Predictive control of wind turbines by considering wind speed forecasting techniques

Fixed speed wind turbines have low efficiency as compared to variable-speed, fixed-pitch wind turbines. The latter are required to optimize power output performance without the aerodynamic controls. A wind turbine system is operated such that the points of wind rotor curve and electrical generator curve coincide. In order to obtain maximum power output of a wind turbine generator system, it is necessary to drive the wind rotor at an optimal rotor speed for a particular wind speed. A Maximum Power Point Tracking (MPPT) controller is used for this purpose. In fixed-pitch variable-speed wind turbines, wind-rotor parameters are fixed and the restoring torque of the generator needs to be adjusted to maintain optimum rotor speed at a particular wind speed for optimum power output. In turbulent wind environment, control of variable-speed fixed-pitch wind turbine systems to continuously operate at the maximum power points becomes difficult due to fluctuation of wind speeds. Therefore, a special emphasis is given to operating at maximum aerodynamic power points of the wind rotor. In this study, wind speed forecasting techniques are considered for predictive optimum control system of wind turbines to reduce response time of the MPPT controller.

[1]  D. Marquardt An Algorithm for Least-Squares Estimation of Nonlinear Parameters , 1963 .

[2]  P. Young,et al.  Time series analysis, forecasting and control , 1972, IEEE Transactions on Automatic Control.

[3]  A. Brett,et al.  The Autocorrelation of Hourly Wind Speed Observations , 1991 .

[4]  Masatoshi Nakamura,et al.  Predictive control of wind turbines in small power systems at high turbulent wind speeds , 1997 .

[5]  T. O. Halawani,et al.  A neural networks approach for wind speed prediction , 1998 .

[6]  Michael Y. Hu,et al.  Forecasting with artificial neural networks: The state of the art , 1997 .

[7]  J. Keith Ord,et al.  Automatic neural network modeling for univariate time series , 2000 .

[8]  Ervin Bossanyi,et al.  Wind Energy Handbook , 2001 .

[9]  M. C. Deo,et al.  Forecasting wind with neural networks , 2003 .

[10]  Robert Kozma,et al.  A dynamic neural network method for time series prediction using the KIII model , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[11]  X. Wang,et al.  Wind speed forecasting for power system operational planning , 2005, 2004 International Conference on Probabilistic Methods Applied to Power Systems.

[12]  M. Bilgili,et al.  Application of artificial neural networks for the wind speed prediction of target station using reference stations data , 2007 .

[13]  Ioannis B. Theocharis,et al.  A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation , 2007, Neurocomputing.

[14]  Mohammad Monfared,et al.  A new strategy for wind speed forecasting using artificial intelligent methods , 2009 .