Optimization Of High Efficiency Operation Strategy For Gas-fired Condensing Heating Boiler

In this paper,a gas-fired condensing boiler in a hospital in Tianjin is taken as the research object.Through field test and theoretical calculation,the energy-saving effect of condensing technology in the deep utilization of exhaust gas and residual heat of gas-fired boiler is studied,and the influence of different factors on the thermal efficiency of gas-fired condensing boiler is analyzed.Based on the actual operation data,the operation regulation method of gas-fired condensing boiler is proposed,using BP and Rb Based on the f neural network model,the backwater temperature and building energy consumption are predicted,and the key parameters of the hot water boiler and the heat exchange station are monitored and controlled in real time based on the Kingview software.Firstly,the paper studies the prediction method of building energy consumption and data preprocessing method,explores the dynamic influence of main meteorological factors on building load and makes correlation analysis.It is found that the average temperature has a significant negative impact on heating energy consumption,while the average relative humidity,average wind speed and sunshine hours have a relatively weak impact on heating energy consumption.At the same time,the multiple stepwise regression method is used to The input variables were selected and the multiple linear regression equation was established.Combined with the actual operation data of a gas-fired condensing boiler in a hospital in Tianjin,the optimal operation strategy for the gas-fired condensing boiler is put forward.It is found that the key operation parameters such as return water temperature and load rate are the most important factors to improve the thermal efficiency of the gas-fired condensing boiler.Different operation adjustment methods should be adopted in different heating stages in winter,and the heating cycle can be divided into three parts according to the meteorological conditions of Tianjin In each stage,keep the circulating water volume unchanged,and adjust the water supply temperature to meet the heating demand;for different functional areas,according to the difference of heating demand,adopt time-sharing and temperature division heating.The energy consumption model of boiler operation is established by using BP neural network method.The input parameters are water supply temperature,water supply pressure,return water pressure,exhaust gas temperature and gas quantity,so as to better predict the return water temperature and other output quantities.Building BP neural network and RBF neural network model,selecting four meteorological parameters of average temperature,average humidity,average wind speed and sunshine hours as the input,respectively predicting the output of building energy consumption and so on,and making short-term prediction comparison,it shows that the short-term load forecasting method using RBF neural network can improve the accuracy of prediction,more suitable for the actual operation needs.Based on the Kingview software,the auxiliary software can be designed to continuously monitor the main operation parameters of gas-fired condensing hot water boiler and heat exchange station around the clock.Combined with the configured database,the operation parameters of the system can be monitored in real time and the historical data can be viewed.Through the interaction with MATLAB software,the new operation data can be imported into the neural network model for calculation,increase the accuracy of the neural network model,more accurate prediction and guidance of boiler operation.