Multi-objective optimization for natural gas pipeline network operation

With the increase in the global energy consumption, natural gas plays a significant role as a clean and abundant energy resource. Natural gas is transported by pipeline networks which serve as the most cost effective transportation means over long distances. Compressors installed in pipeline networks provide the propelling force necessary to boost the pressure of the gas to reach its destination. It is estimated that compressor stations account for 25% to 50% of the total operating cost. Hence, researchers have paid considerable attention to optimize the operation of compressor stations due to its enormous cost saving.;This research work performs a thermodynamic modeling of different pipeline network configurations namely linear, branch and looped topologies to find optimal operating conditions. Two conflicting objectives i.e. fuel consumption minimization and throughput maximization are considered subjected to pipeline and compressor constraints. The optimization of the models is performed using NSGA-II and the algorithm is run using jMetal (Metaheuristic Algorithms in Java) which is an object-oriented Java-based framework for solving multi-objective optimization problems. The solution obtained is a set of Pareto points from which a decision making process is highlighted to select a specific preferred solution.