Passivity-based linear feedback control of permanent magnetic synchronous generator-based wind energy conversion system: design and analysis

Passivity-based linear feedback control of permanent magnetic synchronous generator-based wind energy conversion system: design and analysis

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Renewable Power Generation — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

This study designs a passivity-based linear feedback control scheme of a permanent magnetic synchronous generator-based wind energy conversion system, which attempts to achieve a maximum power point tracking (MPPT) at generator-side voltage source converter (VSC) and enhance fault ride-through (FRT) capability at grid-side VSC simultaneously. A storage function is constructed based on the passivity theory, in which the actual role of each term is meticulously investigated while the beneficial ones are remained so as to significantly improve the transient responses. Then, an auxiliary input is employed in the form of linear feedback control to ensure a desired tracking error convergence. Moreover, the closed-loop system stability is thoroughly analysed, together with a detailed physical interpretation of the storage function. Three case studies are undertaken including step change of wind speed, stochastic wind speed variation, and FRT. Simulation results verify that the proposed approach can effectively achieve MPPT and dramatically improve the FRT capability under various operation conditions against that of vector control and feedback linearisation control.


    1. 1)
      • 1. Liao, S.W., Yao, W., Han, X.N., et al: ‘Chronological operation simulation framework for regional power system under high penetration of renewable energy using meteorological data’, Appl. Energy, 2017, 203, pp. 816828.
    2. 2)
      • 2. Yao, W., Jiang, L., Wen, J.Y., et al: ‘Wide-area damping controller for power system inter-area oscillations: a networked predictive control approach’, IEEE Trans. Control Syst. Technol., 2015, 23, (1), pp. 2736.
    3. 3)
      • 3. Yang, B., Jiang, L., Wang, L., et al: ‘Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine’, Int. J. Electr. Power Energy Syst., 2016, 74, pp. 429436.
    4. 4)
      • 4. Yang, B., Zhang, X.S., Yu, T., et al: ‘Grouped grey wolf optimizer for maximum power point tracking of doubly-fed induction generator based wind turbine’, Energy Convers. Manage., 2017, 133, pp. 427443.
    5. 5)
      • 5. Yao, J., Yu, M., Gao, W., et al: ‘Frequency regulation control strategy for PMSG wind-power generation system with flywheel energy storage unit’, IET Renew. Power Gener., 2017, 11, (8), pp. 10821093.
    6. 6)
      • 6. Youcef, S., Sami, K., Mohcene, B.: ‘Feedback linearization control based particle swarm optimization for maximum power point tracking of wind turbine equipped by PMSG connected to the grid’, Int. J. Hydrog. Energy, 2016, 41, pp. 2095020955.
    7. 7)
      • 7. Yao, J., Guo, L., Zhou, T., et al: ‘Capacity configuration and coordinated operation of a hybrid wind farm with FSIG-based and PMSG-based wind farms during grid faults’, IEEE Trans. Energy Convers., 2017, 32, (3), pp. 11881199.
    8. 8)
      • 8. Shehata, E.G.: ‘A comparative study of current control schemes for a direct-driven PMSG wind energy generation system’, Electr. Power Syst. Res., 2017, 143, pp. 197205.
    9. 9)
      • 9. Chen, J., Jiang, L., Yao, W., et al: ‘A feedback linearization control strategy for maximum power point tracking of a PMSG based wind turbine’. Int. Conf. on Renewable Energy Research and Applications, Madrid, Spain, 20–23 October 2013, pp. 7984.
    10. 10)
      • 10. Seyed, M.M., Maarouf, S., Hani, V., et al: ‘Sliding mode control of PMSG wind turbine based on enhanced exponential reaching law’, IEEE Trans. Ind. Electron., 2016, 63, (10), pp. 61486159.
    11. 11)
      • 11. Riad, A., Toufik, R., Djamila, R., et al: ‘Application of nonlinear predictive control for charging the battery using wind energy with permanent magnet synchronous generator’, Int. J. Hydrog. Energy, 2016, 41, pp. 2096420973.
    12. 12)
      • 12. Fantino, R., Solsona, J., Busada, C.: ‘Nonlinear observer-based control for PMSG wind turbine’, Energy, 2016, 113, pp. 248257.
    13. 13)
      • 13. Chen, J., Jiang, L., Yao, W., et al: ‘Perturbation estimation based nonlinear adaptive control of a full-rated converter wind turbine for fault ride-through capability enhancement’, IEEE Trans. Power Syst., 2014, 29, (6), pp. 27332743.
    14. 14)
