Pitch angle control for a small-scale Darrieus vertical axis wind turbine with straight blades (H-Type VAWT)

Abstract Unlike horizontal axis wind turbines (HAWTs), the Darrieus vertical axis wind turbine (H-type VAWT) has been the subject of only a few recent studies directed at improving its self-starting capability and/or aerodynamic performance. The technique currently used for improving the performance of this type of turbine is pitch angle control. This paper presents intelligent blade pitch control for enhancing the performance of H-type VAWTs with respect to power output. To determine the optimum pitch angles, ANSYS Fluent Computational Fluid Dynamics (CFD) software was used for a study of the aerodynamic performance of a 2D variable pitch angle H-type VAWT at a variety of tip speed ratios (TSRs). For each case examined, the power coefficient ( C p ) was calculated and compared to published experimental and CFD findings. The results obtained from the CFD model were then applied for the construction of an aerodynamic model of an H-type VAWT rotor, which constituted a prerequisite for designing an intelligent pitch angle controller using a multilayer perceptron artificial neural network (MLP-ANN) method. The performance of the MLP-ANN blade pitch controller was compared to that of a conventional controller (PID). The findings demonstrate that for an H-type VAWT, compared to a conventional PID controller, an MLP-ANN results in superior power output.

[1]  Javad Sargolzaei,et al.  Estimation of the power ratio and torque in wind turbine Savonius rotors using artificial neural networks , 2007 .

[2]  Mohit Singh,et al.  Dynamic models for wind turbines and wind power plants , 2011 .

[3]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[4]  Andrzej J. Fiedler,et al.  Blade Offset and Pitch Effects on a High Solidity Vertical Axis Wind Turbine , 2009 .

[5]  F. Menter.  ZONAL TWO EQUATION k-w TURBULENCE MODELS FOR AERODYNAMIC FLOWS , 1993 .

[6]  Hermann-Josef Wagner.  Introduction to wind energy systems , 2013 .

[7]  Yuichi Nakamura,et al.  Approximation of dynamical systems by continuous time recurrent neural networks , 1993, Neural Networks.

[8]  Brian H. Dennis,et al.  Aerodynamic Shape Optimization of a Vertical-Axis Wind Turbine Using Differential Evolution , 2012 .

[9]  P. Würfel,et al.  Physics of solar cells : from basic principles to advanced concepts , 2009 .

[10]  Yan Li,et al.  Numerical Study on the Performance Effect of Solidity on the Straight-Bladed Vertical Axis Wind Turbine , 2010, 2010 Asia-Pacific Power and Energy Engineering Conference.

[11]  A. Laneville,et al.  The aerodynamic forces for a Darrieus rotor with straight blades: Wind tunnel measurements , 1983 .

[12]  Alvaro Luna,et al.  An approach to the Performance-Oriented Model of Variable-Speed Wind turbines , 2010, 2010 IEEE International Symposium on Industrial Electronics.

[13]  J. R. Baker.  Features to aid or enable self starting of fixed pitch low solidity vertical axis wind turbines , 1983 .

[14]  Weiyong Chen,et al.  Application of numercal simulation to obtain the optimization pitch angle for VAWT , 2009, 2009 World Non-Grid-Connected Wind Power and Energy Conference.

[15]  I. Paraschivoiu.  Wind turbine design with emphasis on Darrieus concept [ressource électronique] / Ion Paraschivoiu , 2002 .

[16]  Bjoern Roscher.  Structural Optimization Of A Vertical Axis Wind Turbine With Aeroelastic Analysis , 2014 .

[17]  W. Marsden.  I and J , 2012 .

[18]  F. Saeed,et al.  H-Darrieus Wind Turbine with Blade Pitch Control , 2009 .

[19]  A. Buckspan.  Nonlinear Control of a Wind Turbine , 2012 .

[20]  Kevin Barraclough,et al.  I and i , 2001, BMJ : British Medical Journal.

[21]  Oscar Barambones.  A robust wind turbine control using a Neural Network based wind speed estimator , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[22]  Prediction of the power ratio and torque in wind turbine Savonius rotors using artificial neural networks , 2007 .

[23]  S. Mohanty.  Artificial neural network based system identification and model predictive control of a flotation column , 2009 .

[24]  Richard M. Murray,et al.  A Mathematical Introduction to Robotic Manipulation , 1994 .

[25]  A. Bharathi.  MATLAB Simulation of Power Electronic Converter for PMSG Based Wind Energy Conversion System , 2013 .

[26]  Yuan Zheng,et al.  Variable Pitch Approach for Performance Improving of Straight-Bladed VAWT at Rated Tip Speed Ratio , 2018, Applied Sciences.

[27]  Prerna Badoni,et al.  Modeling and Simulation of 2 MW PMSG Wind Energy Conversion Systems , 2014 .

[28]  Dong-Choon Lee,et al.  Advanced Pitch Angle Control Based on Fuzzy Logic for Variable-Speed Wind Turbine Systems , 2015, IEEE Transactions on Energy Conversion.

[29]  S Sapna,et al.  Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm , 2012 .

[30]  Ning Qin,et al.  Wind tunnel and numerical study of a small vertical axis wind turbine , 2008 .

