Computational Intelligence for Control of Wind Turbine Generators

Authors

Wei Qiao, University of Nebraska–LincolnFollow
Jiaqi Liang, Georgia Institute of TechnologyFollow
Ganesh K. Venayagamoorthy, Missouri University of Science and TechnologyFollow
Ronald Harley, University of KwaZulu-Natal, DurbanFollow

Document Type

Article

Date of this Version

2011

Citation

2011 IEEE Power and Energy Society General Meeting, doi: 10.1109/PES.2011.6039778

Comments

Copyright IEEE (2011). Used by permission.

Abstract

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.