"With 256 figures and 63 tables."

Includes bibliographical references and index.

Optimal Allocation of Power-Electronic Interfaced Wind
Turbines Using a Genetic Algorithm – Monte Carlo Hybrid
Optimization Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Peiyuan Chen, Pierluigi Siano, Zhe Chen, Birgitte Bak-Jensen
Optimal Conductor Size Selection in Distribution Systems
with Wind Power Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
Hamid Falaghi, Chanan Singh
Global Optimization of Wind Farms Using Evolutive
Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
Angel G. Conzalez-Rodriguez, Javier Serrano-Conzalez,
Jesus M. Riquelme-Santos, Manuel Burgos-Pay´an,
Jose Castro-Mora, S.A. Persan
Capacity Benefit Margin Evaluation in Multi-area Power
Systems Including Wind Power Generation Using Particle
Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
Maryam Ramezani, Hamid Falaghi, Chanan Singh
Stochastic Dispatch of Power Grids with High Penetration
of Wind Power Using Pareto Optimization . . . . . . . . . . . . . . . . . . 125
Ali T. Al-Awami, Mohamed A. El-Sharkawi
Wind Turbine Diagnostics Based on Power Curve Using
Particle Swarm Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
Lisa Ann Osadciw, Yanjun Yan, Xiang Ye, Glen Benson, Eric White
Optimal Controller Design of a Wind Turbine with
Doubly Fed Induction Generator for Small Signal Stability
Enhancement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Lihui Yang, Guang Ya Yang, Zhao Xu, Zhao Yang Dong,
Yusheng Xue
Eigenvalue Analysis of a DFIG Based Wind Power System
under Different Modes of Operations . . . . . . . . . . . . . . . . . . . . . . . . 191
Y. Mishra, S. Mishra, Fangxing Li, Z.Y. Dong
An ANN-Based Power System Emergency Control Scheme
in the Presence of High Wind Power Penetration . . . . . . . . . . . . 215
Bevrani H., Tikdari A.G.
Intelligent Control of Power Electronic Systems for Wind
Turbines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
Bharat Singh, S.N. Singh, Elias Kyriakides
Intelligent Controller Design for a Remote Wind-Diesel
Power System: Design and Dynamic Performance
Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 297
Hee-Sang Ko, Kwang Y. Lee, Ho-Chan Kim
Adaptive Fuzzy Control for Variable Speed Wind Systems
with Synchronous Generator and Full Scale Converter . . . . . . . 337
V. Calderaro, C. Cecati, A. Piccolo, P. Siano
Application of TS-Fuzzy Controller for Active Power
and DC Capacitor Voltage Control in DFIG-Based Wind
Energy Conversion Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
S. Mishra, Y. Mishra, Fangxing Li, Z.Y. Dong
Fuzzy Logic as a Method to Optimize Wind Systems
Interconnected with the Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 383
Paulo J. Costa, Adriano S. Carvalho, Ant´onio J. Martins
Intelligent Power System Frequency Regulations
Concerning the Integration of Wind Power Units . . . . . . . . . . . . 407
H. Bevrani, F. Daneshfar, R.P. Daneshmand
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439

Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emitants, and can enhance a nation’s energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution.

Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods,the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up-to-date work and representative practical problems collecting contributions from leading experts in electrical engineering, system engineering, and other disciplines.