本建筑2012年全年日用电能耗，从中国气象局获取2012年全年的气象数据，再通过对该建筑进行能耗模拟得到典型年全年逐日用电能耗。采用一元线性回归的方法，将典型年的日平均气温与2012年实测的日平均气温的差值设为自变量x，实际日用电能耗与模拟用电能耗的差值设为因变量y，得到室外日空气温度变化对建筑总能耗影响的一元线性回归方程式为
0.6690.0055x和室外日空气温度变化对建筑空调能耗影响的一元线性回归方程式为0.5820.00145x，且通过显著性检验，发现在置信概率为0.95的水平上，y和x显著相关。
基于上述分析，将公共建筑进行两级分类。第一级按照公共建筑的使用功能进行分类，分为了政府办公建筑、一般办公建筑、商场建筑、酒店建筑、学校类建筑、医院建筑的六类。在第一级分类的基础上，运用层次聚类分析法进行二级分类，以日负荷率变化为标准将建筑分为ABC三类，A类日总负荷率最高，其次是B类，C类日总负荷率最低。主要步骤是首先得到建筑在四季的典型日负荷率变化矩阵，再采用层次聚类方法，按照日总负荷率的高中低水平分为ABC三类。最后采用多项式拟合，得到每类建筑的典型部分负荷率曲线，得到拟合方程。并取显著性水平0.05，对拟合曲线进行显著性检验，且从R-Square都很接近于1，表示各拟合方程的拟合程度都较高。证明该分类方法科学有效。
并且运用层次聚类分析方法，对照明及插座系统和空调系统的用电使用分布特征曲线进行快速分类。根据聚类步骤之间系数变化率来判断最佳聚类个数，从大量样本建筑进行快速分类，且快速筛选并提取出用电使用率特征曲线。通过对分类结果的分析，发现该方法应用于对大量公共建筑日用电特征进行快速筛选是非常有效的。
而对于未纳入公共建筑监测平台的建筑需要通过预测其日负荷率来进行二级分类判别。因此利用时间序列ARIMA模型建立建筑用电负荷率预测模型。建筑用电负荷率受到建筑使用者行为的影响，具有随机性特点。而时间序列分析模型应用于对建筑用电负荷率的预测可将各种复杂因素的总和效应统一包含于时间序列之中。通过对建筑负荷率建立随机过程模型，并通过使用重庆市69栋政府办公建筑在2012年的用电负荷率数据进行时间序列模型的建立、识别和拟合，得到预测模型ARIMA (1,0,8)(2,1,1)，并对模型的适应性进行了验证。为了进一步验证得到的ARIMA (1,0,8)(2,1,1)的适用性，使用该模型预测两栋政府办公建筑的日用电使用率，发现预测效果与实际检测到的结果差异不大，且实际值基本都落入置信区间之内。该方法也可以推广使用到其他类型建筑的用电负荷率的预测。
最后，在探索公共建筑合理分类的基础上，分别从统计定额和技术定额两个方向制定重庆地区的公共建筑能耗定额。统计定额的服务对象是政府部门，为政府部门制定政策提供参考。技术定额主要服务对象是公共建筑管理人员以及技术人员，为下一步对建筑进行节能改造或节能运行提供参考。并且，建立待评建筑快速判断分类的方法。选取一个在线监测的政府办公建筑为案例，通过比较该建筑的统计定额值、技术定额值和实际监测总用能，检验定额的合理性和有效性。
Global climate change is becoming more and more serious environment problemall over the world. With the deepening of “scientific development” in China, savingresources and protecting environment became the basic state policy of China. There is aproblem to be solved, how to accelerate the pace of urban and rural construction and theconstruction industry, and how to improve the quality of people's life. The construction,which is also an important source of greenhouse gas emissions, have been the top threebig energy consumption as industrial, transportation. There is high energy consumption,long-term growth trend and at the same time have a large energy saving potential andrelatively low cost in the construction field.
