Application of Particle Swarm Optimization (PSO) algorithm for Black Powder (BP) source identification in gas pipeline network based on 1-D model

Black Powder (BP) is a worldwide problem that spans all stages of the natural gas industry from the producing wells to the consuming points since it can endanger the pipeline operations, damage instruments, and contaminate customer supplies. The formation of BP inside natural gas pipeline mainly results from the corrosion of internal walls of the pipeline, which is a complex chemical reaction. A novel algorithm for BP source identification within gas pipelines network based on a one-dimensional model of BP transport and deposition was developed. The optimization algorithm for BP source identification is developed based on the well-known Particle Swarm Optimization algorithm, which can solve constrained optimization problems. By applying this optimization algorithm on the gas transmission pipeline network, the BP source at different junctions could be identified and quantified simultaneously. Extensive simulation studies are carried out to validate the effectivity of the optimization algorithm.