A critical review on optimization parameters and techniques for gas pipeline operation profitability

Abstract

Pipelines have traditionally been recognized as the most cost-effective and safe mode for transporting natural gas. However, since a tremendous amount of gas is transported through pipelines, a massive investment is required to construct and operate pipeline networks. The oil-and-gas sector has embraced pipeline optimization because of its potential to cut down pipeline costs significantly. However, the inclusion of several variables, single or multiple goals, and intricate linear–nonlinear equality and inequality constraints make pipeline optimization a significant challenge. In recent years, the natural gas industry has experienced a surge in pipeline optimization parameters and techniques to lower the pipeline cost. Numerous researchers have previously focused on developing effective algorithmic modifications to enhance certain search capabilities. However, very few review papers have been published, despite being critical for engineering solution providers. The paper tries to fill this gap by detailing the many gas pipeline optimization parameters, fourteen in our case, tuned to obtain the most outstanding pipeline operating advantages. In addition, the six most widely accepted pipeline optimization techniques, viz. Ant colony, Genetic algorithm, Differential evolution, Particle swarm, Simulated annealing, and Whale optimization algorithms, are also detailed. Furthermore, the potential solution approach for pipeline optimization problems is addressed to supplement the application. The findings of this study intend to enhance the understanding of the methodology, techniques, and advantages of implementing optimization to the pipeline industry, allowing for maximum operational benefits in a period of diminishing fossil fuel supplies.