Optimizing the Operation of Natural Gas Pipeline Network by Particle Swarm Optimization

Taking the gas company's income as a goal, an optimal running mathematical model of natural gas pipeline network is established. Conventional direct searching method includes network method and compound method. But these methods involve large amount of workload which results in slowly convergent speed. The Particle Swarm Optimization (PSO) adopts a self-adapting penalty function as a target function and a shrink factor and self-adaptation of the algorithm is amended. Combined with node pressure technique, which is used for steady-state analysis of pipeline network, an applicable program is developed for the purpose of solving the model. Practical example of calculations shows that this method can get a highly optimized performance result effectively in pipeline network operation.