Abstract
Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver the maximum power available. This paper proposes two methods of maximum power point tracking using a fuzzy logic and a neural network approach for photovoltaic (PV) module Kyocera KC200GT using MATLAB software. The two maximum power point tracking controllers receive solar radiation and photovoltaic cell temperature as inputs, and estimated the maximum power point and the current and voltage corresponding to it as outputs. The new method gives a good maximum power operation of any photovoltaic array under different conditions (varying atmospheric conditions) such as changing solar radiation and PV cell temperature. From the simulation results, the Neural Network approach can deliver more power and provides a response time response from the tracking system from the point of maximum power and pics lower than the fuzzy logic control.
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