NDLI: Optimization of natural gas transmission network using genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Jamshidifar, A.A.
Copyright Year	2011
Description	Author affiliation: Iranian Research Organization for Science and Technology, Tehran, Iran (Jamshidifar, A.A.)
Abstract	In this paper, an Evolutionary approach for optimization of cyclic Gas Transmission Network (GTN) is presented. The GTNs comprise of nodes, links, compressor stations and valves where the last one is a main component of GTNs which generally not considered in similar works. In this approach, at first a reduced network will be generated from the original GTN and the cycles of the reduced network will be identified. Then an iterative approach will be used to find the cycles flows which optimize the objective function. This approach calculates the pressure variables at fixed flow rates using dynamic programming (DP) and updates the gas flow rates to improve the objective function in every iteration. The objective function is a weighted summation of total number of running compressor stations and their total fuel consumption. The flow rates will be updated using Genetic Algorithm (GA) which is modified to speed up its convergence. The main modifications are related to decomposing of chromosomes to subchromosomes and finding the upper and lower limits for crossover and mutation. A number of real examples of Iranian GTN are exploited to support the proposed approach.
Starting Page	295
Ending Page	300
File Size	876161
Page Count	6
File Format	PDF
ISBN	9781457716768
ISSN	21647151
e-ISBN	9781457716768
DOI	10.1109/ISDA.2011.6121671
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-11-22
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Genetic Algorithm Valves Mathematical model Fuels Gas transmission Network Biological cells Equations Optimization Cycle Genetic algorithms
Content Type	Text
Resource Type	Article

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