000			06974cam a22004217a 4500
003			CUTN
005			20250402122811.0
008			100421s2010 gw a b 001 0 eng d
020			_a9783662608937
020			_a9783642132490 (hdbk. : acidfree paper)
041			_aEnglish
042			_alccopycat
082	0	4	_a621.450 _222/ger _bWAN
245	0	0	_aWind power systems : _bapplications of computational intelligence / _cLingfeng Wang, Chanan Singh, and Andrew Kusiak (eds.).
260			_aBerlin : _bSpringer-Verlag, _cc2010.
300			_ax, 437 p. : _bill. ; _c24 cm.
490	1		_aGreen energy and technology
500			_a"With 256 figures and 63 tables."
504			_aIncludes bibliographical references and index.
505			_tOptimal 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
520			_aRenewable 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.
650		0	_aWind power.
650		0	_aWind energy conversion systems.
650		0	_aElectric power-plants.
650		0	_aComputational intelligence.
650	0	7	_aWindkraftwerk.
650	0	7	_aSoft Computing.
650	0	7	_2swd _94
650	0	7	_2swd _94
700	1		_aWang, Lingfeng.
700	1		_aSingh, Chanan.
700	1		_aKusiak, Andrew.
830		0	_aGreen energy and technology.
906			_a7 _bcbc _ccopycat _d2 _encip _f20 _gy-gencatlg
942			_2ddc _cBOOKS
999			_c44134 _d44134