      • 14. Yassin, H.M., Hanafy, H.H., Hallouda, M.M.: ‘Enhancement low-voltage ride through capability of permanent magnet synchronous generator-based wind turbines using interval type-2 fuzzy control’, IET Renew. Power Gener., 2016, 10, (3), pp. 339348.
    15. 15)
      • 15. Li, S.Q., Zhang, K.Z., Li, J., et al: ‘On the rejection of internal and external disturbances in a wind energy conversion system with direct-driven PMSG’, ISA Trans., 2016, 61, pp. 95103.
    16. 16)
      • 16. Ortega, R., Schaft, A., Mareels, I., et al: ‘Putting energy back in control’, IEEE Control Syst., 2001, 21, (2), pp. 1833.
    17. 17)
      • 17. Fernando, M.D., Ortega, R.: ‘Adaptive passivity-based control for maximum power extraction of stand-alone windmill systems’, Control Eng. Pract., 2012, 20, pp. 173181.
    18. 18)
      • 18. Santos, G.V., Cupertino, A.F., Mendes, V.F., et al: ‘Interconnection and damping assignment passivity-based control of a PMSG based wind turbine for maximum power tracking’. 2015 IEEE 24th Int. Symp. Industrial Electronics (ISIE), Buzios, Brazil, 3–5 June 2015, pp. 306311.
    19. 19)
      • 19. Zheng, X., Li, Q., Ding, D., et al: ‘Passivity non-singular higher-order sliding mode control for direct-driven PMSG’. IECON 2014–40th Annual Conf. of the IEEE Industrial Electronics Society, Dallas, TX, USA, 29 October–1 November 2014, pp. 55755581.
    20. 20)
      • 20. Yang, B., Yu, T., Shu, H.C., et al: ‘Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine’, Renew. Energy, 2018, 119, pp. 577589.
    21. 21)
      • 21. Jeong, D., Kim, C., Gui, Y., et al: ‘Sliding mode control for LVRT of a PMSG wind turbine using stored energy in rotor inertia’. 2016 IEEE Power and Energy Society General Meeting (PESGM), Boston, MA, USA, 17–21 July 2016, pp. 15.
    22. 22)
      • 22. Gui, Y.H., Kim, C.H., Chung, C.C.: ‘Improved low-voltage ride through capability for PMSG wind turbine based on port-controlled Hamiltonian system’, Int. J. Control, Autom. Syst., 2016, 14, (5), pp. 11951204.
    23. 23)
      • 23. Pahlevani, M., Pan, S., Mash, J., et al: ‘Port-controlled Hamiltonian (PCH)-based control approach for wind energy conversion systems’. 2014 IEEE 5th Int. Symp. Power Electronics for Distributed Generation Systems (PEDG), Galway, Ireland, 24–27 June 2014, pp. 15.
    24. 24)
      • 24. Valenciaga, F., Puleston, P.F., Battaiotto, E., et al: ‘Passivity/sliding mode control of a stand-alone hybrid generation system’, IEE Proc. Control Theory Appl., 2000, 147, (6), pp. 680686.
    25. 25)
      • 25. Fernando, V., Pablo, F.P., Pedro, E.B.: ‘Power control of a solar/wind generation system without wind measurement: a passivity/sliding mode approach’, IEEE Trans. Energy Convers., 2003, 18, (4), pp. 501507.
    26. 26)
      • 26. Cisneros, R., Mancilla-David, F., Ortega, R.: ‘Passivity-based control of a grid-connected small-scale windmill with limited control authority’, IEEE J. Emerg. Sel. Top. Power Electron., 2013, 1, (4), pp. 247259.
    27. 27)
      • 27. Croci, L., Martinez, A., Coirault, P., et al: ‘Comparison of two passivity-based control strategies for a wind power generator’. 2013 – 39th Annual Conf. IEEE Industrial Electronics Society (IECON), Vienna, Austria, 10–13 November 2013, pp. 52485253.
    28. 28)
      • 28. Uehara, A., Pratap, A., Goya, T., et al: ‘A coordinated control method to smooth wind power fluctuations of a PMSG-based WECS’, IEEE Trans. Energy Convers., 2011, 26, (2), pp. 550558.
    29. 29)
      • 29. Yang, B., Yu, T., Shu, H.C., et al: ‘Democratic joint operations algorithm for optimal power extraction of PMSG based wind energy conversion system’, Energy Convers. Manage., 2018, 159, pp. 312326.
    30. 30)
      • 30. Yang, L.H., Xu, Z., Østergaard, J., et al: ‘Advanced control strategy of DFIG wind turbines for power system fault ride through’, IEEE Trans. Power Syst., 2012, 27, (1), pp. 713722.
    31. 31)
      • 31. Xie, D. L., Xu, Z., Yang, L.H., et al: ‘A comprehensive LVRT control strategy for DFIG wind turbines with enhanced reactive power support’, IEEE Trans. Power Syst., 2013, 28, (3), pp. 33023310.
    32. 32)
      • 32. Karakus, O., Kuruoglu, E., Altinkaya, M.: ‘One-day ahead wind speed/power prediction based on polynomial autoregressive model’, IET Renew. Power Gener., 2017, 11, (11), pp. 14301439.
    33. 33)
      • 33. Shen, Y., Yao, W., Wen, J.Y., et al: ‘Adaptive supplementary damping control of VSC-HVDC for interarea oscillation using GrHDP’, IEEE Trans. Power Syst., 2018, 33, (2), pp. 17771789.

Related content

This is a required field
Please enter a valid email address