IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v113y2017icp895-906.html
   My bibliography  Save this article

Adaptive linear prediction for optimal control of wind turbines

Author

Listed:
  • Narayana, Mahinsasa
  • Sunderland, Keith M.
  • Putrus, Ghanim
  • Conlon, Michael F.

Abstract

In order to obtain maximum power output of a Wind Energy Conversion System (WECS), the rotor speed needs to be optimised for a particular wind speed. However, due to inherent inertia, the rotor of a WECS cannot react instantaneously according to wind speed variations. As a consequence, the performance of the system and consequently the wind energy conversion capability of the rotor are negatively affected. This study considers the use of a time series Adaptive Linear Prediction (ALP) technique as a means to improve the performance and conversion efficiency of wind turbines. The ALP technique is introduced as a real time control reference to improve optimal control of wind turbines. In this study, a wind turbine emulator is developed to evaluate the performance of the predictive control strategy. In this regard, the ALP reference control method was applied as a means to control the torque/speed of the emulator. The results show that the employment of a predictive technique increases energy yield by almost 5%.

Suggested Citation

  • Narayana, Mahinsasa & Sunderland, Keith M. & Putrus, Ghanim & Conlon, Michael F., 2017. "Adaptive linear prediction for optimal control of wind turbines," Renewable Energy, Elsevier, vol. 113(C), pages 895-906.
    • Handle: RePEc:eee:renene:v:113:y:2017:i:c:p:895-906
    DOI: 10.1016/j.renene.2017.06.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117305463
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.06.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lei, Ma & Shiyan, Luan & Chuanwen, Jiang & Hongling, Liu & Yan, Zhang, 2009. "A review on the forecasting of wind speed and generated power," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 915-920, May.
    2. Arifujjaman, Md. & Iqbal, M. Tariq & Quaicoe, John E., 2008. "Energy capture by a small wind-energy conversion system," Applied Energy, Elsevier, vol. 85(1), pages 41-51, January.
    3. Bououden, S. & Chadli, M. & Filali, S. & El Hajjaji, A., 2012. "Fuzzy model based multivariable predictive control of a variable speed wind turbine: LMI approach," Renewable Energy, Elsevier, vol. 37(1), pages 434-439.
    4. Tripathi, S.M. & Tiwari, A.N. & Singh, Deependra, 2015. "Grid-integrated permanent magnet synchronous generator based wind energy conversion systems: A technology review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1288-1305.
    5. Lingfei Li & Rafael Mendoza-Arriaga & Zhiyu Mo & Daniel Mitchell, 2016. "Modelling electricity prices: a time change approach," Quantitative Finance, Taylor & Francis Journals, vol. 16(7), pages 1089-1109, July.
    6. Mihai Burcea & Wing-Kai Hon & Hsiang-Hsuan Liu & Prudence W. H. Wong & David K. Y. Yau, 2016. "Scheduling for electricity cost in a smart grid," Journal of Scheduling, Springer, vol. 19(6), pages 687-699, December.
    7. Kortabarria, Iñigo & Andreu, Jon & Martínez de Alegría, Iñigo & Jiménez, Jaime & Gárate, José Ignacio & Robles, Eider, 2014. "A novel adaptative maximum power point tracking algorithm for small wind turbines," Renewable Energy, Elsevier, vol. 63(C), pages 785-796.
    8. ., 2016. "Electric energy utilities," Chapters, in: Public Utilities, Second Edition, chapter 4, pages 69-88, Edward Elgar Publishing.
    9. Narayana, M. & Putrus, G.A. & Jovanovic, M. & Leung, P.S. & McDonald, S., 2012. "Generic maximum power point tracking controller for small-scale wind turbines," Renewable Energy, Elsevier, vol. 44(C), pages 72-79.
    10. Mohandes, Mohamed A. & Rehman, Shafiqur & Halawani, Talal O., 1998. "A neural networks approach for wind speed prediction," Renewable Energy, Elsevier, vol. 13(3), pages 345-354.
    11. Baroudi, Jamal A. & Dinavahi, Venkata & Knight, Andrew M., 2007. "A review of power converter topologies for wind generators," Renewable Energy, Elsevier, vol. 32(14), pages 2369-2385.
    12. Cadenas, Erasmo & Rivera, Wilfrido, 2007. "Wind speed forecasting in the South Coast of Oaxaca, México," Renewable Energy, Elsevier, vol. 32(12), pages 2116-2128.
    13. Do, Linh Phuong Catherine & Lin, Kuan-Heng & Molnár, Peter, 2016. "Electricity consumption modelling: A case of Germany," Economic Modelling, Elsevier, vol. 55(C), pages 92-101.
    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. Karabacak, Murat, 2019. "A new perturb and observe based higher order sliding mode MPPT control of wind turbines eliminating the rotor inertial effect," Renewable Energy, Elsevier, vol. 133(C), pages 807-827.
    2. Ping Jiang & Tianyi Zhang & Jinpeng Geng & Peiguang Wang & Lei Fu, 2023. "An MPPT Strategy for Wind Turbines Combining Feedback Linearization and Model Predictive Control," Energies, MDPI, vol. 16(10), pages 1-16, May.
    3. Barambones, Oscar & Cortajarena, Jose A. & Calvo, Isidro & Gonzalez de Durana, Jose M. & Alkorta, Patxi & Karami-Mollaee, A., 2019. "Variable speed wind turbine control scheme using a robust wind torque estimation," Renewable Energy, Elsevier, vol. 133(C), pages 354-366.
    4. Kaman Thapa Magar & Mark Balas & Susan Frost & Nailu Li, 2017. "Adaptive State Feedback—Theory and Application for Wind Turbine Control," Energies, MDPI, vol. 10(12), pages 1-15, December.
    5. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.

