Hierarchical Pigeon-Inspired Optimization-Based MPPT Method for Photovoltaic Systems Under Complex Partial Shading Conditions

This article proposes a novel maximum power point tracking (MPPT) method based on the variant of the pigeon-inspired optimization (PIO) algorithm for photovoltaic systems under partial shading conditions (PSCs). The proposed method integrates the hierarchical network behavior of pigeon flock and revises the map and compass operator of the original PIO algorithm to improve optimization efficiency. In addition, the landmark operator is used to perform a small-scale search to achieve fast tracking. Based on the combination of these mechanisms and dual-mode dynamic tracking scheme, the proposed hierarchical pigeon-inspired optimization (HPIO) MPPT method has a powerful search ability to deal with PSCs. To verify the superiority of the proposed HPIO MPPT method, it is compared with other existing advanced MPPT methods in simulation and experiments. Compared with traditional MPPT techniques based on artificial intelligence, the proposed HPIO MPPT method has a higher success rate in tracking GMPP and excellent tracking speed under PSCs. And the HPIO method also shows excellent performance under complex PSC with multiple clusters and load-variation conditions.

Automated summary

This article proposes a maximum power point tracking (MPPT) method for photovoltaic systems under partial shading conditions (PSCs) based on the variant of the pigeon-inspired optimization (PIO) algorithm. The method integrates the hierarchical network behavior of pigeon flock and revises the algorithm's operators to improve optimization efficiency. It also uses a landmark operator for fast tracking. The proposed method shows superior performance in tracking GMPP and excellent performance in complex PSCs.