In order to improve the public building energy efficiency, the Chinese Governmenthas established the Energy-saving regulatory system for state organ office buildings andlarge public buildings. A long-standing mechanism have been built to promote thepublic building energy efficiency. The goal of policy system is to gradually establish anationwide network of state organ office buildings and large public buildings energyconsumption monitoring platform. The platform is used to gather the monitor tonational major building energy consumption. To prompt energy conservation operationmanagement level of the state organ office buildings and large public building, thewhole country launch energy audit, energy-using quota and quota price system.Building energy efficiency service market would be cultivated, in order to retrofitenergy consumption of existing high energy-consuming buildings. During the period of"11th five-year plan", the country achieved33000buildings of public building energyconsumption statistics,4850buildings of energy audit, nearly6000of the publicbuilding energy consumption bulletin, and more than1500buildings in the dynamicmonitoring of energy consumption. At the same time,9provinces has carried out theenergy consumption dynamic monitoring platform, such as Beijing, Tianjin, Shenzhen,Jiangsu, Chongqing, Inner Mongolia, Shanghai, Zhejiang, Guizhou. Some provincesand cities have also introduced a test run of public building energy consumption quota.Energy consumption quota is the public building energy efficiency supervision system.It provide the basis for energy consumption quota price and determine the standardsprovide basis of the reform. However, due to the differences of the local climate,construction characteristics and economic development level, it is controversial which method of energy consumption quota should be selected. So energy consumption quotapolicy has failed to get promoted. To guide for Ministry of Housing and Urban-RuralDevelopment to make energy consumption quota policy and fixed-price system, throughinvestigation and study of Chongqing city public building energy consumption statusand energy levels and classified according to the building load rate of change, this paperestablished a scientific and reasonable energy consumption quota method.
First of all, through the research of public buildings in Chongqing monitoringplatform, the basic information and electricity datum in2012of207public buildingshave been collected. Through to the electricity data sorting, there are three types of errordata processing.145public buildings have been selected to study. Through the overalluse of145public buildings can present macroscopic analysis, it is found that existremarkable difference in the energy consumption. Then energy distribution of six typesof public buildings in Chongqing have been studied with significant hypothesis testing,it obey the lognormal distribution.
Then, the energy use of different functions of public buildings were studied bymonthly, weekly, daily. Based on analyzed the sample buildings, the energy usecharacteristics of different buildings have been summarized. The study found that thetotal energy consumption fluctuations are mainly due to the effects of air-conditioningsystem. The month energy consumption have two maximum and minimum values. Dueto different running time of function buildings, there were significant differences in allkinds of building hourly rate. And load rate changes led to use can change. Thedifference daily change of six types buildings energy use identify characteristics ofenergy use. It is reasonable that a public building classification method is established bythe rate change of construction operation stage.
This paper screened the various influence factors of public building energy use.The correlation relationship between all the factors and building energy consumptionhave been analysis. Then the correlation coefficient are ordered. Through the analysisfound at0.01significant level, energy consumption per unit area of lighting socket, airconditioning energy consumption, energy consumption per unit area of power per unitarea and per unit area special system energy consumption and energy consumption perunit area is in significant positive correlation; Air conditioning and air conditioningenergy consumption per unit area significantly positive correlation. Is obtained by theactual energy consumption monitoring samples of a government office building for2012daily energy consumption, in2012, the year's meteorological data was obtained from the China meteorological administration, through to the building energyconsumption simulation can get day by day throughout the year with a typical yearenergy consumption. Using monadic linear regression method, the typical years of dailyaverage temperature and average temperature difference measured,2012as theindependent variable x, the actual daily can simulate the energy consumption and canuse the energy consumption difference as the dependent variable y, and found that therewas a linear relationship between the independent variable and dependent variable x yget day outdoor air temperature changes impact on the total energy consumption of ayuan linear regression equation for day and outdoor air temperature changes impact onbuilding energy consumption of air conditioning of the unary linear regression equationfor, and by significance test, found that when the confidence probability of0.95,regression coefficient is obvious.
