Optimization of power train using Genetic, Particle Swarm and SQP1 Algorithms

In the current study, Single and Multi-objective optimizations were conducted for a compressor station comprising four similar compressor units,four coolers of the same size, and a pipelinesection. Genetic, Particle Swarm and SQP Algorithms were used in this optimization, along with detailed models of the performancecharacteristics of compressors, aerial coolers, and downstream pipeline section. The results showed that Stations having the samecompressor in parallel, the minimum fuel consumption is reached when split flow in all compressors is the same. By the way savings inthe fuel consumption in the order of 2-4 % is achievable