1996IEE Proceedings - Generation Transmission and DistributionRequires access

Economic dispatch of generators with prohibited operating zones: a genetic algorithm approach

S.O. Orero, Malcolm R. Irving

Open publisher page 210 citations

Abstract

The work explores the use of a genetic algorithm for the solution of an economic dispatch problem in power systems where some of the units have prohibited operating zones. Genetic algorithms have a capability to provide global optimal solutions in problem domains where a complete traversion of the whole search space is computationally infeasible. Two different implementations of the genetic algorithm for the solution of this dispatch problem are presented: a standard genetic algorithm, and a deterministic crowding genetic algorithm model. The results demonstrate that the genetic algorithm can be applied successfully in the solution of problems represented with nonconvex functions.

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What this paper is about

The work explores the use of a genetic algorithm for the solution of an economic dispatch problem in power systems where some of the units have prohibited operating zones. Genetic algorithms have a capability to provide global optimal solutions in problem domains where a complete traversion of the whole search space is computationally infeasible. Two different implementations of the genetic algorithm for the solution of this dispatch problem are presented: a standard genetic algorithm, and a deterministic crowding genetic algorithm model. The results demonstrate that the genetic algorithm can be applied successfully in the solution of problems represented with nonconvex functions.

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Available abstract

The work explores the use of a genetic algorithm for the solution of an economic dispatch problem in power systems where some of the units have prohibited operating zones. Genetic algorithms have a capability to provide global optimal solutions in problem domains where a complete traversion of the whole search space is computationally infeasible. Two different implementations of the genetic algorithm for the solution of this dispatch problem are presented: a standard genetic algorithm, and a deterministic crowding genetic algorithm model. The results demonstrate that the genetic algorithm can be applied successfully in the solution of problems represented with nonconvex functions.

Key concepts: Economic dispatch, Genetic algorithm, Mathematical optimization, Computer science, Cultural algorithm, Implementation, Algorithm, Quality control and genetic algorithms

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