Doubly Fed Induction Generators: Control for Wind Energy provides a detailed source of information on the modeling and design of controllers for the doubly fed induction generator (DFIG) used in wind energy applications. Focusing on the use of nonlinear control techniques, this book:
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Discusses the main features and advantages of the DFIG
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Describes key theoretical fundamentals and the DFIG mathematical model
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Develops controllers using inverse optimal control, sliding modes, and neural networks
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Devises an improvement to add robustness in the presence of parametric variations
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Details the results of real-time implementations
All controllers presented in the book are tested in a laboratory prototype. Comparisons between the controllers are made by analyzing statistical measures applied to the control objectives.
Preface
Chapter 1 : Introduction
Chapter 2 : Mathematical Preliminaries
Chapter 3 : Modeling of Wind Turbines
Chapter 4 : DFIG Control for Renewable Energy Systems
Chapter 5 : Neural Network Control of Wind Turbine Induction Generators
Chapter 6 : Implementation of Wind Energy Testbed
Appendix A : Particle Swarm Optimization for Control Algorithms
Appendix B : DFIG Modeling
References
Index
