Disturbance rejection by dual pitch control and self-tuning regulator for wind turbine generator parametric uncertainty compensation

IET Control Theory and Applications

Volumn 1, Issue 5, 2007, Pages 1431-1440

  Muhando, E B ^a   Senjyu, T ^a   Yona, A ^a   Kinjo, H ^a   Funabashi, T ^b  

^a UNIVERSITY OF THE RYUKYUS   (Japan)

^b MEIDENSHA CORPORATION   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPUTER SIMULATION; TUNING; UNCERTAINTY ANALYSIS; WIND TURBINES;

ROTATIONAL SPEED; SELF-TUNING REGULATOR (STR); WIND TURBULENCE INTENSITIES;

DISTURBANCE REJECTION;

EID: 34548045498     PISSN: 17518644     EISSN: 17518652     Source Type: Journal    
DOI: 10.1049/iet-cta:20060448     Document Type: Article

References (15)

1. De Battista, H., Puleston, P.F., Mantz, R.J., and Christiansen, C.F.: ' Sliding mode control of wind energy systems with DOIG - power efficiency and torsional dynamics optimization ', IEEE Trans. Power Syst., 2000, 15, (2), p. 728-734 10.1109/59.867166 0885-8950
2. Eggers, A., Moriarty, P., Chaney, K., Digumarthi, R., and Holley, W.: ' Influence of transition modes and gravity loads on rotor fatigue and power control ', Proc. 21st ASME Wind Energy Symp., 2002, p. 237-245
3. Bhowmik, S., Spee, R., and Enslin, J.: ' Performance optimization for doubly-fed wind power generation systems ', IEEE Trans. Indust. Appl., 1999, 35, (4), p. 949-958
4. Enslin, J., and Wyk, J.V.: ' A study of a wind power converter with micro-computer based maximal power control utilising an over-synchronous electronic scherbius cascade ', Renewable Energy, 1992, 2, (6), p. 551-562 10.1016/0960-1481(92)90018-X
5. Leithead, W.E., de la Salle, S., and Reardon, D.: ' Role and objectives of control for wind turbines ', IEE Proc., 1991, 138C, (2), p. 135-148
6. Goodwin, G.C., and Sin, K.S.: ' Adaptive filtering prediction and control ', (Prentice-Hall, New Jersey, 1984)
7. Muhando, E., Kinjo, H., Uezato, E., Senjyu, T., and Yamamoto, T.: ' Online neurocontrol design optimized by a genetic algorithm for a multi-trailer system ', SICE Trans., 2006, 42, (9), p. 1017-1026
8. Flores, P., Tapia, A., and Tapia, G.: ' Application of a control algorithm for wind speed prediction and active power generation ', Renewable Energy, 2005, 30, p. 523-536
9. Li, S., Wunsch, D.C., O'Hair, E.A., and Giesselmann, M.G.: ' Using neural networks to estimate wind turbine power generation ', IEEE Trans. Energy Convers., 2001, 16, (3), p. 276-282 0885-8969
10. Kariniotakis, G.N., Stavrakakis, G.S., and Nogaret, E.F.: ' Wind power forecasting using advanced neural networks models ', IEEE Trans. Energy Convers., 1996, 11, (4), p. 762-767 0885-8969
11. Slootweg, J.G., de Haan, S.W.H., Polinder, H., and Kling, W.L.: ' General model for representing variable speed wind turbines in power systems dynamics simulations ', IEEE Trans. Power Syst., 2004, 18, (1), p. 144-151 10.1109/TPWRS.2002.807113 0885-8950
12. Wasynczuk, O., Man, D.T., and Sullivan, J.P.: ' Dynamic behavior of a class of wind turbine generators during random wind fluctuations ', IEEE Trans. Power Appl. Syst., 1981, 100, p. 2837-2845
13. Anderson, P.M., and Bose, A.: ' Stability simulation of wind turbine systems ', IEEE Trans. Power Appl. Syst., 1983, 102, p. 3791-3795
14. Nichita, C., Luca, D., Dakyo, B., and Ceanga, E.: ' Large band simulation of the wind speed for real time wind turbine simulators ', IEEE Trans. Energy Convers., 2002, 17, (4), p. 523-529 0885-8969
15. Haykin, S.: ' Neural networks: a comprehensive foundation ', (Prentice-Hall, 1999)