Genetic Algorithm And Backstepping Controller For Photovoltaic System Under Partial Shading Effect

Since the weather conditions are variable and unpredictable, and the PV power depends heavily to these conditions, different MPPT and GMPPT techniques are proposed and improved to make the photovoltaic power works at its maximum of power. In this context, this paper proposes a novel global maximum power point tracking technique based on the genetic algorithm combined with the Backstepping controller. The genetic algorithm serves for looking for the reference voltage corresponding to the global maximum power point, while the robust Backstepping controller is designed to follow this reference by acting on the duty cycle of the SEPIC converter. The performances of the proposed technique are tested and validated by comparing the proposed technique with the P&O-SMC, P&O-BSC, InC-SMC and InC-SMC MPPT techniques, and the GMPPT technique based PSO-SMC. The results have seen that the proposed technique can successfully track the global maximum while the MPPT techniques falling on the local maximum in some cases. In addition, the results show the performances criteria, of the proposed technique, which are better than the PSO-BSC technique tracking performances under the partial shading effect.