
On Advanced Control Methods toward Power Capture and Load Mitigation in Wind Turbines
Yuan Yuan, Jiong Tang
Engineering ›› 2017, Vol. 3 ›› Issue (4) : 494-503.
On Advanced Control Methods toward Power Capture and Load Mitigation in Wind Turbines
This article provides a survey of recently emerged methods for wind turbine control. Multivariate control approaches to the optimization of power capture and the reduction of loads in components under time-varying turbulent wind fields have been under extensive investigation in recent years. We divide the related research activities into three categories: modeling and dynamics of wind turbines, active control of wind turbines, and passive control of wind turbines. Regarding turbine dynamics, we discuss the physical fundamentals and present the aeroelastic analysis tools. Regarding active control, we review pitch control, torque control, and yaw control strategies encompassing mathematical formulations as well as their applications toward different objectives. Our survey mostly focuses on blade pitch control, which is considered one of the key elements in facilitating load reduction while maintaining power capture performance. Regarding passive control, we review techniques such as tuned mass dampers, smart rotors, and microtabs. Possible future directions are suggested.
Wind turbine / Control approach / Power optimization / Load mitigation
[1] |
Ginley DS, Cahen D, editors. Fundamentals of materials for energy and environmental sustainability. Cambridge: Cambridge University Press; 2012.
|
[2] |
Beiter P, Tian T. 2015 Renewable energy data book. Report. Washington D.C.: US Department of Energy; 2016 Nov.
|
[3] |
Pao LY, Johnson KE. A tutorial on the dynamics and control of wind turbines and wind farms. In: Proceedings of the 2009 American Control Conference; 2009 Jun 10–12; St. Louis, MO, USA. Piscataway: IEEE Press; 2009. p. 2076–89.
CrossRef
Google scholar
|
[4] |
Jonkman JM, Butterfield S, Musial W, Scott G. Definition of a 5-MW reference wind turbine for offshore system development. Report. Golden: National Renewable Energy Laboratory; 2009 Feb. Report No.: NREL/TP-500-38060.
|
[5] |
Namik H, Stol K. Disturbance accommodating control of floating offshore wind turbines. In: Proceedings of the 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition; 2009 Jan 5–8; Orlando, FL, USA. Reston: AIAA; 2009. p. 483.
CrossRef
Google scholar
|
[6] |
Pao LY, Johnson KE. Control of wind turbines. IEEE Control Systems 2011;31(2):44–62.
CrossRef
Google scholar
|
[7] |
Wright AD. Modern control design for flexible wind turbines. Report. Golden: National Renewable Energy Laboratory; 2004 Jul. Report No.: NREL/TP-500-35816.
|
[8] |
Wright AD, Balas MJ. Design of controls to attenuate loads in the controls advanced research turbine. J Sol Energy Eng 2004;126(4):1083–91.
CrossRef
Google scholar
|
[9] |
Stol KA, Zhao W, Wright AD. Individual blade pitch control for the controls advanced research turbine (CART). J Sol Energy Eng 2006;128(4):498–505.
CrossRef
Google scholar
|
[10] |
Wright A, Fingersh L, Stol K. Designing and testing controls to mitigate tower dynamic loads in the controls advanced research turbine. In: Proceedings of the 45th AIAA Aerospace Sciences Meeting and Exhibit; 2007 Jan 8–11; Reno, NV, USA. Reston: AIAA; 2007. p. 1021.
CrossRef
Google scholar
|
[11] |
Jonkman JM, Buhl ML Jr. FAST user’s guide. Report. Golden: National Renewable Energy Laboratory; 2005 Aug. Report No.: NREL/EL-500-38230.
|
[12] |
Bossanyi E. GH Bladed theory manual. Bristol: Garrad Hassan & Partners Ltd; 2011.
|
[13] |
Larsen TJ, Hansen AM. How 2 HAWC2, the user's manual. Roskilde: Risø National Laboratory; 2007 Dec.
|
[14] |
Øye S. FLEX4 simulation of wind turbine dynamics. In: Proceedings of the 28th Meeting of Experts on State of the Art of Aerolastic Codes for Wind Turbine Calculation; 1996 Apr 11–12; Lyngby, Denmark. Paris: International Energy Agency; 1996. p. 71–7.
|
[15] |
Moriarty PJ, Hansen AC. AeroDyn theory manual. Report. Golden: National Renewable Energy Laboratory; 2005 Jan. Report No.: NREL/TP-500-36881.
|
[16] |
Miller R. Helicopter control and stability in hovering flight. J Aeronaut Sci 1948;15(8):453–72.
