Study On Prediction Method Of Residential Building Energy Consumption Based On Human Behavior Characteristics In The Yangtze River Basin

Energy,as an important material foundation in human production and life,is closely related to the development of the national economy.As people have higher and higher requirements for material living standards and living environment,the demand for energy is also increasing.The development of urbanization in China has driven the continuous development of the construction industry.In 2018,the energy consumption of the construction industry accounted for 37% of the total energy consumption of our society.Therefore,it is necessary to reduce energy consumption during the construction and operation of buildings,so as to alleviate the contradiction between energy supply and demand in China,and also play an important role in China’s sustainable development strategy.The Yangtze River Basin is densely populated,has a vast territory,special climate characteristics,and rapid economic development.The reduction of building energy consumption in this area has become the focus of energy conservation research.At present,most residents in the Yangtze River Basin use air conditioning to improve the indoor thermal environment in winter and summer.Most previous studies have focused on the impact of factors such as the enclosure structure and meteorological characteristics on the energy consumption of residential buildings in the region,while neglecting the importance of human behavior.Therefore,based on the human behavior in the Yangtze River Basin,this paper screens and sorts the factors that affect energy consumption through questionnaire surveys and analysis of variance,and uses energy consumption simulation software to simulate the energy consumption of different energy consumption models for personnel in this region.On the basis of this,an energy consumption prediction system is established to provide reference for the energy consumption of residents in the area and support the energy-saving work of buildings.First,this study launched a large-scale questionnaire based on the energy consumption of residential buildings in the Yangtze River Basin.A total of 1,272 valid questionnaires were collected,covering 12 provinces and cities in the Yangtze River Basin,including Shanghai,Chongqing,Zhejiang,Sichuan,Jiangsu,Zhejiang,Hunan,and Shaanxi.Analyzed the personal behavior patterns and average monthly electricity bill data of residents in the area.The results show that: the annual household income,the length of time the air conditioners are turned on,the family structure,the building area,the mode of the air conditioners turned on,and the year of construction have significantly reduced the level of significant impact on residential building energy consumption.This shows that behavior is an important factor affecting the energy consumption of air conditioning in residential buildings in the Yangtze River Basin.Secondly,Energy Plus was used to simulate the air-conditioning set temperature,airconditioning turn-on time,and air exchange times and other related air-conditioning behaviors under different envelope structure combinations in seven typical cities in the Yangtze River Basin.The results show that the energy consumption increases by about28% for every degree increase in heating mode in winter,and the energy consumption increases by about 8% for every degree decrease in summer cooling mode.In winter heating mode,every one hour of air conditioning turned on can save 5.56%,and in summer cooling mode,one hour of air conditioning turned on can save 7.51%.Based on the frequency of ventilation 1 time per hour,the energy saving rate of 0.5 times per hour in the heating mode in winter is 62.92%,and in the summer cooling mode is 14.71%.The use of more energy-saving air conditioners should be selected under the basic needs of ensuring the indoor thermal environment of personnel.There are large differences in heating load,cooling load and total load per unit area in different typical cities.The load simulation results are consistent with the heating and cooling demand expectations when dividing sub-climatic zones.Finally,based on the aforementioned research results,23 factors influencing the energy consumption of residential building air conditioning are selected as input factors,and the simulation result of energy consumption is used as the training sample set.The artificial neural network is used to establish a residential air conditioning energy consumption prediction system based on human behavior.To verify the prediction results,the average error of annual cooling energy consumption per unit area is 0.19%,the average error of annual heating energy consumption per unit area is 0.58%,and the average error of annual total energy consumption per unit area is 0.17%.It can be seen that the prediction model established in this study has better prediction accuracy.The user interface of the residential building air conditioning energy consumption prediction system is established,which makes the application of the system more rapid,convenient and intuitive.