Characteristics,Trends And Empirical Studies On Energy Consumption Of Public Buildings Under Structural Reform

The acceleration of urbanization and the rapid economic development have brought about environmental problems with high energy consumption,high emissions,and high pollution.As a key field of energy consumption,the construction field has a rapid increase in energy consumption,so the task of building energy conservation is very difficult.The energy consumption part of public buildings accounts for a large proportion of the total building energy consumption,and its energy-saving potential needs to be further explored.Therefore,this article discusses and studies the characteristics,trends,and empirical studies of public building energy consumption to achieve the goal of dual control of total building energy intensity.So far,there have been a lot of literature and reports on the research of energy consumption in public buildings.Researches can be roughly divided into two categories,one is a top-down research method analyzing from a macro perspective,and the other is a bottom-up method analyzing from a micro perspective.In response to these two ideas,scholars have provided a large number of research methods,and the research results have been well verified.In response to this situation,this paper proposes a public-building energy consumption prediction model based on Bayesian inference for the first time.Firstly,discussing the driving factors of public building energy consumption.Under the policy background of structural reforms,the energy consumption characteristics of public buildings are constantly changing,and determining the factors driving the changes is the key to establishing a public building energy consumption predicting model.Preliminary screening of the driving factors of the energy consumption characteristics of public buildings under structural reforms,integrating the Analytic Hierarchy Process weight method and entropy weight method to obtain comprehensive driving factors weight of public buildings energy consumption.Six driving factors are finally confirmed as the driving factors of public buildings energy consumption,which are the proportion of tertiary industry in GDP,total final energy use,energy consumption per unit of GDP,permanent population,urbanization rate,and the number of employees in the tertiary industry.Secondly,establishing a public building energy consumption predicting model.Based on Bayes’ inclusiveness of small sample variables,a public building energy consumption predicting model is established.By setting priori probability model and posterior probability model,editing model code,loading code and energy consumption data into Open BUGS program,then obtain the estimation of model parameters through fitting and analysis.Judge the convergence of the model based on the final iteration history graph and the kernel density graph.Finally,verifying the public building energy consumption predicting model.Substituting the data of driving factors in provinces statistical yearbook into the Bayesian predicting model of public building energy consumption for training,the calculated value is obtained after sufficient iteration.Compared with true energy consumption value of in the China Building Energy Report,the results are basically the same,indicating that the proposed model can effectively predict the energy consumption of public buildings.