Evaluation of maximum power point tracking methods for photovoltaic systems

The output characteristics of photovoltaic (PV) arrays are nonlinear and change with the solar irradiance and the cell's temperature. Therefore, a maximum power point tracking (MPPT) technique is needed to draw peak power from the solar array to maximize the produced energy. Among the hill climbing methods, the perturb and observe (P&O) method tracks the maximum power point (MPP) by repeatedly increasing or decreasing the output voltage at the MPP of the PV module. The implementation of the method is relatively simple, but it cannot track the MPP when the irradiance varies quickly with time. In addition, itmay cause system oscillation around the peak power points due to the effect of measurement noise. The incremental conductance (IncCond) method is also often used in PV systems. This method tracks the MPPs by comparing the incremental and instantaneous conductances of the solar array. This method requires longer conversion time, and a large amount of power loss results. In addition, extra hardware circuitry is required to implement the system. In this paper, it is shown that the negative effects associated with such a drawback can be greatly reduced if the intelligent method is used to improve P&O and IncCond algorithms. The perturbation step is continuously approximated by using fuzzy logic controller (FLC). By the digital simulation, the validity of the proposed control algorithm is proved