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Mohammed Akherraz
Laboratory of Power Electronics and Control, Mohammadia School's of Engineers, Mohammed V University of Rabat, Morocco
Control & Systems Engineering Electrical & Electronics Engineering

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Advanced Direct Power Control for Grid-connected Distribution Generation System Based on Fuzzy Logic and Artificial Neural Networks Techniques Mustapha Jamma; Abderrahim Bennassar; Mohamed Barara; Mohammed Akherraz
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 8, No 3: September 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v8.i3.pp979-989

Abstract

This paper proposes an improvement of the direct power control (DPC) scheme of a grid connected three phase voltage source inverter based on artificial neural networks (ANN) and fuzzy logic (FL) techniques for the renewable energy applications. This advanced control strategy is based on two intelligent operations, the first one is the replacement of the conventional switching table of a three phase voltage source inverter (VSI) by a selector based on artificial neural networks approach, and the second one is the replacement of the hysteresis comparators by fuzzy logic controllers for the instantaneous active and reactive power errors. These operations enable to reduce the power ripples, the harmonic disturbances and increase the response time period of the system. Finally, the simulation results were obtained by Matlab/Simulink environment, under a unity power factor (UPF). These results verify the transient performances, the validity and the efficiency of the proposed DPC scheme.
Co-Authors Abderrahim Bennassar Mohamed Barara Mustapha Jamma