A Fast MPPT Algorithm for Smart Grid-PV Connected System Based on Multiple Sparse-Aware Time-Varying Stepsize Adaptation Technique

The performance of solar photovoltaic systems integrated into the smart grid is dependent on utilization of the Maximum Power Point Tracking (MPPT) algorithm. In order to enhance the tracking ability, attaining stability, and terminating the possibility of misestimating a decreasing or increasing solar photovoltaic voltage, a multiple sparse-aware time-varying stepsize adaptation algorithm for the conventional MPPT method is proposed in this paper. The underlying purpose of this proposed technique, rather than using currently estimated power values, is to predict the power values of solar PV system to maximize efficiency and attain better performance. The prediction of power builds on an L-1 formerly estimated values of the PV voltage. Furthermore, the adaptation process is based on a time-adjusting stepsize that modifies according to the log value of the individual input voltage of the PV system to the adaptive filter. The proposed approach offers a fast-tracking capability and possesses a quick reaction to environmental alterations such as temperature and irradiance. Simulations show the superiority of the proposed technique in terms of supplying instantaneous tracking ability to the maximum power point, maintaining low steady-state error, and achieving a robust performance under rapid variations of atmospheric circumstances compared with standard algorithms.