Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected dfig-wecs
Adaptive control systems; Asynchronous generators; Controllers; Electric current control; Electric drives; Electric fault currents; Electric power system control; Electric power transmission networks; Energy conversion; Fuzzy inference; Reactive power; Robust control; Two term control systems; Wind...
Saved in:
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2023
|
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| id |
my.uniten.dspace-24666 |
|---|---|
| record_format |
dspace |
| spelling |
my.uniten.dspace-246662023-05-29T15:25:38Z Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected dfig-wecs Amin I.K. Nasir Uddin M. Hannan M.A. Alam A.H.M.Z. 10040907100 55663372800 7103014445 57195185389 Adaptive control systems; Asynchronous generators; Controllers; Electric current control; Electric drives; Electric fault currents; Electric power system control; Electric power transmission networks; Energy conversion; Fuzzy inference; Reactive power; Robust control; Two term control systems; Wind power; Adaptive network fuzzy inference systems; ANFIS; Conventional proportional integrals; Doubly fed induction generator (DFIG); Doubly fed induction generators; Neuro-fuzzy controller; Voltage dip; Wind energy conversion system; Electric machine control 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. � 2019 IEEE. Final 2023-05-29T07:25:38Z 2023-05-29T07:25:38Z 2019 Conference Paper 10.1109/IEMDC.2019.8785362 2-s2.0-85070957469 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070957469&doi=10.1109%2fIEMDC.2019.8785362&partnerID=40&md5=e4dd6042fada1a9d29e256368e965e1a https://irepository.uniten.edu.my/handle/123456789/24666 8785362 2101 2106 Institute of Electrical and Electronics Engineers Inc. Scopus |
| institution |
Universiti Tenaga Nasional |
| building |
UNITEN Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Tenaga Nasional |
| content_source |
UNITEN Institutional Repository |
| url_provider |
http://dspace.uniten.edu.my/ |
| description |
Adaptive control systems; Asynchronous generators; Controllers; Electric current control; Electric drives; Electric fault currents; Electric power system control; Electric power transmission networks; Energy conversion; Fuzzy inference; Reactive power; Robust control; Two term control systems; Wind power; Adaptive network fuzzy inference systems; ANFIS; Conventional proportional integrals; Doubly fed induction generator (DFIG); Doubly fed induction generators; Neuro-fuzzy controller; Voltage dip; Wind energy conversion system; Electric machine control |
| author2 |
10040907100 |
| author_facet |
10040907100 Amin I.K. Nasir Uddin M. Hannan M.A. Alam A.H.M.Z. |
| format |
Conference Paper |
| author |
Amin I.K. Nasir Uddin M. Hannan M.A. Alam A.H.M.Z. |
| spellingShingle |
Amin I.K. Nasir Uddin M. Hannan M.A. Alam A.H.M.Z. Adaptive neuro-fuzzy controller for grid voltage dip compensations of grid connected dfig-wecs |
| author_sort |
Amin I.K. |
| 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 |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806424523115855872 |
| score |
13.222552 |