Title : 
Improved genetic algorithm and its application in power dispatch of wind turbines
         
        
            Author : 
Guo-Huang Li;Guo-Li Zhang;Le-Feng Zhang
         
        
            Author_Institution : 
Department of Mathematics &
         
        
        
        
            fDate : 
7/1/2015 12:00:00 AM
         
        
        
        
            Abstract : 
The local search capability of classical genetic algorithm is weak, and hardly deals with constraints. To solve these problems, the adaptive crossover probability and mutation probability are developed, and a new genetic algorithm with quasi-simplex technique is proposed in this paper. An active power and reactive power dispatch model of wind farm turbine is established, and a better scheduling scheme can be worked out by using improved genetic algorithm. This scheduling scheme obtains less copper loss and shows that the improved genetic algorithm has a good application value.
         
        
        
            Conference_Titel : 
Machine Learning and Cybernetics (ICMLC), 2015 International Conference on
         
        
        
            DOI : 
10.1109/ICMLC.2015.7340658