Combined use of Particle Swarm Optimization and genetic algorithm methods to solve the Unit Commitment problem

Author

Marrouchi, Sahbi ; Chebbi, Souad

Author_Institution

Nat. Super. Sch. of Eng. of Tunis (ENSIT), Univ. of Tunis, Tunis, Tunisia

fYear

2014

Firstpage

600

Lastpage

604

Abstract

Solving the Unit Commitment problem (UCP) optimizes the combination of production units operations and determines the appropriate operational scheduling of each production units to satisfy the expected consumption which varies from one day to one month. Besides, each production unit is conducted to constraints that render this problem complex, combinatorial and nonlinear. In this paper, we proposed a new strategy based on the combination of the Particle Swarm Optimization method and the genetic algorithm applied to an IEEE electrical network 14 buses containing 5 production units to solve the Unit Commitment problem in one side and to find an optimized combination scheduling in the other side leading to minimize the total production cost.

Keywords

genetic algorithms; particle swarm optimisation; power generation dispatch; power generation scheduling; IEEE electrical network 14 buses; genetic algorithm; operational scheduling; particle swarm optimization; problem complex; production units operations; unit commitment problem; Convergence; Genetic algorithms; Particle swarm optimization; Scheduling; Sociology; Statistics; Genetic algorithm; Optimization; Particle Swarm Optimization; Unit commitment; scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Sciences and Techniques of Automatic Control and Computer Engineering (STA), 2014 15th International Conference on

Type

conf

DOI

10.1109/STA.2014.7086752

Filename

7086752