Enhancing Real-Time Simulation of the Complexity Natural Gas Pipeline Network Through MLP-Newton Algorithm for High Precision and Reliability

Aiming at the challenge of high-precision and high-reliability simulation of urban medium- and high-pressure natural gas pipeline networks, the model establishment is analyzed in detail, solution algorithm and optimization process in gas pipeline network simulation, and designs a modeling and solution method that is easy to analyze and implement to solve the complexity problem of existing natural gas pipeline network simulation algorithms. First, a steady-state simulation model was established, and the nonlinear equations were converted to linear equations using Newton’s iterative method. Then, Kirchhoff’s law and the nodal pipe segment correlation matrix are applied to establish the system of equations. Finally, by combining the iterative process of Newton’s method with the “numerical table” method, a simple calculation method based on the contribution value is established. To solve the sensitivity problem of Newton’s iterative method, the advantages of Multilayer Perceptron (MLP) in data prediction are utilized in this work. A new initial value prediction algorithm of Newton’s iterative method is proposed based on the multilayer perceptron in the real-time simulation system of gas pipeline network. In the simulation of a complex natural gas network with 134 nodes and a total length of 35.843 kilometers, the results show that the average number of iterations of the Newton’s iterative method after inputting the predicted values is reduced by 87.51% and the computation time of the simulation system is reduced by 47.32%. In addition, the absolute error between the pressure values calculated by our proposed algorithm and the pressure values calculated by the commercial software TGNET software is within 1.3% for a single point, and the average absolute error for multiple points is within 0.9%. The experimental results demonstrate the advantages of the proposed algorithm in terms of real-time, effectiveness and stability.