DocumentCode
1083877
Title
Optimization method for reactive power planning by using a modified simple genetic algorithm
Author
Lee, Kwang Y. ; Bai, Xiaomin ; Park, Youn-Moon
Author_Institution
Dept. of Electr. Eng., Pennsylvania State Univ., University Park, PA, USA
Volume
10
Issue
4
fYear
1995
Firstpage
1843
Lastpage
1850
Abstract
This paper presents an improved simple genetic algorithm developed for reactive power system planning. Successive linear programming is used to solve operational optimization sub-problems. A new population selection and generation method which makes the use of Benders´ cut is presented in this paper. It is desirable to find the optimal solution in few iterations, especially in some test cases where the optimal results are expected to be obtained easily. However, the simple genetic algorithm has failed in finding the solution except through an extensive number of iterations. Different population generation and crossover methods are also tested and discussed. The method has been tested for 6 bus and 30 bus power systems to show its effectiveness. Further improvement for the method is also discussed.
Keywords
genetic algorithms; iterative methods; linear programming; power system analysis computing; power system planning; reactive power; Benders´ cut; computer simulation; crossover methods; iterations; modified simple genetic algorithm; operational optimization sub-problems; optimization method; population generation; population selection; power system planning; reactive power; successive linear programming; Computational modeling; Genetic algorithms; Investments; Linear programming; Optimization methods; Power system planning; Reactive power; Robustness; Simulated annealing; Testing;
fLanguage
English
Journal_Title
Power Systems, IEEE Transactions on
Publisher
ieee
ISSN
0885-8950
Type
jour
DOI
10.1109/59.476049
Filename
476049
Link To Document