A genetic algorithm solution for optimization of smarted station "perdawd gas station in Kurdistan"

Genetic Algorithm is established on the process of natural biological evolution that is used to simulate and mimic natural in looking for optimal solution of certain problem. Genetic Algorithms is employed in the electric power system (EPS) to optimize its' parameters using natural operators. This paper depicts the concept of Genetic Algorithm as an optimization tool to synthesize the optimal parameters of a specific case study, Perdwad Power Station in Kurdistan, which are Power System Stabilizer (PSS) and Excitation system. It's trend to automate the real case as a smart state. A population set of parameters is randomly generated, which is, proper solutions for the search space. Whereas two parent chromosomes from a population is selected to produce offspring which is depending on the fitness. The parent's selection has a bigger chance when the fitness is better. The obtained results have proved that Genetic Algorithm are a powerful tools for optimizing the PSS parameters, and more robustness for the studied PSS. The simulations were executed by SIMULINK\MATLAB environment. The simulation results show the parameters of genetic controllers, smart control, are better than from conventional controllers.