Based on the above analysis, public buildings are categorized according to the twolevels. The first level is classified according to the use function of public buildings,divided into the government office buildings, office buildings, shopping mall, hotel,school construction, hospital buildings of six categories. Based on the first levelclassification, the second level, on the basis of using the hierarchical clustering analysismethod, is classified by r day load rate changes. The second level divided buildings intoABC three categories. The total load rate of Cass A is highest, followed by the class B,the minimum load rate is class C. Before clustering analysis, it is need to get the typicaldaily load rate curve of architecture in the four seasons firstly. By hierarchicalclustering method, the "typical day" partial load curve, according to the overall load rate,is divided into ABC three categories. By using polynomial fitting, respectively to fit thecurve of each type of construction of several typical load rate synthesis of a benchmarkpart load rate curve, fitting equation is obtained. And take the significance level of0.05,significance test was carried out on the fitting curve, and from the R-Square are veryclose to1, said the fitting equation of fitting degree is higher. Prove that theclassification method is scientific and effective.
The hierarchical cluster analysis method is used for the rapidly classification ofenergy consumption curves of lighting and power system and air-conditioning system.According to the rate of clustering coefficient, the best clustering number can bedetermined. It make it possible to quickly classify a large number of buildings andextract the characteristic curves of every categories. Observed the classification results,this method is very effective to rapid classify the electrical characteristics of public buildings.
In order to judge the secondary classification of public buildings which are notbeing dynamic monitoring, it need to forecast the daily load rate of buildings. SoARIMA model can be used to predict building electricity load rate. Building electricityload rate is random and complex which affected by the building user behavior. Andtime series analysis model can be applied to forecast for building electricity load rate byconsider all kinds of complicated factors. Established the random process model ofbuilding load rate, the forecasting model ARIMA(1,0,8)(1,1,2) is obtained by using theelectricity load datum of69government office buildings in Chong Qing in2012. Andthe adaptability of the model is verified. To further verify the applicability ofARIMA(1,0,8)(1,1,2), the model was used to predict daily electricity load rate of twogovernment office buildings. The result indicated that the difference between predictionresults and actual results is not big, and the actual results basically fall into theconfidence interval. This method can be used to predict the electricity load rate of othertypes of public buildings.
Finally, exploring the public building, on the basis of reasonable classification, thepublic building energy consumption quota of Chongqing have been establishedrespectively from the statistical quota and technical norm two direction. Statistical quotaservice object is the government department, provide reference for governmentdepartments to formulate policies. Technology norm main service object is the publicbuilding management personnel and technical personnel, for the next step of buildingenergy saving renovation or energy-saving operation to provide the reference. Andestablished for evaluation of the building to quickly determine classification method.Select a case of the on-line monitoring of government office buildings, by comparingthe statistical quota value of the building, technical quota can always use value and theactual monitoring, the rationality and validity of the inspection norm.
