access icon free Model predictive stator current control of doubly fed induction generator during network unbalance

© The Institution of Engineering and Technology
Received 18/01/2017, Accepted 31/08/2017, Revised 04/08/2017, Published 31/08/2017

This study proposes a model predictive stator current control (MPSCC) strategy of doubly fed induction generator (DFIG) under unbalanced grid voltage conditions. Sinusoidal and balanced stator currents injected into the power grid can be ensured due to the direct control of stator currents rather than rotor currents. Model predictive control instead of traditional vector control is adopted, which can increase the current loop bandwidth and obtain faster dynamic responses. Conventional resonant regulators such as second-order generalised integrators or second-order vector integrators that are usually used to eliminate unbalanced components in stator currents can also be avoided. Moreover, both extractions of negative sequence components in rotor or stator currents and calculation of commanded rotor current are avoided, which simplifies the control scheme. The proposed MPSCC strategy can also implement the grid connection by introducing the virtual stator currents without any changes in the control scheme. Finally, experimental results based on a 1 kW lab DFIG system are provided to validate the effectiveness of the proposed control strategy.

Inspec keywords: rotors; predictive control; electric current control; stators; dynamic response; power grids; asynchronous generators; machine control; machine vector control

Other keywords: vector control; current loop bandwidth; dynamic responses; DFIG system; unbalanced grid voltage conditions; power grid; second-order vector integrators; power 1 kW; virtual stator currents; network unbalance; doubly fed induction generator; model predictive stator current control; resonant regulators; rotor currents; balanced stator currents; MPSCC strategy; negative sequence components; second-order generalised integrators

Subjects: Asynchronous machines; Optimal control; Current control; Control of electric power systems

