Multi-objective Extremum Seeking Control for Enhancement of Wind Turbine Power Capture with Load Reduction

The primary objective in below rated wind speed (Region 2) is to maximize the turbine's energy capture. Due to uncertainty, variability of turbine characteristics and lack of inexpensive but precise wind measurements, model-free control strategies that do not use wind measurements such as Extremum Seeking Control (ESC) have received significant attention. Based on a dither-demodulation scheme, ESC can maximize the wind power capture in real time despite uncertainty, variabilities and lack of accurate wind measurements. The existing work on ESC based wind turbine control focuses on power capture only. In this paper, a multi-objective extremum seeking control strategy is proposed to achieve nearly optimum wind energy capture while decreasing structural fatigue loads. The performance index of the ESC combines the rotor power and penalty terms of the standard deviations of selected fatigue load variables. Simulation studies of the proposed multi-objective ESC demonstrate that the damage-equivalent loads of tower and/or blade loads can be reduced with slight compromise in energy capture.

[1]  Lucy Pao,et al.  Optimal Control of Wind Energy Systems: Towards a Global Approach (Munteanu, I. et al.; 2008) [Bookshelf] , 2009, IEEE Control Systems.

[2]  Yaoyu Li,et al.  Maximizing Wind Turbine Energy Capture Using Multivariable Extremum Seeking Control , 2009 .

[3]  Miroslav Krstic,et al.  Power optimization and control in wind energy conversion systems using extremum seeking , 2014, 2013 American Control Conference.

[4]  Azad Ghaffari,et al.  Multivariable Newton-based extremum seeking , 2012, Autom..

[5]  Bart Peeters,et al.  Full-scale modal wind turbine tests: comparing shaker excitation with wind excitation , 2011 .

[6]  Miroslav Krstic,et al.  Performance improvement and limitations in extremum seeking control , 2000 .

[7]  Hai-Jiao Guo,et al.  Review and critical analysis of the research papers published till date on maximum power point tracking in wind energy conversion system , 2010, 2010 IEEE Energy Conversion Congress and Exposition.

[8]  Jakob Stoustrup,et al.  Gain-scheduled Linear Quadratic Control of Wind Turbines Operating at High Wind Speed , 2007, 2007 IEEE International Conference on Control Applications.

[9]  Kathryn E. Johnson,et al.  Methods for Increasing Region 2 Power Capture on a Variable-Speed Wind Turbine , 2004 .

[10]  Kathryn E. Johnson,et al.  A tutorial on the dynamics and control of wind turbines and wind farms , 2009, 2009 American Control Conference.

[11]  Jason Jonkman,et al.  FAST User's Guide , 2005 .

[12]  Xin Ma,et al.  Adaptive Extremum Control and Wind Turbine Control , 1997 .

[13]  Kathryn E. Johnson,et al.  Controls Advanced Research Turbine: Lessons Learned during Advanced Controls Testing , 2005 .

[14]  M Soliman,et al.  Multiple Model Predictive Control for Wind Turbines With Doubly Fed Induction Generators , 2011, IEEE Transactions on Sustainable Energy.

[15]  Mario A. Rotea,et al.  Analysis of multivariable extremum seeking algorithms , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[16]  Yaoyu Li,et al.  Experimental evaluation of extremum seeking based region-2 controller for CART3 wind turbine , 2016 .

[17]  Chee Wei Tan,et al.  A review of maximum power point tracking algorithms for wind energy systems , 2012 .

[18]  M. Krstić,et al.  Real-Time Optimization by Extremum-Seeking Control , 2003 .

[19]  Quan Chen,et al.  Dual-loop self-optimizing robust control of wind power generation with Doubly-Fed Induction Generator. , 2015, ISA transactions.