An improved mind evolutionary algorithm for reactive power optimization

This paper presents an improved mind evolutionary algorithm (IMEA) to optimal reactive power dispatch and voltage control of power system. The improved mind evolutionary algorithm introduces the niche technique into the classical swarm algorithm to improve the global search capability, keeps the swarm diversity and accelerate the searching speed. Study the IMEA to construct the collection of discrete solution values, then the transformer taps and the reactive power source accurately described as discrete value during the whole optimization process. By this way, making the variable expression accurately reflects the actual situation, optimized results are more realistic. The IMEA applied for reactive power optimization is evaluated on an IEEE 30-bus power system. Simulation results compared with the others same type algorithms, proved its effectiveness and superiority.