Advanced SOA-ANFIS technique for maximum power extraction in grid-linked PV systems

Extracting the maximum energy yield from the solar Photovoltaic (PV) systems is the most essential and crucial tasks due to the increased need of energy demand. Hence, the different types of Maximum Power Point Tracking (MPPT) controlling mechanisms are developed in the existing work. Among other types, an intelligent optimization based MPPT techniques are widely used in many works, due to their accurate solution and convergence velocity. However, it faced the challenges relevant to the factors of complex system modeling, more time, increased error rate, and inaccurate tracking. Therefore, the proposed research work intends to implement an intelligent Seagull Optimization Algorithm (SOA) – Adaptive Neuro Fuzzy Inference System (ANFIS) based MPPT controlling algorithm for gaining the maximum possible power from the PV systems. Here, an interleaved boost DC-DC converter has been utilized to boost and regulate the output voltage of PV systems with reduced oscillations. Also, Pulse Width Generator (PWM) signals are generated for the inverter to reduce the harmonic distortions in the output. During analysis, an extensive simulation results are taken by using the MATLAB/Simulink tool based on various evaluation parameters.