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ThinkMind // FUTURE COMPUTING 2015, The Seventh International Conference on Future Computational Technologies and Applications // View article future_computing_2015_2_20_30016


Assessment of MVAR Injection in Power Optimization for a Hydrocarbon Industrial Plant Using a Genetic Algorithm

Authors:
Mohammed Abido
Muhammad Al-Hajri
Mohamed Darwish

Keywords: genetic algorithm, power loss optimization, electrical submersible pump, hydrocarbon facility, British thermal unit (BTU), millions of standard cubical feet of gas (MMscf).

Abstract:
In this paper, a genetic algorithm (GA) is considered for assessing the effect of Million Volt-Ampere Reactive (MVAR) power injection via shunt capacitors in optimizing the electrical power loss for a real hydrocarbon industrial plant. The subject plant electrical system consists of 275 buses, two gas turbine generators, two steam turbine generators, large synchronous motors, and other rotational and static loads. The minimization of power losses objective is used to guide the optimization process, and, consequently, the injected power in the grid is monitored. First, the optimal locations of MVAR injection will be identified using a voltage stability index. The potential of power loss optimization with and without MVAR injection versus the base case will be discussed in the results. The results obtained demonstrate the potential and effectiveness of the proposed approach to optimize the power consumption in both scenarios (with and without MVAR injection). Also, in this paper a cost appraisal for the potential daily, monthly and annual cost saving in both scenarios will be addressed.

Pages: 31 to 37

Copyright: Copyright (c) IARIA, 2015

Publication date: March 22, 2015

Published in: conference

ISSN: 2308-3735

ISBN: 978-1-61208-389-6

Location: Nice, France

Dates: from March 22, 2015 to March 27, 2015

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