IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v51y2015icp1288-1305.html
   My bibliography  Save this article

Grid-integrated permanent magnet synchronous generator based wind energy conversion systems: A technology review

Author

Listed:
  • Tripathi, S.M.
  • Tiwari, A.N.
  • Singh, Deependra

Abstract

The growing trends in wind energy technology are motivating the researchers to work in this area with the aim towards the optimization of the energy extraction from the wind and the injection of the quality power into the grid. Over the last few years, wind generators based on permanent magnet synchronous machines (PMSMs) are becoming the most popular solution for the modern wind energy conversion systems (WECSs). This paper presents a concise review of the grid-integrated WECSs employing permanent magnet synchronous generators (PMSGs). It reviews the trends in converter topologies, control methodologies, and methods for maximum energy extraction in PMSG based WECSs, which have been reported in various research literatures primarily in reputed research journals and transactions during last few years. It also presents an overview to the grid interconnection issues related to output power smoothing and reactive power control in addition to fault-ride-through (FRT) and grid support capabilities of PMSG based WECSs. This review article will serve the researchers working in the area of grid-integrated PMSG based WECSs in the exploration of trends, developments and challenges in the past research works and in finding out the relevant references for their research work.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:rensus:v:51:y:2015:i:c:p:1288-1305
    DOI: 10.1016/j.rser.2015.06.060
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032115006322
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2015.06.060?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. Hae Gwang Jeong & Ro Hak Seung & Kyo Beum Lee, 2012. "An Improved Maximum Power Point Tracking Method for Wind Power Systems," Energies, MDPI, vol. 5(5), pages 1-16, May.
    2. Ying Zhu & Ming Cheng & Wei Hua & Wei Wang, 2012. "A Novel Maximum Power Point Tracking Control for Permanent Magnet Direct Drive Wind Energy Conversion Systems," Energies, MDPI, vol. 5(5), pages 1-15, May.
    3. Mohamed, Amal Z. & Eskander, Mona N. & Ghali, Fadia A., 2001. "Fuzzy logic control based maximum power tracking of a wind energy system," Renewable Energy, Elsevier, vol. 23(2), pages 235-245.
    4. Abdullah, M.A. & Yatim, A.H.M. & Tan, C.W. & Saidur, R., 2012. "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3220-3227.
    5. Senjyu, Tomonobu & Tamaki, Satoshi & Muhando, Endusa & Urasaki, Naomitsu & Kinjo, Hiroshi & Funabashi, Toshihisa & Fujita, Hideki & Sekine, Hideomi, 2006. "Wind velocity and rotor position sensorless maximum power point tracking control for wind generation system," Renewable Energy, Elsevier, vol. 31(11), pages 1764-1775.
    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. 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.
    2. Manisha Sawant & Sameer Thakare & A. Prabhakara Rao & Andrés E. Feijóo-Lorenzo & Neeraj Dhanraj Bokde, 2021. "A Review on State-of-the-Art Reviews in Wind-Turbine- and Wind-Farm-Related Topics," Energies, MDPI, vol. 14(8), pages 1-30, April.
    3. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    4. Hoffstaedt, J.P. & Truijen, D.P.K. & Fahlbeck, J. & Gans, L.H.A. & Qudaih, M. & Laguna, A.J. & De Kooning, J.D.M. & Stockman, K. & Nilsson, H. & Storli, P.-T. & Engel, B. & Marence, M. & Bricker, J.D., 2022. "Low-head pumped hydro storage: A review of applicable technologies for design, grid integration, control and modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    5. 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).
