Optimization of city gas network: a case study from Gujarat, India

Abstract

A natural gas flow network consists of city gate station, district regulator, pipelines, compressors and valves. The performance of such a complex system cannot be studied by analysing individual constituents. Simultaneous performance of integrated system can be expressed using non-linear equations to simulate and forecast operational behaviour. The operational behaviour is subject to various alternative operational conditions also. Nodal analysis is performed to calculate the flow capacity of each network segment and the pressure at each node. Two conditions are evaluated, namely, keeping flow capacity unknown or by making nodal pressure primary unknown. The resulting set of governing equations are then solved simultaneously. Genetic algorithm method is applied to solve the desired target unknown. Compressor governs the energy supply required to transport gas from one end to another. The compressor equation is also incorporated in city gas network simulation. The simulations are performed by straight gas ducts and complex gas ducts. Boundary conditions are dependent on the form in which gas duct is fed. It is assumed that the gas duct takes gas from City Gate Station at x = 0 and supplies the gas to a consumer located at x = L according to a time variable curve demand Q n (L, t). The capacity of the compressor is also changed and it is observed that the demand is usually periodic in nature. Flow demand at individual node of a gas pipeline network is calculated. Pressures at various nodes are also calculated and matched with original pressure at nodes. Percentage deviation error suggest a range between 0 and 1.02%. The aim of this paper is to optimise certain parameters of a gas transmission pipeline network namely flow rate, mass, cost and pressure. This optimization is performed to gas transmission pipeline network of Gandhinagar, district, where Gujarat State Petronet Limited (GSPL) and Sabarmati Gas Limited (SGL) are the major players. The network which has been chosen for pipeline network consists of 10 CNG stations and 10 DRS.

Two Iterative Methods for Sizing Pipe Diameters in Gas Distribution Networks with Loops

“…The optimisation methods shown in this article are valid for a steady state of gas flow, while gas is treated as noncompressible due to the relatively small variations in pressure in the network [13] (modification for unsteady states [14,15], fluctuating demands [16], or more complex networks [17] can be achieved).…”

“…Explanations of the first and second Kirchhoff laws for nodes and loops [12]; • Various situations that can occur in gas distribution [13][14][15][16][17];…”