Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm
Doubly fed induction generators (DFIGs) are vulnerable to grid related electrical faults. Standards require DFIGs to be disconnected from the grid unless augmented with a fault ride through (FRT) capability. A fault current limiter (FCL) can enhance the overall stability of wind farms and allow them...
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doaj-2c4dd3ce938d410680bd5aba6743fbcd2021-03-30T02:26:32ZengIEEEIEEE Access2169-35362020-01-01811531411533410.1109/ACCESS.2020.30004629109350Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind FarmMd. Rashidul Islam0https://orcid.org/0000-0001-8415-0206Jakir Hasan1Md. Rezaur Rahman Shipon2Mohammad Ashraf Hossain Sadi3Ahmed Abuhussein4Tushar Kanti Roy5Department of Electrical and Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshDepartment of Electrical and Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshDepartment of Electrical and Electronic Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshCollege of Health, Science, and Technology, University of Central Missouri, Warrensburg, MO, USADepartment of Electrical and Computer Engineering, Gannon University, Erie, PA, USADepartment of Electronics and Telecommunication Engineering, Rajshahi University of Engineering and Technology, Rajshahi, BangladeshDoubly fed induction generators (DFIGs) are vulnerable to grid related electrical faults. Standards require DFIGs to be disconnected from the grid unless augmented with a fault ride through (FRT) capability. A fault current limiter (FCL) can enhance the overall stability of wind farms and allow them to maintain grid-code requirements. In this paper, a neuro fuzzy logic controlled parallel resonance type fault current limiter (NFLC-PRFCL) is proposed to enhance the FRT capability of the DFIG based wind farm. Theoretical and graphical analysis of the proposed method are carried out by MATLAB/Simulink software. The performance of the NFLC-PRFCL is compared with other documented FCL devices, e.g., the bridge type fault current limiter (BFCL) and the series dynamic braking resistor (SDBR). The performance of the NFLC-PRFCL is also compared with that of the existing fuzzy logic controlled parallel resonance fault current limiter (FLC-PRFCL). From the simulation results, it is found that the NFLC-PRFCL outperforms its competitors and enables the DFIG to maintain a near-seamless performance during various fault events.https://ieeexplore.ieee.org/document/9109350/Doubly fed induction generator (DFIG)fault ride through (FRT)fuzzy logic controller (FLC)neuro fuzzy logic controller (NFLC)parallel resonance fault current limiter (PRFCL) |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Md. Rashidul Islam Jakir Hasan Md. Rezaur Rahman Shipon Mohammad Ashraf Hossain Sadi Ahmed Abuhussein Tushar Kanti Roy |
spellingShingle |
Md. Rashidul Islam Jakir Hasan Md. Rezaur Rahman Shipon Mohammad Ashraf Hossain Sadi Ahmed Abuhussein Tushar Kanti Roy Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm IEEE Access Doubly fed induction generator (DFIG) fault ride through (FRT) fuzzy logic controller (FLC) neuro fuzzy logic controller (NFLC) parallel resonance fault current limiter (PRFCL) |
author_facet |
Md. Rashidul Islam Jakir Hasan Md. Rezaur Rahman Shipon Mohammad Ashraf Hossain Sadi Ahmed Abuhussein Tushar Kanti Roy |
author_sort |
Md. Rashidul Islam |
title |
Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm |
title_short |
Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm |
title_full |
Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm |
title_fullStr |
Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm |
title_full_unstemmed |
Neuro Fuzzy Logic Controlled Parallel Resonance Type Fault Current Limiter to Improve the Fault Ride Through Capability of DFIG Based Wind Farm |
title_sort |
neuro fuzzy logic controlled parallel resonance type fault current limiter to improve the fault ride through capability of dfig based wind farm |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2020-01-01 |
description |
Doubly fed induction generators (DFIGs) are vulnerable to grid related electrical faults. Standards require DFIGs to be disconnected from the grid unless augmented with a fault ride through (FRT) capability. A fault current limiter (FCL) can enhance the overall stability of wind farms and allow them to maintain grid-code requirements. In this paper, a neuro fuzzy logic controlled parallel resonance type fault current limiter (NFLC-PRFCL) is proposed to enhance the FRT capability of the DFIG based wind farm. Theoretical and graphical analysis of the proposed method are carried out by MATLAB/Simulink software. The performance of the NFLC-PRFCL is compared with other documented FCL devices, e.g., the bridge type fault current limiter (BFCL) and the series dynamic braking resistor (SDBR). The performance of the NFLC-PRFCL is also compared with that of the existing fuzzy logic controlled parallel resonance fault current limiter (FLC-PRFCL). From the simulation results, it is found that the NFLC-PRFCL outperforms its competitors and enables the DFIG to maintain a near-seamless performance during various fault events. |
topic |
Doubly fed induction generator (DFIG) fault ride through (FRT) fuzzy logic controller (FLC) neuro fuzzy logic controller (NFLC) parallel resonance fault current limiter (PRFCL) |
url |
https://ieeexplore.ieee.org/document/9109350/ |
work_keys_str_mv |
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