Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Bücher
Zeitschriften
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
ATZ-Fachkongress

Chassis.tech plus 2024


4 Kongresse in einer Veranstaltung

Treffen Sie in München die Fachleute von Chassis, Lenkung, Bremsen sowie Reifen/Räder.
Erweiterte Suche
Anmelden
nach oben
Energy Systems
Erschienen in: Energy Systems 1/2023

05.08.2021 | Original Paper

Nonlinear pitch angle control of an onshore wind turbine by considering the aerodynamic nonlinearities and deriving an aeroelastic model

verfasst von: Farshad Golnary, Hamed Moradi, K. T. Tse

Erschienen in: Energy Systems | Ausgabe 1/2023

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

In this paper, the control problem of a wind turbine in region 3 (where the wind velocity is between the rated wind velocity and cut out wind velocity) has been investigated by considering the aerodynamic nonlinear behavior of the wind-structure interaction. The model has been developed by using the blade element momentum (BEM) theory to obtain the aerodynamic torque and aerodynamic loads in edgewise and flapwise directions. For validation, the aerodynamic behavior of the onshore NREL 5 MW turbine has been compared with the Fatigue, Aerodynamics, Structures, and Turbulence (FAST) aeroelastic code in terms of the power coefficient. Wind speed is modelled as a three-dimensional profile with Kaimal spectrum distribution. The wind profile data is modeled in the frequency domain by the Kaimal spectrum distribution function. Then, an inverse Fourier transformation is needed to convert the data into the time domain. In the next, the sliding mode approach is applied to the three DOFs model of the drivetrain system which includes the rotor speed, low-speed shaft angle, and pitch angle. Finally, to consider the complete behavior of the onshore wind turbine, an eleven DOFs model is obtained. This model considers three DOFs for the flapwise vibrations of the blades, another three DOFs for the edgewise vibrations of the wind turbine, two DOFs for the side-side and fore-aft vibrations of the tower, and three DOFs for the drive-train system of the wind turbine. The performance of the proposed sliding mode control methods has been compared with the conventional PID controller for the above-rated wind velocity region. Results demonstrate that the wind turbine performance has been improved.
Vorheriger Artikel An optimized fractional order cascade controller for frequency regulation of power system with renewable energies and electric vehicles
Nächster Artikel Utilization of device parameters to assess the performance of a monocrystalline solar module under varied temperature and irradiance

