Reactive Power Optimization Based On Adaptive Mutation Multi-group Particle Swarm Optimization Algorithm

Particle swarm optimization (PSO) based on swarm intelligence is a newevolutionary computational tool. This thesis introduces the algorithm of PSO and itscharacteristics, and also, some current applications in electric power systems. Then itputs forward a new algorithm—Adaptive Mutation Multi-group Particle SwarmOptimization (AMMPSO). The mutation positions are chosen to be global best (gbest),particle best (pbest) and multi-group best (mbest) respectively. The mutation of mbestproved to be the most satisfactory. Then it is applied to IEEE 6, 14 and 30 bus systemsand the validity and efficiency are confirmed by the numerical results.