Computational intelligence for control of wind turbine generators

This paper summarizes past and ongoing research in the area of the application of computational intelligence (CI) for control of wind turbine generators (WTGs). Several intelligent design approaches and control strategies, including optimal design of WTG controllers using particle swarm optimization (PSO) and mean-variance optimization (MVO) algorithms and adaptive critic design-based coordinated optimal adaptive control for wind plants and shunt FACTS devices, are presented for dynamic performance and fault ride-through enhancement of WTGs and the associated power grid. The effectiveness of these intelligent design approaches and control strategies are demonstrated by nonreal- and real-time simulations in PSCAD/EMTDC and RSCAD/RTDS, respectively.