Abstract


 
 The analysis of the operating conditions of a typical district heating system, in particular, a hot water gas boiler, was carried out. It is shown that the boiler, as the main control object, operates under conditions of constant change in external heat load, which, due to their random nature, leads to a number of uncertainties. The expediency of the mathematical description of uncertainties using the stochastic method as the most tested in practical conditions is substantiated. According to the results of the passive experiment on the hot water gas boiler KVG6.5-150 of the district heating system of one of the districts of Kharkov, an array of hourly experimental data was obtained, reflecting the main performance indicators of the hot water boiler. As a result of data processing by the least squares method, a mathematical model of the boiler was obtained in the form of a linear regression equation, reflecting the relationship between the temperature of the coolant at the boiler outlet and the ambient air temperature, the temperature of the coolant at the inlet to the boiler and with the flow rates of natural gas and coolant to the boiler. The obtained regression equation was verified by Student's t-test, which confirmed the significance of all coefficients of the regression model. The practical significance of the multiple regression equation was assessed using the coefficient of determination. The quality of the multiple regression equation as a whole was assessed using Fisher's F-test. Since parallel surveys were not conducted, instead of checking the adequacy, the quality of the approximation of the experimental points by the accepted regression equation was assessed, that is, it was checked whether this equation makes sense. Such a test was carried out by comparing the residual variance and the variance relative to the mean. The calculation results showed that the value of the coefficient of determination significantly exceeds the allowable value, and the actual value of the Fisher criterion significantly exceeds the table value. The obtained indicators led to the conclusion that the relationship between the variables in the regression model is significant, and the proposed stochastic method and the multiple linear regression equation can be used to make decisions in the process of synthesizing the technical structure of a computer-integrated control system for objects of a district heating system.
 
 
 
 
 

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