为有效提高公共建筑能源利用效率，建立促进公共建筑节能的长效机制，中国政府建立了国家机关办公建筑和大型公共建筑节能监管体系。该政策体系的工作目标是逐步建立起全国联网的国家机关办公建筑和大型公共建筑能耗监测平台，对全国重点城市重点建筑能耗进行实时监测，并通过能耗统计、能源审计、用能定额和超定额加价等制度，促使国家机关办公建筑和大型公共建筑提高节能运行管理水平，培育建筑节能服务市场，为高能耗建筑的进一步节能改造准备条件。在“十一五”期间，全国共完成国家机关办公建筑和大型公共建筑能耗统计33000栋，完成能源审计4850栋，公示了近6000栋建筑的能耗状况，已对1500余栋建筑的能耗进行了动态监测。同时，北京、天津、深圳、江苏、重庆、内蒙古、上海、浙江、贵州等九个省市已开展能耗动态监测平台建设试点工作，部分省市也已出台了试运行的公共建筑用能定额。用能定额是整个公共建筑节能监管体系当中的一个重要环节，它为制定超定额加价和确定节能改造标准提供依据。但是，由于各地气候、建筑用电特点以及经济发展水平等差异，选取何种能耗定额分析方法存在较大争议，致使能耗定额政策迟迟未能得到推广。为了给住房和城乡建设部制定用能定额和超定额加价政策提供参考，本文以重庆地区为例，通过调查研究重庆市公共建筑的能耗现状和用能水平，从建筑运行阶段的负荷率变化来进行分类，探索制定了一种较为科学合理的用能定额方法。
首先，通过调研随机抽取重庆市公共建筑监测平台的207栋公共建筑的基本信息，以及它们在2012年全年各小时的用电数据。通过对用电数据进行整理，对主要存在的三种类型错误数据（突发错误、数据延迟和数据中断）进行处理，最终筛选出145栋公共建筑进行详细研究。通过对145栋公共建筑的总体用电现状进行统计分析，发现不同使用功能建筑的用电水平差异很大，相同功能的公共建筑之间年能耗的差异也很大。再分别对重庆市的政府办公建筑、商场建筑、一般办公建筑、酒店建筑这四类公共建筑的用电分布进行统计分析，得到其用电水平、电耗特征和电耗分布情况，发现建筑电耗分布规律服从对数正态分布。
而后对不同功能公共建筑的月、周用电变化进行研究。通过对样本建筑的周用电变化、月用电变化进行分析，获得不同建筑的用电特征。研究发现，总能耗的波动主要是受到空调系统用电的影响，全年月能耗有两个波峰和两个波谷。由于不同功能建筑的运行时间不同，导致各类建筑逐时负荷率存在很大差异。负荷率变化导致了用电变化。不同功能建筑的日用电变化在一定程度上表征该类建筑的用电特点。论证了从建筑运行阶段的负荷率变化出发建立公共建筑分类方法的合理性。
本文筛选了影响公共建筑用电的各主要因素，对影响因素与建筑能耗之间进行相关性分析和影响权重排序。分析发现，在α=0.01显著性水平上，单位面积的照明插座能耗、单位面积空调能耗、单位面积动力能耗和单位面积特殊系统能耗与单位面积年能耗显著性正相关；空调形式与单位面积空调能耗显著性正相关。通过实际能耗监测得到某一政府办公样本建筑2012年全年日用电能耗，从中国气象局获取2012年全年的气象数据，再通过对该建筑进行能耗模拟得到典型年全年逐日用电能耗。采用一元线性回归的方法，将典型年的日平均气温与2012年实测的日平均气温的差值设为自变量x，实际日用电能耗与模拟用电能耗的差值设为因变量y，得到室外日空气温度变化对建筑总能耗影响的一元线性回归方程式为
0.6690.0055x和室外日空气温度变化对建筑空调能耗影响的一元线性回归方程式为0.5820.00145x，且通过显著性检验，发现在置信概率为0.95的水平上，y和x显著相关。
基于上述分析，将公共建筑进行两级分类。第一级按照公共建筑的使用功能进行分类，分为了政府办公建筑、一般办公建筑、商场建筑、酒店建筑、学校类建筑、医院建筑的六类。在第一级分类的基础上，运用层次聚类分析法进行二级分类，以日负荷率变化为标准将建筑分为ABC三类，A类日总负荷率最高，其次是B类，C类日总负荷率最低。主要步骤是首先得到建筑在四季的典型日负荷率变化矩阵，再采用层次聚类方法，按照日总负荷率的高中低水平分为ABC三类。最后采用多项式拟合，得到每类建筑的典型部分负荷率曲线，得到拟合方程。并取显著性水平0.05，对拟合曲线进行显著性检验，且从R-Square都很接近于1，表示各拟合方程的拟合程度都较高。证明该分类方法科学有效。
并且运用层次聚类分析方法，对照明及插座系统和空调系统的用电使用分布特征曲线进行快速分类。根据聚类步骤之间系数变化率来判断最佳聚类个数，从大量样本建筑进行快速分类，且快速筛选并提取出用电使用率特征曲线。通过对分类结果的分析，发现该方法应用于对大量公共建筑日用电特征进行快速筛选是非常有效的。
而对于未纳入公共建筑监测平台的建筑需要通过预测其日负荷率来进行二级分类判别。因此利用时间序列ARIMA模型建立建筑用电负荷率预测模型。建筑用电负荷率受到建筑使用者行为的影响，具有随机性特点。而时间序列分析模型应用于对建筑用电负荷率的预测可将各种复杂因素的总和效应统一包含于时间序列之中。通过对建筑负荷率建立随机过程模型，并通过使用重庆市69栋政府办公建筑在2012年的用电负荷率数据进行时间序列模型的建立、识别和拟合，得到预测模型ARIMA (1,0,8)(2,1,1)，并对模型的适应性进行了验证。为了进一步验证得到的ARIMA (1,0,8)(2,1,1)的适用性，使用该模型预测两栋政府办公建筑的日用电使用率，发现预测效果与实际检测到的结果差异不大，且实际值基本都落入置信区间之内。该方法也可以推广使用到其他类型建筑的用电负荷率的预测。
最后，在探索公共建筑合理分类的基础上，分别从统计定额和技术定额两个方向制定重庆地区的公共建筑能耗定额。统计定额的服务对象是政府部门，为政府部门制定政策提供参考。技术定额主要服务对象是公共建筑管理人员以及技术人员，为下一步对建筑进行节能改造或节能运行提供参考。并且，建立待评建筑快速判断分类的方法。选取一个在线监测的政府办公建筑为案例，通过比较该建筑的统计定额值、技术定额值和实际监测总用能，检验定额的合理性和有效性。
Global climate change is becoming more and more serious environment problemall over the world. With the deepening of “scientific development” in China, savingresources and protecting environment became the basic state policy of China. There is aproblem to be solved, how to accelerate the pace of urban and rural construction and theconstruction industry, and how to improve the quality of people's life. The construction,which is also an important source of greenhouse gas emissions, have been the top threebig energy consumption as industrial, transportation. There is high energy consumption,long-term growth trend and at the same time have a large energy saving potential andrelatively low cost in the construction field.
