Genetic Algorithm Based Load Flow Solution Problem in Electrical Power Systems

Sami Mahmood, Samir; A. Kubba, Hassan

	Genetic Algorithm Based Load Flow Solution Problem in Electrical Power Systems
Journal of Engineering
Article 1, Volume 15, Issue 4, 2009, Pages 4142-4162
Authors
Samir Sami Mahmood; Hassan A. Kubba
Abstract
In this paper, a proposed method based on real-coded genetic algorithm is presented and applied to solve multiple load flow solution problem. Genetic algorithm is a kind of stochastic search algorithm based on the mechanics of natural selection and natural genetics. They combine the concepts of survival of the fittest with genetic operators such as selection, crossover and mutation abstracted from nature to form a surprisingly robust mechanism that has been successfully applied to solve a variety of search and optimization problems. Elitist method is also used in this research, and blending models are implemented for crossover operator. In the proposed work, five busbars typical test system and 362-bus Iraqi National Grid are used to demonstrate the efficiency and performance of the proposed method. The results show that, genetic algorithm is on-line load flow solution problem for small-scale power systems, but for large-scale power systems, it is recommended that the load flow solution using genetic algorithm is for planning studies. The main important feature of the purposed method is to give high accurate solution with respect to the conventional methods.
Keywords
Continuous Genetic Algorithm; Chromosome Crossover; Load Flow Analysis; Newton; Raphson Method; Mutation; multi; Objective Minimization

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