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Maximum power point tracking (MPPT) techniques are a fundamental part in photovoltaic system design for increasing the generated output power of a photovoltaic array. Whilst varying techniques have been proposed, the adaptive neural-fuzzy inference system (ANFIS) is the most powerful method for an MPPT because of its fast response and less oscillation. However, accurate training data are a big challenge for designing an efficient ANFIS-MPPT. In this work, an ANFIS-MPPT method based on a large simulation training data is designed to avoid the system from experiencing a high training error. To evaluate the performance, the proposed ANFIS-MPPT method is simulated using a MATLAB/Simulink model for a photovoltaic system. The results reveal that the proposed method accurately tracks the optimized maximum power point whilst achieving efficiencies of more than 99.3%.

MATLAB Implementation of ANFIS Based MPPT for Solar PV System

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