Design and comparison of MPPT controllers with fuzzy logic and particle swarm optimization for PV power conversion

Abstract

The string and micro inverters are the widely used new device topologies in solar power conversion. In many solar inverters, the dc/dc converter is used in a two-stage structure, and are operated by a single maximum power point tracking (MPPT) controller. This study deals with the improvement of MPPT algorithms that are proposed with fuzzy logic controller (FLC), hybrid Perturb-Observe (P&O) based FLC, and particle swarm optimization (PSO). The presented methods have been improved and compared in terms of efficiency and tracking capability over conventional P&O method. The comparisons have been performed regarding, to rapidly changing irradiation values and corresponding PV voltages. Several weather conditions simulated have been applied to three MPPT controllers, and simulation results have been investigated. The obtained results have proved that FLC and P&O FLC MPPT methods are significantly efficient in tracking MPP degrade. The observed case studies have also shown that the proposed FLC based and PSO MPPT algorithms remarkably eliminate the limitations with efficiency exceeding 95% comparing to individual P&O algorithm.