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- W2350455000 abstract "On the basis of using genetic algorithm,this paper through improving the shortcomings of the theory to make the algorithm have some advantages in application to reactive power optimization in power system,The theory: improved encoded,selection operator,self-adaptively crossover rate and mutation rate,and also compounded the fitness function with simulated annealing and chaos algorithm,which made the improved genetic algorithm converge to the optimal solution with high speed as well as accurately. Traditional genetic algorithm's shortcoming of bad convergency and efficiency is overcome. This paper established a mathematical model of reactive power optimization based on it and gives specific steps. The algorithm is tested on IEEE30-bus,and the results verify the feasibility and effectiveness of the proposed algorithm." @default.
- W2350455000 created "2016-06-24" @default.
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- W2350455000 date "2014-01-01" @default.
- W2350455000 modified "2023-09-23" @default.
- W2350455000 title "Reactive Power Optimization based on Improved Hybrid Genetic Algorithm" @default.
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