Efficient Method for Steady-State Simulation of Natural Gas Pipeline Networks Based on Spatial Decomposition

As the scale of natural gas pipeline networks expands annually, their topological structures become increasingly complex, leading to a continuous increase in the difficulty and time cost of solving pipeline network simulation problems. Addressing the technical challenge of balancing accuracy and timeliness in natural gas pipeline network simulation, a new method for accelerating the solution of natural gas pipeline network simulations based on spatial decomposition and parallel computing is proposed, under the condition of clarifying the principles for determining simulation boundary conditions. In this study, the core issue is the steady-state hydraulic simulation of natural gas pipeline networks, which is transformed into an unconstrained optimization problem. Based on the hydraulic simulation equations, the objective function of the corresponding optimization model is constructed, transforming the solution of the simulation model into an extreme value optimization process of the optimization model. Thus, an optimization-based solution model for steady-state simulation of natural gas pipeline networks is established. By conducting a partitioned demonstration of the mathematical characteristics of the objective function and the properties of extreme points, the prerequisites for the uniqueness of the solution are clarified, providing rigorous mathematical theoretical support for model simplification through spatial decomposition and partitioned decoupling. Combined with a case study of pipeline network simulation, the conclusion is further proven: when solving the steady-state simulation problem of natural gas pipeline networks, under the condition of at least one given node pressure, the solution to the steady-state hydraulic calculation of the pipeline network is unique. Meanwhile, the results of simulation calculations using spatial decomposition and parallel acceleration (SDPA) for natural gas pipeline networks with complex topological structures show that, compared to TGNET result data, the average error in pressure is 0.10%, and the average error in flow rate is 1.25%. Under the premise of ensuring the calculation accuracy of the solution, the calculation time is reduced by 59.65%.