In order to improve the public building energy efficiency, the Chinese Governmenthas established the Energy-saving regulatory system for state organ office buildings andlarge public buildings. A long-standing mechanism have been built to promote thepublic building energy efficiency. The goal of policy system is to gradually establish anationwide network of state organ office buildings and large public buildings energyconsumption monitoring platform. The platform is used to gather the monitor tonational major building energy consumption. To prompt energy conservation operationmanagement level of the state organ office buildings and large public building, thewhole country launch energy audit, energy-using quota and quota price system.Building energy efficiency service market would be cultivated, in order to retrofitenergy consumption of existing high energy-consuming buildings. During the period of"11th five-year plan", the country achieved33000buildings of public building energyconsumption statistics,4850buildings of energy audit, nearly6000of the publicbuilding energy consumption bulletin, and more than1500buildings in the dynamicmonitoring of energy consumption. At the same time,9provinces has carried out theenergy consumption dynamic monitoring platform, such as Beijing, Tianjin, Shenzhen,Jiangsu, Chongqing, Inner Mongolia, Shanghai, Zhejiang, Guizhou. Some provincesand cities have also introduced a test run of public building energy consumption quota.Energy consumption quota is the public building energy efficiency supervision system.It provide the basis for energy consumption quota price and determine the standardsprovide basis of the reform. However, due to the differences of the local climate,construction characteristics and economic development level, it is controversial which method of energy consumption quota should be selected. So energy consumption quotapolicy has failed to get promoted. To guide for Ministry of Housing and Urban-RuralDevelopment to make energy consumption quota policy and fixed-price system, throughinvestigation and study of Chongqing city public building energy consumption statusand energy levels and classified according to the building load rate of change, this paperestablished a scientific and reasonable energy consumption quota method.
First of all, through the research of public buildings in Chongqing monitoringplatform, the basic information and electricity datum in2012of207public buildingshave been collected. Through to the electricity data sorting, there are three types of errordata processing.145public buildings have been selected to study. Through the overalluse of145public buildings can present macroscopic analysis, it is found that existremarkable difference in the energy consumption. Then energy distribution of six typesof public buildings in Chongqing have been studied with significant hypothesis testing,it obey the lognormal distribution.
Then, the energy use of different functions of public buildings were studied bymonthly, weekly, daily. Based on analyzed the sample buildings, the energy usecharacteristics of different buildings have been summarized. The study found that thetotal energy consumption fluctuations are mainly due to the effects of air-conditioningsystem. The month energy consumption have two maximum and minimum values. Dueto different running time of function buildings, there were significant differences in allkinds of building hourly rate. And load rate changes led to use can change. Thedifference daily change of six types buildings energy use identify characteristics ofenergy use. It is reasonable that a public building classification method is established bythe rate change of construction operation stage.
