Abstract
The power available by the photovoltaic system changes with the change in insolation, temperature and load due to the nonlinear V-I characteristics of solar cell. A Maximum Power Point Tracking (MPPT) technique maximizes the output power of PV array by continuously tracking the maximum power point. This paper presents comparative analysis of two intelligent algorithms: Fuzzy logic and Artificial Neural Network based MPPT to track the maximum power point from the PV array. Fuzzy logic does not require the exact knowledge of the model and use heuristic reasoning based on experience which deal with the nonlinearity of PV arrays while ANN is trained with the output voltage and current of PV for analyzing the duty cycle of dc-dc boost converter followed by tracking the maximum power point of PV arrays. The designed intelligent algorithms have been compared with Incremental Conductance algorithm based on their dynamic behavior, efficiency and performance parameters.
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