Research On Energy Consumption Influencing Mechanism And Energy Saving Prediction Of Public Teaching Buildings Of Universities In Beijing

Currently,humanity is facing a series of problems,such as an energy crisis,climate change,and environmental degradation.Countries worldwide have begun to reflect on high energy consumption and their high carbon emission behavior and gradually focus on energy conservation and research on reducing pollutant emission.Currently available data show that the construction industry’s energy consumption accounts for about 30-40%of the world’s total energy consumption,and its greenhouse gas emissions account for about 40-50%of the world’s total emissions.Among them,the construction industry’s energy consumption in China accounts for about 20%of the total energy consumption,showing a rising trend.This development makes the construction industry a key area for urgent implementation of energy-saving measures and promotion of carbon-neutral processes;therefore,energy-saving design and research on energy consumption in buildings is imperative.A large number of studies and practices have shown that more than 40%of the energy-saving potential has its origin in architectural design,and,at this stage,the choice of the source will have an impact on energy consumption in buildings.Therefore,energy-saving research in architectural design is imperative.However,the currently available parameter choices mostly rely on empirical judgment and qualitative analysis.Although relevant researchers have initiated quantitative studies,the depth and breadth of their research still need to be supplemented and advanced.This study has selected public teaching buildings of colleges and universities with rapid growth and huge energy-saving potential for detailed research.This research study is based on screening domestic and foreign research results for a“library construction of archetypal building models”,building energy efficiency,teaching building energy efficiency,and analysis of the evolutionary trends and research hotspots of domestic“energy consumption simulation”and“building energy efficiency”.The research is focused on the Beijing area,which has a large number of universities,to study the energy consumption influencing mechanism and energy saving prediction of public teaching buildings in colleges and universities.The specific contents and findings of the research are as follows:（1）Constructed the database of archetypal energy consumption models for public teaching buildings in Beijing universities._A○1_EAForty public teaching buildings of Beijing colleges and universities were surveyed on the spot,and data were collected on a large scale according to the four major aspects,which include building space&form,enclosure structure,HVAC system,and internal load._A○2_EACollected meteorological data on the Beijing area,systematically sorted and adjusted them based on actual survey data,industry-related standards,and domestic and overseas research results._A○3_EAThe 26 types of parameters that characterize the energy consumption of the building were sorted and counted.Their characteristics and value spaces were summarized to lay a firm foundation for further research on the law and characteristics of the factors influencing energy consumption.（2）Analyzed the characteristics and interaction laws between 10 design parameters（partial dynamic changes）and energy consumption in various building archetypes.This paper quantitatively analyzes the interaction mechanisms between 10 types of parameters（building shape,orientation,the window-to-wall ratio in each direction,and the parameters of envelope structure,etc.）,which are related to building space and form,and the various types of energy consumption one by one through simulation of the annual dynamic energy consumption and application of the local sensitivity method.It also conducts detailed analysis from the perspectives of peak value,valley value,energy saving rate,maximum energy saving,and carbon neutral potential.The results show that:_A○1_EAFor various building shapes without windows,such as“Rectangle”archetype,“L”archetype,“U”archetype and“Courtyard”archetype,and with the same relative shape coefficient,the trend of energy consumption and the relative shape coefficient are basically the same;In buildings with windows,the energy consumption varies with the relative shape coefficient,which indicates that the properties of the windows are factors that interact with the building shape._A○2_EAThe present paper discusses the function characteristics and mechanisms of the orientation factor（Orien）on energy consumption.It concludes that it may be the primary influencing factor on energy consumption,related to variations in the area distribution and proportional settings of walls and windows in different directions._A○3_EADifferent window-to-wall ratios（WWR）in all dimensions have a significant impact on the various forms of energy consumption;the thickness of the external wall and the roof insulation layer(Insul_d-wall and Insul_d-roof)have an“economic value”;the solar heat gain coefficient（SHGC）and the heat transfer coefficient of external windows(K_window)have opposite effects on the heating and cooling energy consumption.（3）Determined the sensitivity rankings of 9 design parameters（global dynamic changes）for each form of energy consumption,compared and analyzed the similarities and differences of the parameter sensitivity rankings of different building archetype models.The collaborative computing platforms of Energy Plus,Design Builder,and j EPlus were built.The global sensitivity and qualitative method of Morris and quantitative method of Sobol were comprehensively applied to evaluate the impact of the input space on the model output under the dynamic changes of all parameters.The interaction mechanism between various parameters and energy consumption was revealed;the critical parameters affecting various types of energy consumption was identified;the sensitivity ranking of 9 types of parameters under 3 types of response variables was determined;the sensitivity index of each input factor corresponding to each form of energy consumption was calculated.The results show that for different energy consumption types,the parameter sensitivity rankings are greatly different;the parameter sensitivity rankings are roughly the same for different building shapes with the same energy consumption,but there are local fluctuations;there is a strong interaction effect with the orientation factor._A○1_EAFor heating energy consumption:The heat transfer coefficient of the external windows(K_window)and the solar heat gain coefficient（SHGC）are highly sensitive parameters.In the“Rectangle”archetype model,their total-order（first-order）sensitivity indexes are 0.509（0.481）and 0.270（0.259）,respectively.In the“L”archetypal model,they are 0.552（0.533）and 0.292（0.286）.They are 0.618（0.561）and 0.193（0.172）in the“U”archetype;0.634（0.610）and 0.264（0.258）in the“Courtyard”archetype.Five parameters,such as the north or south window-to-wall(WWR_north,WWR_south)ratio,orientation（Orien）and heat transfer coefficients of external wall and roof(K_wall,K_roof),are moderately sensitive parameters.For different building forms,the order of the five parameters varies with location（uncertainty）;The west or east window-to-wall ratios(WWR_west,WWR_east)are low sensitivity parameters._A○2_EAFor cooling energy consumption:For the four archetypes of building shapes,the solar heat gain coefficient（SHGC）is dominating and is the most sensitive to cooling energy consumption,then followed by the north or south window-to-wall ratio(WWR_north,WWR_south),the orientation factor（Orien）,and the east or west window-to-wall ratio(WWR_east,WWR_west).The more homogeneous“Courtyard”archetype shows some variation in the order of the sensitivity parameters.The total-order（first order）effect indexes of the SHGC for the four archetypes of building shapes are 0.645（0.620）,0.705（0.698）,0.708（0.675）,and 0.856（0.817）,respectively._A○3_EAFor lighting energy consumption:the south or north window-to-wall ratio(WWR_north,WWR_south)has the highest sensitivity.These research results could serve as supporting information for choosing building design parameters and implementing low energy consumption building practices.（4）Derived energy consumption prediction models and designed energy consumption-prediction tools at the building design stage._A○1_EAThe standardized regression coefficients（SRC）coefficients were superimposed to determine the positive and negative effects of various parameters and the four types of energy consumption.The analysis shows that the annual energy consumption is dominated by the heating energy consumption in winter._A○2_EABased on the Latin hypercube sampling（LHS）method and multiple linear regression,correlations between the comprehensive energy consumption and each part of the energy consumption of the four building shapes and 9parameters were established,and the prediction model was verified and evaluated._A○3_EAA tool for estimating the energy consumption of public teaching buildings in colleges and universities with four usage modes was developed;the interface layout,operation steps and usage modes of the tool were described in detail to enhance and extend the application value of the research findings.