Improved FMAC Based Adaptive Neural Power System Stabilizer for a DFIG

An adaptive neural power system stabilizer (ANPSS) based on the improved flux magnitude and angle control (IFMAC) was proposed to control a double fed induction generator (DFIG) based wind turbine. Firstly, the dynamic of DFIG including the transient dynamic of rotor and stator was theoretically analyzed, and based on which, the IFMAC strategy was also given and analyzed. Secondly, based on which, an ELAMN artificial neural network (ANN) was used to stabilize oscillations of DFIGs during various disturbances, where the classical back-propagation (BP) algorithm was introduced to train the ANN online for adaptive purpose, and the Jacobian Matrix was replaced by its sign to reduce the computational burden. The comparative results show that the proposed ANPSS worked with the IFMAC together can enhance system damping and improve power system transient stability.