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Literatur
1.
Council, Global Wind Energy: GWEC global wind report 2016. Global Wind Energy Council, Bonn (2017)
2.
3.
4.
Barambones, O., Cortajarena, J.A., Calvo, I., de Durana, J.M.G., Alkorta, P., Karami-Mollaee, A.: Variable speed wind turbine control scheme using a robust wind torque estimation. Renew. Energy 133, 354–366 (2019)MATHCrossRef
5.
Zappalá, D., Sarma, N., Djurović, S., Crabtree, C.J., Mohammad, A., Tavner, P.J.: Electrical and mechanical diagnostic indicators of wind turbine induction generator rotor faults. Renew. Energy 131, 14–24 (2019)CrossRef
6.
Tong, W.: Wind power generation and wind turbine design. WIT press (2010)
7.
Bossanyi, E.A.: Wind turbine control for load reduction. Wind Energy 6(3), 229–244 (2003)CrossRef
8.
Bianchi, F.D., De Battista, H., Mantz, R.J.: Wind turbine control systems: principles, modelling and gain scheduling design. Springer Science & Business Media, Berlin (2006)
9.
Boukhezzar, B., Lupu, L., Siguerdidjane, H., Hand, M.: Multivariable control strategy for variable speed, variable pitch wind turbines. Renew. Energy 32(8), 1273–1287 (2007)CrossRef
10.
Boukhezzar, B., Siguerdidjane, H.: Nonlinear control with wind estimation of a DFIG variable speed wind turbine for power capture optimization. Energy Convers. Manage. 50(4), 885–892 (2009)CrossRef
11.
Boukhezzar, B., Siguerdidjane, H.: Nonlinear control of a variable-speed wind turbine using a two-mass model. IEEE Trans. Energy Convers. 26(1), 149–162 (2010)CrossRef
12.
Boukhezzar, B., Siguerdidjane, H.: Nonlinear control of variable speed wind turbines without wind speed measurement. In: Proceedings of the 44th IEEE Conference on Decision and Control, pp. 3456–3461, IEEE (2005)
13.
14.
Kaviani, H., Nejat, A.: Aeroacoustic and aerodynamic optimization of a MW class HAWT using MOPSO algorithm. Energy 140, 1198–1215 (2017)CrossRef
15.
Kaviani, H.R., Nejat, A.: Aerodynamic noise prediction of a MW-class HAWT using shear wind profile. J. Wind Eng. Ind. Aerodyn. 168, 164–176 (2017)CrossRef
16.
Abo-Khalil, A.G., Lee, D.C.: MPPT control of wind generation systems based on estimated wind speed using SVR. IEEE Trans. Industr. Electron. 55(3), 1489–1490 (2008)CrossRef
17.
Golnary, F., Moradi, H.: Dynamic modelling and design of various robust sliding mode controls for the wind turbine with estimation of wind speed. Appl. Math. Model. 65, 566–585 (2019)MathSciNetMATHCrossRef
18.
Hughes, F.M., Anaya-Lara, O., Jenkins, N., Strbac, G.: Control of DFIG-based wind generation for power network support. IEEE Trans. Power Syst. 20(4), 1958–1966 (2005)CrossRef
19.
Hao, F. E. N. G., Lei, P. A. N., Xiu-fang, P. E. N. G., Tian-wei, Z.: Coordinated control strategy of mppt and pitch angle of wind turbine generator based on neural network. In: 2019 IEEE Sustainable Power and Energy Conference (iSPEC), pp. 99–104, IEEE (2019)
20.
Tapia, A., Tapia, G., Ostolaza, J.X., Saenz, J.R.: Modeling and control of a wind turbine driven doubly fed induction generator. IEEE Trans. Energy Convers. 18(2), 194–204 (2003)CrossRef
21.
22.
Bektache, A., Boukhezzar, B.: Nonlinear predictive control of a DFIG-based wind turbine for power capture optimization. Int. J. Electr. Power Energy Syst. 101, 92–102 (2018)CrossRef
23.
Nayeh, R.F., Moradi, H., Vossoughi, G.: Multivariable robust control of a horizontal wind turbine under various operating modes and uncertainties: a comparison on sliding mode and H∞ control. Int. J. Elect. Power Energy Syst. 115, 105474 (2020)CrossRef
24.
Corradini, M.L., Ippoliti, G., Orlando, G.J.C.E.P.: An observer-based blade-pitch controller of wind turbines in high wind speeds. Control. Eng. Pract. 58, 186–192 (2017)CrossRef
25.
Chen, P., Han, D., Tan, F., Wang, J.: Reinforcement-based robust variable pitch control of wind turbines. IEEE Access. 8, 20493–20502 (2020)CrossRef
26.
Kong, X., Ma, L., Liu, X., Abdelbaky, M.A., Wu, Q.: Wind turbine control using nonlinear economic model predictive control over all operating regions. Energies 13(1), 184 (2020)CrossRef
27.
Lin, Z., Chen, Z., Liu, J., Wu, Q.: Coordinated mechanical loads and power optimization of wind energy conversion systems with variable-weight model predictive control strategy. Appl. Energy 236, 307–317 (2019)CrossRef
28.
Zhang, Z., Nielsen, S.R., Blaabjerg, F., Zhou, D.: Dynamics and control of lateral tower vibrations in offshore wind turbines by means of active generator torque. Energies 7(11), 7746–7772 (2014)CrossRef
29.
Zhang, Z., Fitzgerald, B.: Tuned mass-damper-inerter (TMDI) for suppressing edgewise vibrations of wind turbine blades. Eng. Struct. 221, 110928 (2020)CrossRef
