An optimized fuzzy maximum power point tracker for stand alone photovoltaic systems: Ant colony approach

In this paper, an optimized efficient technique for the maximum power point tracking (MPPT) of photovoltaic (PV) systems is introduced. This developed technique is derived from blending the ant system optimization method with the enhanced fuzzy agent technique. The fine tuning of the input weighting for the fuzzy agent is explored using Ant colony system algorithm. The proposed MPPT technique enhances the initial starting point of the traditional fuzzy MPPT algorithm using fractional open circuit voltage method leading to fast and accurate convergence to the maximum power point (MPP). The proposed ant based adaptive fuzzy-MPPT controller is tested on a simulated stand alone PV array with battery load and showed an optimal response. The developed controller not only ensures maximum power transfer but also outperforms the conventional fuzzy agent system proposed in our previous work. Simulation results reflect fast settling time and accurate tracking even under extreme variations in irradiance levels.