Assessment of genetic algorithm selection, crossover and mutation techniques in power loss optimization for a hydrocarbon facility

In this paper, different selection, crossover including deferential evolution and mutation techniques are considered for optimizing the electrical power loss in real hydrocarbon industrial plant using genetic algorithm (GA). The subject plant electrical system consists of 275 buses, two gas turbine...

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Bibliographic Details

Published in:	2015 50th International Universities Power Engineering Conference (UPEC) pp. 1 - 6
Main Authors:	Al-Hajri, Muhammad Tami, Abido, M. A., Darwish, M. K.
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.09.2015
Subjects:	Biological cells British thermal unit (BTU) electrical submersible pump Generators genetic algorithm Genetic algorithms hydrocarbon facility millions of standard cubical feet of gas (MMscf) Optimization power loss optimization Sociology Statistics Synchronous motors
Online Access:	Get full text
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