IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v106y2016icp137-146.html
   My bibliography  Save this article

New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system

Author

Listed:
  • Medjber, Ahmed
  • Guessoum, Abderrezak
  • Belmili, Hocine
  • Mellit, Adel

Abstract

This work presents a new control strategy to ensure maximum power point tracking for a DFIG (doubly fed induction generator) based WECS (wind energy conversion system). The proposed strategy uses neural networks and fuzzy logic controllers to control the power transfer between the machine and the grid using the indirect vector control and reactive power control techniques. This transfer is ensured by controlling the rotor via two identical converters. The first converter is connected to the RSC (rotor side) and the second is connected to the GSC (grid side) via a filter. The DC (Direct Current) link voltage is controlled by a fuzzy controller. This control strategy is used to control the rotor side currents and to protect the generator by limiting the output current (or voltage).

Suggested Citation

  • Medjber, Ahmed & Guessoum, Abderrezak & Belmili, Hocine & Mellit, Adel, 2016. "New neural network and fuzzy logic controllers to monitor maximum power for wind energy conversion system," Energy, Elsevier, vol. 106(C), pages 137-146.
    • Handle: RePEc:eee:energy:v:106:y:2016:i:c:p:137-146
    DOI: 10.1016/j.energy.2016.03.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216302705
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2016.03.026?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. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    2. Lin, Whei-Min & Hong, Chih-Ming & Cheng, Fu-Sheng, 2010. "Fuzzy neural network output maximization control for sensorless wind energy conversion system," Energy, Elsevier, vol. 35(2), pages 592-601.
    3. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.
    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. Zheng, Chong-wei & Xiao, Zi-niu & Peng, Yue-hua & Li, Chong-yin & Du, Zhi-bo, 2018. "Rezoning global offshore wind energy resources," Renewable Energy, Elsevier, vol. 129(PA), pages 1-11.
    2. Das, Soubhagya K. & Verma, Deepak & Nema, Savita & Nema, R.K., 2017. "Shading mitigation techniques: State-of-the-art in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 369-390.
    3. Marugán, Alberto Pliego & Márquez, Fausto Pedro García & Perez, Jesus María Pinar & Ruiz-Hernández, Diego, 2018. "A survey of artificial neural network in wind energy systems," Applied Energy, Elsevier, vol. 228(C), pages 1822-1836.
    4. Fathy, Ahmed & Rezk, Hegazy & Yousri, Dalia & Kandil, Tarek & Abo-Khalil, Ahmed G., 2022. "Real-time bald eagle search approach for tracking the maximum generated power of wind energy conversion system," Energy, Elsevier, vol. 249(C).
    5. Bodha, Venugopal Reddy & Srujana, A. & Chandrashekar, O., 2018. "A modified H-bridge voltage source converter with Fault Ride Capability," Energy, Elsevier, vol. 165(PB), pages 1380-1391.

    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. Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
    2. Lin, Whei-Min & Hong, Chih-Ming & Cheng, Fu-Sheng, 2010. "On-line designed hybrid controller with adaptive observer for variable-speed wind generation system," Energy, Elsevier, vol. 35(7), pages 3022-3030.
    3. Belkacem Belabbas & Tayeb Allaoui & Mohamed Tadjine & Mouloud Denai, 2019. "Comparative study of back-stepping controller and super twisting sliding mode controller for indirect power control of wind generator," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(6), pages 1555-1566, December.
    4. Hamid Chojaa & Aziz Derouich & Mohammed Taoussi & Seif Eddine Chehaidia & Othmane Zamzoum & Mohamed I. Mosaad & Ayman Alhejji & Mourad Yessef, 2022. "Nonlinear Control Strategies for Enhancing the Performance of DFIG-Based WECS under a Real Wind Profile," Energies, MDPI, vol. 15(18), pages 1-23, September.
    5. Al-Falahi, Monaaf D.A. & Jayasinghe, Shantha D.G. & Enshaei, Hossein, 2019. "Hybrid algorithm for optimal operation of hybrid energy systems in electric ferries," Energy, Elsevier, vol. 187(C).
    6. Jen Chun Wang & Kuo-Tsang Huang & Meng Yun Ko, 2019. "Using the Fuzzy Delphi Method to Study the Construction Needs of an Elementary Campus and Achieve Sustainability," Sustainability, MDPI, vol. 11(23), pages 1-13, December.
    7. Hannan, M.A. & Ali, Jamal A. & Mohamed, Azah & Hussain, Aini, 2018. "Optimization techniques to enhance the performance of induction motor drives: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 1611-1626.
    8. Laura Canale & Anna Rita Di Fazio & Mario Russo & Andrea Frattolillo & Marco Dell’Isola, 2021. "An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings," Energies, MDPI, vol. 14(4), pages 1-33, February.
    9. Phan, Dinh-Chung & Yamamoto, Shigeru, 2016. "Rotor speed control of doubly fed induction generator wind turbines using adaptive maximum power point tracking," Energy, Elsevier, vol. 111(C), pages 377-388.
    10. 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.
    11. Nima Mirzaei, 2022. "A Multicriteria Decision Framework for Solar Power Plant Location Selection Problem with Pythagorean Fuzzy Data: A Case Study on Green Energy in Turkey," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    12. Sellak, Hamza & Ouhbi, Brahim & Frikh, Bouchra & Palomares, Iván, 2017. "Towards next-generation energy planning decision-making: An expert-based framework for intelligent decision support," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1544-1577.
    13. Kara Mostefa Khelil, Chérifa & Amrouche, Badia & Benyoucef, Abou soufiane & Kara, Kamel & Chouder, Aissa, 2020. "New Intelligent Fault Diagnosis (IFD) approach for grid-connected photovoltaic systems," Energy, Elsevier, vol. 211(C).
    14. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    15. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    16. Harrou, Fouzi & Sun, Ying & Taghezouit, Bilal & Saidi, Ahmed & Hamlati, Mohamed-Elkarim, 2018. "Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches," Renewable Energy, Elsevier, vol. 116(PA), pages 22-37.
    17. Md Alamgir Hossain & Hemanshu Roy Pota & Walid Issa & Md Jahangir Hossain, 2017. "Overview of AC Microgrid Controls with Inverter-Interfaced Generations," Energies, MDPI, vol. 10(9), pages 1-27, August.
    18. Burgaç, Alper & Yavuz, Hakan, 2019. "Fuzzy Logic based hybrid type control implementation of a heaving wave energy converter," Energy, Elsevier, vol. 170(C), pages 1202-1214.
    19. Ganjefar, Soheil & Ghassemi, Ali Akbar & Ahmadi, Mohamad Mehdi, 2014. "Improving efficiency of two-type maximum power point tracking methods of tip-speed ratio and optimum torque in wind turbine system using a quantum neural network," Energy, Elsevier, vol. 67(C), pages 444-453.
    20. Kumar, Rajesh & Agarwala, Arun, 2016. "Renewable energy technology diffusion model for techno-economics feasibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1515-1524.

    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:energy:v:106:y:2016:i:c:p:137-146. 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/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.