Black powder source identification in a gas pipeline network based on a One-D model

Black Powder (BP) is a phenomenon experienced worldwide by transmission gas pipeline operators with internally uncoated lines. It can cause serious problems in pipeline operation and instruments, and contaminate customer supply. It is regenerative and forms inside natural gas pipelines due to corrosion of the internal walls of the pipeline and chemical reactions. The aim of the present study is to develop a novel algorithm for BP source identification within gas pipelines network based on a 1-D static model. The proposed identification method is based on the well-known Particle Swarm Optimization (PSO) algorithm, which is able to identify and quantify BP source at different junctions simultaneously. Extensive simulation results are given to illustrate the effectiveness of the proposed optimization algorithm for BP identification.