Application of computer based simulation in gas network system using graph theory algorithms and numerical methods

Abstract

The existing gas network software is highly depending on the Breadth First Search (BFS) and the Depth First Search (DFS) in performing gas network computation of any topology. This is causing the other graph theory algorithms remain least known to users. Apart from that, there are many numerical methods that can be used in performing the gas pipeline network analysis. Thus, the hypothesis of the method states that the Newton Gauss Elimination method is faster and more accurate than the Newton Gauss Seidel method. The objectives of this research are to determine the fastest graph theory algorithm , and to determine the fastest and the most accurate numerical method, in the development of gas network computer simulator. The developed computer simulator applies the Newton Nodal Method in performing the network analysis. Object oriented approach was used in designing the structure of the computer simulator. Two case studies and one extended case study were performed. Case study 1 and 2 involve 5 nodes low pressure gas pipeline network and 6 nodes medium pressure gas pipeline network respectively. The extended case study 1 involves 7 nodes high pressure gas pipeline network. The flow results from the computer simulator in the case study 1 and 2 were compared with GaPIS version 2.3. While in the extended case study, two flow equations for high pressure gas network system were compared for the accuracy. In conclusion, the BFS is the fastest graph theory with 5.37 milliseconds for case study 1, 5.48 milliseconds for case study 2 and 5.62 milliseconds for extended case study 1. The Newton Gauss Elimination is the fastest numerical method with 34.86 milliseconds for case study 1, 46.35 milliseconds for case study 2 and 50.26 milliseconds for extended case study 1. The combination of BFS and Newton Gauss Elimination gives the fastest speed, with 40.23 milliseconds in case study 1, 51.83 milliseconds in case study 2 and 55.87 milliseconds in extended case study 1. The average accurac ies of both numerical methods for case study 1, case study 2 and extended case study 1 are 99.22%, 95.64% and 91.71% respectively.