Advanced Direct Power Control for Grid-connected Distribution Generation System Based on Fuzzy Logic and Artificial Neural Networks Techniques

Mustapha Jamma (Laboratory of Power Electronics and Control, Mohammadia School's of Engineers, Mohammed V University of Rabat, Morocco)
Abderrahim Bennassar (Laboratory of Power Electronics and Control, Mohammadia School's of Engineers, Mohammed V University of Rabat, Morocco)
Mohamed Barara (Université de Lyon, F-69622, Université Claude Bernard Lyon 1, Villeurbanne CNRS UMR 5005, Laboratoire Ampère, Lyon, France)
Mohammed Akherraz (Laboratory of Power Electronics and Control, Mohammadia School's of Engineers, Mohammed V University of Rabat, Morocco)

International Journal of Power Electronics and Drive Systems (IJPEDS)
Vol 8, No 3: September 2017

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.