An Adaptive Perturb and Observe Algorithm With Enhanced Skipping Feature for Fast Global Maximum Power Point Tracking Under Partial Shading Conditions

Solar energy exposed its prominence to diminish the growing energy demands. But the formation of multiple peaks under partial shading conditions causes the conventional maximum power point tracking controllers to fail to track the global maximum power point (GMPP). Scanning the whole power-voltage curve to locate the GMPP takes extreme time and reduces algorithm effectiveness. Thus, the proposed method devotes the skipping and scanning mechanism incorporated with the perturb and observe (P & O) algorithm to reduce the scanning area drastically. The skipping mechanism skips over the scanning areas between successive peaks based on a specific formula that narrows down the scanning zone. Along with a buck-boost converter, the system includes a voltage control loop controlled by a proportional-integral controller. The proposed algorithm's effectiveness is tested in both simulation and experimental environments on discretized partial shading patterns, while GMPP is deployed at different locations. According to the experimental outcomes, the proposed algorithm outperforms the modified maximum power trapezium, skipping fast GMPP, modified cuckoo search, and the conventional P & O algorithm with an average convergence time of 1.02 s and average efficiency of 99.44%.