IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i16p4158-d397717.html
   My bibliography  Save this article

Power Optimization for Wind Turbines Based on Stacking Model and Pitch Angle Adjustment

Author

Listed:
  • Zhikun Luo

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Zhifeng Sun

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Fengli Ma

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Yihan Qin

    (College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Shihao Ma

    (Wuzhong Baita Wind Power Corporation Limited, Wuzhong 751100, China)

Abstract

As we know, power optimization for wind turbines has great significance in the area of wind power generation, which means to make use of wind resources more efficiently. Especially nowadays, wind power generation has become more and more important. Generally speaking, many parameters could be optimized to enhance power output, including blade pitch angle, which is usually ignored. In this article, a stacking model composed of Random Forest (RF), Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBOOST) and Light Gradient Boosting Machine (LGBM) is trained based on historical data exported from the Supervisory Control and Data Acquisition (SCADA) system for output power prediction. Then, we carry out power optimization through pitch angle adjustment based on the obtained prediction model. Our research results indicate that power output could be enhanced by adjusting pitch angle appropriately.

Suggested Citation

  • Zhikun Luo & Zhifeng Sun & Fengli Ma & Yihan Qin & Shihao Ma, 2020. "Power Optimization for Wind Turbines Based on Stacking Model and Pitch Angle Adjustment," Energies, MDPI, vol. 13(16), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4158-:d:397717
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/16/4158/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/16/4158/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tongke Yuan & Zhifeng Sun & Shihao Ma, 2019. "Gearbox Fault Prediction of Wind Turbines Based on a Stacking Model and Change-Point Detection," Energies, MDPI, vol. 12(22), pages 1-20, November.
    2. Mérida, Jován & Aguilar, Luis T. & Dávila, Jorge, 2014. "Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization," Renewable Energy, Elsevier, vol. 71(C), pages 715-728.
    3. Dai, Kaoshan & Bergot, Anthony & Liang, Chao & Xiang, Wei-Ning & Huang, Zhenhua, 2015. "Environmental issues associated with wind energy – A review," Renewable Energy, Elsevier, vol. 75(C), pages 911-921.
    4. Song, M.X. & Chen, K. & Zhang, X. & Wang, J., 2015. "The lazy greedy algorithm for power optimization of wind turbine positioning on complex terrain," Energy, Elsevier, vol. 80(C), pages 567-574.
    5. Fan, Zhixin & Zhu, Caichao, 2019. "The optimization and the application for the wind turbine power-wind speed curve," Renewable Energy, Elsevier, vol. 140(C), pages 52-61.
    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. Ming-Fa Tsai & Chung-Shi Tseng & Bor-Yuh Lin, 2020. "Phase Voltage-Oriented Control of a PMSG Wind Generator for Unity Power Factor Correction," Energies, MDPI, vol. 13(21), pages 1-22, October.
    2. Ramesh Kumar Behara & Akshay Kumar Saha, 2022. "Artificial Intelligence Control System Applied in Smart Grid Integrated Doubly Fed Induction Generator-Based Wind Turbine: A Review," Energies, MDPI, vol. 15(17), pages 1-56, September.
    3. Zbigniew Skibko & Magdalena Tymińska & Wacław Romaniuk & Andrzej Borusiewicz, 2021. "Impact of the Wind Turbine on the Parameters of the Electricity Supply to an Agricultural Farm," Sustainability, MDPI, vol. 13(13), pages 1-15, June.
    4. Jiyuan Zhang & Qihong Feng & Xianmin Zhang & Qiujia Hu & Jiaosheng Yang & Ning Wang, 2020. "A Novel Data-Driven Method to Estimate Methane Adsorption Isotherm on Coals Using the Gradient Boosting Decision Tree: A Case Study in the Qinshui Basin, China," Energies, MDPI, vol. 13(20), pages 1-21, October.

