Estimation of the wind turbine yaw error by support vector machines

Nida Sheibat-Othman, Sami Othman, Raoaa Tayari, Sakly Anis, Peter Fogh Odgaard, Lars Finn Sloth Larsen

Research output: Contribution to journalConference article in JournalResearchpeer-review

3 Citations (Scopus)

Abstract

Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators) are considered. The validation step is done under different conditions of wind shear, speed and direction, giving good estimation results.
Original languageEnglish
Book seriesI F A C Workshop Series
Volume48
Issue number30
Pages (from-to)339-344
ISSN1474-6670
DOIs
Publication statusPublished - Dec 2015
Event9th IFAC Symposium on Control of Power and Energy Systems CPES 2015 - New Delhi, India
Duration: 9 Dec 201511 Dec 2015

Conference

Conference9th IFAC Symposium on Control of Power and Energy Systems CPES 2015
CountryIndia
CityNew Delhi
Period09/12/201511/12/2015

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Wind turbines
Support vector machines
Structural loads
Turbomachine blades
Actuators

Cite this

Sheibat-Othman, N., Othman, S., Tayari, R., Anis, S., Odgaard, P. F., & Larsen, L. F. S. (2015). Estimation of the wind turbine yaw error by support vector machines. I F A C Workshop Series, 48(30), 339-344. https://doi.org/10.1016/j.ifacol.2015.12.401
Sheibat-Othman, Nida ; Othman, Sami ; Tayari, Raoaa ; Anis, Sakly ; Odgaard, Peter Fogh ; Larsen, Lars Finn Sloth. / Estimation of the wind turbine yaw error by support vector machines. In: I F A C Workshop Series. 2015 ; Vol. 48, No. 30. pp. 339-344.
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abstract = "Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators) are considered. The validation step is done under different conditions of wind shear, speed and direction, giving good estimation results.",
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Sheibat-Othman, N, Othman, S, Tayari, R, Anis, S, Odgaard, PF & Larsen, LFS 2015, 'Estimation of the wind turbine yaw error by support vector machines', I F A C Workshop Series, vol. 48, no. 30, pp. 339-344. https://doi.org/10.1016/j.ifacol.2015.12.401

Estimation of the wind turbine yaw error by support vector machines. / Sheibat-Othman, Nida; Othman, Sami; Tayari, Raoaa; Anis, Sakly; Odgaard, Peter Fogh; Larsen, Lars Finn Sloth.

In: I F A C Workshop Series, Vol. 48, No. 30, 12.2015, p. 339-344.

Research output: Contribution to journalConference article in JournalResearchpeer-review

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AU - Sheibat-Othman, Nida

AU - Othman, Sami

AU - Tayari, Raoaa

AU - Anis, Sakly

AU - Odgaard, Peter Fogh

AU - Larsen, Lars Finn Sloth

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N2 - Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators) are considered. The validation step is done under different conditions of wind shear, speed and direction, giving good estimation results.

AB - Wind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators) are considered. The validation step is done under different conditions of wind shear, speed and direction, giving good estimation results.

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Sheibat-Othman N, Othman S, Tayari R, Anis S, Odgaard PF, Larsen LFS. Estimation of the wind turbine yaw error by support vector machines. I F A C Workshop Series. 2015 Dec;48(30):339-344. https://doi.org/10.1016/j.ifacol.2015.12.401