AN Optimized Genetic Algorithm (GA)-Based MPPT for Off-Grid Solar Photovoltaic System
Mariem Mallat, Olfa Bel Hadj Brahim Kechiche, Kawther Ezzeddine, Mahmoud Hamouda
Abstract
Maximum power point tracking (MPPT) algorithms play a key role in a photovoltaic (PV) energy conversion system, which should inherently operate at its maximum available power. Genetic algorithms (GA) have shown their capability to solve different optimization problems and also their superiority to many other methods. In this paper, a GA-based MPPT algorithm is implemented to extract the maximum power from an off-grid PV system. To convert the generated DC power from the PV arrays into adequate AC power to supply different types of loads, a double-stage power conversion topology is adopted. A DC-DC boost converter is firstly, connected to the terminals of the PV modules. The GAbased MPPT algorithm is, thereafter, implemented to adjust the duty cycle of the boost converter in a way to achieve MPP operation of the PV modules. Then, a stand-alone PV inverter is connected in cascade with the boost converter to feed the AC loads. A numerical model of the whole PV conversion platform is developed using Matlab/Simulink software. Thereafter, different simulation tests are performed considering a real case of an off-grid PV installation located in the city of Mzaougha, Monastir (Tunisia) in an isolated area from distribution grid of the national company of electricity. An adequate PV module, which satisfies the energetic needs of the site is also selected and its real model is used for simulations. The obtained results confirm the feasibility of the proposed technique and its effectiveness in controlling an off-grid PV system.