IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v8y2020i11p2012-d443391.html
   My bibliography  Save this article

Modeling and Performance Improvement of Direct Power Control of Doubly-Fed Induction Generator Based Wind Turbine through Second-Order Sliding Mode Control Approach

Author

Listed:
  • Mohammed Mazen Alhato

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis (ENIT), University of Tunis, El Manar, BP 37, Le Belvédère, Tunis 1002, Tunisia)

  • Soufiene Bouallègue

    (Research Laboratory in Automatic Control (LARA), National Engineering School of Tunis (ENIT), University of Tunis, El Manar, BP 37, Le Belvédère, Tunis 1002, Tunisia
    Higher Institute of Industrial Systems of Gabès, Gabès 6011, Tunisia)

  • Hegazy Rezk

    (College of Engineering at Wadi Addawaser, Prince Sattam Bin Abdulaziz University, Al-Kharj 11911, Saudi Arabia
    Electrical Engineering Department, Faculty of Engineering, Minia University, Minia 61517, Egypt)

Abstract

A second-order sliding mode (SOSM)-based direct power control (DPC) of a doubly-fed induction generator (DFIG) is introduced in this research paper. Firstly, the DFIG output powers are regulated with the developed SOSM controller-based DPC scheme. The Super Twisting Algorithm (STA) has been used to reduce the chattering phenomenon. The proposed strategy is a combination of the Lyapunov theory and metaheuristics algorithms, which has been considered to identify the optimal gains of the STA-SOSM controllers. The Lyapunov function method is employed to define the stability regions of the controller parameters. On the other hand, the metaheuristics algorithms are mainly employed to select the fine controllers’ parameters from the predefined ranges. A Thermal Exchange Optimization (TEO) method is used to compute the optimal gain parameters. To prove the superiority of the proposed TEO, its obtained results have been compared with those obtained by other algorithms, including particle swarm optimization, genetic algorithm, water cycle algorithm, grasshopper optimization algorithm and harmony search algorithm. Moreover, the results of the introduced TEO-based SOSM controller have been also compared with the Proportional-Integral (PI)-based vector control and the conventional sliding mode control-based DPC. Moreover, an empirical comparison is carried out to investigate the indication of every metaheuristics method by employing Friedman’s rank and Bonferroni tests. The main findings indicate the effectiveness of STA-SOSM control for system stability and power quality improvement. The ripples in the active and reactive powers are minimized and the harmonics’ distortions of stator and rotor currents are improved. Besides, the STA-SOSM controller shows a superior performance of control in terms of chattering phenomenon elimination.

