Application of catastrophic adaptive genetic algorithm to reactive power optimization in power system with wind farm

A catastrophic adaptive genetic algorithm and its application to reactive power optimization in power system with farm are studied in detail. The multi-objective mathematical model is established, and the model includes network loss, stability margin of static voltage and average deviation of voltage. To improve convergence rate and avoid the premature convergence, the cataclysm operator is added into the adaptive genetic algorithm, and in reproduction operator, the method of retaining optimal individual is combined with the competition method; in mutation operator, the mutation probability Pm is improved. The new algorithm has been applied to IEEE 30-bus testing system with wind farm, and the test shows that the novel algorithm is effective and feasible.