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A sliding mode control and artificial neural network based MPPT for a direct grid‐connected photovoltaic source
Authors:Sid‐Ahmed Touil  Nasserdine Boudjerda  Ahsene Boubakir  Khalil El Khamlichi Drissi
Abstract:A robust sliding mode controller for a grid‐connected photovoltaic source is proposed in this paper. The objective of the presented control scheme is to force both the output voltage of the photovoltaic PV source and the power factor at the inverter output to follow a certain trajectory reference. The main idea is to apply the robust sliding mode controller directly to the nonlinear state model of the system composed of the PV source and the inverter with its input and output filters. In order to operate the PV system at the maximum power point and to satisfy the environmental factors, such as solar irradiance and temperature, we included a rigorous maximum power point tracker based on an artificial neural network. Simulation results are presented to illustrate the performance of the proposed control scheme. In addition, we show that the grid current satisfies the harmonic limits of the IEEE standard for interconnecting distributed energy sources with electric power systems.
Keywords:artificial neural network  grid connection  harmonic distortion  maximum power point tracker  photovoltaic source  sliding mode control
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