CrossRef
Google scholar
|
[17] |
Bir G. Multiblade coordinate transformation and its application to wind turbine analysis. Report. Golden: National Renewable Energy Laboratory; 2008 Jan. Report No.: NREL/CP-500-42553.
|
[18] |
Laks J, Pao L, Wright A, Kelley N, Jonkman B. The use of preview wind measurements for blade pitch control. Mechatronics 2011;21(4):668–81.
CrossRef
Google scholar
|
[19] |
Yuan Y, Chen X, Tang J.Disturbance observer based pitch control of wind turbines for disturbance rejection. In: Proceedings of the SPIE Smart Structures and Materials and Nondestructive Evaluation and Health Monitoring. 2016 March 20–24; Las Vegas, USA. Bellingham: SPIE; 2016. p. 980609.
|
[20] |
Frost SA, Balas MJ, Wright AD. Direct adaptive control of a utility-scale wind turbine for speed regulation. Int J Robust Nonlinear Control 2009;19(1):59–71.
CrossRef
Google scholar
|
[21] |
Johnson C. Theory of disturbance-accommodating controllers. Contr Dyn Syst 1976;12:387–489.
CrossRef
Google scholar
|
[22] |
Johnson C. Disturbance-accommodating control—Overview of the subject. J Interdiscipl Model Simulat 1980;3(1):1–29.
|
[23] |
Johnson C. Discrete-time disturbance-accommodating control theory with applications to missile digital control. J Guid Control Dyn 1981;4(2):116–25.
CrossRef
Google scholar
|
[24] |
Johnson C. Disturbance-accommodating control—An overview. In: Proceedings of the 1986 American Control Conference; 1986 Jun 18–20; Seattle, USA. Piscataway: IEEE Press; 2009. p. 526–36.
|
[25] |
Kendall L, Balas MJ, Lee Y, Fingersh L. Application of proportional-integral and disturbance accommodating control to variable speed variable pitch horizontal axis wind turbines. Wind Eng 1997;21(1):21–38.
|
[26] |
Balas MJ, Lee YJ, Kendall L. Disturbance tracking control theory with application to horizontal axis wind turbines. In: Proceedings of the 1998 ASME Wind Energy Symposium; 1998 Jan 12–15; Reno, NV, USA. Reston: AIAA; 1998. p. 95–9.
CrossRef
Google scholar
|
[27] |
Stol K, Rigney B, Balas M. Disturbance accommodating control of a variable-speed turbine using a symbolic dynamics structural model. In: Proceeding of the 2000 ASME Wind Energy Symposium; 2000 Jan 10–13; Reno, NV, USA. Reston: AIAA; 2000. p. 84.
CrossRef
Google scholar
|
[28] |
Stol KA, Balas MJ. Periodic disturbance accommodating control for blade load mitigation in wind turbines. J Sol Energy Eng 2003;125(4):379–85.
CrossRef
Google scholar
|
[29] |
Hand MM. Mitigation of wind turbine/vortex interaction using disturbance accommodating control. Report. Golden: National Renewable Energy Laboratory; 2003 Dec. Report No.: NREL/TP-500-35172.
|
[30] |
Hand MM, Balas MJ. Blade load mitigation control design for a wind turbine operating in the path of vortices. Wind Energy 2007;10(4):339–55.
CrossRef
Google scholar
|
[31] |
Wang N, Wright AD, Balas MJ. Disturbance-accommodating control-based individual blade pitch control design for two-bladed turbines. In: Proceedings of the 34th Wind Energy Symposium, AIAA SciTech Forum; 2016 Jan 4–8; San Diego, CA, USA. Reston: AIAA; 2016. p. 1736.
|
[32] |
Wang N, Wright AD, Johnson KE. Independent blade pitch controller design for a three-bladed turbine using disturbance accommodating control. In: Proceedings of the 2016 American Control Conference; 2016 Jul 6–8; Boston, MA, USA. Golden: National Renewable Energy Laboratory; 2016. p. 2301–6.
CrossRef
Google scholar
|
[33] |
Wang N, Wright AD, Balas MJ. Disturbance accommodating control design for wind turbines using solvability conditions. J Dyn Syst Meas Control 2017;139(4):041007.
