The Research On Energy Consumption Of Envelope On Public Buildings In Hot Summer And Cold Winter Area

Since China’s open and reform policy,its urbanization speed and economic growth have been rapidly developed.The demands of higher living quality and indoor environments from people also keep increasing which results in more energy consumption in buildings.Hot summer and cold winter area has the characteristics of powerful economy,dense population,and high energy consumption in buildings,especially for newly built and existing public buildings,whose energy consumption is more than 10 times of residential buildings.Therefore,it is truly necessary to reduce energy consumption of public buildings in hot summer and cold winter area and enhance the indoor environments.Building envelope will directly influence the heat exchange,natural ventilation,and natural lighting between buildings and surrounding environments,thus put impacts on energy consumption of buildings.This paper firstly summarizes relevant technologies of building envelope,mainly focuses on introducing the operating principle and application status of roof,wall and windows.Then compare how Chinese and USA standards define thermal performance of building envelope,and how to determine whether buildings meet the national requirement.Secondly,three energy-efficient models have been built in simulation software“Gbsware-BECS” according the drawing information and analyze how thermal characteristics of envelope influence building energy consumption.Due to Structural differences,three models show various tendencies.With simulation in software BECS,it can be found that the specific outlines of building will influence their energy consumption.In the end,combined with Artificial Neural Network prediction of energy consumption,the relationships between envelope cost increasement and yearly building energy consumption have been discussed according to thermal enforcements of roof,wall and windows under contrast of worst operating condition.Results show that the cost recovery periods are all less than 10 years.Energy prediction combined with artificial neural network shows strong computing advantages when dealing with huge amounts of data,while maintaining great accuracy.Cost recovery period will provide economic advices for building owners,thus improve their enthusiasm in energy efficiency of buildings.