30.
Golnary, F., Moradi, H.: Design and comparison of quasi continuous sliding mode control with feedback linearization for a large scale wind turbine with wind speed estimation. Renew. Energy 127, 495–508 (2018)CrossRef
31.
Mérida, J., Aguilar, L.T., Dávila, J.: Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization. Renew. Energy 71, 715–728 (2014)CrossRef
32.
Moodi, H., Bustan, D.: Wind turbine control using TS systems with nonlinear consequent parts. Energy 172, 922–931 (2019)CrossRef
33.
Venkaiah, P., Sarkar, B.K.: Hydraulically actuated horizontal axis wind turbine pitch control by model free adaptive controller. Renew. Energy 147, 55–68 (2020)CrossRef
34.
Hansen, M.O.: Aerodynamics of wind turbines. Routledge, London (2015)CrossRef
35.
Chaviaropoulos, P.K., Hansen, M.O.: Investigating three-dimensional and rotational effects on wind turbine blades by means of a quasi-3D Navier-Stokes solver. J. Fluids Eng. 122(2), 330–336 (2000)CrossRef
36.
Glauert, H.: Airplane propellers. In Aerodynamic theory, pp. 169–360. Springer, Berlin (1935)CrossRef
37.
Bossanyi, E., Burton, T., Sharpe, D., Jenkins, N.: Wind energy handbook. Wiley, Hoboken (2000)
38.
Jonkman, B.J.: TurbSim user’s guide: version 1.50 (No. NREL/TP-500-46198). National Renewable Energy Lab(NREL), Golden (2009)CrossRef
39.
Yarmohammadi, M.J., Sadeghzadeh, A., Taghizadeh, M.: Gain-scheduled control of wind turbine exploiting inexact wind speed measurement for full operating range. Renew. Energy 149, 890–901 (2020)CrossRef
40.
Perruquetti, W., Barbot, J.P.: Sliding mode control in engineering. CRC Press, Boca Raton (2002)CrossRef
41.
42.
Shtessel, Y., Edwards, C., Fridman, L., Levant, A.: Sliding mode control and observation. Springer, New York (2014)CrossRef
43.
44.
Slotine, J.J.E., Li, W.: Applied nonlinear control (Vol. 199, No. 1). Prentice hall, Englewood Cliffs (1991)
45.
Jonkman, J., Butterfield, S., Musial, W., Scott, G.: Definition of a 5-MW reference wind turbine for offshore system development (No. NREL/TP-500-38060). National Renewable Energy Lab (NREL), Golden (2009)CrossRef
46.
Zhang, Z., Nielsen, S.R., Basu, B., Li, J.: Nonlinear modeling of tuned liquid dampers (TLDs) in rotating wind turbine blades for damping edgewise vibrations. J. Fluids Struct. 59, 252–269 (2015)CrossRef
47.
Manikandan, R., Saha, N.: Dynamic modelling and non-linear control of TLP supported offshore wind turbine under environmental loads. Mar. Struct. 64, 263–294 (2019)CrossRef
48.
Sun, C.: Semi-active control of monopile offshore wind turbines under multi-hazards. Mech. Syst. Signal Process. 99, 285–305 (2018)CrossRef
49.
Sun, C., Jahangiri, V., Sun, H.: Performance of a 3D pendulum tuned mass damper in offshore wind turbines under multiple hazards and system variations. Smart Struct. Syst. 24(1), 53–65 (2019)
50.
Jahangiri, V., Sun, C.: Integrated bi-directional vibration control and energy harvesting of monopile offshore wind turbines. Ocean Eng. 178, 260–269 (2018)CrossRef
51.
Greenwood, D.T.: Advanced dynamics. Cambridge University Press, Cambridge (2006)
52.
Rao, S.S.: Vibration of continuous systems, vol. 464. Wiley, New York (2007)
53.
Howland, M.F., González, C.M., Martínez, J.J.P., Quesada, J.B., Larranaga, F.P., Yadav, N.K., Dabiri, J.O.: Influence of atmospheric conditions on the power production of utility-scale wind turbines in yaw misalignment. J. Renew. Sustain. Energy. 12(6), 063307 (2020)CrossRef
Metadaten
Titel
Nonlinear pitch angle control of an onshore wind turbine by considering the aerodynamic nonlinearities and deriving an aeroelastic model
verfasst von
Farshad Golnary
Hamed Moradi
K. T. Tse
Publikationsdatum
05.08.2021
Verlag
Springer Berlin Heidelberg
Erschienen in
Energy Systems / Ausgabe 1/2023
Print ISSN: 1868-3967
Elektronische ISSN: 1868-3975
DOI
https://doi.org/10.1007/s12667-021-00469-1

Weitere Artikel der Ausgabe 1/2023

Energy Systems 1/2023 Zur Ausgabe

Original Paper

Point and interval forecasts of electricity demand with Reg-SARMA models

Original Paper

Intelligent and sensor data driven mobile wind energy systems

Original Paper

Comparative analysis of PID and fractional order PID controllers in automatic generation control process with coordinated control of TCSC

Original Paper

A hybrid metaheuristic algorithm to solve the electric vehicle routing problem with battery recharging stations for sustainable environmental and energy optimization

Original Paper

A game-theoretic approach to assess peer-to-peer rooftop solar PV electricity trading under constrained power supply

Review Article

Recent progress in thermal and optical enhancement of low temperature solar collector