CrossRef
Google scholar
|
[34] |
Pace A, Johnson K, Wright A. Preventing wind turbine overspeed in highly turbulent wind events using disturbance accommodating control and light detection and ranging. Wind Energy 2015;18(2):351–68.
CrossRef
Google scholar
|
[35] |
Camacho EF, Bordons C. Model predictive control . Berlin: Springer; 1999.
CrossRef
Google scholar
|
[36] |
Soliman M, Malik O, Westwick D. Multiple model MIMO predictive control for variable speed variable pitch wind turbines. In: Proceedings of the 2010 American Control Conference; 2010 Jun 30–Jul 2; Baltimore, MD, USA. Piscataway: IEEE Press; 2010. p. 2778–84.
CrossRef
Google scholar
|
[37] |
Henriksen LC. Model predictive control of a wind turbine [dissertation]. Lyngby: Technical University of Denmark; 2007.
|
[38] |
Schlipf D, Grau P, Raach S, Duraiski R, Trierweiler J, Cheng PW. Comparison of linear and nonlinear model predictive control of wind turbines using LIDAR. In: Proceedings of the 2014 American Control Conference; 2014 Jun 4–6; Portland, OR, USA. Piscataway: IEEE Press; 2014. p. 3742–7.
CrossRef
Google scholar
|
[39] |
Kumar A, Stol K. Scheduled model predictive control of a wind turbine. In: Proceedings of the 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition; 2009 Jan 5–8; Orlando, FL, USA. Reston: AIAA; 2009. p. 481.
CrossRef
Google scholar
|
[40] |
Schlipf D, Schlipf DJ, Kühn M. Nonlinear model predictive control of wind turbines using LIDAR. Wind Energy 2013;16(7):1107–29.
CrossRef
Google scholar
|
[41] |
Bottasso C, Croce A, Savini B. Performance comparison of control schemes for variable-speed wind turbines. J Phys Conf Ser 2007;75:012079.
CrossRef
Google scholar
|
[42] |
Mirzaei M, Soltani M, Poulsen NK, Niemann HH. Model predictive control of wind turbines using uncertain LIDAR measurements. In: Proceedings of the 2013 American Control Conference; 2013 Jun 17–19; Washington D.C., USA. Piscataway: IEEE Press; 2013. p. 2235–40.
CrossRef
Google scholar
|
[43] |
Korber A, King R. Model predictive control for wind turbines. In: Proceedings of the European Wind Energy Conference ; 2010 Apr 20–23; Warsaw, Poland. Brussels: WindEurope; 2010.
|
[44] |
Simley E, Pao LY, Frehlich R, Jonkman B, Kelley N. Analysis of wind speed measurements using continuous wave LIDAR for wind turbine control. In: Proceedings of the 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. 2011 Jan 4–7; Orlando, FL, USA. Reston: AIAA; 2011. p. 263.
CrossRef
Google scholar
|
[45] |
Laks J, Pao LY, Simley E, Wright A, Kelley N, Jonkman B. Model predictive control using preview measurements from LIDAR. In: Proceedings of the 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition. 2011 Jan 4–7; Orlando, FL, USA. Reston: AIAA; 2011. p. 813.
CrossRef
Google scholar
|
[46] |
Santos RA. Damage mitigating control for wind turbines [dissertation]. Boulder: University of Colorado at Boulder; 2007.
|
[47] |
Odgaaard PF, Knudsen T, Overgaard A, Steffensen H, Jørgensen M. Importance of dynamic inflow in model predictive control of wind turbines. IFAC-PapersOnLine 2015;48(30):90–5.
CrossRef
Google scholar
|
[48] |
Spencer MD, Stol KA, Unsworth CP, Cater JE, Norris SE. Model predictive control of a wind turbine using short-term wind field predictions. Wind Energy 2013;16(3):417–34.
CrossRef
Google scholar
|
[49] |
Jain A, Schildbach G, Fagiano L, Morari M. On the design and tuning of linear model predictive control for wind turbines. Renew Energy 2015;80:664–73.
CrossRef
Google scholar
|
[50] |
Odgaard PF, Larsen LF, Wisniewski R, Hovgaard TG. On using Pareto optimality to tune a linear model predictive controller for wind turbines. Renew Energy 2016;87(Pt 2):884–91.
CrossRef
Google scholar
|
[51] |
Lescher F, Zhao JY, Martinez A. Multiobjective H2/H∞ control of a pitch regulated wind turbine for mechanical load reduction. Renew Energy Power Quality J 2006;1:100–5.
