Two different controllers-based DPC of the doubly-fed induction generator with real-time implementation on dSPACE 1104 controller board
The direct power command (DPC) of the doubly-fed induction generators (DFIG) has garnered increasing attention due to its simplicity, ease of implementation, and fast dynamic response that distinguished it from other controls. Recently, nonlinear controllers have been suggested to improve the DPC ro...
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Published in | Measurement and control (London) Vol. 57; no. 8; pp. 1123 - 1145 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
London, England
SAGE Publications
01.08.2024
Sage Publications Ltd SAGE Publishing |
Subjects | |
Online Access | Get full text |
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Summary: | The direct power command (DPC) of the doubly-fed induction generators (DFIG) has garnered increasing attention due to its simplicity, ease of implementation, and fast dynamic response that distinguished it from other controls. Recently, nonlinear controllers have been suggested to improve the DPC robustness, in particular the minimization of the DFIG power fluctuations. In the present research work, two different controls are used to regulate the DFIG power, where the first is a traditional DPC and the second is the DPC based on neural super-twisting algorithm (NSTA) controllers. The NSTA controllers were used instead of hysteresis comparators in the DPC technique, and the pulse width modulation (PWM) technique was used as a suitable solution instead of the switching table to better manage the state of switches and simplify the control system. The proposed controls were investigated and implemented using Matlab software and Dspace 1104 card with different tests to determine the best control. Experimental and simulation results show the good efficiency of the NSTA controller in improving energy and current quality. Also, the comparison is made between both techniques and the other controls in terms of reducing current harmonic distortions and ratios of the DFIG power fluctuations. |
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ISSN: | 0020-2940 2051-8730 |
DOI: | 10.1177/00202940241236288 |