Novel Hybrid MPPT based on modified incremental conductance-grey wolf optimization for grid connected PV systems

In recent years, the utilization of renewable energy sources has expanded significantly to mitigate the adverse effects associated with conventional energy sources, particularly carbon dioxide (CO₂) emissions. Due to the intermittent nature of the Photovoltaic (PV) system, the output power of the PV system fluctuates which affects the output power and power quality of the power system. Maximum power point tracking techniques (MPPT) are utilized to overcome efficiency and power quality problems. In this paper, a hybrid MPPT algorithm is proposed to improve efficiency and power quality for grid-connected PV systems. The proposed MPPT combines modified incremental conductance and grey wolf Optimization. Incremental Conductance (INC), Modified Incremental Conductance (M_INC), Perturb & Observe (P&O), Modified Perturb & Observe (M_P&O), and Grey Wolf Optimization (GWO) MPPT methods are implemented in MATLAB and compared with the proposed algorithm. The simulation results ensure the outperform of the proposed algorithm to the other algorithms by possessing the lowest THD of 2.31% and it reaches the efficiency of 99.71% with less oscillation at the output.