An Improved PSO-Based Maximum Power Point Tracking Algorithm for Distributed Photovoltaic System Under Partial Shading

Abstract:
Module-level power electronics with distributed characteristics makes it possible to significantly improve the output power of traditional centralized photovoltaic(PV) systems in the case of series or parallel mismatches. However, for distributed PV systems, when partial shading occurs in a single PV module, there will still be multiple local extreme points on its Power-voltage(P-V) characteristic curve, forming a multi-peak feature, which makes traditional maximum power point tracking(MPPT) methods ineffective and unable to find the true maximum power point of the module. Therefore, this paper takes advantage of module-level power electronics, and designs the four-switch Buck-Boost converter as the module-level power optimizer for distributed PV systems. At the same time, the paper focusing on the module multipeak seeking optimization problem in distributed PV power systems, proposes a module-level multipeak MPPT optimization algorithm based on the improved particle swarm optimization(PSO), which utilizes an improved particle swarm optimization algorithm based on the traditional perturbation observation method in order to perform a global search for multi-peaks. Compared to the traditional PSO algorithm, the proposed algorithm operates on the principle of prioritizing particles that are closer to the global best power value, which filters the initial positions and search areas of the particles. This approach reduces the number of iterations needed in the tracking process, decreases power oscillations during transient tracking of the maximum power point, and improves the tracking accuracy of the traditional PSO algorithm.