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Small Wind Turbine Emulator Based on Lambda-Cp Curves Obtained under Real Operating Conditions

Author

Listed:
  • Camilo I. Martínez-Márquez

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

  • Jackson D. Twizere-Bakunda

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

  • David Lundback-Mompó

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

  • Salvador Orts-Grau

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

  • Francisco J. Gimeno-Sales

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

  • Salvador Seguí-Chilet

    (Instituto Interuniversitario de Investigación de Reconocimiento Molecular y Desarrollo Tecnológico, Universitat Politècnica de València, Camino de Vera 14, 46022 Valencia, Spain)

Abstract

This paper proposes a new on-site technique for the experimental characterization of small wind systems by emulating the behavior of a wind tunnel facility. Due to the high cost and complexity of these facilities, many manufacturers of small wind systems do not have a well knowledge of the characteristic λ - C p curve of their turbines. Therefore, power electronics converters connected to the wind generator are usually programmed with speed/power control curves that do not optimize the power generation. The characteristic λ - C p curves obtained through the proposed method will help manufacturers to obtain optimized speed/power control curves. In addition, a low cost small wind emulator has been designed. Programmed with the experimental λ - C p curve, it can validate, improve, and develop new control algorithms to maximize the energy generation. The emulator is completed with a new graphic user interface that monitors in real time both the value of the λ - C p coordinate and the operating point on the 3D working surface generated with the characteristic λ - C p curve obtained from the real small wind system. The proposed method has been applied to a small wind turbine commercial model. The experimental results demonstrate that the point of operation obtained with the emulator is always located on the 3D surface, at the same coordinates (rotor speed/wind speed/power) as the ones obtained experimentally, validating the designed emulator.

Suggested Citation

  • Camilo I. Martínez-Márquez & Jackson D. Twizere-Bakunda & David Lundback-Mompó & Salvador Orts-Grau & Francisco J. Gimeno-Sales & Salvador Seguí-Chilet, 2019. "Small Wind Turbine Emulator Based on Lambda-Cp Curves Obtained under Real Operating Conditions," Energies, MDPI, vol. 12(13), pages 1-17, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2456-:d:242991
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    References listed on IDEAS

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    1. Bo Li & Wenhu Tang & Kaishun Xiahou & Qinghua Wu, 2017. "Development of Novel Robust Regulator for Maximum Wind Energy Extraction Based upon Perturbation and Observation," Energies, MDPI, vol. 10(4), pages 1-21, April.
    2. Aman Abdulla Tanvir & Adel Merabet & Rachid Beguenane, 2015. "Real-Time Control of Active and Reactive Power for Doubly Fed Induction Generator (DFIG)-Based Wind Energy Conversion System," Energies, MDPI, vol. 8(9), pages 1-20, September.
    3. Martinez, Fernando & Herrero, L. Carlos & de Pablo, Santiago, 2014. "Open loop wind turbine emulator," Renewable Energy, Elsevier, vol. 63(C), pages 212-221.
    4. Dai, Juchuan & Liu, Deshun & Wen, Li & Long, Xin, 2016. "Research on power coefficient of wind turbines based on SCADA data," Renewable Energy, Elsevier, vol. 86(C), pages 206-215.
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    Cited by:

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    2. Mohammad AlMuhaini & Abass Yahaya & Ahmed AlAhmed, 2023. "Distributed Generation and Load Modeling in Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    3. Nikolaos Chrysochoidis-Antsos & Gerard J.W. van Bussel & Jan Bozelie & Sander M. Mertens & Ad J.M. van Wijk, 2021. "Performance Characteristics of A Micro Wind Turbine Integrated on A Noise Barrier," Energies, MDPI, vol. 14(5), pages 1-29, February.

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