Simulation model for natural gas transmission pipeline network system |
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| Authors: | Abraham Debebe Woldeyohannes Mohd Amin Abd Majid |
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| Affiliation: | 1. Curtin University of Technology, CDT 250, 98009 Miri, Sarawak, Malaysia;2. Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak, Malaysia;1. Department of Chemical Engineering, Tarbiat Modares University, Tehran, Iran;2. Dispatching Management, National Iranian Gas Company, Tehran, Iran;1. Energy Systems Improvement Laboratory (ESIL), Mechanical Engineering Department, Iran University of Science and Technology (IUST), Narmak, Tehran, Iran;2. Department of Mechanical Engineering, Faculty of Engineering, University of Guilan, P.O. Box 3756, Rasht, Iran;1. Universidad Autónoma de Nuevo León (UANL), Graduate Program in Systems Engineering, AP 111-F, Cd. Universitaria, San Nicolás de los Garza, NL 66450, Mexico;2. Energy and Infrastructure Analysis Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA;1. School of Petroleum Engineering, Southwest Petroleum University, Chengdu 610500, China;2. CNPC Key Laboratory of Oil & Gas Storage and Transportation, Southwest Petroleum University, Chengdu 610500, China;3. CNOOC Research Institute, Beijing 100027, China |
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| Abstract: | This paper focuses on developing a simulation model for the analysis of transmission pipeline network system (TPNS) with detailed characteristics of compressor stations. Compressor station is the key element in the TPNS since it provides energy to keep the gas moving. The simulation model is used to create a system that simulates TPNS with different configurations to get pressure and flow parameters. The mathematical formulations for the TPNS simulation were derived from the principles of flow of fluid through pipe, mass balance and compressor characteristics. In order to determine the unknown pressure and flow parameters, a visual C++ code was developed based on Newton–Raphson solution technique. Using the parameters obtained, the model evaluates the energy consumption for various configurations in order to guide for the selection of optimal TPNS. Results from the evaluations of the model with the existing TPNS and comparison with the existing approaches showed that the developed simulation model enabled to determine the operational parameters with less than 10 iterations. Hence, the simulation model could assist in decisions regarding the design and operations of the TPNS. |
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