    6. Sofia Kontos & Anar Ibrayeva & Jennifer Leijon & Gustav Mörée & Anna E. Frost & Linus Schönström & Klas Gunnarsson & Peter Svedlindh & Mats Leijon & Sandra Eriksson, 2020. "An Overview of MnAl Permanent Magnets with a Study on Their Potential in Electrical Machines," Energies, MDPI, vol. 13(21), pages 1-14, October.
    7. 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.
    8. Wajahat Ullah Khan Tareen & Muhammad Aamir & Saad Mekhilef & Mutsuo Nakaoka & Mehdi Seyedmahmoudian & Ben Horan & Mudasir Ahmed Memon & Nauman Anwar Baig, 2018. "Mitigation of Power Quality Issues Due to High Penetration of Renewable Energy Sources in Electric Grid Systems Using Three-Phase APF/STATCOM Technologies: A Review," Energies, MDPI, vol. 11(6), pages 1-41, June.
    9. 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).
    10. Muhammad Maaruf & Md Shafiullah & Ali T. Al-Awami & Fahad S. Al-Ismail, 2021. "Adaptive Nonsingular Fast Terminal Sliding Mode Control for Maximum Power Point Tracking of a WECS-PMSG," Sustainability, MDPI, vol. 13(23), pages 1-19, December.
    11. Tavakol Aghaei, Vahid & Ağababaoğlu, Arda & Bawo, Biram & Naseradinmousavi, Peiman & Yıldırım, Sinan & Yeşilyurt, Serhat & Onat, Ahmet, 2023. "Energy optimization of wind turbines via a neural control policy based on reinforcement learning Markov chain Monte Carlo algorithm," Applied Energy, Elsevier, vol. 341(C).
    12. Youssef, Abdel-Raheem & Mousa, Hossam H.H. & Mohamed, Essam E.M., 2020. "Development of self-adaptive P&O MPPT algorithm for wind generation systems with concentrated search area," Renewable Energy, Elsevier, vol. 154(C), pages 875-893.
    13. 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).
    14. Qi, Jinling & Li, Weixing & Chao, Pupu & Liang, Xiaodong & Sun, Yong & Li, Zhimin, 2021. "Generic EMT modeling method of Type-4 wind turbine generators based on detailed FRT studies," Renewable Energy, Elsevier, vol. 178(C), pages 1129-1143.
    15. Ramji Tiwari & Sanjeevikumar Padmanaban & Ramesh Babu Neelakandan, 2017. "Coordinated Control Strategies for a Permanent Magnet Synchronous Generator Based Wind Energy Conversion System," Energies, MDPI, vol. 10(10), pages 1-17, September.
    16. Barra, P.H.A. & de Carvalho, W.C. & Menezes, T.S. & Fernandes, R.A.S. & Coury, D.V., 2021. "A review on wind power smoothing using high-power energy storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    17. Hu, Yong & Bu, Siqi & Luo, Jianqiang & Wen, Jiaxin, 2023. "Generalization of oscillation loop and energy flow analysis for investigating various oscillations of renewable energy systems," Renewable Energy, Elsevier, vol. 218(C).
    18. Abrar Ahmed Chhipa & Vinod Kumar & Raghuveer Raj Joshi & Prasun Chakrabarti & Michal Jasinski & Alessandro Burgio & Zbigniew Leonowicz & Elzbieta Jasinska & Rajkumar Soni & Tulika Chakrabarti, 2021. "Adaptive Neuro-Fuzzy Inference System-Based Maximum Power Tracking Controller for Variable Speed WECS," Energies, MDPI, vol. 14(19), pages 1-19, October.
    19. Fathabadi, Hassan, 2016. "Maximum mechanical power extraction from wind turbines using novel proposed high accuracy single-sensor-based maximum power point tracking technique," Energy, Elsevier, vol. 113(C), pages 1219-1230.
    20. Ayodele, T.R. & Ogunjuyigbe, A.S.O. & Adetokun, B.B., 2017. "Optimal capacitance selection for a wind-driven self-excited reluctance generator under varying wind speed and load conditions," Applied Energy, Elsevier, vol. 190(C), pages 339-353.
    21. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.
    22. 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.
    23. Sun, Haiying & Qiu, Changyu & Lu, Lin & Gao, Xiaoxia & Chen, Jian & Yang, Hongxing, 2020. "Wind turbine power modelling and optimization using artificial neural network with wind field experimental data," Applied Energy, Elsevier, vol. 280(C).

