Home // FUTURE COMPUTING 2017, The Ninth International Conference on Future Computational Technologies and Applications // View article
Authors:
Muhammad Alhajri
Mohamed Darwish
Mohammed Abido
Keywords: genetic algorithm; differential evolution algorithm; power loss optimization; hydrocarbon facility; millions of standard cubical feet of gas (MMscf).
Abstract:
In this paper, a techno-economic assessment of a real life hydrocarbon facility electrical system real power loss optimization is addressed. This optimization was attained by using the Genetic Algorithm (GA) and the Differential Evolution Algorithm (DEA). The study is the first of its kind as none of the previous studies were conducted in the context of a real life hydrocarbon facility’s electrical system. The hydrocarbon facility’s electrical system examined in the study consisted of 275 buses, two gas turbine generators, two steam turbine generators, and large synchronous motors, with both rotational and static loads. For the real life hydrocarbon facility, the performance of the GA and the DEA were benchmarked in the course of optimizing the subject objective. The problem was articulated as a constrained nonlinear problem. The constraints were all real values reflecting the system equipment and components’ limitations. The consequences obtained from the study showed the efficiency and prospects of the proposed algorithms in solving the described optimization case. Also presented in this study is the annual fuel cost avoidance.
Pages: 1 to 6
Copyright: Copyright (c) IARIA, 2017
Publication date: February 19, 2017
Published in: conference
ISSN: 2308-3735
ISBN: 978-1-61208-530-2
Location: Athens, Greece
Dates: from February 19, 2017 to February 23, 2017