Maximum Power Point Tracking for Photovoltaic Optimization Using Ripple-Based Extremum Seeking Control

This study develops a maximum power point tracking algorithm that optimizes solar array performance and adapts to rapidly varying irradiance conditions. In particular, a novel extremum seeking (ES) controller that utilizes the natural inverter ripple is designed and tested on a simulated solar array with a grid-tied inverter. The new algorithm is benchmarked against the perturb and observe (PO) method using high-variance irradiance data gathered on a rooftop array experiment in Princeton, NJ. The ES controller achieves efficiencies exceeding 99% with transient rise-time to the maximum power point of less than 0.1 s. It is shown that voltage control is more stable than current control and allows for accurate tracking of faster irradiance transients. The limitations of current control are demonstrated in an example. Finally, the effect of capacitor size on the performance of ripple-based ES control is investigated.