    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. Tariq Ullah & Krzysztof Sobczak & Grzegorz Liśkiewicz & Amjid Khan, 2022. "Two-Dimensional URANS Numerical Investigation of Critical Parameters on a Pitch Oscillating VAWT Airfoil under Dynamic Stall," Energies, MDPI, vol. 15(15), pages 1-19, August.
    2. Martínez-Martínez, Yenisleidy & Dewulf, Jo & Casas-Ledón, Yannay, 2022. "GIS-based site suitability analysis and ecosystem services approach for supporting renewable energy development in south-central Chile," Renewable Energy, Elsevier, vol. 182(C), pages 363-376.
    3. Schumacher, Kim & Yang, Zhuoxiang, 2018. "The determinants of wind energy growth in the United States: Drivers and barriers to state-level development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 1-13.
    4. Abdul, Daud & Wenqi, Jiang & Tanveer, Arsalan, 2022. "Prioritization of renewable energy source for electricity generation through AHP-VIKOR integrated methodology," Renewable Energy, Elsevier, vol. 184(C), pages 1018-1032.
    5. Lee, Kyung-Sook & Kim, Ju-Hee & Yoo, Seung-Hoon, 2021. "Would people pay a price premium for electricity from domestic wind power facilities? The case of South Korea," Energy Policy, Elsevier, vol. 156(C).
    6. Long, Huan & Xu, Shaohui & Gu, Wei, 2022. "An abnormal wind turbine data cleaning algorithm based on color space conversion and image feature detection," Applied Energy, Elsevier, vol. 311(C).
    7. A. G. Olabi & Khaled Obaideen & Mohammad Ali Abdelkareem & Maryam Nooman AlMallahi & Nabila Shehata & Abdul Hai Alami & Ayman Mdallal & Asma Ali Murah Hassan & Enas Taha Sayed, 2023. "Wind Energy Contribution to the Sustainable Development Goals: Case Study on London Array," Sustainability, MDPI, vol. 15(5), pages 1-22, March.
    8. Salomon, Hannes & Drechsler, Martin & Reutter, Felix, 2020. "Minimum distances for wind turbines: A robustness analysis of policies for a sustainable wind power deployment," Energy Policy, Elsevier, vol. 140(C).
    9. Moravec, David & Barták, Vojtěch & Puš, Vladimír & Wild, Jan, 2018. "Wind turbine impact on near-ground air temperature," Renewable Energy, Elsevier, vol. 123(C), pages 627-633.
    10. Shakoor, Rabia & Hassan, Mohammad Yusri & Raheem, Abdur & Rasheed, Nadia, 2016. "Wind farm layout optimization using area dimensions and definite point selection techniques," Renewable Energy, Elsevier, vol. 88(C), pages 154-163.
    11. Justė Jankevičienė & Arvydas Kanapickas, 2021. "Projected Near-Surface Wind Speed Trends in Lithuania," Energies, MDPI, vol. 14(17), pages 1-13, August.
    12. Kisvari, Adam & Lin, Zi & Liu, Xiaolei, 2021. "Wind power forecasting – A data-driven method along with gated recurrent neural network," Renewable Energy, Elsevier, vol. 163(C), pages 1895-1909.
    13. Song, MengXuan & Wu, BingHeng & Chen, Kai & Zhang, Xing & Wang, Jun, 2016. "Simulating the wake flow effect of wind turbines on velocity and turbulence using particle random walk method," Energy, Elsevier, vol. 116(P1), pages 583-591.
    14. Marcus Eichhorn & Mattes Scheftelowitz & Matthias Reichmuth & Christian Lorenz & Kyriakos Louca & Alexander Schiffler & Rita Keuneke & Martin Bauschmann & Jens Ponitka & David Manske & Daniela Thrän, 2019. "Spatial Distribution of Wind Turbines, Photovoltaic Field Systems, Bioenergy, and River Hydro Power Plants in Germany," Data, MDPI, vol. 4(1), pages 1-15, February.
    15. Lidong Zhang & Qikai Li & Yuanjun Guo & Zhile Yang & Lei Zhang, 2018. "An Investigation of Wind Direction and Speed in a Featured Wind Farm Using Joint Probability Distribution Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    16. Abolvafaei, Mahnaz & Ganjefar, Soheil, 2020. "Maximum power extraction from wind energy system using homotopy singular perturbation and fast terminal sliding mode method," Renewable Energy, Elsevier, vol. 148(C), pages 611-626.
    17. Alessia Cogato & Francesco Marinello & Andrea Pezzuolo, 2023. "Soil Footprint and Land-Use Change to Clean Energy Production: Implications for Solar and Wind Power Plants," Land, MDPI, vol. 12(10), pages 1-10, September.
    18. Yoshihide Tominaga, 2023. "CFD Prediction for Wind Power Generation by a Small Vertical Axis Wind Turbine: A Case Study for a University Campus," Energies, MDPI, vol. 16(13), pages 1-19, June.
    19. Suškevičs, M. & Eiter, S. & Martinat, S. & Stober, D. & Vollmer, E. & de Boer, C.L. & Buchecker, M., 2019. "Regional variation in public acceptance of wind energy development in Europe: What are the roles of planning procedures and participation?," Land Use Policy, Elsevier, vol. 81(C), pages 311-323.
    20. Yanwei Jing & Hexu Sun & Lei Zhang & Tieling Zhang, 2017. "Variable Speed Control of Wind Turbines Based on the Quasi-Continuous High-Order Sliding Mode Method," Energies, MDPI, vol. 10(10), pages 1-21, October.

    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:13:y:2020:i:16:p:4158-:d:397717. 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.