Abstract
Economic dispatch problem is an optimization problem where objective function is highly nonlinear. In this paper, an efficient method based on hybrid genetic algorithm- particle swarm optimization (GA-PSO) for economic dispatch (ED) problem is proposed. In the proposed method, children created by using similarity measurement between mother and father chromosomes relationship. The feasibility of the proposed approach is demonstrated for solve various types of economic dispatch (ED) problems in power systems such as, economic dispatch with valve point (EDVP) effects, the ED of generators with prohibited operating zones and ED with only fuel options and it is compared in the recent literature. The study results show that the proposed approach is more efficient in finding higher quality solutions in various type ED problems. Ill. 3, bibl. 20, tabl. 10 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.108.2.155
Highlights
The Economic Dispatch (ED) problem is one of the non-linear optimization problems in electrical power systems in which the main objective is to reduce the total power generation cost, while satisfying various equality and inequality constraints
Many optimization methods have been used to overcome the ED problem. These methods can be classified as classical optimization, artificial neural networks and heuristic algorithms
Other approaches based on artificial neural networks and heuristic algorithms have been proposed to solve various ED problems
Summary
The Economic Dispatch (ED) problem is one of the non-linear optimization problems in electrical power systems in which the main objective is to reduce the total power generation cost, while satisfying various equality and inequality constraints. In this paper a new hybrid GA-PSO based on similarity method in order to solve the ED problems are proposed. The ED problem with prohibited zones minimizes the total fuel cost based on quadratic functions This function presents the regions where the operation is not allowed and this can be represented as the inequality constraints given in (10). The total transmission losses are given in (11): Pi. PikL and PU ik 1 are lower and upper bound of the kth prohibited zone unit i and zi the number of prohibited zones of unit ith nn PL ¦ ¦ Pi Bij Pj ¦ Boi Pi Boo. Evolutionary algorithms aim at reaching the global minimum or maximum value for the problems wished to be overcome using the proposed method. Power losses are considered for this system using the B-matrix from [13]
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