Statistics And Evaluation For Heating Energy Consumption Of Rural Residential Houses In Cold Regions

With the deepening of China’s building energy conservation work carried out andthe majority of the economic development of rural areas, rural areas of residentialenergy consumption problem caused increasing concern to the industry. Heating energyconsumption of cold area farm house is occupied most of the proportion of the totalenergy consumption of the building is the top priority of building energy efficiency.Fully understand the energy situation and influencing factors of farm house in coldregions, scientific statistical analysis and evaluation of the national rural building energypolicy formulation, development and implementation of energy-efficient buildingtechnologies important basis.First, rural farm house for building energy characteristics, the basic situation of thefamily includes the establishment, construction of basic information, basic informationon the building envelope, winter indoor environmental information, five large farmhouse with a system of statistical indicators can information. Initially establishedresidential heating in cold area of agricultural energy database. The status quo cold areafarm house, conducted a comprehensive description of the basic statistical analysis.Depth investigation and analysis of the farm house in rural northeastern provinces totalbuilding energy use, heating energy and non-commodity goods with the use of energy,get a number of statistics households total annual heating energy consumption, and werecompared with the measured data.Application Mean difference test analysis method of the main factors in cold areafarm house heating energy consumption were associated with the intensity of selectionand analysis. Using independent samples t-test analysis of each factor has two levels,get four significant at the0.05level factors. Single-factor analysis of variance methodsfor each factor has three or more levels were analyzed,11significant at the0.05levelfactors and comparative analysis of post-excavation of deep differences between thegroups. Study interactions between factors of influence, to interactively building heatingarea and other factors continue to do a case study of two-factor analysis of variance,aimed at finding those who interact with the heating area of farm house heating energyconsumption in households has significantly affected by factors, on the basis of variousfactors simply do excluded under the influence of the main effect of heating area ofanalysis.Multiple linear regression analysis were used logistic regression analysis, and thetwo methods, the significant factor affecting rural farm house heating energy into theregression analysis, multivariate regression model suitable and validated in order toachieve a minimum of variables to use for farm house describe the thermal energy, explain and predict. In multiple linear regression analysis, the study by comparingmultiple models, to determine the final selection of the equation coefficient, predictionerror rate is low, since the number of variables contained less interaction an exponentialmodel, this model can be applied to farmers in cold regions home heating energyconsumption forecast, get agricultural residential units in the area of heating degreedays heating unit energy consumption forecasts. Logistic regression analysis can befrom another angle, high cold regions farm house heating energy consumption, mediumor low probability prediction classification, logistic regression analysis to evaluate theheating energy consumption is worth learning.Based on statistical analysis of the results of the foregoing, the basic informationfrom the user’s main index, the building envelope thermal indicators, heating energy andsystem indicators, environmental indicators and residential heating with thermalbehavior of indicators in five areas total20sub-indicators of cold District heatingenergy farm house evaluation. Using AHP, according to the results of statistical analysisand inference structure comparison judgment matrix calculation to determine the weightof each level index, Evaluation by calculating the index values can make the cold zoneheating energy consumption evaluation of agricultural house.