IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v130y2020ics096007791930342x.html
   My bibliography  Save this article

An innovative optimal RPO-FOSMC based on multi-objective grasshopper optimization algorithm for DFIG-based wind turbine to augment MPPT and FRT capabilities

Author

Listed:
  • Darvish Falehi, Ali

Abstract

Doubly Fed Induction Generator (DFIG) with consideration of its exceptional capabilities, i.e.: variable speed operation, low mechanical stresses, and excellent power quality in limited-range speed applications is a famous kind of wind turbines. Even so, there is a challenge due to its nonlinear dynamic features and several uncertainties like unknown non-linear disturbances and parameter uncertainties. Hence, this paper proposes a novel Robust Perturbation Observer based Fractional Order Sliding Mode Controller (RPO-FOSMC) for DFIG to extract the maximum power and improve the Fault Ride-Through (FRT) capability. The strong nonlinear aerodynamics of wind turbine, the uncertain dynamic parameters of induction generator and the stochastic characteristics of wind waves are constructed in perturbation term which is estimated using the proposed RPO-FOSMC. Accordingly, the perturbation compensator provides an appropriate robustness concerning different uncertain models and attains an exceptional control capability during stochastic wind waves. Considering the inherent multi-objective nature of the nonlinear control design problem, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) has been implemented to augment the robustness and dynamic performance of RPO-FOSMC. Three distinct conditions are considered to compare and analyse the fast and robust dynamic performance of optimal RPO-FOSMC against other conventional approaches. Eventually, the comprehensive simulation results have revealed and validated the exceptional dynamic capability of the suggested control strategy.