Suggested Citation

  • Mohammed Mazen Alhato & Soufiene Bouallègue & Hegazy Rezk, 2020. "Modeling and Performance Improvement of Direct Power Control of Doubly-Fed Induction Generator Based Wind Turbine through Second-Order Sliding Mode Control Approach," Mathematics, MDPI, vol. 8(11), pages 1-31, November.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:11:p:2012-:d:443391
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/8/11/2012/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/8/11/2012/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Oscar Barambones & Jose A. Cortajarena & Patxi Alkorta & Jose M. Gonzalez De Durana, 2014. "A Real-Time Sliding Mode Control for a Wind Energy System Based on a Doubly Fed Induction Generator," Energies, MDPI, vol. 7(10), pages 1-22, October.
    2. Linyun Xiong & Penghan Li & Hao Li & Jie Wang, 2017. "Sliding Mode Control of DFIG Wind Turbines with a Fast Exponential Reaching Law," Energies, MDPI, vol. 10(11), pages 1-19, November.
    3. Mohamed, Mohamed A. & Zaki Diab, Ahmed A. & Rezk, Hegazy, 2019. "Partial shading mitigation of PV systems via different meta-heuristic techniques," Renewable Energy, Elsevier, vol. 130(C), pages 1159-1175.
    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. Habib Benbouhenni & Nicu Bizon & Ilhami Colak & Phatiphat Thounthong & Noureddine Takorabet, 2022. "Simplified Super Twisting Sliding Mode Approaches of the Double-Powered Induction Generator-Based Multi-Rotor Wind Turbine System," Sustainability, MDPI, vol. 14(9), pages 1-22, April.
    2. Habib Benbouhenni & Zinelaabidine Boudjema & Nicu Bizon & Phatiphat Thounthong & Noureddine Takorabet, 2022. "Direct Power Control Based on Modified Sliding Mode Controller for a Variable-Speed Multi-Rotor Wind Turbine System Using PWM Strategy," Energies, MDPI, vol. 15(10), pages 1-25, May.
    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. Mohammed Mazen Alhato & Mohamed N. Ibrahim & Hegazy Rezk & Soufiene Bouallègue, 2021. "An Enhanced DC-Link Voltage Response for Wind-Driven Doubly Fed Induction Generator Using Adaptive Fuzzy Extended State Observer and Sliding Mode Control," Mathematics, MDPI, vol. 9(9), pages 1-18, April.
    2. Irfan Sami & Shafaat Ullah & Zahoor Ali & Nasim Ullah & Jong-Suk Ro, 2020. "A Super Twisting Fractional Order Terminal Sliding Mode Control for DFIG-Based Wind Energy Conversion System," Energies, MDPI, vol. 13(9), pages 1-20, May.
    3. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    4. Nassef, Ahmed M. & Olabi, A.G. & Rodriguez, Cristina & Abdelkareem, Mohammad Ali & Rezk, Hegazy, 2021. "Optimal operating parameter determination and modeling to enhance methane production from macroalgae," Renewable Energy, Elsevier, vol. 163(C), pages 2190-2197.
    5. Ghazi A. Ghazi & Hany M. Hasanien & Essam A. Al-Ammar & Rania A. Turky & Wonsuk Ko & Sisam Park & Hyeong-Jin Choi, 2022. "African Vulture Optimization Algorithm-Based PI Controllers for Performance Enhancement of Hybrid Renewable-Energy Systems," Sustainability, MDPI, vol. 14(13), pages 1-26, July.
    6. Ahmed Fathy & Hegazy Rezk & Dalia Yousri & Essam H. Houssein & Rania M. Ghoniem, 2021. "Parameter Identification of Optimized Fractional Maximum Power Point Tracking for Thermoelectric Generation Systems Using Manta Ray Foraging Optimization," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    7. Ehtisham Lodhi & Fei-Yue Wang & Gang Xiong & Ghulam Ali Mallah & Muhammad Yaqoob Javed & Tariku Sinshaw Tamir & David Wenzhong Gao, 2021. "A Dragonfly Optimization Algorithm for Extracting Maximum Power of Grid-Interfaced PV Systems," Sustainability, MDPI, vol. 13(19), pages 1-27, September.
    8. Tanveer, Waqas Hassan & Rezk, Hegazy & Nassef, Ahmed & Abdelkareem, Mohammad Ali & Kolosz, Ben & Karuppasamy, K. & Aslam, Jawad & Gilani, Syed Omer, 2020. "Improving fuel cell performance via optimal parameters identification through fuzzy logic based-modeling and optimization," Energy, Elsevier, vol. 204(C).
    9. Hegazy Rezk & Ziad Mohammed Ali & Omer Abdalla & Obai Younis & Mohamed Ramadan Gomaa & Mauia Hashim, 2019. "Hybrid Moth-Flame Optimization Algorithm and Incremental Conductance for Tracking Maximum Power of Solar PV/Thermoelectric System under Different Conditions," Mathematics, MDPI, vol. 7(10), pages 1-21, September.
    10. N. Kanagaraj & Hegazy Rezk & Mohamed R. Gomaa, 2020. "A Variable Fractional Order Fuzzy Logic Control Based MPPT Technique for Improving Energy Conversion Efficiency of Thermoelectric Power Generator," Energies, MDPI, vol. 13(17), pages 1-18, September.
    11. Rok Pajer & Amor Chowdhury & Miran Rodič, 2019. "Control of a Multiphase Buck Converter, Based on Sliding Mode and Disturbance Estimation, Capable of Linear Large Signal Operation," Energies, MDPI, vol. 12(14), pages 1-26, July.
    12. Sairam, Seshapalli & Seshadhri, Subathra & Marafioti, Giancarlo & Srinivasan, Seshadhri & Mathisen, Geir & Bekiroglu, Korkut, 2022. "Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes," Renewable Energy, Elsevier, vol. 185(C), pages 1425-1440.
    13. Jian Zhang & Yong Wan & Quan Ouyang & Meng Dong, 2023. "Nonlinear Stochastic Adaptive Control for DFIG-Based Wind Generation System," Energies, MDPI, vol. 16(15), pages 1-19, July.
    14. Cristian Napole & Oscar Barambones & Mohamed Derbeli & José Antonio Cortajarena & Isidro Calvo & Patxi Alkorta & Pablo Fernandez Bustamante, 2021. "Double Fed Induction Generator Control Design Based on a Fuzzy Logic Controller for an Oscillating Water Column System," Energies, MDPI, vol. 14(12), pages 1-19, June.
    15. Tian, B. & Loonen, R.C.G.M. & Bognár, Á. & Hensen, J.L.M., 2022. "Impacts of surface model generation approaches on raytracing-based solar potential estimation in urban areas," Renewable Energy, Elsevier, vol. 198(C), pages 804-824.
    16. Habib Benbouhenni & Nicu Bizon, 2021. "Third-Order Sliding Mode Applied to the Direct Field-Oriented Control of the Asynchronous Generator for Variable-Speed Contra-Rotating Wind Turbine Generation Systems," Energies, MDPI, vol. 14(18), pages 1-20, September.
    17. Mohamed R. Gomaa & Hegazy Rezk & Ramadan J. Mustafa & Mujahed Al-Dhaifallah, 2019. "Evaluating the Environmental Impacts and Energy Performance of a Wind Farm System Utilizing the Life-Cycle Assessment Method: A Practical Case Study," Energies, MDPI, vol. 12(17), pages 1-25, August.
    18. Jouda Arfaoui & Hegazy Rezk & Mujahed Al-Dhaifallah & Mohamed N. Ibrahim & Mami Abdelkader, 2020. "Simulation-Based Coyote Optimization Algorithm to Determine Gains of PI Controller for Enhancing the Performance of Solar PV Water-Pumping System," Energies, MDPI, vol. 13(17), pages 1-17, August.
    19. Roummani, Khayra & Hamouda, Messaoud & Mazari, Benyounes & Bendjebbar, Mokhtar & Koussa, Khaled & Ferroudji, Fateh & Necaibia, Ammar, 2019. "A new concept in direct-driven vertical axis wind energy conversion system under real wind speed with robust stator power control," Renewable Energy, Elsevier, vol. 143(C), pages 478-487.
    20. 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.

    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:gam:jmathe:v:8:y:2020:i:11:p:2012-:d:443391. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.