Improved genetic algorithm for reactive power optimization of distribution system

2003 ◽  
Author(s):  
Zhao Hongwei
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Reactive Power ◽  
Power Optimization ◽  
Reactive Power Optimization ◽  
Improved Genetic Algorithm

scholarly journals Reactive Power Optimization of Wind Farm based on Improved Genetic Algorithm

2012 ◽  
Vol 14 ◽  
pp. 1362-1367 ◽  
Author(s):  
Xiang-jun Zeng ◽  
Jin Tao ◽  
Ping Zhang ◽  
Hui Pan ◽  
Yuan-yuan Wang
Keyword(s):  
Genetic Algorithm ◽  
Wind Farm ◽  
Reactive Power ◽  
Power Optimization ◽  
Reactive Power Optimization ◽  
Improved Genetic Algorithm

Reactive Power Optimization of Hydropower Station Based on Improved Genetic Algorithm

2011 ◽  
Vol 71-78 ◽  
pp. 2214-2217
Author(s):  
Wei Tian ◽  
Jin Chan Wang ◽  
Yu Cheng Ye ◽  
Wei Chen
Keyword(s):  
Genetic Algorithm ◽  
Reactive Power ◽  
Power Optimization ◽  
Hydropower Station ◽  
Reactive Power Optimization ◽  
Improved Genetic Algorithm ◽  
C Language ◽  
Crossover Probability ◽  
Mutation Strategy ◽  
Crossover And Mutation

In this paper, an improved GA was proposed to minimum the disadvantages of classic GA. This modified GA improved the crossover and mutation strategy by using of sort program to arrange chromosome from big to small. The crossover probability and mutation probability were decided by the numbers of the order. Samples were chosen to take part in interbreeding. The convergence speed and results can be improved in this way. Moreover, premature convergence and local convergence were avoided at the same time. The modified GA was implemented by an optimization program compiled in visual C++ language. It has been successfully applied in the reactive power optimization of a Hydropower station. The results showed the feasibility and validity of this modified genetic algorithm.

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