Abstract
This paper presents a new adaptive neural control technique for maximum power point tracking (MPPT) in standalone photovoltaic (PV) system. The proposed strategy exploits the online-trained adaptive linear neuron (ADALINE). The proposal is based on the PV panel power characteristic to control its output voltage for reaching the maximum power point. For more reliability, the ADALINE based MPPT strategy is implemented with indirect control mode. Therefore, a proportional-integral controller is designed in order to generate a desired duty cycle. Efficiency and dynamic performances of the proposed MPPT methods are tested according to the European Standard EN 50530 Test. Experimental tests are conducted to prove the proposals efficiency. Comparisons with the conventional perturb & observe (P&O) algorithm is performed. Obtained results lead to conclude that the ADALINE based MPPT methods yields better performances than the conventional P&O algorithm, especially, in term of convergence speed and efficiency at low and fast irradiance profile.
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