| In recent years,under the dual background of the double carbon target and the new crown epidemic,the energy saving needs of a large number of existing university buildings in China have been further increased,and under the traditional operation and maintenance management mode,each building energy-using equipment and system operates independently,lacking targeted new air energy-saving control methods and three-dimensional visualization of the operation and maintenance management system,and the overall energy efficiency level is low,so it is necessary to accelerate the transformation and upgrade of the traditional operation and maintenance mode of existing buildings.Therefore,it is necessary to accelerate the transformation and upgrading of the traditional operation and maintenance mode of existing buildings into an intelligent and digital one,so as to facilitate the development of green and low-carbon buildings under the"double carbon target"in China.In this paper,an existing university teaching building in Beijing is selected as the research target,and energy efficiency testing is carried out on its central air-conditioning and cooling system.A combination of on-site measurements and software simulations was used to analyze the energy consumption of the air-conditioning system and to carry out intelligent and digital improvement research.(1)The COP of the chiller plant is 4.84,which is in line with the national standard of 4.60.The overall performance of the plant meets the standard and has a high operating efficiency.The COP of the refrigeration system measured by calculation is 2.98,which is very close to the energy efficiency standard required by the code.(2)Using De ST energy simulation software,the maximum cooling load indicator of the building is 96.74 W/m~2,of which the fresh air load accounts for approximately 30%in the cooling season,which is a relatively high percentage overall.The total building energy consumption(including lighting,equipment and other energy consumption)in the cooling season is 472,900 k W·h,of which 238,400k W·h is for air conditioning,accounting for approximately 50%of the total building energy consumption.(3)In view of the high fresh air load in the building and the current situation of the New Crown epidemic prevention and control,this paper proposes a new method of intelligent fresh air control based on the regulation of the number of people in the room,and develops the relevant control system.In view of the current situation of the new crown epidemic(a special situation with large fluctuations in the number of people in the room),the energy consumption of the air-conditioning system during the cooling season was simulated using De ST energy simulation software,and the total power consumption of the air-conditioning system before and after the improvement was 238,400 k W·h and 193,300 k W·h respectively,with a reduction of18.9%in the power consumption of the air-conditioning system during the cooling season,resulting in a more obvious energy-saving effect.(4)In order to further investigate the energy efficiency of the above-mentioned solution and the operation of the equipment in the refrigeration room from a visual perspective,this paper builds a 3D visualization operation and maintenance management system for existing university buildings based on open source software,which combines intuitive visualization of operation and maintenance management with statistical analysis of energy consumption.The front-end of the system includes the development of a back-end management system and a 3D visualization screen.The back-end management system is built based on the mainstream Vue.js framework and the Element-UI component library,while the visualization screen module uses Three.js and Echarts to visualize 3D scenes and real-time charts respectively.The back-end of the system uses the combination of"Node.js+Mongo DB"to build the server and database,while the Io T monitoring equipment designed and produced by the system itself collects real-time indoor thermal environment and equipment operating parameters,and stores them in the Mongo DB database in real time.The front and back end of the system interacts with various data and information through API interfaces to achieve dynamic visualization of 3D scenes and real-time data.The system not only realizes the collaborative display of the building’s 3D scene and energy consumption data,but also presents the indoor thermal environment parameters and equipment operation energy consumption data in the form of more intuitive visual charts,and brings a more interactive visual control experience for users and managers,facilitating managers to carry out energy consumption analysis and"health diagnosis".It has certain engineering application value for the construction of intelligent operation and maintenance systems for existing buildings. |
