In grid connected wind turbine (WT) systems, the maximum power point tracking (MPPT) approach has a crucial role in optimizing the wind energy efficiency. To search for the maximum power value of the wind turbine, this contribution proposes a new Maximum Power Point Tracking System (MPPT) for wind turbine related to a permanent magnet synchronous generator (PMSG)). The new proposed MPPT combines two techniques: Artificial Neural Network (ANN) and Fuzzy Logic (FL). The ANN is employed to estimate the maximum voltage of the WT, for various values of wind speed, while the control of DC-DC boost converter operation is executed by applying Fuzzy Logic technique. The comparison of our proposed algorithm to P&O technique has shown that it ensures more efficiency, and we used for that a simulation under Matlab/Simulink.

This work presents a new Maximum Power Point Tracking (MPPT) for the connection of the wind turbine system (WT) to the synchronous permanent magnet generator (PMSG). To search the maximum power of the wind turbine, we have proposed a new MPPT which combines two techniques: Artificial Neural Network (ANN) and incremental conductance (IncCond) method. The advantage of ANN-based WT model method is the fast MPP approximation base on the ability of ANN according the parameters of WT that used. The advantage of IncCond method is the ability to search the exactly MPP based on the feedback voltage. In our case the ANN is employed to predict the maximum voltage of the WT, under different values of wind speed, and the control of DC–DC boost converter operation is executed by applying incremental conductance (IncCond) technique. The proposed system includes a wind turbine associated to a permanent magnet synchronous generator (PMSG), a rectifier and a DC-DC converter with MPPT control. The proposed algorithm is tested under MATLAB SIMULINK.

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This paper proposes a new maximum power point tracking (MPPT) technique for wind turbine Connection to a permanent magnet synchronous generator (PMSG), based on the Particle Swarm Optimization (PSO) algorithm. The PSO technique aims to control the boost converter by calculating the duty cycle value based on the voltage and current values. The Wind Energy Conversion System (WECS) includes a wind turbine, a PMSG, rectifier and a DC/DC boost converter that is connected to a load. To verify the performance of the suggested algorithm PSO, The results of the simulation are compared with those of fuzzy logic and (Perturb and Observe)P&O techniques, under step wind variations, using MATLAB/SIMULINK. The results of the simulation show that the proposed PSO technique ensures a good tracking of the maximum power point as the results obtained are more stable and the oscillations are eliminated.