CrossRef
Google scholar
|
[52] |
Sloth C, Esbensen T, Niss MO, Stoustrup J, Odgaard PF.Robust LMI-based control of wind turbines with parametric uncertainties. In: Proceedings of the IEEE International Conference on Control Applications & Intelligent Control (2009); 2009 Jul 8–10; St. Petersburg, Russia. Piscataway: IEEE Press; 2009. p. 776–81.
CrossRef
Google scholar
|
[53] |
De Corcuera AD, Pujana-Arrese A, Ezquerra JM, Segurola E, Landaluze J. H∞ based control for load mitigation in wind turbines. Energies 2012;5(4):938–67.
CrossRef
Google scholar
|
[54] |
Vali M, van Wingerden JW, Kýhn M. Optimal multivariable individual pitch control for load reduction of large wind turbines. In: Proceedings of the 2016 American Control Conference; 2016 Jul 6–8; Boston, MA, USA. Piscataway: IEEE Press; 2016. p. 3163–9.
CrossRef
Google scholar
|
[55] |
Ozdemir AA, Seiler PJ, Balas GJ. Performance of disturbance augmented control design in turbulent wind conditions. Mechatronics 2011;21(4):634–44.
CrossRef
Google scholar
|
[56] |
Laks J, Pao L, Wright A. Combined feedforward/feedback control of wind turbines to reduce blade flap bending moments. In: Proceedings of the 47th AIAA Aerospace Sciences Meeting including The New Horizons Forum and Aerospace Exposition; 2009 January 5–8; Orlando, FL, USA. Reston: AIAA; 2009. p. 687.
CrossRef
Google scholar
|
[57] |
Wang N, Johnson KE. Combined LIDAR-based feedforward and feedback controllers for wind turbines with tower and blade damping. In: Proceedings of the 49th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition; 2011 Jan 4–7; Orlando, FL, USA. Reston: AIAA; 2011. p. 814.
CrossRef
Google scholar
|
[58] |
Van der Hooft E, Van Engelen T. Estimated wind speed feed forward control for wind turbine operation optimization. In: Proceedings of the European Wind Energy Conference; 2004 Nov 22 – 25; London, UK. Petten: Energy Research Centre of the Netherlands; 2004. p. 126.
|
[59] |
Selvam K, Kanev S, van Wingerden JW, van Engelen T, Verhaegen M. Feedback–feedforward individual pitch control for wind turbine load reduction. Int J Robust Nonlinear Control 2009;19(1):72–91.
CrossRef
Google scholar
|
[60] |
Laks J, Pao LY, Wright A, Kelley N, Jonkman B. Blade pitch control with preview wind measurements. In: Proceedings of the 48th AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition; 2010 Jan 4–7; Orlando, FL, USA. Reston: AIAA; 2010. p. 251.
CrossRef
Google scholar
|
[61] |
Dunne F, Pao LY, Wright AD, Jonkman B, Kelley N. Adding feedforward blade pitch control to standard feedback controllers for load mitigation in wind turbines. Mechatronics 2011;21(4):682–90.
CrossRef
Google scholar
|
[62] |
Wang N, Johnson KE, Wright AD. FX-RLS-based feedforward control for LIDAR-enabled wind turbine load mitigation. IEEE Trans Contr Syst Technol 2012;20(5):1212–22.
CrossRef
Google scholar
|
[63] |
Simley E, Pao L. Reducing LIDAR wind speed measurement error with optimal filtering. In: Proceedings of the 2013 American Control Conference; 2013 Jun 17–19; Washington, DC , USA. Piscataway: IEEE Press; 2013. p. 621–7.
CrossRef
Google scholar
|
[64] |
Scholbrock A, Fleming P, Fingersh L, Wright A, Schlipf D, Belen F. Field testing LIDAR based feedforward controls on the NREL controls advanced research turbine. In: Proceedings of the 51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and Aerospace Exposition; 2013 Jan 7–10; Grapevine, TX, USA. Reston: AIAA; 2013. p. 0818.
CrossRef
Google scholar
|
[65] |
Fleming P, Scholbrock A, Jehu A, Davoust S, Osler E, Wright A, et al.Field-test results using a nacelle-mounted LIDAR for improving wind turbine power capture by reducing yaw misalignment. J Phys Conf Ser 2014;524:012002.
