ANN-based adaptive PI control for wind turbine with doubly fed induction generator

Baohua Dong, Sohrab Asgarpoor, Wei Qiao
2011 2011 North American Power Symposium  
This paper focuses on developing a novel algorithm which dynamically optimizes the controllers of doubly fed induction generator (DFIG) driven by a wind turbine (WT) to increase DFIG transient performance in all wind speed conditions. Particle swarm optimization (PSO) is proposed to optimize parameters of PI controllers of DFIG's rotor side/grid side converters (RSC/GSC) at different wind speeds in order to maximize the damping ratios of the system eigenvalues in small signal stability
more » ... stability analysis. Based on the optimal values and the wind speed data set, an artificial neural network (ANN) is designed, trained, and it has the ability to quickly forecast the optimal values of parameters. Adaptive PI controllers (including ANN) are designed which dynamically change PI gain values according to different wind speeds. Simulation is done via PSCAD software for a single machine connected to an infinite bus (SMIB) system. The results show that the DFIG of ANNbased adaptive PI control could significantly contribute in the transient performance improvement in a wide wind speed range. Index Terms-Particle swarm optimization, DFIG, small signal stability, artificial neural network, damping ratio, optimal control, transient performance, and PSCAD
doi:10.1109/naps.2011.6025106 fatcat:lhossjr3ubayparzkre7njg3yu