[31]  Giovanni Ferrara,et al.  Critical issues in the CFD simulation of Darrieus wind turbines , 2016 .

[32]  David Wood,et al.  Observations of the starting behaviour of a small horizontalaxis wind turbine , 1997 .

[33]  Rajesh Bhaskaran,et al.  Introduction to CFD Basics , 2009 .

[34]  Brian Kinloch Kirke.  Evaluation of Self-Starting Vertical Axis Wind Turbines for Stand-Alone Applications , 1998 .

[35]  Jaime Peraire,et al.  Performance Characterization of Cyclic Blade Pitch Variation on a Vertical Axis Wind Turbine , 2011 .

[36]  Chao Li,et al.  2.5D large eddy simulation of vertical axis wind turbine in consideration of high angle of attack flow , 2013 .

[37]  Zhang Liang,et al.  Difference between Fixed and Variable Pitch Vertical Axis Tidal Turbine-Using CFD Analysis in CFX , 2013 .

[38]  Cheng-Hsiung Kuo,et al.  Effects of pitch angle and blade camber on flow characteristics and performance of small-size Darrieus VAWT , 2013, J. Vis..

[39]  Václav Skala,et al.  Vector Field Interpolation with Radial Basis Functions , 2016, SIGRAD.

[40]  Ratna Kishore Velamati,et al.  Numerical Analysis of Effect of Pitch Angle on a Small Scale Vertical Axis Wind Turbine , 2014 .

[41]  Toshiaki Murata,et al.  Comparative study on transient stability analysis of wind turbine generator system using different drive train models , 2007 .

[42]  Lorenzo Ferrari,et al.  Start-Up Behavior of a Three-Bladed H-Darrieus VAWT: Experimental and Numerical Analysis , 2011 .

[43]  S. Tullis,et al.  Flow separation on a high Reynolds number, high solidity vertical axis wind turbine with straight and canted blades and canted blades with fences , 2012 .

[44]  Fakhreddine O. Karray,et al.  Soft Computing and Intelligent Systems Design, Theory, Tools and Applications , 2006, IEEE Transactions on Neural Networks.

[45]  Sung-Hun Lee,et al.  Sliding mode controller for torque and pitch control of wind power system based on PMSG , 2010, ICCAS 2010.

[46]  Chi-Cong Nguyen,et al.  A Numerical Study of Thickness Effect of the Symmetric NACA 4-Digit Airfoils on Self Starting Capability of a 1kW H-Type Vertical Axis Wind Turbine , 2015 .

[47]  Greg Semrau,et al.  Dynamic modeling and characterization of a wind turbine system leading to controls development , 2010 .

[48]  Hans Bernhoff,et al.  Measurements of the Aerodynamic Normal Forces on a 12-kW Straight-Bladed Vertical Axis Wind Turbine , 2015 .

[49]  Yan Chen.  Numerical simulation of the aerodynamic performance of an H-rotor , 2011 .

[50]  Sang-Hoon Oh,et al.  Error back-propagation algorithm for classification of imbalanced data , 2011, Neurocomputing.

[51]  Weeratunge Malalasekera,et al.  An introduction to computational fluid dynamics - the finite volume method , 2007 .

[52]  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..

[53]  S. Nikravesh.  Nonlinear Systems Stability Analysis: Lyapunov-Based Approach , 2013 .

[54]  R. Stephenson.  A and V , 1962, The British journal of ophthalmology.

[55]  Neil Genzlinger.  A. and Q , 2006 .

[56]  Pinal Thakkar.  Neural Networks Satisfying Stone-weiestrass Theorem And Approximating , 2004 .

[57]  Maciej Chmielewski,et al.  Three-zonal Wall Function for k-ε Turbulence Models , 2013 .

[58]  Abhishek Abhishek,et al.  Performance prediction and fundamental understanding of small scale vertical axis wind turbine with variable amplitude blade pitching , 2016 .

[59]  Tarun Khanna,et al.  Foundations of neural networks , 1990 .

[60]  Chi Jeng Bai,et al.  Performance analysis of vertical-axis-wind-turbine blade with modified trailing edge through computational fluid dynamics , 2016 .

[61]  C. Masson,et al.  An extended k–ε model for turbulent flow through horizontal-axis wind turbines , 2008 .

[62]  S. Y. Liang,et al.  Design and Test of a Vertical-Axis Wind Turbine with Pitch Control , 2012 .

[63]  Dhruv Rathi.  Performance Prediction and Dynamic Model Analysis of Vertical Axis Wind Turbine Blades with Aerodynamically Varied Blade Pitch. , 2012 .

[64]  P. Olver.  Nonlinear Systems , 2013 .

[65]  Nikola Kasabov,et al.  Foundations Of Neural Networks, Fuzzy Systems, And Knowledge Engineering [Books in Brief] , 1996, IEEE Transactions on Neural Networks.

[66]  Seung Jo Kim,et al.  Efficiency improvement of a new vertical axis wind turbine by individual active control of blade motion , 2006, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[67]  Ramji Tiwari,et al.  Comparative Analysis of Pitch Angle Controller Strategies for PMSG Based Wind Energy Conversion System , 2017 .

[68]  Yibing Liu,et al.  Intelligent control for large-scale variable speed variable pitch wind turbines , 2004 .