Over a period of years, Maximum Power Point Tracking has become a mandatory requirement for Solar Photo Voltaic (PV) systems. Being dependent to environmental changes, the PV power constantly fluctuates due to change in irradiation. Under such conditions, large PV array connected in interconnection will experience non-uniform irradiation thus results multiple peaks in P-V characteristics. Although many conventional and soft computing techniques have been proposed in literature, the ability to identify global peak under strong shading conditions is not guaranteed. Particularly, local peak in close agreement to global peak makes most of the algorithms to get trapped in local peaks. This condition often occurs due to insufficient randomness in algorithm hence, a new Flower Pollination Algorithm (FPA) is investigated in this research. Proposed method has dual mode search ability which creates required randomness in every iteration is the key reason to suit FPA for MPPT. Simulation and experimental results verified with different patterns portray FPA excellence under all irradiated conditions. Further performance of FPA is verified with Particle swarm Optimization method and conventional P&O method.
