Title :
Power optimization for a hydrocarbon industrial plant using a genetic algorithm
Author :
Al-Hajri, Muhammad Tami ; Abido, M.A. ; Darwish, M.K.
Author_Institution :
Brunel Univ., Uxbridge, UK
Abstract :
In this paper, a genetic algorithm (GA) is considered for optimizing electrical power loss for a real hydrocarbon industrial plant as a single objective problem. 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 (J1) objective is used to guide the optimization process, and, consequently, the injected power into the grid (PRInject) is increased. The results obtained demonstrate the potential and effectiveness of the proposed approach to optimize the power consumption. Also, in this paper a cost appraisal for the potential daily, monthly and annual cost saving will be addressed.
Keywords :
gas turbines; genetic algorithms; industrial plants; steam turbines; synchronous motors; electrical power loss; gas turbine generators; genetic algorithm; hydrocarbon industrial plant; plant electrical system; power consumption; power losses; power optimization; rotational loads; static loads; steam turbine generators; synchronous motors; Biological cells; Generators; Genetic algorithms; Linear programming; Optimization; Reactive power; Synchronous motors; BTU: British thermal unit; ESP: electrical submersible pump; GA: genetic algorithm; MMscf: millions of standard cubical feet of gas;
Conference_Titel :
Power Engineering Conference (UPEC), 2014 49th International Universities
Conference_Location :
Cluj-Napoca
Print_ISBN :
978-1-4799-6556-4
DOI :
10.1109/UPEC.2014.6934599