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A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems

Author

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  • Ahmed G. Abo-Khalil

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia
    Department of Electrical Engineering, College of Engineering, Assuit University, Assuit 71515, Egypt)

  • Ali M. Eltamaly

    (Saudi Electricity Company Chair in Power System Reliability and Security, King Saud University, Riyadh 11421, Saudi Arabia
    Sustainable Energy Technologies Center, King Saud University, Riyadh 11421, Saudi Arabia
    Electrical Engineering Department, Mansoura University, Mansoura 35516, Egypt)

  • Praveen R.P.

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia)

  • Ali S. Alghamdi

    (Department of Electrical Engineering, College of Engineering, Majmaah University, Almajmaah 11952, Saudi Arabia)

  • Iskander Tlili

    (Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
    Faculty of Civil Engineering, Duy Tan University, Da Nang 550000, Vietnam)

Abstract

Currently, among the topologies of wind energy conversion systems, those based on full power converters are growing. The permanent magnet synchronous generator (PMSG) uses full power converter to allow wide speed ranges to extract the maximum power from the wind. In order to obtain efficient vector control in a synchronous generator with permanent magnets, it is necessary to know the position of the rotor. The PMSGs work over a wide range of speed, and it is mandatory to measure or estimate their speed and position. Usually, the position of the rotor is obtained through Resolver or Encoder. However, the presence of these sensor elements increases the cost, in addition to reducing the system’s reliability. Moreover, in high wind power turbine, the measured wind speed by the anemometer is taken at the level of the blades which makes the measurement of the wind speed at a single point inaccurate. This paper is a study on the sensorless control that removes the rotor position, speed sensors and anemometer from the speed control. The estimation of the rotor position is based on the output of a rotor current controller and the wind speed estimator is based on the opposition-based learning (OBL), particle swarm optimization and support vector regression.

Suggested Citation

  • Ahmed G. Abo-Khalil & Ali M. Eltamaly & Praveen R.P. & Ali S. Alghamdi & Iskander Tlili, 2020. "A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems," Sustainability, MDPI, vol. 12(20), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:20:p:8481-:d:428080
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    References listed on IDEAS

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    1. Senjyu, Tomonobu & Tamaki, Satoshi & Muhando, Endusa & Urasaki, Naomitsu & Kinjo, Hiroshi & Funabashi, Toshihisa & Fujita, Hideki & Sekine, Hideomi, 2006. "Wind velocity and rotor position sensorless maximum power point tracking control for wind generation system," Renewable Energy, Elsevier, vol. 31(11), pages 1764-1775.
    2. Ali Mohamed Eltamaly & Mamdooh Al-Saud & Khairy Sayed & Ahmed G. Abo-Khalil, 2020. "Sensorless Active and Reactive Control for DFIG Wind Turbines Using Opposition-Based Learning Technique," Sustainability, MDPI, vol. 12(9), pages 1-14, April.
    3. Ahmed G. Abo-Khalil & Abdel-Rahman Al-Qawasmi & Ali M. Eltamaly & B. G. Yu, 2020. "Condition Monitoring of DC-Link Electrolytic Capacitors in PWM Power Converters Using OBL Method," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    4. Ahmed G. Abo-Khalil & Saeed Alyami & Khairy Sayed & Ayman Alhejji, 2019. "Dynamic Modeling of Wind Turbines Based on Estimated Wind Speed under Turbulent Conditions," Energies, MDPI, vol. 12(10), pages 1-25, May.
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    Cited by:

    1. A. Padmaja & Allusivala Shanmukh & Siva Subrahmanyam Mendu & Ramesh Devarapalli & Javier Serrano González & Fausto Pedro García Márquez, 2021. "Design of Capacitive Bridge Fault Current Limiter for Low-Voltage Ride-Through Capacity Enrichment of Doubly Fed Induction Generator-Based Wind Farm," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    2. Ahmed G. Abo-Khalil & Mohammad Alobaid, 2023. "Optimized Control for PMSG Wind Turbine Systems under Unbalanced and Distorted Grid Voltage Scenarios," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    3. Ahmed G. Abo-Khalil & Ali S. Alghamdi, 2021. "MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression," Sustainability, MDPI, vol. 13(4), pages 1-15, February.

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