IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i18p5818-d635409.html
   My bibliography  Save this article

Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines

Author

Listed:
  • Taesu Jeon

    (Department of Integrated Energy & Infra System, Kangwon National University, Gangwon, Chuncheon 24341, Korea)

  • Dongmyoung Kim

    (Department of Integrated Energy & Infra System, Kangwon National University, Gangwon, Chuncheon 24341, Korea)

  • Yuan Song

    (Department of Advanced Mechanical Engineering, Kangwon National University, Gangwon, Chuncheon 24341, Korea)

  • Insu Paek

    (Department of Integrated Energy & Infra System, Kangwon National University, Gangwon, Chuncheon 24341, Korea
    Department of Mechatronics Engineering Kangwon National University, Gangwon, Chuncheon 24341, Korea)

Abstract

In this study, a demanded power point tracking (DPPT) control algorithm was designed for the application of multiple-input multiple-output (MIMO) modern control algorithms. The proposed DPPT control algorithm has been newly implemented as a multiple reference trajectory method for applying an MIMO control algorithm without mode switches. Dynamic simulations and wind tunnel experiments were performed using a scaled wind turbine to validate the proposed control algorithm. The wind speeds were 4.6 and 7.3 m/s, the average wind speeds corresponding to region 2 and region 3, respectively, with a turbulence intensity of 10%. Both sets of results demonstrated satisfactory performance for tracking the power commands transmitted from the wind farm controller. Furthermore, the proposed control algorithm was compared and validated with a DPPT control algorithm proposed in previous studies, and its improved control performance and validity were confirmed.

