寒區(qū)農(nóng)宅供熱能耗統(tǒng)計及評價研究
發(fā)布時間：2019-05-10 02:56
【摘要】：伴隨我國建筑節(jié)能工作的深入開展和廣大村鎮(zhèn)地區(qū)的經(jīng)濟發(fā)展，村鎮(zhèn)地區(qū)住宅的節(jié)能降耗問題日益引起業(yè)界關(guān)注。寒區(qū)農(nóng)宅的供熱能耗更是占據(jù)了建筑總能耗的大部分比例，是我國建筑節(jié)能的重中之重。充分了解寒區(qū)農(nóng)宅的能耗現(xiàn)狀和影響因素，進行科學(xué)的統(tǒng)計分析和評價，是國家制定農(nóng)村建筑節(jié)能政策、制定并實施有效建筑節(jié)能技術(shù)的重要依據(jù)。 首先針對寒區(qū)農(nóng)宅建筑用能特點，建立包含家庭基本情況、建筑基本信息、建筑圍護結(jié)構(gòu)基本信息、冬季室內(nèi)環(huán)境信息、農(nóng)宅用能信息的五大塊統(tǒng)計指標體系。初步建立寒區(qū)農(nóng)宅供熱能耗數(shù)據(jù)庫。針對寒區(qū)農(nóng)宅的現(xiàn)狀，進行了全面的基本信息描述統(tǒng)計分析。深入調(diào)查分析了東北三省村鎮(zhèn)農(nóng)宅的建筑總用能、供熱商品用能和非商品用能的使用情況，得到戶年供熱總能耗若干統(tǒng)計量，并與實測數(shù)據(jù)進行對照分析。 應(yīng)用平均數(shù)差異檢驗分析的方法對寒區(qū)農(nóng)宅供熱能耗的主要影響因素進行遴選和關(guān)聯(lián)強度分析。采用獨立樣本t檢驗針對具有兩個水平的各影響因素進行分析，得到4個在0.05水平上顯著的因素。采用單因素方差分析的方法針對具有三個及以上水平的各影響因素進行分析，得到11個在0.05水平顯著的因素，并進行事后比較分析發(fā)掘各組之間深層的差異。為研究因素間交互作用的影響，以建筑供熱面積和其他各因素的交互分析為例繼續(xù)做雙因素方差分析，旨在尋找那些與供熱面積交互后對農(nóng)宅戶年供熱能耗有顯著影響的因素，在此基礎(chǔ)上做剔除供熱面積影響下的各因素單純主效應(yīng)分析。 分別采用多元線性回歸分析和邏輯斯回歸分析兩種方法，將影響村鎮(zhèn)農(nóng)宅供熱能耗的顯著因素納入回歸分析，得到適宜的多元回歸模型并加以驗證，，以期實現(xiàn)利用最少變量對農(nóng)宅供熱能耗的描述、解釋和預(yù)測。在多元線性回歸分析中，通過多個模型對比研究，最終選定了擬合優(yōu)度高、預(yù)測誤差比率低、自變量個數(shù)較少的包含交互的指數(shù)模型1，應(yīng)用此模型可以對寒區(qū)農(nóng)宅供熱能耗進行預(yù)測，得到農(nóng)宅單位度日數(shù)單位供熱面積年供熱能耗的預(yù)測值。邏輯斯回歸分析可以從另外一個角度，對寒區(qū)農(nóng)宅供熱能耗高、中、低進行分類概率預(yù)測，邏輯斯回歸分析結(jié)果對于供熱能耗評價有借鑒意義。 依據(jù)前述統(tǒng)計分析結(jié)果，主要從用戶基本信息指標、建筑圍護結(jié)構(gòu)熱工指標、供熱能源與系統(tǒng)指標、供熱環(huán)境指標和居民用熱行為指標五個方面合計20個分項指標，對寒區(qū)農(nóng)宅供熱能耗進行評價。采用層次分析法，依據(jù)統(tǒng)計分析與推斷的結(jié)果構(gòu)造比較判斷矩陣，計算確定各層級指標權(quán)重，通過指標評價值的計算可以做出寒區(qū)農(nóng)宅供熱能耗評價。
[Abstract]:With the in-depth development of building energy conservation in China and the economic development of villages and towns, the problem of energy saving and consumption reduction of residential buildings in villages and towns has attracted more and more attention of the industry. The heating energy consumption of agricultural houses in cold region accounts for most of the total building energy consumption, and it is the most important part of building energy saving in our country. It is an important basis for the state to formulate rural building energy conservation policy and to formulate and implement effective building energy saving technology to fully understand the present situation and influencing factors of energy consumption of agricultural houses in cold region and to carry out scientific statistical analysis and evaluation. Firstly, according to the characteristics of energy consumption of agricultural houses in cold region, five statistical index systems are established, which include the basic situation of family, the basic information of architecture, the basic information of building envelope, the information of indoor environment in winter and the information of energy consumption of agricultural houses. The database of heating energy consumption of agricultural houses in cold region is established. According to the present situation of rural houses in cold region, a comprehensive statistical analysis of basic information is carried out. The total building energy consumption, heating commodity energy consumption and non-commodity energy consumption of rural houses in the three provinces of Northeast China are investigated and analyzed deeply, and some statistics of total household heating energy consumption are obtained and compared with the measured data. The main influencing factors of heating energy consumption of agricultural houses in cold region are selected and analyzed by means of average difference test and analysis. The independent sample t test was used to analyze the influencing factors with two levels, and four significant factors at 0.05 level were obtained. The single factor variance analysis method was used to analyze the influencing factors with three or more levels, and 11 significant factors at 0.05 level were obtained, and the deep differences among the three groups were compared and analyzed afterwards. In order to study the influence of interaction among factors, taking the interactive analysis of building heating area and other factors as an example, the two-factor variance analysis was continued in order to find out those factors that had significant influence on the annual heating energy consumption of farm and homestead households after interacting with heating area. On this basis, the simple main effect analysis of each factor under the influence of eliminating heating area is made. By using multiple linear regression analysis and logic regression analysis, the significant factors affecting the heating energy consumption of rural houses in villages and towns are brought into the regression analysis, and the suitable multiple regression model is obtained and verified. In order to realize the description, explanation and prediction of the heating energy consumption of agricultural houses by using the minimum variables. In the multivariate linear regression analysis, through the comparative study of multiple models, the exponential model 1, which has high goodness of fit, low prediction error ratio and small number of independent variables, is selected. This model can be used to predict the heating energy consumption of agricultural houses in cold region, and the predicted value of annual heating energy consumption per unit heating area of agricultural houses can be obtained. Logic regression analysis can predict the classification probability of high, medium and low heating energy consumption in cold region from another point of view. The results of logic regression analysis can be used for reference in the evaluation of heating energy consumption. According to the above statistical analysis results, there are 20 sub-indexes from five aspects: the basic information index of users, the thermal index of building enclosure structure, the index of heating energy and system, the index of heating environment and the index of thermal behavior of residents. The energy consumption of heating in rural houses in cold region is evaluated. By using the analytic hierarchy process (AHP), the comparative judgment matrix is constructed according to the results of statistical analysis and inference, and the index weight of each level is calculated and determined. Through the calculation of the evaluation value of the index, the energy consumption evaluation of agricultural house heating in cold region can be made.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TU833
