Numerical Monitoring of Natural Gas Distribution Discrepancy Using CFD Simulator

Abstract

The paper describes a new method for numerical monitoring of discrepancies in natural gas supply to consumers, who receive gas from gas distribution loops. This method serves to resolve the vital problem of commercial natural gas accounting under the conditions of deficient field measurements of gas supply volumes. Numerical monitoring makes it possible to obtain computational estimates of actual gas deliveries over given time spans and to estimate their difference from corresponding values reported by gas consumers. Such estimation is performed using a computational fluid dynamics simulator of gas flows in the gas distribution system of interest. Numerical monitoring of the discrepancy is based on a statement and numerical solution of identification problem of a physically proved gas dynamics mode of natural gas transmission through specified gas distribution networks. The identified mode parameters should have a minimum discrepancy with field measurements of gas transport at specified reference points of the simulated pipeline network.

Special numerical analysis methods for mathematical models of gas flow in trunkline network

“…As conjugation conditions we can define boundary conditions simulating a complete rupture of the pipeline and/or its shutoff, operation of valves, etc. To numerically solve the system of equations (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14), the computational core of GDS usually employs grid methods. Unfortunately, distribution trunkline networks contain a large number of pipe joints distributed on general collectors extremely nonuniformly.…”

“…2. Gas dynamic variables of the gas mixture flow at the next time step 1 j t + are calculated (using difference equations approximating the gas dynamics equations (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14), except for the component continuity equations (2, 5, 7) and energy equations (4, 6, 7)). The values of the specific component fractions at mesh nodes are defined by interpolation between these values for the Lagrangian particles adjacent to the mesh node.…”

“…Publications [1][2][3][4][5][6] propose industry-oriented approaches to numerical modeling of operating conditions of complex trunkline networks that transport process gases, liquids and multiphase fluids. These publications repeatedly pointed at the necessity of improving the accuracy of simulations using the mathematical models proposed, first of all, to enable credible simulation-aided commercial accounting of gas supply to consumers.…”

Numerical Adaptation of Pipeline Network Models on Measurement Archive

“…In order to improve the quality and efficiency of the above fitting procedure and to minimize the influence of human intervention on the results of subsequent calculations, it makes sense to computerize it [4]. The basic prerequisite for such computerization as applied to a specific gas pipeline system is that the corresponding gas transport or gas distribution company should have an electronic data archive, including valve positions, gas withdrawal by consumers, and in-house gas consumption (here and below we do not differentiate between the terms "gas" and "gas mixture"), results of field measurements of basic gas flow parameters in the gas pipeline system, and parameters of gas transmission equipment.…”

“…To computerize the equivalent roughness fitting procedure, linear gas pipeline segments of the simulated gas pipeline network are conventionally divided into nonoverlapping regions [4]. Neighboring of resulting pipeline regions is admissible (i.e., the regions can have a common boundary in space).…”