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A new fuzzy design for switching gain adaptation of sliding mode controller for a wind energy conversion system using a doubly fed induction generator

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper proposes a newrobust fuzzy gain adaptation of the sliding mode (SMC) power control strategy for the wind energy conversion system (WECS), based on a doubly fed induction generator (DFIG), to maximize the power extracted from the wind turbine (WT). The sliding mode controller can deal with any wind speed, ingrained nonlinearities in the system, external disturbances and model uncertainties, yet the chattering phenomenon that characterizes classical SMC can be destructive. This problem is suitably lessened by adopting adaptive fuzzy-SMC. For this proposed approach, the adaptive switching gains are adjusted by a supervisory fuzzy logic system, so the chattering impact is avoided. Moreover, the vector control of the DFIG as well as the presented one have been used to achieve the control of reactive and active power of the WECS to make the wind turbine adaptable to diverse constraints. Several numerical simulations are performed to assess the performance of the proposed control scheme. The results show robustness against parameter variations, excellent response characteristics with a reduced chattering phenomenon as compared with classical SMC.
Rocznik
Strony
273--291
Opis fizyczny
Bibliogr. 27 poz., rys., tab., wz.
Twórcy
  • Laboratoire d’Automatique de Tlemcen (LAT) National School of Electrical and Energetic Engineering of Oran Oran 31000, Algeria
  • Manufacturing Engineering Laboratory of Tlemcen Hight School of Applied Sciences Tlemcen 13000, Algeria
autor
  • Laboratoire d’Automatique de Tlemcen (LAT) Université de Lorraine GREEN, EA 4366F-54500, Vandoeuvre-lès-Nancy, France
autor
  • Laboratory of Power Equipment Characterization and Diagnosis University of Science and Technology Houari Boumediene Algiers 16000, Algeria
Bibliografia
  • [1] Chemidi A., Horch M., Bourouis M.E.A., A new robust RST controller based on PSO optimization for DFIG wind turbine, European Journal of Electrical Engineering, vol. 24, no. 1, pp. 13–20 (2022), DOI: 10.18280/ejee.240102.
  • [2] Hadji C., Khodja D.E., Chakroune S., Sensorless backstepping control using a Luenberger o server for double-star induction motor, Archives of Electrical Engineering, vol. 69, no. 1, pp. 101–116 (2020), DOI: 10.24425/aee.2020.131761.
  • [3] Liu S., Han Y., Du C., Li S., Zhang H., Fuzzy PI Control for Grid-side Converter of DFIG-based Wind Turbine System, Proceedings of 40th Chinese Control Conference (CCC), Shanghai, China, pp. 5788–5793 (2021), DOI: 10.23919/CCC52363.2021.9550601.
  • [4] Benbouhenni H., Bizon N., 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, vol. 14, no. 18, p. 5877, DOI: 10.3390/en14185877.
  • [5] Saidi Y., Mezouar A., Miloud Y., Advanced non-linear backstepping control design for variable speed wind turbine power maximization based on tip-speed-ratio approach during partial load operation, International Journal of Dynamics and Control, vol. 8, pp. 615–628 (2020), DOI: 10.1007/s40435-019-00564-3.
  • [6] Eisa S.A., Wedeward K., Stone W., Wind turbines control system: nonlinear modeling, simulation, two and three time scale approximations, and data validation, International Journal of Dynamics and Control, vol. 6, no. 4, pp. 1776–1798 (2018), DOI: 10.1007/s40435-018-0420-4.
  • [7] Javed U., Arshad M.A., Jawad M., Shabbir N., Kütt L and Rassõlkin A., Active and Reactive Power Control of DFIG using Optimized Fractional Order-PI Controller, IEEE 19th International Power Electronics and Motion Control Conference (PEMC), Gliwice, Poland, pp. 398–404 (2021), DOI: 10.1109/PEMC48073.2021.9432608.
  • [8] Dekali Z., Baghli L., Boumediene A., Improved Super Twisting Based High Order Direct Power Sliding Mode Control of a Connected DFIG Variable Speed Wind Turbine, Periodica Polytechnica Electrical Engineering and Computer Science, vol. 65, no. 4, pp. 352–372 (2021), DOI: 10.3311/PPee.17989.
  • [9] Blaabjerg F., Xu D., Chen W., Zhu N., Advanced Control of Doubly Fed Induction Generator For Wind Power Systems, Wiley-IEEE Press (2018), DOI: 10.1002/9781119172093.
  • [10] Kerrouche K.D.E., Mezouar A., Boumediene L., Van Den Bossche A., Modeling and Lyapunov-designed based on adaptive gain sliding mode control for wind turbines, Journal of Power Technologies, vol. 96, no. 2, pp. 124–136 (2016).
  • [11] Iov F., Hansen A.D., Sørensen P., Blaabjerg F., Wind Turbine Blockset in Matlab/Simulink, General Overview and Description of the Models, Aalborg University and RISØ National Laboratory, Denmark (2004).