本文編號：2473292
[Abstract]:With the in-depth development of building energy conservation in China and the economic development of villages and towns, the problem of energy saving and consumption reduction of residential buildings in villages and towns has attracted more and more attention of the industry. The heating energy consumption of agricultural houses in cold region accounts for most of the total building energy consumption, and it is the most important part of building energy saving in our country. It is an important basis for the state to formulate rural building energy conservation policy and to formulate and implement effective building energy saving technology to fully understand the present situation and influencing factors of energy consumption of agricultural houses in cold region and to carry out scientific statistical analysis and evaluation. Firstly, according to the characteristics of energy consumption of agricultural houses in cold region, five statistical index systems are established, which include the basic situation of family, the basic information of architecture, the basic information of building envelope, the information of indoor environment in winter and the information of energy consumption of agricultural houses. The database of heating energy consumption of agricultural houses in cold region is established. According to the present situation of rural houses in cold region, a comprehensive statistical analysis of basic information is carried out. The total building energy consumption, heating commodity energy consumption and non-commodity energy consumption of rural houses in the three provinces of Northeast China are investigated and analyzed deeply, and some statistics of total household heating energy consumption are obtained and compared with the measured data. The main influencing factors of heating energy consumption of agricultural houses in cold region are selected and analyzed by means of average difference test and analysis. The independent sample t test was used to analyze the influencing factors with two levels, and four significant factors at 0.05 level were obtained. The single factor variance analysis method was used to analyze the influencing factors with three or more levels, and 11 significant factors at 0.05 level were obtained, and the deep differences among the three groups were compared and analyzed afterwards. In order to study the influence of interaction among factors, taking the interactive analysis of building heating area and other factors as an example, the two-factor variance analysis was continued in order to find out those factors that had significant influence on the annual heating energy consumption of farm and homestead households after interacting with heating area. On this basis, the simple main effect analysis of each factor under the influence of eliminating heating area is made. By using multiple linear regression analysis and logic regression analysis, the significant factors affecting the heating energy consumption of rural houses in villages and towns are brought into the regression analysis, and the suitable multiple regression model is obtained and verified. In order to realize the description, explanation and prediction of the heating energy consumption of agricultural houses by using the minimum variables. In the multivariate linear regression analysis, through the comparative study of multiple models, the exponential model 1, which has high goodness of fit, low prediction error ratio and small number of independent variables, is selected. This model can be used to predict the heating energy consumption of agricultural houses in cold region, and the predicted value of annual heating energy consumption per unit heating area of agricultural houses can be obtained. Logic regression analysis can predict the classification probability of high, medium and low heating energy consumption in cold region from another point of view. The results of logic regression analysis can be used for reference in the evaluation of heating energy consumption. According to the above statistical analysis results, there are 20 sub-indexes from five aspects: the basic information index of users, the thermal index of building enclosure structure, the index of heating energy and system, the index of heating environment and the index of thermal behavior of residents. The energy consumption of heating in rural houses in cold region is evaluated. By using the analytic hierarchy process (AHP), the comparative judgment matrix is constructed according to the results of statistical analysis and inference, and the index weight of each level is calculated and determined. Through the calculation of the evaluation value of the index, the energy consumption evaluation of agricultural house heating in cold region can be made.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TU833
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