Document Type : Original Article

Author

Labo. LAAS, Departement de Génie Electrique, Ecole Nationale Polytechnique d’Oran Maurice Audin, Oran, Algeria.

10.22044/rera.2021.10694.1053

Abstract

In this paper, a novel switching table (ST) of the twelve sectors direct power command (DPC) strategy of doubly-fed induction generator (DFIG) based dual rotor wind power (DRWP) is proposed using two-level hysteresis controllers for reactive and active power and feedforward neural networks (FNNs) algorithms. This intelligent technique was used to replace the conventional ST in order to reduce rotor flux ripple, active power ripple, total harmonic distortion (THD) of stator voltage, torque and reactive power undulations. The simulation and modeling of the proposed strategy were carried out in Matlab software. The DFIG is tested in association with a DRWP systems. The simulation results show that the DPC with FNN controller (DPC-FNN) reduced the THD value of stator voltage, rotor flux undulation, active/reactive power undulation, and electromagnetic torque ripple compared to conventional DPC strategy. It was found that the current waveform becomes purely sinusoidal with a reduction in the THD rate to 0.64%.

Keywords

[1] Hu, J., Zhu, J., Dorrell, D.G. (2015).  Predictive direct power control of doubly fed induction generators under unbalanced grid voltage conditions for power quality improvement. IEEE Transactions on Sustainable Energy, Vol. 6, No. 3.

[2] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2019). Direct vector control of a DFIG supplied by an intelligent SVM inverter for wind turbine system. Iranian Journal of Electrical & Electronic Engineering, Vol. 15, No. 1, pp. 45-55.

[3] Benbouhenni, H. (2019). Application of five-level NPC inverter in DPC-ANN of  doubly fed induction generator for wind power generation systems. International Journal of Smart Grid, Vol. 3, No. 3, pp. 128-137.

[4] Izanlo, A., Gholamian, S. A., and Kazemi, M.V. (2017). Comparative study between two sensorless methods for direct power control of doubly fed induction generator. Rev. Roum. Sci. Techn.-Electrotechn. Et Energ, Vol. 62, No. 4, pp. 358-364.

[5] Benbouhenni, H. (2019). Direct power control of a DFIG fed by a seven-level inverter using SVM strategy. International Journal of Smart Grid, Vol. 3, No. 2,       pp. 54-62.

[6] Kazemi, M.V., Yazdankhah, A.S., and Kojabadi, H.M. (2010). Direct power control of DFIG based on discrete space vector modulation. Renewable Energy, Vol. 35, pp. 1033-1042.

[7] Wa, Y. and Yang, W. (2016). Different control strategies on the rotor side converter in DFIG-based wind turbines. Energy Procedia, Elsevier, Vol. 100,       pp. 551-555.

[8] Benbouhenni, H. (2018). Five-level DTC with 12 sectors of induction motor drive using neural networks controller for low torque ripple. Acta Electrotechnica et Informatica,  Vol. 18, No. 2, pp. 61-66.

[9] Benbouhenni, H. (2018). Seven-level direct torque control of induction motor based on artificial neural networks with regulation speed using fuzzy PI controller. Iranian Journal of Electrical and Electronic Engineering, Vol. 14, No. 1,    pp. 85-94.

[10] Benbouhenni, H. (2019). Seven-level NPC inverter-based neuronal direct torque control of the PMSM drives with regulation speed using neural PI controller. International Journal of Intelligent Information Systems, Vol. 8, No. 5, pp. 85-96.

[11] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2019). A novel matlab/simulink model of DFIG drive using NSMC method with NSVM strategy. International Journal of Applied Power Engineering (IJAPE),  Vol. 8, No. 3, pp. 221-233.

[12] Benbouhenni, H. (2020). Intelligence hysteresis comparators for a multilevel DTC control scheme of IM drive, Majlesi Journal of Mechatronic Systems. Vol. 9, No. 2, pp. 15-21.

[13] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2018). Neuro-second order sliding mode control of a DFIG supplied by a two-level NSVM inverter for wind turbine system. Iranian Journal of Electrical & Electronic Engineering, Vol. 14, No. 4, pp. 362-373.

[14] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2019). Using four-level NSVM technique to improve DVC control of a DFIG based wind turbine systems. Periodica Polytechnica Electrical Engineering and Computer Science, Vol. 63, No. 3.

[15] Benbouhenni, H. (2018). Comparative study between NSVM and FSVM strategy for a DFIG-based wind turbine system controlled by neuro-second order sliding mode. Majlesi Journal of Mechatronic Systems, Vol. 7, No. 1, pp. 33-43.

[16] Benbouhenni, H. (2019). Sliding mode with neural network regulateur for DFIG using two-level NPWM strategy. Iranian Journal of Electrical & Electronic Engineering, Vol. 15, No. 3, pp. 411-419.

[17] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2019). Power ripple reduction of DPC DFIG drive using ANN controller. Acta Electrotechnica et Informatica, Vol. 20, No. 1, pp. 15-22.

