Maximum power tracking under partial shading conditions in photovoltaic systems

Due to the effects of fossil fuels on global warming and the decrease in their amount day by day, the production of electrical energy from these fuels is replaced by renewable energy sources. For this reason, the costs of solar energy, in other words photovoltaic (PV) systems, which were not preferred in terms of application costs in the past, have been reduced with the development of technology and thus their use has increased. The maximum power value that can be obtained from PV systems can vary continuously depending on environmental conditions such as temperature, solar irradiation and partial shading conditions. Especially in cases of partial shading, direct current-direct current (DC-DC) converters and maximum power point tracking (MPPT) algorithms are required in order to operate the PV system at the maximum power point, that is, to extract the maximum possible power value from the system. In this study, simulation studies have been carried out for two different partial shading scenarios using the boost type DC-DC converter and MPPT algorithm in a PV array consisting of 3 panels connected in series. In simulation studies, system output power obtained by the application of particle swarm optimization, cuckoo optimization, bat optimization, firefly optimization and perturb and observe techniques as MPPT algorithm has been compared. In the scenarios examined, it has been observed that the firefly optimization algorithm reached the maximum power point faster and the firefly optimization method has obtained the highest average power at the end of the simulation periods.