An enhanced genetic algorithm to solve the static and multistage transmission network expansion planning
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Data
2012-04-23
Autores
Gallego, Luis A. [UNESP]
Rider, Marcos J. [UNESP]
Lavorato, Marina [UNESP]
Paldilha-Feltrin, Antonio [UNESP]
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Resumo
An enhanced genetic algorithm (EGA) is applied to solve the long-term transmission expansion planning (LTTEP) problem. The following characteristics of the proposed EGA to solve the static and multistage LTTEP problem are presented, (1) generation of an initial population using fast, efficient heuristic algorithms, (2) better implementation of the local improvement phase and (3) efficient solution of linear programming problems (LPs). Critical comparative analysis is made between the proposed genetic algorithm and traditional genetic algorithms. Results using some known systems show that the proposed EGA presented higher efficiency in solving the static and multistage LTTEP problem, solving a smaller number of linear programming problems to find the optimal solutions and thus finding a better solution to the multistage LTTEP problem. Copyright © 2012 Luis A. Gallego et al.
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Palavras-chave
Comparative analysis, Enhanced genetic algorithms, Higher efficiency, Initial population, Linear programming problem, Multistage transmission, Optimal solutions, Transmission expansion planning, Genetic algorithms, Heuristic algorithms, Linear programming, Problem solving
Como citar
Journal of Electrical and Computer Engineering.