TARIQ KAMAL, Luis M. Fernández-Ramírez, Murat Karabacak, Raúl Sarrias-Mena, Pablo García-Triviño, and Syed Zulqadar Hassan
Adaptive control, Photovoltaic , Inverter, Wavelet, Renewable Energy
Inverters are critical for injecting power from renewable energy sources into the grid or grid-integrated load. This paper provides a novel improved adaptive neuro-fuzzy control of inverter for grid-coupled photovoltaic systems. The improvement is performed by the integration of Jacobi wavelet in the existing neuro-fuzzy controller. Unlike existing neuro-fuzzy controller, the new proposed controller is capable to locate the exact local minima, which sequentially improves the performance of the proposed controller. Simulations are performed to show that the proposed controller is better than the existing state-of-the- art in terms of power transfer, inverter output efficiency, and load voltage frequency.
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