Photovoltaic (PV) systems have become essential in the transition to sustainable energy solutions. However, these systems face challenges in maximizing energy extraction, particularly under partial shading conditions. This study introduces an advanced Maximum Power Point Tracking (MPPT) approach that combines the Particle Swarm Optimization (PSO) algorithm with a Dynamic Monitoring Reset (DMR) mechanism. The DMR enhances the PSO’s ability to adapt and maintain tracking accuracy in rapidly changing shading environments, providing robust tracking of the Global Maximum Power Point (GMPP). Simulation results demonstrate that the PSO-DMR method significantly improves PV system efficiency, reducing energy losses and optimizing performance under variable and complex shading patterns.

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A PSO-Based MPPT with Dynamic Monitoring Reset for PV Systems

  • Igor de Matos da Rosa,
  • Alison R. Panisson,
  • Lenon Schmitz

摘要

Photovoltaic (PV) systems have become essential in the transition to sustainable energy solutions. However, these systems face challenges in maximizing energy extraction, particularly under partial shading conditions. This study introduces an advanced Maximum Power Point Tracking (MPPT) approach that combines the Particle Swarm Optimization (PSO) algorithm with a Dynamic Monitoring Reset (DMR) mechanism. The DMR enhances the PSO’s ability to adapt and maintain tracking accuracy in rapidly changing shading environments, providing robust tracking of the Global Maximum Power Point (GMPP). Simulation results demonstrate that the PSO-DMR method significantly improves PV system efficiency, reducing energy losses and optimizing performance under variable and complex shading patterns.