Suggested Citation

  • Taesu Jeon & Dongmyoung Kim & Yuan Song & Insu Paek, 2021. "Design and Validation of Demanded Power Point Tracking Control Algorithm for MIMO Controllers in Wind Turbines," Energies, MDPI, vol. 14(18), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5818-:d:635409
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/18/5818/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/18/5818/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hyungyu Kim & Kwansu Kim & Carlo Luigi Bottasso & Filippo Campagnolo & Insu Paek, 2018. "Wind Turbine Wake Characterization for Improvement of the Ainslie Eddy Viscosity Wake Model," Energies, MDPI, vol. 11(10), pages 1-19, October.
    2. Siniscalchi-Minna, Sara & Bianchi, Fernando D. & De-Prada-Gil, Mikel & Ocampo-Martinez, Carlos, 2019. "A wind farm control strategy for power reserve maximization," Renewable Energy, Elsevier, vol. 131(C), pages 37-44.
    3. Taesu Jeon & Insu Paek, 2021. "Design and Verification of the LQR Controller Based on Fuzzy Logic for Large Wind Turbine," Energies, MDPI, vol. 14(1), pages 1-17, January.
    4. Asier Diaz De Corcuera & Aron Pujana-Arrese & Jose M. Ezquerra & Edurne Segurola & Joseba Landaluze, 2012. "H ∞ Based Control for Load Mitigation in Wind Turbines," Energies, MDPI, vol. 5(4), pages 1-30, April.
    5. Kwansu Kim & Hyunjong Kim & Hyungyu Kim & Jaehoon Son & Jungtae Kim & Jongpo Park, 2021. "Resonance Avoidance Control Algorithm for Semi-Submersible Floating Offshore Wind Turbine," Energies, MDPI, vol. 14(14), pages 1-17, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Taesu Jeon & Dongmyoung Kim & Insu Paek, 2022. "Improvements to and Experimental Validation of PI Controllers Using a Reference Bias Control Algorithm for Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-18, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Carolina G. Marcelino & João V. C. Avancini & Carla A. D. M. Delgado & Elizabeth F. Wanner & Silvia Jiménez-Fernández & Sancho Salcedo-Sanz, 2021. "Dynamic Electric Dispatch for Wind Power Plants: A New Automatic Controller System Using Evolutionary Algorithms," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    2. Yolanda Vidal & Leonardo Acho & Ningsu Luo & Mauricio Zapateiro & Francesc Pozo, 2012. "Power Control Design for Variable-Speed Wind Turbines," Energies, MDPI, vol. 5(8), pages 1-18, August.
    3. Edmunds, Calum & Martín-Martínez, Sergio & Browell, Jethro & Gómez-Lázaro, Emilio & Galloway, Stuart, 2019. "On the participation of wind energy in response and reserve markets in Great Britain and Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    4. Taesu Jeon & Dongmyoung Kim & Insu Paek, 2022. "Improvements to and Experimental Validation of PI Controllers Using a Reference Bias Control Algorithm for Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-18, November.
    5. Hyungyu Kim & Kwansu Kim & Insu Paek, 2019. "A Study on the Effect of Closed-Loop Wind Farm Control on Power and Tower Load in Derating the TSO Command Condition," Energies, MDPI, vol. 12(10), pages 1-19, May.
    6. Yancai Xiao & Tieling Zhang & Zeyu Ding & Chunya Li, 2016. "The Study of Fuzzy Proportional Integral Controllers Based on Improved Particle Swarm Optimization for Permanent Magnet Direct Drive Wind Turbine Converters," Energies, MDPI, vol. 9(5), pages 1-17, May.
    7. Vincenzo Iannino & Valentina Colla & Mario Innocenti & Annamaria Signorini, 2017. "Design of a H ∞ Robust Controller with μ -Analysis for Steam Turbine Power Generation Applications," Energies, MDPI, vol. 10(7), pages 1-31, July.
    8. Yuan, Yuan & Chen, Xu & Tang, J., 2020. "Multivariable robust blade pitch control design to reject periodic loads on wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 329-341.
    9. Dong, Xinghui & Li, Jia & Gao, Di & Zheng, Kai, 2021. "Wind speed modeling for cascade clusters of wind turbines Part 2: Wind speed reduction and aggregation superposition," Energy, Elsevier, vol. 215(PB).
    10. Wang, Ni & Li, Jian & Yu, Xiang & Zhou, Dao & Hu, Weihao & Huang, Qi & Chen, Zhe & Blaabjerg, Frede, 2020. "Optimal active and reactive power cooperative dispatch strategy of wind farm considering levelised production cost minimisation," Renewable Energy, Elsevier, vol. 148(C), pages 113-123.
    11. Del Pozo González, Héctor & Domínguez-García, José Luis, 2022. "Non-centralized hierarchical model predictive control strategy of floating offshore wind farms for fatigue load reduction," Renewable Energy, Elsevier, vol. 187(C), pages 248-256.
    12. Zili Zhang & Søren R. K. Nielsen & Frede Blaabjerg & Dao Zhou, 2014. "Dynamics and Control of Lateral Tower Vibrations in Offshore Wind Turbines by Means of Active Generator Torque," Energies, MDPI, vol. 7(11), pages 1-27, November.
    13. Miloš Milašinović & Damjan Ivetić & Milan Stojković & Dragan Savić, 2023. "Failure Conditions Assessment of Complex Water Systems Using Fuzzy Logic," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(3), pages 1153-1182, February.
    14. Puertas-Frías, Carmen M. & Willson, Clinton S. & García-Salaberri, Pablo A., 2022. "Design and economic analysis of a hydrokinetic turbine for household applications," Renewable Energy, Elsevier, vol. 199(C), pages 587-598.
    15. Pombo, Daniel Vázquez & Martinez-Rico, Jon & Spataru, Sergiu V. & Bindner, Henrik W. & Sørensen, Poul E., 2023. "Decarbonizing energy islands with flexibility-enabling planning: The case of Santiago, Cape Verde," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    16. Jau-Woei Perng & Guan-Yan Chen & Shan-Chang Hsieh, 2014. "Optimal PID Controller Design Based on PSO-RBFNN for Wind Turbine Systems," Energies, MDPI, vol. 7(1), pages 1-19, January.
    17. Del Pozo Gonzalez, Hector & Bianchi, Fernando D. & Dominguez-Garcia, Jose Luis & Gomis-Bellmunt, Oriol, 2023. "Co-located wind-wave farms: Optimal control and grid integration," Energy, Elsevier, vol. 272(C).
    18. Iván Pazmiño & Sergio Martinez & Danny Ochoa, 2021. "Analysis of Control Strategies Based on Virtual Inertia for the Improvement of Frequency Stability in an Islanded Grid with Wind Generators and Battery Energy Storage Systems," Energies, MDPI, vol. 14(3), pages 1-18, January.
    19. Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.
    20. Ning Zhang & Wei Gu & Haojun Yu & Wei Liu, 2013. "Application of Coordinated SOFC and SMES Robust Control for Stabilizing Tie-Line Power," Energies, MDPI, vol. 6(4), pages 1-16, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5818-:d:635409. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.