Intelligent maximum power point tracker enhanced by sliding mode control

Hussain Attia, Ahmad Elkhateb


In solar photovoltaic systems applications, the maximum power point tracker has been involved for different purposes to support their performance. The maximum power point tracking (MPPT) works on growing the obtained electricity from the solar photovoltaic energy and consequently increases the quantity of the delivered electrical power from the photovoltaic (PV) system. Relying on this point, this paper introduces an intelligent tracker to guarantee the MPP working condition for a small size 150 W stand-alone PV system. In this study, an intelligent algorithm is proposed to have a fast and accurate tracker. Moreover, a robust sliding mode controller is inserted for improving the performance of a direct current (DC-DC) boost converter. The converter is working in a continuous conduction mode operation to enhances the MPP tracker. Simulink of MATLAB is adopted to implement the system. The results of the simulated tracker are evaluated comparatively based on the artificial neural network (ANN) algorithm with and without inserting the sliding mode (SM) controller for different light intensity trends and levels. Simulation results analyzed and confirmed the effectiveness of the proposed tracker.


ANN algorithm; DC-DC boost converter; MPPT; Photovoltaic PV cell; Sliding mode control SMC

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