    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. Emejeamara, F.C. & Tomlin, A.S. & Millward-Hopkins, J.T., 2015. "Urban wind: Characterisation of useful gust and energy capture," Renewable Energy, Elsevier, vol. 81(C), pages 162-172.
    2. 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.
    3. Tania García-Sánchez & Arbinda Kumar Mishra & Elías Hurtado-Pérez & Rubén Puché-Panadero & Ana Fernández-Guillamón, 2020. "A Controller for Optimum Electrical Power Extraction from a Small Grid-Interconnected Wind Turbine," Energies, MDPI, vol. 13(21), pages 1-16, November.
    4. 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.
    5. 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.
    6. Héctor Zazo & Esteban Del Castillo & Jean François Reynaud & Ramon Leyva, 2012. "MPPT for Photovoltaic Modules via Newton-Like Extremum Seeking Control," Energies, MDPI, vol. 5(8), pages 1-15, July.
    7. Ewa Chomać-Pierzecka & Anna Sobczak & Dariusz Soboń, 2022. "Wind Energy Market in Poland in the Background of the Baltic Sea Bordering Countries in the Era of the COVID-19 Pandemic," Energies, MDPI, vol. 15(7), pages 1-21, March.
    8. Mokhtari, Yacine & Rekioua, Djamila, 2018. "High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine," Renewable Energy, Elsevier, vol. 126(C), pages 1055-1063.
    9. Billy Muhando, Endusa & Senjyu, Tomonobu & Urasaki, Naomitsu & Yona, Atsushi & Kinjo, Hiroshi & Funabashi, Toshihisa, 2007. "Gain scheduling control of variable speed WTG under widely varying turbulence loading," Renewable Energy, Elsevier, vol. 32(14), pages 2407-2423.
    10. Ram, J.Prasanth & Rajasekar, N. & Miyatake, Masafumi, 2017. "Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1138-1159.
    11. Akour, Salih N. & Al-Heymari, Mohammed & Ahmed, Talha & Khalil, Kamel Ali, 2018. "Experimental and theoretical investigation of micro wind turbine for low wind speed regions," Renewable Energy, Elsevier, vol. 116(PA), pages 215-223.
    12. Dinh-Chung Phan & Shigeru Yamamoto, 2015. "Maximum Energy Output of a DFIG Wind Turbine Using an Improved MPPT-Curve Method," Energies, MDPI, vol. 8(10), pages 1-19, October.
    13. Bo Li & Wenhu Tang & Kaishun Xiahou & Qinghua Wu, 2017. "Development of Novel Robust Regulator for Maximum Wind Energy Extraction Based upon Perturbation and Observation," Energies, MDPI, vol. 10(4), pages 1-21, April.
    14. 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.
    15. Constantin Voloşencu, 2021. "A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking," Mathematics, MDPI, vol. 9(19), pages 1-33, September.
    16. Alizadeh, Mojtaba & Kojori, Shokrollah Shokri, 2015. "Augmenting effectiveness of control loops of a PMSG (permanent magnet synchronous generator) based wind energy conversion system by a virtually adaptive PI (proportional integral) controller," Energy, Elsevier, vol. 91(C), pages 610-629.
    17. Pustina, L. & Biral, F. & Serafini, J., 2022. "A novel Economic Nonlinear Model Predictive Controller for power maximisation on wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    18. 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.
    19. Ademi, Sul & Jovanovic, Milutin, 2016. "Control of doubly-fed reluctance generators for wind power applications," Renewable Energy, Elsevier, vol. 85(C), pages 171-180.
    20. Yin, Xiu-xing & Lin, Yong-gang & Li, Wei & Gu, Ya-jing & Liu, Hong-wei & Lei, Peng-fei, 2015. "A novel fuzzy integral sliding mode current control strategy for maximizing wind power extraction and eliminating voltage harmonics," Energy, Elsevier, vol. 85(C), pages 677-686.

    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:rensus:v:51:y:2015:i:c:p:1288-1305. 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/600126/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.