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Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms

Author

Listed:
  • Unai Elosegui

    (Maxwind, Portuetxe 83, 3, 20018 Donostia, Spain
    These authors contributed equally to this work.)

  • Igor Egana

    (Maxwind, Portuetxe 83, 3, 20018 Donostia, Spain
    These authors contributed equally to this work.)

  • Alain Ulazia

    (Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Otaola 29, 20600 Eibar, Spain
    These authors contributed equally to this work.)

  • Gabriel Ibarra-Berastegi

    (Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Alda, Urkijo, 48013 Bilbao, Spain
    Joint Research Unit (UPV/EHU-IEO) Plentziako Itsas Estazioa (PIE), University of Basque Country (UPV/EHU), Areatza Hiribidea 47, 48620 Plentzia, Spain
    These authors contributed equally to this work.)

Abstract

In addition to human error, manufacturing tolerances for blades and hubs cause pitch angle misalignment in wind turbines. As a consequence, a significant number of turbines used by existing wind farms experience power production loss and a reduced turbine lifetime. Existing techniques, such as photometric technology and laser-based methods, have been used in the wind industry for on-field pitch measurements. However, in some cases, regular techniques have difficulty achieving good and accurate measurements of pitch angle settings, resulting in pitch angle errors that require cost-effective correction on wind farms. Here, the authors present a novel patented method based on laser scanner measurements. The authors applied this new method and achieved successful improvements in the Annual Energy Production of various wind farms. This technique is a benchmarking-based approach for pitch angle calibration. Two case studies are introduced to demonstrate the effectiveness of the pitch angle calibration method to yield Annual Energy Production increase.

Suggested Citation

  • Unai Elosegui & Igor Egana & Alain Ulazia & Gabriel Ibarra-Berastegi, 2018. "Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms," Energies, MDPI, vol. 11(12), pages 1-20, December.
  • Handle: RePEc:gam:jeners:v:11:y:2018:i:12:p:3357-:d:186895
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    References listed on IDEAS

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    1. Mehlan, Felix C. & Nejad, Amir R., 2023. "Rotor imbalance detection and diagnosis in floating wind turbines by means of drivetrain condition monitoring," Renewable Energy, Elsevier, vol. 212(C), pages 70-81.
    2. Nuria Novas & Alfredo Alcayde & Isabel Robalo & Francisco Manzano-Agugliaro & Francisco G. Montoya, 2020. "Energies and Its Worldwide Research," Energies, MDPI, vol. 13(24), pages 1-41, December.
    3. Arkaitz Rabanal & Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Unai Elosegui, 2018. "MIDAS: A Benchmarking Multi-Criteria Method for the Identification of Defective Anemometers in Wind Farms," Energies, MDPI, vol. 12(1), pages 1-19, December.
    4. Kerman López de Calle & Susana Ferreiro & Constantino Roldán-Paraponiaris & Alain Ulazia, 2019. "A Context-Aware Oil Debris-Based Health Indicator for Wind Turbine Gearbox Condition Monitoring," Energies, MDPI, vol. 12(17), pages 1-19, September.
    5. Van-Hai Bui & Akhtar Hussain & Woon-Gyu Lee & Hak-Man Kim, 2019. "Multi-Objective Optimization for Determining Trade-Off between Output Power and Power Fluctuations in Wind Farm System," Energies, MDPI, vol. 12(22), pages 1-18, November.
    6. Davide Astolfi & Francesco Castellani, 2019. "Wind Turbine Power Curve Upgrades: Part II," Energies, MDPI, vol. 12(8), pages 1-20, April.
    7. Mazhar Hussain Baloch & Dahaman Ishak & Sohaib Tahir Chaudary & Baqir Ali & Ali Asghar Memon & Touqeer Ahmed Jumani, 2019. "Wind Power Integration: An Experimental Investigation for Powering Local Communities," Energies, MDPI, vol. 12(4), pages 1-24, February.
    8. Shuting Wan & Kanru Cheng & Xiaoling Sheng & Xuan Wang, 2019. "Characteristic Analysis of DFIG Wind Turbine under Blade Mass Imbalance Fault in View of Wind Speed Spatiotemporal Distribution," Energies, MDPI, vol. 12(16), pages 1-14, August.
    9. Tingting Cai & Sutong Liu & Gangui Yan & Hongbo Liu, 2019. "Analysis of Doubly Fed Induction Generators Participating in Continuous Frequency Regulation with Different Wind Speeds Considering Regulation Power Constraints," Energies, MDPI, vol. 12(4), pages 1-20, February.
    10. Alain Ulazia & Ander Nafarrate & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia, 2019. "The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential," Energies, MDPI, vol. 12(13), pages 1-18, July.
    11. Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia & Santos J. González-Rojí, 2019. "Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula," Sustainability, MDPI, vol. 11(13), pages 1-22, July.

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