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

被引：6
|
作者：
Gallego, Luis A. [1 ]
Rider, Marcos J. [1 ]
Lavorato, Marina [1 ]
Paldilha-Feltrin, Antonio [1 ]
机构：
[1] Univ Estadual Paulista Julio Mesquita Filho UNESP, Fac Engn Ilha Solteira, Dept Engn Eletr, Ave Brasil 56, BR-15385000 Ilha Solteira, SP, Brazil
来源：
JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING | 2012年 / 2012卷
关键词：
D O I：
10.1155/2012/781041
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页数：12
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