References

    1. 1)
      • 14. Liu, P., Wang, Y., Cong, W.L., et al: ‘Grouping-sorting-optimized model predictive control for modular multilevel converter with reduced computational load’, IEEE Trans. Power Electron., 2016, 31, (3), pp. 1896–1907.
    2. 2)
      • 2. Blaabjerg, F., Liserre, M., Ma, K.: ‘Power electronics converters for wind turbine systems’, IEEE Trans. Ind. Appl., 2012, 48, (2), pp. 708–719.
    3. 3)
      • 8. Nian, H., Cheng, P., Zhu, Z.Q.: ‘Independent operation of DFIG-based WECS using resonant feedback compensators under unbalanced grid voltage conditions’, IEEE Trans. Power Electron., 2015, 30, (7), pp. 3650–3661.
    4. 4)
      • 22. Arbi, J., Ghorbal, M.J.-B., Slama-Belkhodja, I., et al: ‘Direct virtual torque control for doubly fed induction generator grid connection’, IEEE Trans. Ind. Electron., 2009, 56, (10), pp. 4163–4173.
    5. 5)
      • 11. Cheng, P., Nian, H., Wu, C., et al: ‘Direct stator current vector control strategy of DFIG without phase-locked loop during network unbalance’, IEEE Trans. Power Electron., 2017, 32, (1), pp. 284–297.
    6. 6)
      • 16. Elizondo, J.L., Olloqui, A., Rivera, M., et al: ‘Model-based predictive rotor current control for grid synchronization of a DFIG driven by an indirect matrix converter’, IEEE J. Emerg. Sel. Top. Power Electron., 2014, 2, (4), pp. 715–726.
    7. 7)
      • 10. Cheng, P., Nian, H.: ‘Collaborative control of DFIG system during network unbalance using reduced-order generalized integrators’, IEEE Trans. Energy Convers., 2015, 30, (2), pp. 453–464.
    8. 8)
      • 17. Sun, D., Wang, X.H.: ‘Low-complexity model predictive direct power control for DFIG under both balanced and unbalanced grid conditions’, IEEE Trans. Ind. Electron., 2016, 63, (8), pp. 5186–5196.
    9. 9)
      • 13. Siami, M., Khaburi, D.A., Abbaszadeh, A., et al: ‘Robustness improvement of predictive current control using prediction error correction for permanent magnet synchronous machines’, IEEE Trans. Ind. Electron., 2016, 63, (6), pp. 3458–3466.
    10. 10)
      • 23. Shin, M.H., Hyun, D.S., Cho, S.B., et al: ‘An improved stator flux estimation for speed sensorless stator flux orientation control of induction motors’, IEEE Trans. Power Electron., 2000, 15, (2), pp. 312–318.
    11. 11)
      • 9. Song, Y.P., Nian, H.: ‘Modularized control strategy and performance analysis of DFIG system under unbalanced and harmonic grid voltage’, IEEE Trans. Power Electron., 2015, 30, (9), pp. 4831–4842.
    12. 12)
      • 1. Li, P., Song, Y.D., Li, D.Y., et al: ‘Control and monitoring for grid-friendly wind turbines: research overview and suggested approach’, IEEE Trans. Power Electron., 2015, 30, (4), pp. 1979–1986.
    13. 13)
      • 18. Hu, J.F., Zhu, J.G., Dorrell, D.G.: ‘Predictive direct power control of doubly fed induction generators under unbalanced grid voltage conditions for power quality improvement’, IEEE Trans. Sustain. Energy, 2015, 6, (3), pp. 943–950.
    14. 14)
      • 12. Young, H.A., Perez, M.A., Rodriguez, J.: ‘Analysis of finite-control-set model predictive current control with model parameter mismatch in a three-phase inverter’, IEEE Trans. Ind. Electron., 2016, 63, (5), pp. 3100–3107.
    15. 15)
      • 24. Wang, X.H., Sun, D.: ‘Three-vector-based low-complexity model predictive direct power control strategy for doubly fed induction generators’, IEEE Trans. Power Electron., 2017, 32, (1), pp. 773–782.
    16. 16)
      • 3. Tapia, A., Tapia, G., Ostolaza, J.X., et al: ‘Modeling and control of a wind turbine driven doubly fed induction generator’, IEEE Trans. Energy Convers., 2003, 18, (2), pp. 194–204.
    17. 17)
      • 21. Golestan, S., Monfared, M., Freijedo, F.D.: ‘Design-oriented study of advanced synchronous reference frame phase-locked loops’, IEEE Trans. Power Electron., 2013, 28, (2), pp. 765–778.
    18. 18)
      • 19. Standard NB/T 31078-2016: ‘Evaluation method for grid code compliance of wind farms’, 2016.
    19. 19)
      • 5. Zhou, Y., Bauer, P., Ferreira, J.A., et al: ‘Operation of grid-connected DFIG under unbalanced grid voltage condition’, IEEE Trans. Energy Convers., 2009, 24, (1), pp. 240–246.
    20. 20)
      • 4. Zhu, R.W., Chen, Z., Tang, Y., et al: ‘Dual-loop control strategy for DFIG-based wind turbines under grid voltage disturbances’, IEEE Trans. Power Electron., 2016, 31, (3), pp. 2239–2253.
    21. 21)
      • 15. Guo, L.L., Zhang, X., Yang, S., et al: ‘A model predictive control-based common-mode voltage suppression strategy for voltage-source inverter’, IEEE Trans. Ind. Electron., 2016, 63, (10), pp. 6115–6125.
    22. 22)
      • 6. Xu, L., Wang, Y.: ‘Dynamic modeling and control of DFIG-based wind turbines under unbalanced network conditions’, IEEE Trans. Power Syst., 2007, 22, (1), pp. 314–323.
    23. 23)
      • 25. GB/T 15543–2008: ‘Power quality – three-phase voltage unbalance’, 2008.
    24. 24)
      • 20. Xu, H.L., Hu, J.B., He, Y.K.: ‘Operation of wind-turbine-driven DFIG systems under distorted grid voltage conditions: analysis and experimental validations’, IEEE Trans. Power Electron., 2012, 27, (5), pp. 2354–2366.
    25. 25)
      • 7. Hu, J.B., He, Y.K.: ‘Modeling and enhanced control of DFIG under unbalanced grid voltage conditions’, Electr. Power Syst. Res., 2009, 79, (2), pp. 273–281.
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