Photovoltaics are extensively used as a premium device for generating electric-ity from solar planet's power. Under uniform radiation, the photovoltaics' output char-acteristics have a non-linear frame with a unique maximum power point. This point changes its position when a sudden change in solar radiation occurs. Otherwise, when the PV string is subjected to partial shading conditions, several power peaks have appeared with only one Global maximum power. The classical maximum power point tracking strategies always fails to deal with these dynamic difficulties, especially, under unex-pected climatic changes. Many soft computing methods are previously constructed to deal with these problems, but the main hurdles remain how to manage this tracking with the fastest time, the smallest power oscillations, and the greatest efficiency. In this paper, a modified Particle Swarm Optimization algorithm was proposed that capable of excluding or promoting certain parts of the solution search area until reach and track the max power point. The suggested method has been simulated and practically tested and the results indicate that the suggested method outperforms the typical Particle Swarm Optimization algorithm with regards to the speed of Global maximum power point tracking with the lowest oscillation and highest efficiency.