Research Description
Maximum Power Point Tracking (MPPT) is a promising technology for extracting
peak power from single or multiple solar modules for improving Photovoltaic (PV)
system performance and satisfying economic operation. The tracker should continu-
ously follow the MPP of the PV module at all operating and weather conditions. The
Particle Swarm Optimization (PSO) algorithm represents a powerful optimal MPP
tracker due to its simplicity and has enhanced greatest exploration characteristics.
This article proposes a new technique based on PSO enhanced with Quasi-Newton
local search for improving power quality while minimizing oscillation. This tracking
process is making the MPPT comparable between high accuracy and fast tracking
speed. MPPT proposal algorithm results are compared to the results of the hybrid
PSO-P&O algorithm at different operating conditions. The proposed algorithm results
show that MPP extraction has been done with a high-speed response and the best
efficiency. Moreover, the PSO is enhanced with a Quasi-Newton (QN) local search
method for tuning the optimal MPP.
