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. © 2011 IEEE.
Recommended Citation
W. Qiao et al., "Computational Intelligence for Control of Wind Turbine Generators," IEEE Power and Energy Society General Meeting, article no. 6039778, Institute of Electrical and Electronics Engineers, Dec 2011.
The definitive version is available at https://doi.org/10.1109/PES.2011.6039778
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Computational intelligence (CI); doubly fed induction generator (DFIG); dual heuristic programming (DHP); FACTS device; heuristic dynamic programming (HDP); particle swarm optimization (PSO); radial basis function neural network (RBFNN); wind turbine
International Standard Book Number (ISBN)
978-145771001-8
International Standard Serial Number (ISSN)
1944-9933; 1944-9925
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
09 Dec 2011
