A.M. Al-Naamany, A Gastli, and H. Bourdoucen (Oman)
Maximum Power point, Tracker, PhotoVoltaic, Fuzzy logic Controller
This paper presents an Adaptive Neuro Fuzzy-based maximum power point tracking controller. The controller uses temperature and sun light irradiation as input variables and outputs the corresponding peak power and voltage values. The model used in the controller offers efficient way to maximise the power output of the solar cells. This is achieved by identifying the optimal operating features of the power-voltage characteristics of the cells. The designed Neuro Fuzzy Controller is trained using a set of data generated by simulation samples of solar cell I V characteristics. The model was validated using the training data as well as other set of data different from the one used during the training process.
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