Generalized cryptographic image processing approaches using integer-series transformation for solar power optimization under partial shading

Abstract

Extracting the optimal power from the PV arrays under partial shading conditions (PSC) is challenging. Despite employing bypass diodes, maximum power point trackers, and current injection strategies to mitigate the shading impact, the array yields a considerably sub-optimal output. So, array reconfiguration strategies are employed to overcome this. However, most of the existing static reconfiguration strategies suffer scalability is sues, perform arbitrary shade dispersal, and yield distorted array characteristics. Hence, this paper proposes novel PV array configurations based on three distinct image processing strategies employing the integer sequence-based transformation to optimize the array output under PSC. The effectiveness of the proposed strategies is examined using the encryption parameters, histogram analysis and correlation scatter plots. Further, they are implemented for 9 × 9 symmetrical and 5 × 10 unsymmetrical PV arrays and their performance is compared with the 20 existing strategies under 24 distinct shading conditions. Besides, the proposed reconfi guration approaches are validated experimentally for a 4 × 4 PV array in the laboratory and outdoor environ ments. The qualitative comparison of proposed strategies with state-of-art techniques is discussed in detail. The simulation and hardware results confirm the competency and superiority of the proposed strategies in optimally reconfiguring the PV array yielding the enhancement in output by 32.62%, 20.66%, 16.67%, 14.79%, 13.68%, 13.48% under distinct cases.