This paper screened the various influence factors of public building energy use.The correlation relationship between all the factors and building energy consumptionhave been analysis. Then the correlation coefficient are ordered. Through the analysisfound at0.01significant level, energy consumption per unit area of lighting socket, airconditioning energy consumption, energy consumption per unit area of power per unitarea and per unit area special system energy consumption and energy consumption perunit area is in significant positive correlation; Air conditioning and air conditioningenergy consumption per unit area significantly positive correlation. Is obtained by theactual energy consumption monitoring samples of a government office building for2012daily energy consumption, in2012, the year's meteorological data was obtained from the China meteorological administration, through to the building energyconsumption simulation can get day by day throughout the year with a typical yearenergy consumption. Using monadic linear regression method, the typical years of dailyaverage temperature and average temperature difference measured,2012as theindependent variable x, the actual daily can simulate the energy consumption and canuse the energy consumption difference as the dependent variable y, and found that therewas a linear relationship between the independent variable and dependent variable x yget day outdoor air temperature changes impact on the total energy consumption of ayuan linear regression equation for day and outdoor air temperature changes impact onbuilding energy consumption of air conditioning of the unary linear regression equationfor, and by significance test, found that when the confidence probability of0.95,regression coefficient is obvious.
Based on the above analysis, public buildings are categorized according to the twolevels. The first level is classified according to the use function of public buildings,divided into the government office buildings, office buildings, shopping mall, hotel,school construction, hospital buildings of six categories. Based on the first levelclassification, the second level, on the basis of using the hierarchical clustering analysismethod, is classified by r day load rate changes. The second level divided buildings intoABC three categories. The total load rate of Cass A is highest, followed by the class B,the minimum load rate is class C. Before clustering analysis, it is need to get the typicaldaily load rate curve of architecture in the four seasons firstly. By hierarchicalclustering method, the "typical day" partial load curve, according to the overall load rate,is divided into ABC three categories. By using polynomial fitting, respectively to fit thecurve of each type of construction of several typical load rate synthesis of a benchmarkpart load rate curve, fitting equation is obtained. And take the significance level of0.05,significance test was carried out on the fitting curve, and from the R-Square are veryclose to1, said the fitting equation of fitting degree is higher. Prove that theclassification method is scientific and effective.
The hierarchical cluster analysis method is used for the rapidly classification ofenergy consumption curves of lighting and power system and air-conditioning system.According to the rate of clustering coefficient, the best clustering number can bedetermined. It make it possible to quickly classify a large number of buildings andextract the characteristic curves of every categories. Observed the classification results,this method is very effective to rapid classify the electrical characteristics of public buildings.
In order to judge the secondary classification of public buildings which are notbeing dynamic monitoring, it need to forecast the daily load rate of buildings. SoARIMA model can be used to predict building electricity load rate. Building electricityload rate is random and complex which affected by the building user behavior. Andtime series analysis model can be applied to forecast for building electricity load rate byconsider all kinds of complicated factors. Established the random process model ofbuilding load rate, the forecasting model ARIMA(1,0,8)(1,1,2) is obtained by using theelectricity load datum of69government office buildings in Chong Qing in2012. Andthe adaptability of the model is verified. To further verify the applicability ofARIMA(1,0,8)(1,1,2), the model was used to predict daily electricity load rate of twogovernment office buildings. The result indicated that the difference between predictionresults and actual results is not big, and the actual results basically fall into theconfidence interval. This method can be used to predict the electricity load rate of othertypes of public buildings.
Finally, exploring the public building, on the basis of reasonable classification, thepublic building energy consumption quota of Chongqing have been establishedrespectively from the statistical quota and technical norm two direction. Statistical quotaservice object is the government department, provide reference for governmentdepartments to formulate policies. Technology norm main service object is the publicbuilding management personnel and technical personnel, for the next step of buildingenergy saving renovation or energy-saving operation to provide the reference. Andestablished for evaluation of the building to quickly determine classification method.Select a case of the on-line monitoring of government office buildings, by comparingthe statistical quota value of the building, technical quota can always use value and theactual monitoring, the rationality and validity of the inspection norm.
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