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 :
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