CrossRef
Google scholar
|
[66] |
Johnson KE. Adaptive torque control of variable speed wind turbines. Report. Golden: National Renewable Energy Laboratory; 2004 Aug. Report No.: NREL/TP-500-36265.
|
[67] |
Johnson KE, Pao LY, Balas MJ, Kulkami V, Fingersh LJ. Stability analysis of an adaptive torque controller for variable speed wind turbines. In: Proceedings of the 43rd IEEE Conference on Decision and Control; 2004 Dec 14–17; Nassau, Bahamas. Piscataway: IEEE Press; 2005. p. 4087–94.
|
[68] |
Magar KT, Balas MJ, Frost SA. Direct adaptive torque control for maximizing the power captured by wind turbine in partial loading condition. Wind Energy 2015;19(5):911–22.
CrossRef
Google scholar
|
[69] |
Beltran B, Ahmed-Ali T, Benbouzid MEH. High-order sliding-mode control of variable-speed wind turbines. IEEE Trans Ind Electron 2009;56(9):3314–21.
CrossRef
Google scholar
|
[70] |
Boukhezzar B, Lupu L, Siguerdidjane H, Hand M. Multivariable control strategy for variable speed, variable pitch wind turbines. Renew Energy 2007;32(8):1273–87.
CrossRef
Google scholar
|
[71] |
Ekelund T. Yaw control for reduction of structural dynamic loads in wind turbines. J Wind Eng Ind Aerodyn 2000;85(3):241–62.
CrossRef
Google scholar
|
[72] |
Gebraad P, Teeuwisse F, Wingerden J, Fleming PA, Ruben S, Marden J, et al.Wind plant power optimization through yaw control using a parametric model for wake effects—A CFD simulation study. Wind Energy 2016;19(1):95–114.
CrossRef
Google scholar
|
[73] |
Marathe N, Swift A, Hirth B, Walker R, Schroeder J. Characterizing power performance and wake of a wind turbine under yaw and blade pitch. Wind Energy 2015;19(5):963–78.
CrossRef
Google scholar
|
[74] |
Fleming PA, Ning A, Gebraad PM, Dykes K. Wind plant system engineering through optimization of layout and yaw control. Wind Energy 2016;19(2):329–44.
CrossRef
Google scholar
|
[75] |
Gebraad P, Thomas JJ, Ning A, Fleming P, Dykes K. Maximization of the annual energy production of wind power plants by optimization of layout and yaw-based wake control. Wind Energy 2016;20(1):97–107.
CrossRef
Google scholar
|
[76] |
Murtagh P, Ghosh A, Basu B, Broderick B. Passive control of wind turbine vibrations including blade/tower interaction and rotationally sampled turbulence. Wind Energy 2008;11(4):305–17.
CrossRef
Google scholar
|
[77] |
Lackner MA, Rotea MA. Passive structural control of offshore wind turbines. Wind Energy 2011;14(3):373–88.
CrossRef
Google scholar
|
[78] |
Van Wingerden JW, Hulskamp AW, Barlas T, Marrant B, van Kuik G, Molenaar D, et al.On the proof of concept of a “smart” wind turbine rotor blade for load alleviation. Wind Energy 2008;11(3):265–80.
CrossRef
Google scholar
|
[79] |
Yen D, van Dam C, Smith R, Collins S. Active load control for wind turbine blades using MEM translational tabs. In: Proceedings of the 20th 2011 ASME Wind Energy Symposium; 2001 Jan 11–14; Reno, NV, USA. Reston: AIAA; 2001. p. 0031.
CrossRef
Google scholar
|
[80] |
Macquart T, Maheri A, Busawon K. Microtab dynamic modelling for wind turbine blade load rejection. Renew Energy 2014;64:144–52.
CrossRef
Google scholar
|
[81] |
Nakafuji DY, van Dam CP, Michel J, Morrison P. Load control for turbine blades: A non-traditional microtab approach. In: Proceedings of the 2002 ASME Wind Energy Symposium; 2002 Jan 14–17; Reno, NV, USA. Reston: AIAA; 2002. p. 321–30.
CrossRef
Google scholar
|
[82] |
Kumar AA, Bossanyi EA, Scholbrock AK, Fleming P, Boquet M, Krishnamurthy R.Field testing of LIDAR assisted feedforward control algorithms for improved speed control and fatigue load reduction on a 600 kW wind turbine. Report. Golden: National Renewable Energy Laboratory; 2015 Nov. Report No.: NREL/CP-5000-65062.
|
/
〈 |
|
〉 |