Simulation Analysis of a New Improved P&O Algorithm in Photovoltaic Controllers

In the context of escalating global energy demands and environmental challenges, renewable energy utilization has garnered significant attention. Among these, photovoltaic (PV) power generation stands out as a crucial form of renewable energy, profoundly influencing both energy utilization efficiency and economic benefits. Nonetheless, practical PV generation frequently encounters issues like uneven lighting and localized shading, phenomena that trigger array mismatches and hot spots, significantly diminishing the power generation efficiency and system safety. To tackle these challenges and enhance the speed and precision of Maximum Power Point Tracking (MPPT) in complex shadowing scenarios, this study introduces an innovative MPPT control method that combines the strengths of the Improved Particle Swarm Optimization (IPSO) and Disturbance and Observation (P&O) algorithms. The performance of this method in PV controllers is then rigorously analyzed. The findings reveal that under challenging shadow conditions, our proposed IPSO-P&O algorithm significantly enhances MPPT tracking speed and accuracy, effectively mitigates the negative impacts of array mismatches and hot spots on power generation efficiency, and ultimately improves the overall performance and safety of PV power generation systems.