Suggested Citation

  • Darvish Falehi, Ali, 2020. "An innovative optimal RPO-FOSMC based on multi-objective grasshopper optimization algorithm for DFIG-based wind turbine to augment MPPT and FRT capabilities," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    • Handle: RePEc:eee:chsofr:v:130:y:2020:i:c:s096007791930342x
    DOI: 10.1016/j.chaos.2019.109407
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S096007791930342X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2019.109407?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. Jurasz, Jakub & Dąbek, Paweł B. & Kaźmierczak, Bartosz & Kies, Alexander & Wdowikowski, Marcin, 2018. "Large scale complementary solar and wind energy sources coupled with pumped-storage hydroelectricity for Lower Silesia (Poland)," Energy, Elsevier, vol. 161(C), pages 183-192.
    2. Sorrell, Steve, 2015. "Reducing energy demand: A review of issues, challenges and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 74-82.
    3. Hansen, Ulrich Elmer & Lema, Rasmus, 2019. "The co-evolution of learning mechanisms and technological capabilities: Lessons from energy technologies in emerging economies," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 241-257.
    4. Raju, S.Krishnama & Pillai, G.N., 2016. "Design and real time implementation of type-2 fuzzy vector control for DFIG based wind generators," Renewable Energy, Elsevier, vol. 88(C), pages 40-50.
    5. Taveiros, F.E.V. & Barros, L.S. & Costa, F.B., 2015. "Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines," Energy, Elsevier, vol. 89(C), pages 896-906.
    6. Saad, Naggar H. & Sattar, Ahmed A. & Mansour, Abd El-Aziz M., 2015. "Low voltage ride through of doubly-fed induction generator connected to the grid using sliding mode control strategy," Renewable Energy, Elsevier, vol. 80(C), pages 583-594.
    7. Chuang, Ming-Tung & Chang, Shih-Yu & Hsiao, Ta-Chih & Lu, Yun-Ru & Yang, Tsung-Yeh, 2019. "Analyzing major renewable energy sources and power stability in Taiwan by 2030," Energy Policy, Elsevier, vol. 125(C), pages 293-306.
    8. Gayen, P.K. & Chatterjee, D. & Goswami, S.K., 2015. "Stator side active and reactive power control with improved rotor position and speed estimator of a grid connected DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 89(C), pages 461-472.
    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.
    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. Wang, Jianzhou & Zhou, Yilin & Li, Zhiwu, 2022. "Hour-ahead photovoltaic generation forecasting method based on machine learning and multi objective optimization algorithm," Applied Energy, Elsevier, vol. 312(C).
    2. Chou, Jui-Sheng & Truong, Dinh-Nhat, 2020. "Multiobjective optimization inspired by behavior of jellyfish for solving structural design problems," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    3. Mousavi, Yashar & Bevan, Geraint & Kucukdemiral, Ibrahim Beklan & Fekih, Afef, 2022. "Sliding mode control of wind energy conversion systems: Trends and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(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. Yang, Bo & Yu, Tao & Shu, Hongchun & Dong, Jun & Jiang, Lin, 2018. "Robust sliding-mode control of wind energy conversion systems for optimal power extraction via nonlinear perturbation observers," Applied Energy, Elsevier, vol. 210(C), pages 711-723.
    2. Rafael Peña Gallardo & Adalberto Ospino Castro & Aurelio Medina Ríos, 2020. "An Image Processing-Based Method to Assess the Monthly Energetic Complementarity of Solar and Wind Energy in Colombia," Energies, MDPI, vol. 13(5), pages 1-17, February.
    3. Mustaffa, Nur Kamaliah & Kudus, Sakhiah Abdul, 2022. "Challenges and way forward towards best practices of energy efficient building in Malaysia," Energy, Elsevier, vol. 259(C).
    4. Vadim Manusov & Svetlana Beryozkina & Muso Nazarov & Murodbek Safaraliev & Inga Zicmane & Pavel Matrenin & Anvari Ghulomzoda, 2022. "Optimal Management of Energy Consumption in an Autonomous Power System Considering Alternative Energy Sources," Mathematics, MDPI, vol. 10(3), pages 1-17, February.
    5. Filippo Corsini & Rafael Laurenti & Franziska Meinherz & Francesco Paolo Appio & Luca Mora, 2019. "The Advent of Practice Theories in Research on Sustainable Consumption: Past, Current and Future Directions of the Field," Sustainability, MDPI, vol. 11(2), pages 1-19, January.
    6. Ikutegbe, Charles A. & Farid, Mohammed M., 2020. "Application of phase change material foam composites in the built environment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    7. Martín Lallana & Adrián Almazán & Alicia Valero & Ángel Lareo, 2021. "Assessing Energy Descent Scenarios for the Ecological Transition in Spain 2020–2030," Sustainability, MDPI, vol. 13(21), pages 1-34, October.
    8. He, Xianghui & Yang, Jiandong & Yang, Jiebin & Zhao, Zhigao & Hu, Jinhong & Peng, Tao, 2023. "Evolution mechanism of water column separation in pump turbine: Model experiment and occurrence criterion," Energy, Elsevier, vol. 265(C).
    9. Feng, Chun-Chiang & Chang, Kuei-Feng & Lin, Jin-Xu & Lee, Tsung-Chen & Lin, Shih-Mo, 2022. "Toward green transition in the post Paris Agreement era: The case of Taiwan," Energy Policy, Elsevier, vol. 165(C).
    10. Wang, Gang & Zhang, Zhen & Lin, Jianqing, 2024. "Multi-energy complementary power systems based on solar energy: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
    11. Carmen de la Cruz-Lovera & Alberto-Jesus Perea-Moreno & José Luis de la Cruz-Fernández & Francisco G. Montoya & Alfredo Alcayde & Francisco Manzano-Agugliaro, 2019. "Analysis of Research Topics and Scientific Collaborations in Energy Saving Using Bibliometric Techniques and Community Detection," Energies, MDPI, vol. 12(10), pages 1-23, May.
    12. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
    13. Bobrova, Yekatherina & Papachristos, George & Chiu, Lai Fong, 2021. "Homeowner low carbon retrofits: Implications for future UK policy," Energy Policy, Elsevier, vol. 155(C).
    14. Mahdy, Ahmed & Hasanien, Hany M. & Helmy, Waleed & Turky, Rania A. & Abdel Aleem, Shady H.E., 2022. "Transient stability improvement of wave energy conversion systems connected to power grid using anti-windup-coot optimization strategy," Energy, Elsevier, vol. 245(C).
    15. Piotr Dzikowski, 2022. "Product and process innovation patterns in Polish low and high technology systems," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 747-773, September.
    16. Bienvenido-Huertas, David & Sánchez-García, Daniel & Rubio-Bellido, Carlos & Marín-García, David, 2024. "Holistic analysis to reduce energy poverty in social dwellings in southern Spain considering envelope, systems, operational pattern, and income levels," Energy, Elsevier, vol. 288(C).
    17. Kangas, Hanna-Liisa & Lazarevic, David & Kivimaa, Paula, 2018. "Technical skills, disinterest and non-functional regulation: Barriers to building energy efficiency in Finland viewed by energy service companies," Energy Policy, Elsevier, vol. 114(C), pages 63-76.
    18. Seung-Min Jung & Sungwoo Park & Seung-Won Jung & Eenjun Hwang, 2020. "Monthly Electric Load Forecasting Using Transfer Learning for Smart Cities," Sustainability, MDPI, vol. 12(16), pages 1-20, August.
    19. Ioan G. Pop & Sebastian Văduva & Mihai-Florin Talpoș, 2017. "Energetic Sustainability and the Environment: A Transdisciplinary, Economic–Ecological Approach," Sustainability, MDPI, vol. 9(6), pages 1-12, May.
    20. Morley, Janine, 2018. "Rethinking energy services: The concept of ‘meta-service’ and implications for demand reduction and servicizing policy," Energy Policy, Elsevier, vol. 122(C), pages 563-569.

    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:chsofr:v:130:y:2020:i:c:s096007791930342x. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.