An approach for transmission expansion planning using neurocomputing hybridized with a genetic algorithm

1995 ◽  
Vol 115 (6) ◽  
pp. 18-32 ◽  
Author(s):  
Katsuhisa Yoshimoto ◽  
Keiichiro Yasuda ◽  
Ryuichi Yokoyama ◽  
Hideo Tanaka ◽  
Yoshiakira Akimoto
Keyword(s):  
Genetic Algorithm ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion

scholarly journals An Enhanced Genetic Algorithm to Solve the Static and Multistage Transmission Network Expansion Planning

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Luis A. Gallego ◽  
Marcos J. Rider ◽  
Marina Lavorato ◽  
Antonio Paldilha-Feltrin
Keyword(s):  
Genetic Algorithm ◽  
Linear Programming ◽  
Heuristic Algorithms ◽  
Initial Population ◽  
Expansion Planning ◽  
Transmission Expansion Planning ◽  
Transmission Expansion ◽  
Local Improvement ◽  
Linear Programming Problems

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.

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