Abstract
ABSTRACT This article visualises the growth of harvesting solar energy by a solar photovoltaic (SPV) system and techniques for tracking the maximal power point. An active maximal power point tracking controller is put forward to harvest the solar power named an improved analysis of variance (ANOVA)-tuned algorithm. In this configuration of the SPV system, maximal power yield is obtained from the multi photovoltaic (PV) string through the DC–DC boost converter. To obtain the maximal power from the PV string, the optimal duty cycle has to be maintained in a DC–DC boost converter. To achieve a sustained duty cycle, an improved ANOVA-tuned maximum power point tracking (MPPT) controller is proposed as an optimal controller. The performance of the proposed controller was compared with that of a conventional perturb and observe controller for steady-state and dynamic conditions. The result of the proposed MPPT scheme has maximal power and obviously a better tracking path. The simulation is carried out in the MATLAB/Simulink environment, and the experimental result shows the benefits of the proposed MPPT techniques. The supremacies of the proposed controller are a preferable tracking response, less training data time, effective steady state and dynamic performances.
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