Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS
This paper presents an adaptive neuro-fuzzy controller (NFC)to deal with grid voltage dip conditions for grid-connected operation of doubly fed induction generator (DFIG)driven wind energy conversion system (WECS). Due to the partial scale power converters, wind turbines based on DFIG are very sensi...
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my.iium.irep.745812019-09-26T01:39:19Z http://irep.iium.edu.my/74581/ Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS Amin, Ifte Khairul Nasir Uddin, Mohammad Hannan, Mahammad Abdul Alam, A. H. M. Zahirul TK Electrical engineering. Electronics Nuclear engineering This paper presents an adaptive neuro-fuzzy controller (NFC)to deal with grid voltage dip conditions for grid-connected operation of doubly fed induction generator (DFIG)driven wind energy conversion system (WECS). Due to the partial scale power converters, wind turbines based on DFIG are very sensitive to grid disturbances. Current saturation at the rotor side converter (RSC)and overvoltage at the dc-link are the major concerns of DFIG driven WECS during grid-voltage fluctuation. In synchronous reference frame, an oscillatory stator flux appears during voltage dip and it is difficult to suppress with conventional proportional-integral (PI)controllers considering nonlinear system dynamics. Therefore, an adaptive-network fuzzy inference system based NFC is proposed in this paper to handle the system uncertainties and minimize the effect of grid voltage fluctuations. During normal operation, the proposed controller aims to regulate the currents as demanded by the reference real and reactive power. Under voltage dip condition, the controllers adjust the positive sequence d-q axis current components both at the grid and rotor sides by supplying required reactive power to the grid. The negative sequence reference currents at rotor end actuate the demagnetization effect of minimizing the impact of voltage dips. The simulation results exhibit the proposed NFC performance through its robust control over the rotor side currents and bus voltage during both the voltage dip and normal operation. IEEE 2019-08-05 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/74581/7/74581%20Adaptive%20Neuro-Fuzzy%20Controller.pdf application/pdf en http://irep.iium.edu.my/74581/8/74581%20Adaptive%20Neuro-Fuzzy%20Controller%20SCOPUS.pdf Amin, Ifte Khairul and Nasir Uddin, Mohammad and Hannan, Mahammad Abdul and Alam, A. H. M. Zahirul (2019) Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS. In: 2019 IEEE International Electric Machines & Drives Conference (IEMDC), 12th-15th May 2019, San Diego, CA, USA, USA. https://ieeexplore.ieee.org/document/8785362 10.1109/IEMDC.2019.8785362 |
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TK Electrical engineering. Electronics Nuclear engineering Amin, Ifte Khairul Nasir Uddin, Mohammad Hannan, Mahammad Abdul Alam, A. H. M. Zahirul Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
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This paper presents an adaptive neuro-fuzzy controller (NFC)to deal with grid voltage dip conditions for grid-connected operation of doubly fed induction generator (DFIG)driven wind energy conversion system (WECS). Due to the partial scale power converters, wind turbines based on DFIG are very sensitive to grid disturbances. Current saturation at the rotor side converter (RSC)and overvoltage at the dc-link are the major concerns of DFIG driven WECS during grid-voltage fluctuation. In synchronous reference frame, an oscillatory stator flux appears during voltage dip and it is difficult to suppress with conventional proportional-integral (PI)controllers considering nonlinear system dynamics. Therefore, an adaptive-network fuzzy inference system based NFC is proposed in this paper to handle the system uncertainties and minimize the effect of grid voltage fluctuations. During normal operation, the proposed controller aims to regulate the currents as demanded by the reference real and reactive power. Under voltage dip condition, the controllers adjust the positive sequence d-q axis current components both at the grid and rotor sides by supplying required reactive power to the grid. The negative sequence reference currents at rotor end actuate the demagnetization effect of minimizing the impact of voltage dips. The simulation results exhibit the proposed NFC performance through its robust control over the rotor side currents and bus voltage during both the voltage dip and normal operation. |
format |
Conference or Workshop Item |
author |
Amin, Ifte Khairul Nasir Uddin, Mohammad Hannan, Mahammad Abdul Alam, A. H. M. Zahirul |
author_facet |
Amin, Ifte Khairul Nasir Uddin, Mohammad Hannan, Mahammad Abdul Alam, A. H. M. Zahirul |
author_sort |
Amin, Ifte Khairul |
title |
Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
title_short |
Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
title_full |
Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
title_fullStr |
Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
title_full_unstemmed |
Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected DFIG-WECS |
title_sort |
adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected dfig-wecs |
publisher |
IEEE |
publishDate |
2019 |
url |
http://irep.iium.edu.my/74581/7/74581%20Adaptive%20Neuro-Fuzzy%20Controller.pdf http://irep.iium.edu.my/74581/8/74581%20Adaptive%20Neuro-Fuzzy%20Controller%20SCOPUS.pdf http://irep.iium.edu.my/74581/ https://ieeexplore.ieee.org/document/8785362 |
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