Modified Artificial Fish Swarm Algorithm (MAFSA) based on the global search characteristic of Artificial Fish Swarm Algorithm (AFSA), and combined with the local search of chao optimization algorithm(COA), can avoid trapping into local minimal value and decrease the iteration numbers, which was a swarm intelligence optimization algorithm applied to continuous space. MAFSA was proposed to optimize the reactive power optimization, which applied for optimal reactive power is evaluated on an IEEE 30-bus power system. The modeling of reactive power optimization is established taking the minimum network losses as the objective. The simulation results and the comparison results with various optimization algorithms demonstrated that the MAFSA converges to better solutions than other approaches and the algorithm can make effectively use in reactive power optimization. Simultaneously, the validity and superiority of MAFSA was proved.
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