Method for Estimating the Calorific Value of Natural Gas for Branched Networks Using Express Quality Control Tools

The chapter proposes a new approach to determining the calorific value of natural gas based on physicochemical parameters and has practical application for commercial purposes. The correlation between the parameters measured by means of express gas quality control at the network inlets and the calorific value of gas at the consumer level (after mixing gas from different inlets) was evaluated. It showed a partial multicollinearity between some of the measured parameters—the CO2 content in natural gas and the ultrasound transmission speed measured for an energy resource from one inlet (the correlation coefficient is more than |-0.8|, which, according to the Chaddock school, indicates a high strength of the relationship) and the percentage of natural gas volumes entering the network from different pipelines. Also, taking into account the statistical analysis of the significance of the regression parameters, it was found that the use of linear regression is not adequate. A number of dependencies for estimating the calorific value of gas after mixing were obtained by non-linear regression analysis. A comparative analysis of the obtained models was carried out according to the following parameters: multiple correlation coefficient, determination coefficient, adjusted determination coefficient, actual value of Fisher's criterion, tabulated value of Fisher's criterion, and relative calculation error. The last parameter is significant in choosing the best model, as it directly reflects the accuracy of the calculations. For the obtained models, the relative error in calculating the caloric content of natural gas varies in a wide range from 0.24% to 89.4%. The study showed that the use of nonlinear model with conventional and combined parameters, taking into account the constant, in the process of calculating the calorific value of natural gas in a network with two inputs allows obtaining data that correspond to accuracy class A. This indicates the potential suitability of the methodology for commercial calculations.