New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system

• Extraction MPP (maximum power point) in WECS.
• Using new neural networks and fuzzy logic controllers to extract the MPP.
• These controllers applied to grid connected DFIG.
• Controlling active and reactive powers through the rotor circuit and the grid.

This work presents a new control strategy to ensure maximum power point tracking for a DFIG (doubly fed induction generator) based WECS (wind energy conversion system). The proposed strategy uses neural networks and fuzzy logic controllers to control the power transfer between the machine and the grid using the indirect vector control and reactive power control techniques. This transfer is ensured by controlling the rotor via two identical converters. The first converter is connected to the RSC (rotor side) and the second is connected to the GSC (grid side) via a filter. The DC (Direct Current) link voltage is controlled by a fuzzy controller. This control strategy is used to control the rotor side currents and to protect the generator by limiting the output current (or voltage).