A new hybrid MPPT algorithm combining P&O and fuzzy logic techniques - Mrhar, Oumaima; Kandoussi, Khalid; Eljouad, Mohamed (Institute of Advanced Engineering and Science, 2025)
This study introduces an innovative approach to maximum power point tracking (MPPT) in photovoltaic systems using a hybrid algorithm that combines perturb and observe (P&O) with fuzzy logic. The novelty of this work lies in the choice of input variables for the fuzzy controller, specifically dV and dP, which addresses significant challenges such as slow response to environmental condition variations and limited responsiveness under low solar irradiation. This method of MPPT is modified to make it particularly suitable for extracting peak power from photovoltaic systems. To evaluate the effectiveness of this approach, a simulation was conducted using MATLAB/Simulink software on a system comprising a photovoltaic panel connected to the new controller. Simulation results indicate that the suggested hybrid algorithm surpasses traditional methods like perturb and observe (P&O) and fuzzy logic (FL) in several ways. It notably excels in response time and tracking efficiency, achieving a remarkable success rate of 99.7% in pinpointing the maximum power point. These outcomes could significantly boost the performance of photovoltaic systems and, consequently, further the adoption of renewable energy while lessening environmental impacts.