Research On User-Side Monitoring System Of Heating System Based On Internet Of Things

With the implementation of my country’s “carbon neutral” strategy,increasing coal utilization and reducing carbon emissions have become an important direction for my country’s demand-side reforms.At present,the domestic central heating industry still has many shortcomings compared with developed countries in Europe and America,which are mainly reflected in Household heat metering technology and heat metering methods.Relying on electronic sensor technology and communication technology,this subject builds an Io T architecture system from data collection,remote communication,and management analysis,builds a user-side monitoring system for heating systems,and designs a user-side monitoring system software platform according to user needs.Based on the historical operating data of a heating power company in Luoyang,the heat load forecast of the heating system was researched,and a correction method for forecasting indoor temperature to forecast load was proposed.Firstly,this article introduces the hardware equipment composition of the user-side monitoring system,the system’s network communication structure,the MODBUS communication protocol and the TCP/IP communication protocol,and the Lab VIEW software as the platform is used to design the terminal acquisition equipment and the scene The wired communication scheme between monitoring centers and the wireless communication scheme between on-site monitoring and remote monitoring centers.Then,using Lab VIEW software as the platform,combined with the needs of the staff,the user-side monitoring system platform of the heating system is designed.The user-side monitoring system platform functions include user login,data collection and dynamic monitoring,wireless communication management,equipment status monitoring and alarming,establishment of Microsoft Access database,data storage,and historical data retrieval and query.Finally,the basic principles,modeling methods and parameter selection of time series load forecasting are introduced in detail,and a correction method of predicting indoor temperature to the time series method of load forecasting is proposed.The actual operation data of a heating power company in Luoyang is used for example analysis..The results show that there is a relatively high prediction accuracy for a relatively stable time series,but because the model only focuses on linear fitting from the law of the sequence itself,when there is a sudden fluctuation in load data,the prediction deviation is relatively large.