Design of a hybrid MPPT method for PV systems under partial shading conditions

Nowadays where the world population is increasing rapidly, it is important to discuss the importance of limited resources along with the advancement of industry and technology. In recent years, the energy demand has been at an unprecedented level, leading humanity to seek new and inexhaustible resources. The fact that solar electricity production depends on factors such as solar radiation, temperature, and shading has led researchers to seek maximum utilization of this energy. Partial shading conditions on solar panels in particular have been one of the important factors that reduce the efficiency of photovoltaic systems. Various Maximum Power Point Tracking (MPPT) algorithms have been developed to prevent power losses due to weather conditions and partial shading. These algorithms aim to keep the system at the maximum power point by monitoring the current and voltage irregularities that occur in solar energy production. The aim of this thesis is to examine the MPPT methods, to compare various features and to develop a new hybrid method based on Perturb and Observe and Particle Swarm Optimization. In the study, a hybrid MPPT method is developed by using MATLAB/Simulink environment. The proposed method was tested under different irradiation level irradiance values of 1000 W/m2, 500 W/m2, 600 W/m2, 900 W/m2 and 800 W/m2, respectively. In addition, the developed algorithm was compared with various MPPT methods and the obtained results were examined in detail. It was concluded that the applied method was an efficient method in terms of convergence speed, tracking accuracy, and fluctuations for partial shading situations.