IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v357y2024ics0306261923018561.html
   My bibliography  Save this article

A single current sensor based adaptive step size MPPT control of a small scale variable speed wind energy conversion system

Author

Listed:
  • Mendi, Balaji
  • Pattnaik, Monalisa
  • Srungavarapu, Gopalakrishna

Abstract

Due to the limited size and lower environmental impact, a small-scale wind energy conversion system (WECS) is a promising alternative for remote locations and residential areas where installing large wind turbines is not feasible. This system employs a permanent magnet synchronous generator (PMSG) as a variable speed wind generator due to its advantages such as high torque density, gearless, and require no external excitation, etc. This article proposes a single load current sensor-based adaptive step size (LCAS) maximum power point extraction (MPPT) method which utilizes the load current information to track the maximum power. This method does not require rotor speed information and knowledge of the turbine parameters. Also, this article uses a simple and cost-effective switch mode rectifier topology (AC–DC and DC–DC boost converters) for the PMSG-based variable speed WECS. The proposed method is validated in a 1.5 kW test rig using an OPAL-RT digital signal controller and also compared with various fixed step size (FSS) MPPT algorithms at various operating conditions. Extensive experimental work has been carried out for the LCAS MPPT method that confirms the tracking efficiency is better and tracking speed is faster along with the improved steady state as well as transient performance.

Suggested Citation

  • Mendi, Balaji & Pattnaik, Monalisa & Srungavarapu, Gopalakrishna, 2024. "A single current sensor based adaptive step size MPPT control of a small scale variable speed wind energy conversion system," Applied Energy, Elsevier, vol. 357(C).
    • Handle: RePEc:eee:appene:v:357:y:2024:i:c:s0306261923018561
    DOI: 10.1016/j.apenergy.2023.122492
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923018561
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2023.122492?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. 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.
    2. 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.
    3. 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.
    Full references (including those not matched with items on IDEAS)

    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. Younes Azelhak & Loubna Benaaouinate & Hicham Medromi & Youssef Errami & Tarik Bouragba & Damien Voyer, 2021. "Exhaustive Comparison between Linear and Nonlinear Approaches for Grid-Side Control of Wind Energy Conversion Systems," Energies, MDPI, vol. 14(13), pages 1-20, July.
    3. 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.
    4. Rocha, P. A. Costa & Rocha, H. H. Barbosa & Carneiro, F. O. Moura & da Silva, M. E. Vieira & de Andrade, C. Freitas, 2016. "A case study on the calibration of the k–ω SST (shear stress transport) turbulence model for small scale wind turbines designed with cambered and symmetrical airfoils," Energy, Elsevier, vol. 97(C), pages 144-150.
    5. 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.
    6. 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.
    7. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    8. Tai Li & Yanbo Wang & Sunan Sun & Huimin Qian & Leqiu Wang & Lei Wang & Yanxia Shen & Zhicheng Ji, 2023. "Fuzzy Active Disturbance Rejection-Based Virtual Inertia Control Strategy for Wind Farms," Energies, MDPI, vol. 16(10), pages 1-16, May.
    9. Zhicheng Lin & Song Zheng & Zhicheng Chen & Rong Zheng & Wang Zhang, 2019. "Application Research of the Parallel System Theory and the Data Engine Approach in Wind Energy Conversion System," Energies, MDPI, vol. 12(5), pages 1-20, March.
    10. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    11. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    12. 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.
    13. Dongran Song & Jian Yang & Mei Su & Anfeng Liu & Yao Liu & Young Hoon Joo, 2017. "A Comparison Study between Two MPPT Control Methods for a Large Variable-Speed Wind Turbine under Different Wind Speed Characteristics," Energies, MDPI, vol. 10(5), pages 1-18, May.
    14. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
    15. 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.
    16. Ganesh Mayilsamy & Balasubramani Natesan & Young Hoon Joo & Seong Ryong Lee, 2022. "Fast Terminal Synergetic Control of PMVG-Based Wind Energy Conversion System for Enhancing the Power Extraction Efficiency," Energies, MDPI, vol. 15(8), pages 1-22, April.
    17. Matheus Schramm Dall’Asta & Telles Brunelli Lazzarin, 2024. "A Review of Fast Power-Reserve Control Techniques in Grid-Connected Wind Energy Conversion Systems," Energies, MDPI, vol. 17(2), pages 1-29, January.
    18. Vasudevan, Krishnakumar R. & Ramachandaramurthy, Vigna K. & Venugopal, Gomathi & Ekanayake, J.B. & Tiong, S.K., 2021. "Variable speed pumped hydro storage: A review of converters, controls and energy management strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. 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.
    20. 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.

    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:appene:v:357:y:2024:i:c:s0306261923018561. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.