Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults

Jiateng Gu; Zhenbin Zhang; Zhen Li; Jose Rodriguez

doi:10.1109/PRECEDE57319.2023.10174594

Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults

Jiateng Gu, Zhenbin Zhang^*, Zhen Li, Jose Rodriguez

^*Corresponding author for this work

Shandong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

Low-voltage ride-through (LVRT) capability of the doubly fed induction generator (DFIG) is seen as insufficient under severe grid faults due to it being prone to suffering from overcurrent. Especially in the asymmetrical grid faults, large oscillations of electromagnetic torque and output power of DFIG will also be caused. To suppress electromagnetic torque oscillation and improve DFIG system LVRT capability, the rotor current reference value should be set to follow the stator flux under severe asymmetrical grid faults. However, the stator flux contains AC components in the synchronous reference frame under asymmetrical grid faults. The classical proportional-integral controller cannot accurately track AC references. To solve this problem, a model predictive control (MPC) method for the DFIG rotor-side converter in the stationary reference frame was proposed in this paper. With this proposal, the tracking accuracy of the rotor current reference value has been considerably improved under asymmetrical grid faults. Thus, the electronic torque oscillation has been reduced to a large extent, and the DFIG system LVRT capability was improved. Finally, simulations verified the effectiveness of the proposed method.

Original language	English
Title of host publication	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350396867
DOIs	https://doi.org/10.1109/PRECEDE57319.2023.10174594
State	Published - 2023
Event	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 - Wuhan, China Duration: 2023 → 2023

Publication series

Name	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Conference

Conference	2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023
Country/Territory	China
City	Wuhan
Period	16/06/23 → 19/06/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

ASJC Scopus subject areas

Control and Optimization
Modeling and Simulation
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Mechanical Engineering
Safety, Risk, Reliability and Quality

Access to Document

10.1109/PRECEDE57319.2023.10174594

Cite this

Gu, J., Zhang, Z., Li, Z., & Rodriguez, J. (2023). Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRECEDE57319.2023.10174594

Gu, Jiateng ; Zhang, Zhenbin ; Li, Zhen et al. / Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

@inproceedings{57270298ecb4442d943c1a2e4378314a,

title = "Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults",

abstract = "Low-voltage ride-through (LVRT) capability of the doubly fed induction generator (DFIG) is seen as insufficient under severe grid faults due to it being prone to suffering from overcurrent. Especially in the asymmetrical grid faults, large oscillations of electromagnetic torque and output power of DFIG will also be caused. To suppress electromagnetic torque oscillation and improve DFIG system LVRT capability, the rotor current reference value should be set to follow the stator flux under severe asymmetrical grid faults. However, the stator flux contains AC components in the synchronous reference frame under asymmetrical grid faults. The classical proportional-integral controller cannot accurately track AC references. To solve this problem, a model predictive control (MPC) method for the DFIG rotor-side converter in the stationary reference frame was proposed in this paper. With this proposal, the tracking accuracy of the rotor current reference value has been considerably improved under asymmetrical grid faults. Thus, the electronic torque oscillation has been reduced to a large extent, and the DFIG system LVRT capability was improved. Finally, simulations verified the effectiveness of the proposed method.",

keywords = "asymmetrical grid faults, doubly fed induction generator, low-voltage ride-through",

author = "Jiateng Gu and Zhenbin Zhang and Zhen Li and Jose Rodriguez",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023 ; Conference date: 16-06-2023 Through 19-06-2023",

year = "2023",

doi = "10.1109/PRECEDE57319.2023.10174594",

language = "English",

series = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023",

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Gu, J, Zhang, Z, Li, Z & Rodriguez, J 2023, Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults. in 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023, Wuhan, China, 16/06/23. https://doi.org/10.1109/PRECEDE57319.2023.10174594

Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults. / Gu, Jiateng; Zhang, Zhenbin; Li, Zhen et al.
2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults

AU - Gu, Jiateng

AU - Zhang, Zhenbin

AU - Li, Zhen

AU - Rodriguez, Jose

PY - 2023

Y1 - 2023

N2 - Low-voltage ride-through (LVRT) capability of the doubly fed induction generator (DFIG) is seen as insufficient under severe grid faults due to it being prone to suffering from overcurrent. Especially in the asymmetrical grid faults, large oscillations of electromagnetic torque and output power of DFIG will also be caused. To suppress electromagnetic torque oscillation and improve DFIG system LVRT capability, the rotor current reference value should be set to follow the stator flux under severe asymmetrical grid faults. However, the stator flux contains AC components in the synchronous reference frame under asymmetrical grid faults. The classical proportional-integral controller cannot accurately track AC references. To solve this problem, a model predictive control (MPC) method for the DFIG rotor-side converter in the stationary reference frame was proposed in this paper. With this proposal, the tracking accuracy of the rotor current reference value has been considerably improved under asymmetrical grid faults. Thus, the electronic torque oscillation has been reduced to a large extent, and the DFIG system LVRT capability was improved. Finally, simulations verified the effectiveness of the proposed method.

AB - Low-voltage ride-through (LVRT) capability of the doubly fed induction generator (DFIG) is seen as insufficient under severe grid faults due to it being prone to suffering from overcurrent. Especially in the asymmetrical grid faults, large oscillations of electromagnetic torque and output power of DFIG will also be caused. To suppress electromagnetic torque oscillation and improve DFIG system LVRT capability, the rotor current reference value should be set to follow the stator flux under severe asymmetrical grid faults. However, the stator flux contains AC components in the synchronous reference frame under asymmetrical grid faults. The classical proportional-integral controller cannot accurately track AC references. To solve this problem, a model predictive control (MPC) method for the DFIG rotor-side converter in the stationary reference frame was proposed in this paper. With this proposal, the tracking accuracy of the rotor current reference value has been considerably improved under asymmetrical grid faults. Thus, the electronic torque oscillation has been reduced to a large extent, and the DFIG system LVRT capability was improved. Finally, simulations verified the effectiveness of the proposed method.

KW - asymmetrical grid faults

KW - doubly fed induction generator

KW - low-voltage ride-through

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U2 - 10.1109/PRECEDE57319.2023.10174594

DO - 10.1109/PRECEDE57319.2023.10174594

M3 - Conference contribution

AN - SCOPUS:85166267126

T3 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

BT - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023

Y2 - 16 June 2023 through 19 June 2023

ER -

Gu J, Zhang Z, Li Z, Rodriguez J. Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults. In 2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE International Conference on Predictive Control of Electrical Drives and Power Electronics, PRECEDE 2023). doi: 10.1109/PRECEDE57319.2023.10174594

Model Predictive Control for DFIG to Improve the LVRT Capability under Severe Asymmetrical Grid Faults

Abstract

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ASJC Scopus subject areas

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