Pitch angle control using hybrid controller for all operating regions of SCIG wind turbine system

In the past, wind power penetration was extremely limited compared to the total power production. As a result, the interconnection requirements for wind farms were not included in the grid codes. However, in the recent years, the significant amount of energy injected by wind farms has already impacted the power system, both from a technical and a regulatory point of view in the recent years. Large wind plants have a significant influence on power system operation since they are related to unpredictability of the primary source. Thus wind turbines must improve their quality production to ensure the stability and reliability of the power system as conventional power plants. Wind energy is not constant and, since wind turbines output is proportional to the cube of wind speed, this causes the power output of Squirrel-Cage Induction Generator Wind Turbine (SCIG WT) to fluctuate. In order to improve power quality and maintain the stable output generated from SCIG wind farm, this paper presents a hybrid controller based on PI and fuzzy technique for the pitch angle controller which has been one of the most common methods for smoothing output power fluctuations. All models as well as controllers here presented are developed using Matlab-Simulink software.

[1]  M. A. Chowdhury,et al.  Smoothing wind power fluctuations by fuzzy logic pitch angle controller , 2012 .

[2]  Thomas Ackermann,et al.  Wind Power in Power Systems , 2005 .

[3]  Tomonobu Senjyu,et al.  Output power leveling of wind turbine Generator for all operating regions by pitch angle control , 2006 .

[4]  Tomonobu Senjyu,et al.  Output leveling of wind power generation system by EDLC energy storage system , 2006 .

[5]  Ahmet Serdar Yilmaz,et al.  Pitch angle control in wind turbines above the rated wind speed by multi-layer perceptron and radial basis function neural networks , 2009, Expert Syst. Appl..

[6]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[7]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[8]  T. Funabashi,et al.  Output power leveling of wind turbine generator by pitch angle control using adaptive control method , 2004, 2004 International Conference on Power System Technology, 2004. PowerCon 2004..

[9]  Junji Tamura,et al.  Smoothing control of wind generator output fluctuations by PWM voltage source converter and chopper controlled SMES , 2011 .

[10]  Earl Cox,et al.  The fuzzy systems handbook - a practitioner's guide to building, using, and maintaining fuzzy systems , 1994 .

[11]  Francesco Grimaccia,et al.  Hybrid model for hourly forecast of photovoltaic and wind power , 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[12]  J. G. Slootweg,et al.  Representing wind turbine electrical generating systems in fundamental frequency simulations , 2003 .

[13]  J. Clare,et al.  Power smoothing in wind generation systems using a sensorless vector controlled induction Machine driving a flywheel , 2004, IEEE Transactions on Energy Conversion.

[14]  Tomonobu Senjyu,et al.  Terminal voltage and output power control of induction generator by series and parallel compensation using SMES , 2004 .

[15]  Marcelo Godoy Simões,et al.  Controle e modelagem Fuzzy , 1999 .

[16]  Mariesa L. Crow,et al.  Performance Indices for the Dynamic Performance of FACTS and FACTS with Energy Storage , 2004 .

[17]  Rashad M. Kamel,et al.  Wind power smoothing using fuzzy logic pitch controller and energy capacitor system for improvement Micro-Grid performance in islanding mode , 2010 .

[18]  Toshiaki Murata,et al.  Application of energy capacitor system to wind power generation , 2008 .

[19]  S. Arnalte,et al.  Automatic Generation Control of a Wind Farm with Variable Speed Wind Turbines , 2002, IEEE Power Engineering Review.

[20]  Nicholas Jenkins,et al.  Comparison of fixed speed and doubly-fed induction wind turbines during power system disturbances , 2003 .

[21]  Shigeo Abe.  Fuzzy function approximators with ellipsoidal regions , 1999, IEEE Trans. Syst. Man Cybern. Part B.

[22]  S. H. Jangamshetti,et al.  Normalized Power Curves as a Tool for Identification of Optimum Wind Turbine Generator Parameters , 2001, IEEE Power Engineering Review.

[23]  Geng Yang,et al.  Output Power Control for Variable-Speed Variable-Pitch Wind Generation Systems , 2010, IEEE Transactions on Energy Conversion.

[24]  S.M. Muyeen,et al.  Wind Generator Output Power Smoothing and Terminal Voltage Regulation by Using STATCOM/ESS , 2007, 2007 IEEE Lausanne Power Tech.

[25]  R. Jones,et al.  Application of a power-controlled flywheel drive for wind power conditioning in a wind/diesel power system , 1999, IEMDC 1999.

[26]  Tomonobu Senjyu,et al.  Output power leveling of wind farm using pitch angle control with fuzzy neural network , 2006 .

[27]  J. Cidras,et al.  Synchronization of asynchronous wind turbines , 2002 .