  • [12] Zouggar E.O., Chaouch S., Abdelhamid L., Abdeslam D.O., Real-time implementation of the MPPT control algorithms of a wind energy conversion system by the digital simulator OPAL_RT, European Journal of Electrical Engineering, vol. 23, no. 1, pp. 45–52 (2021), DOI: 10.18280/ejee.230106.
  • [13] Matthew K., Saravanakumar R., Design of Double Integral Sliding Mode Control for Variable Speed Wind Turbine at Partial Load Region, IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), Coimbatore, India, pp. 1–5 (2017), DOI: 10.1109/ICCIC.2017.8524196.
  • [14] Mohamed H., Abdelmadjid B., Lotfi B., Improvement of direct torque control performances for induction machine using a robust backstepping controller and a new stator resistance compensator, European Journal of Electrical Engineering, vol. 22, no. 2, pp. 137–144 (2020), DOI: 10.18280/ejee.220207.
  • [15] Kelkoul B., Boumediene A., Stability analysis and study between classical sliding mode control (SMC) and super twisting algorithm (STA) for doubly fed induction generator (DFIG) under wind turbine, Energy, vol. 214, p. 118871 (2021), DOI: 10.1016/j.energy.2020.118871.
  • [16] Baghli L., Contribution à La Commande de La MAS, Utilisation de La Logique Floue, Des Réseaux de Neurones et Des Algorithmes Génétiques, PhD Thesis, Université de lorraine (1999).
  • [17] Mousakazemi S., Mohammad H., Comparison of the error-integral performance indexes in a GA- tuned PID controlling system of a PWR-type nuclear reactor point-kinetics model, Progress in Nuclear Energy, vol. 132, ISSN 0149-1970 (2021), DOI: 10.1016/j.pnucene.2020.103604.
  • [18] Almabrok A., Psarakis M., Dounis A., Fast Tuning of the PID Controller in An HVAC System Using the Big Bang–Big Crunch Algorithm and FPGA Technology, Algorithms, vol. 11, no. 10, 146 (2018), DOI: 10.3390/a11100146.
  • [19] Zeghdi Z., Barazane L., Bekakra Y., Larabi A., Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm, Periodica Polytechnica Electrical Engineering and Computer Science, vol. 66, no. 1, pp. 43–59 (2022), DOI: 10.3311/PPee.18716.
  • [20] Taoussi M., Bossoufi B., Bouderbala M., Motahhir S., Alkhammash E.H., Masud M., Zinelaabidine N., Karim M., Implementation and Validation of Hybrid Control for a DFIG Wind Turbine Using an FPGA Controller Board, Electronics, vol. 10, no. 24 (2021), DOI: 10.3390/electronics10243154.
  • [21] Salhi S., Salah S., LQR Robust Control for Active and Reactive Power Tracking of a DFIG based WECS, International Journal of Advanced Computer Science and Applications (IJACSA), vol. 10, no. 1 (2019), DOI: 10.14569/IJACSA.2019.0100172.
  • [22] Nguyen A.T., Lee C., Sensorless Control of DFIG Wind Turbine Systems Based on SOGI and Rotor Position Correction, IEEE Transactions on Power Electronics, vol. 36, no. 5, pp. 5486–5495 (2021), DOI: 10.1109/TPEL.2020.3027888.
  • [23] Lazrak A., Abbou A., Robust Power Control of DFIG Based Wind Turbine without Currents Rotor Sensor, International Renewable and Sustainable Energy Conference (IRSEC), Tangier, Morocco (2017), DOI: 10.1109/IRSEC.2017.8477340.
  • [24] Mensou S., Essadki A., Nasser T., Bououlid Idrissi B., A direct power control of a DFIG based-WECS during symmetrical voltage dips, Protection and Control of Modern Power Systems, vol. 5, no. 1, pp. 1–12 (2020), DOI: 10.1016/j.egyr.2016.08.001.
  • [25] Benzouaoui A., Zoubi A.F., Khelfi M.F., Nonlinear control scheme based on a second order sliding mode: application to DFIG supplied by five-level PWM inverter, International Journal of Automation and Control, vol. 13, no. 4, pp. 498516 (2019), DOI: 10.1504/IJAAC.2019.100472.
  • [26] Bennouk A., Nejmi A., Ramzi M., Stability enhancement of a wind plant based on a DFIG and a PMSM: A Lyapunov approach, Energy Reports, vol. 4, no. 2018, pp. 13–22 (2018), DOI: 10.1016/j.egyr.2017.10.001.
  • [27] Hao Z., Haiying D., Baoping Z., Tong W., Changwen C., Research on beam supply control strategy based on sliding mode control, Archives of Electrical Engineering, vol. 69, no. 2, pp. 349–364 (2020), DOI: 10.24425/aee.2020.133030.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-011ca368-2aec-4904-b215-5edf8423fd2d
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