Using Genetic Algorithm for Fuel Consumption Optimization of a Natural Gas Transmission Compressor Station
Author(s) -
Golnaz Habibvand,
Reza Mossayebi Behbahani
Publication year - 2012
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/6064-8180
Subject(s) - computer science , gas compressor , genetic algorithm , compressor station , transmission (telecommunications) , natural gas , fuel efficiency , consumption (sociology) , algorithm , operations research , mathematical optimization , telecommunications , automotive engineering , mechanical engineering , machine learning , waste management , mathematics , engineering , social science , sociology
In this study the goal is to optimize the compressors’ fuel consumption through manipulating the compressors’ affecting parameters as well as the operating condition parameters of the turbines and the air coolers within a gas compression station unit in operation phase by using Genetic Algorithm. The simulation part is written in a custom-built computer program and is checked by known software and optimization is through the use of Genetic Algorithm. By considering the complexity of these systems, GA is used to do the optimization part in a proper manner. The results show that in compressor stations with same turbo compressor packages which are designed in recent years, despite nonlinear relations, linear load sharing will be the most optimized choice (the effect of air coolers and line pack has been studied too). And also Genetic Algorithm optimization method is a good one for optimization of gas transmission systems.
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