    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. Ata, Rasit, 2015. "Artificial neural networks applications in wind energy systems: a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 534-562.
    2. Dixon, Christopher & Reynolds, Steve & Rodley, David, 2016. "Micro/small wind turbine power control for electrolysis applications," Renewable Energy, Elsevier, vol. 87(P1), pages 182-192.
    3. Wild, Phillip, 2017. "Determining commercially viable two-way and one-way ‘Contract-for-Difference’ strike prices and revenue receipts," Energy Policy, Elsevier, vol. 110(C), pages 191-201.
    4. Aithal, Avinash & Li, Gen & Wu, Jianzhong & Yu, James, 2018. "Performance of an electrical distribution network with Soft Open Point during a grid side AC fault," Applied Energy, Elsevier, vol. 227(C), pages 262-272.
    5. Hilden, Mikael & Huuki, Hannu & Kivisaari, Visa & Kopsakangas-Savolainen, Maria, 2018. "The importance of transnational impacts of climate change in a power market," Energy Policy, Elsevier, vol. 115(C), pages 418-425.
    6. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2017. "The feasibility of solar parking lots for electric vehicles," Energy, Elsevier, vol. 140(P1), pages 1182-1197.
    7. Bizhani, Hamed & Noroozian, Reza & Muyeen, S.M. & Blaabjerg, Frede, 2022. "Grid integration of multiple wind turbines using a multi-port converter—A novel simultaneous space vector modulation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    8. De Kooning, Jeroen D.M. & Vandoorn, Tine L. & Van de Vyver, Jan & Meersman, Bart & Vandevelde, Lieven, 2016. "Displacement of the maximum power point caused by losses in wind turbine systems," Renewable Energy, Elsevier, vol. 85(C), pages 273-280.
    9. Méndez-Gordillo, Alma Rosa & Cadenas, Erasmo, 2021. "Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    10. Philippopoulos, Kostas & Deligiorgi, Despina, 2012. "Application of artificial neural networks for the spatial estimation of wind speed in a coastal region with complex topography," Renewable Energy, Elsevier, vol. 38(1), pages 75-82.
    11. Seixas, M. & Melício, R. & Mendes, V.M.F. & Couto, C., 2016. "Blade pitch control malfunction simulation in a wind energy conversion system with MPC five-level converter," Renewable Energy, Elsevier, vol. 89(C), pages 339-350.
    12. Cadenas, Erasmo & Rivera, Wilfrido, 2010. "Wind speed forecasting in three different regions of Mexico, using a hybrid ARIMA–ANN model," Renewable Energy, Elsevier, vol. 35(12), pages 2732-2738.
    13. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    14. Loeb, Benjamin & Kockelman, Kara M., 2019. "Fleet performance and cost evaluation of a shared autonomous electric vehicle (SAEV) fleet: A case study for Austin, Texas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 374-385.
    15. 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.
    16. Tran, Thomas T.D. & Smith, Amanda D., 2017. "fEvaluation of renewable energy technologies and their potential for technical integration and cost-effective use within the U.S. energy sector," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1372-1388.
    17. Rodrigues, Eugénio & Gomes, Álvaro & Gaspar, Adélio Rodrigues & Henggeler Antunes, Carlos, 2018. "Estimation of renewable energy and built environment-related variables using neural networks – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 959-988.
    18. Zhang, Xi & Strbac, Goran & Teng, Fei & Djapic, Predrag, 2018. "Economic assessment of alternative heat decarbonisation strategies through coordinated operation with electricity system – UK case study," Applied Energy, Elsevier, vol. 222(C), pages 79-91.
    19. Yang, Zhimin & Chai, Yi, 2016. "A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 345-359.
    20. Saira Al-Zadjali & Ahmed Al Maashri & Amer Al-Hinai & Sultan Al-Yahyai & Mostafa Bakhtvar, 2019. "An Accurate, Light-Weight Wind Speed Predictor for Renewable Energy Management Systems," Energies, MDPI, vol. 12(22), pages 1-20, November.

    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:eee:renene:v:113:y:2017:i:c:p:895-906. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    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.