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A Study on Available Power Estimation Algorithm and Its Validation

Author

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  • Dongmyoung Kim

    (Department of Integrated Energy and Infra System, Kangwon National University, Engineering Building 6-319, 1 Gangwondaehak-gil, Chuncheon-si 24341, Gangwon-do, Korea)

  • Taesu Jeon

    (Department of Integrated Energy and Infra System, Kangwon National University, Engineering Building 6-319, 1 Gangwondaehak-gil, Chuncheon-si 24341, Gangwon-do, Korea)

  • Insu Paek

    (Department of Mechatronics Engineering, Kangwon National University, Engineering Building 6-319, 1 Gangwondaehak-gil, Chuncheon-si 24341, Gangwon-do, Korea)

  • Daeyoung Kim

    (R and D Institute, Hanjin Ind. Co., Ltd., 1981-48, Yangsan-daero, Habuk-myeon, Yangsan-si 50509, Gyeongsangnam-do, Korea)

Abstract

Three different algorithms that can be used to estimate the available power of a wind turbine are investigated and validated in this study. The first method is the simplest and using the power curve with the measured nacelle wind speed. The other two are to estimate the equivalent wind speed first without using the measured Nacelle wind speed and to estimate the available power from the rotor power equation. The two methods are different in that the second method is to use the drive-train model to estimate the rotor torque but the third method is to use a simplified equation to avoid sharp peaks in the wind speed estimation. Simulations were performed to validate the constructed available power estimation algorithms with the measured data of a 2 MW target wind turbine. It was found from the validation that the third available power estimation algorithm works properly and is closer to the power actually generated from the wind turbine than the other methods considered. In addition, the third algorithm that showed the best performance was further validated with the DPPT (demanded power point tracking) operation with Matlab/Simulink environment. It was found from the simulation that the third algorithm works well in the DPPT operation to estimate the available power of the wind turbine.

Suggested Citation

  • Dongmyoung Kim & Taesu Jeon & Insu Paek & Daeyoung Kim, 2022. "A Study on Available Power Estimation Algorithm and Its Validation," Energies, MDPI, vol. 15(7), pages 1-14, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2648-:d:786919
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    References listed on IDEAS

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    1. Xiaodong Wang & Yunong Liu & Luyao Wang & Lin Ding & Hui Hu, 2019. "Numerical Study of Nacelle Wind Speed Characteristics of a Horizontal Axis Wind Turbine under Time-Varying Flow," Energies, MDPI, vol. 12(20), pages 1-19, October.
    2. Hansen, Anca D. & Sørensen, Poul & Iov, Florin & Blaabjerg, Frede, 2006. "Centralised power control of wind farm with doubly fed induction generators," Renewable Energy, Elsevier, vol. 31(7), pages 935-951.
    3. Ebrahimi, F.M. & Khayatiyan, A. & Farjah, E., 2016. "A novel optimizing power control strategy for centralized wind farm control system," Renewable Energy, Elsevier, vol. 86(C), pages 399-408.
    4. Jonathan J. Buonocore & Ernani Choma & Aleyda H. Villavicencio & John D. Spengler & Dinah A. Koehler & John S. Evans & Jos Lelieveld & Piet Klop & Ramon Sanchez-Pina, 2019. "Metrics for the sustainable development goals: renewable energy and transportation," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-14, December.
    5. Baskut, Omer & Ozgener, Onder & Ozgener, Leyla, 2011. "Second law analysis of wind turbine power plants: Cesme, Izmir example," Energy, Elsevier, vol. 36(5), pages 2535-2542.
    6. Yuan Song & Insu Paek, 2020. "Prediction and Validation of the Annual Energy Production of a Wind Turbine Using WindSim and a Dynamic Wind Turbine Model," Energies, MDPI, vol. 13(24), pages 1-15, December.
    7. González, Javier Serrano & Gonzalez Rodriguez, Angel G. & Mora, José Castro & Santos, Jesús Riquelme & Payan, Manuel Burgos, 2010. "Optimization of wind farm turbines layout using an evolutive algorithm," Renewable Energy, Elsevier, vol. 35(8), pages 1671-1681.
    8. Hyun-Goo Kim & Jin-Young Kim, 2021. "Analysis of Wind Turbine Aging through Operation Data Calibrated by LiDAR Measurement," Energies, MDPI, vol. 14(8), pages 1-12, April.
    9. Jonathan J. Buonocore & Ernani Choma & Aleyda H. Villavicencio & John D. Spengler & Dinah A. Koehler & John S. Evans & Jos Lelieveld & Piet Klop & Ramon Sanchez-Pina, 2019. "Correction: Metrics for the sustainable development goals: renewable energy and transportation," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-2, December.
    10. Stoyan Kanev & Edwin Bot & Jack Giles, 2020. "Wind Farm Loads under Wake Redirection Control," Energies, MDPI, vol. 13(16), pages 1-15, August.
    11. XU Jianzhong & Albina Assenova & Vasilii Erokhin, 2018. "Renewable Energy and Sustainable Development in a Resource-Abundant Country: Challenges of Wind Power Generation in Kazakhstan," Sustainability, MDPI, vol. 10(9), pages 1-21, September.
    12. José F. Herbert-Acero & Oliver Probst & Pierre-Elouan Réthoré & Gunner Chr. Larsen & Krystel K. Castillo-Villar, 2014. "A Review of Methodological Approaches for the Design and Optimization of Wind Farms," Energies, MDPI, vol. 7(11), pages 1-87, October.
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