[18] Benbouhenni, H. (2018). A new SVM scheme based on ANN controller of a PMSG controlled by DPC strategy. Majlesi Journal of Energy Management, Vol. 7, No. 1, pp. 11-19.

[19] Benbouhenni, H. (2018). Rotor flux and torque ripples minimization for direct torque control of DFIG by NSTSM algorithm. Majlesi Journal of Energy Management, Vol. 7, No. 3.

[20] Tiwari, R. and Babu, N.R. (2019). Artificial neural network-based control strategies for PMSG-based grid connected wind energy conversion system. International Journal of Materials and Product Technology, Vol. 58, No. 4, pp. 323-341.

[21] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2020). Twelve-sector DPC control based on neural hysteresis comparators of the DFIG integrated to wind power. International Journal of Smart Grid, Vol. 4, No. 1.

[22] Yaichi, I., Semmah, A., and Wira, P. (2019). Direct Power Control of a Wind Turbine based on Doubly Fed Induction Generator. European Journal of Electrical Engineering, Vol. 21, No. 5, pp. 457-464. https://doi.org/10.18280/ejee.210508.

[23] Benbouhenni, H. (2017). Hybrid neural sliding mode control of a DFIG speed in wind turbines. Majlesi Journal of Energy Management, Vol. 6, No. 4, pp. 31-41.

[24] Yahdou, A., Hemici, B., and Boudjema, Z. (2015). Sliding mode control of dual rotor wind turbine system. The mediternanean Journal of Measurement and Control, Vol. 11, No. 2, pp. 412-419.

[25] Yahdou, A., Hemici, B., and Boudjema, Z. (2015). Second-order sliding mode control of a dual-rotor wind turbine system by employing a matrix converter. Journal of Electrical Engineering, Vol. 16, No. 3, pp. 1-11.

[26] Xiong, P. and Sun, D. (2016). Backstepping-based DPC Strategy of a Wind Turbine-Driven DFIG under Normal and Harmonic Grid Voltage," in IEEE Transactions on Power Electronics, Vol. 31, No. 6, pp. 4216-4225. DOI: 10.1109/TPEL.2015.2477442.

[27] Huang, Q. and Cui, L. (2019). Design and application of face recognition algorithm based on improved backpropagation neural network. Revue d’intelligence artificielle. Vol. 33, No. 1, pp. 25-32. https://doi.org/10.18280/ria.330105.

[28] Benbouhenni, H. (2019). Comparison study between SVPWM and FSVPWM strategy in fuzzy second-order sliding mode control of a DFIG-based wind turbine. Carpathian Journal of Electronic and Computer Engineering, Vol. 12, No. 2, pp. 1-10.

[29] Benbouhenni, H., Boudjema, Z., and Belaidi, A. (2019). Higher control scheme using neural second order sliding mode and ANFIS-SVM strategy for a DFIG-based wind turbine. International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems, Vol. 8, No. 2, pp. 17-28.

[30] Yusoff, N. A., Razali, A. M., Karim, K. A., Sutikno, T., and Jidin, A. (2017). A Concept of Virtual-Flux Direct Power Control of Three-Phase AC-DC Converter. International Journal of Power Electronics and Drive System (IJPEDS), Vol. 8, No. 4, pp. 1776-1784. DOI: 10.11591/ijpeds.v8i4.pp1776-1784.

[31] Amrane, F., Chaiba, A., Babes, B.E., and Mekhilef, S. (2016). Design and implementation of high performance field oriented control for grid-connected doubly fed induction generator via hysteresis rotor current controller. Rev. Roum. Sci. Techn.-Electrotechn. Et Energ, Vol. 61, No. 4, pp. 319-324.

[32] Benbouhenni, H., Boudjema, Z., Belaidi, A. (2021). Direct power control with NSTSM algorithm for DFIG using SVPWM technique. Iranian Journal of Electrical & Electronic Engineering, Vol. 17, No. 2.

[33] Djeriri Y., Meroufel A., Belabbes, B., and Massoum A. (2013). Three-level NPC voltage source converter based direct power control of the doubly fed induction generator at low constant switching frequency. Revue des Energies Renouvelables, Vol. 16, No. 1, pp. 91-103.

[34] Benbouhenni, H. (2019). A direct power control of the doubly fed induction generator based on the three-level NSVPWM technique. International Journal of Smart Grid, Vol. 3, No. 4.

[35] Benbouhenni, H. (2018). Comparative Study between direct vector control and fuzzy sliding mode controller in three-level space vector modulation inverter of reactive and active power command of DFIG-based wind turbine systems. International Journal of Smart Grid, Vol. 2, No. 4, pp. 188-196.

[36] Fayssal,  A. and Azeddine, C. (2016). A novel direct power control for grid-connected doubly fed induction generator based on hybrid artificial intelligent control with space vector modulation. Rev. Roum. Sci. Techn.-Electrotechn. Et Energ, Vol. 61, No. 3, pp. 263-268.

[37] Naïma, M. and Mohamed-Saïd, N. (2017). Direct s-power control for a doubly fed induction generator. Rev. Roum. Sci. Techn.-Electrotechn. Et Energ, Vol. 62, No. 4, pp. 365-370.