LAPSE:2023.8285
Published Article
LAPSE:2023.8285
Control Strategy and Parameter Optimization Based on Grid Side Current Dynamic Change Rate for Doubly-Fed Wind Turbine High Voltage Ride Through
Jun Deng, Zhenghao Qi, Nan Xia, Tong Gao, Yang Zhang, Jiandong Duan
February 24, 2023
Abstract
High voltage ride through (HVRT) control strategies for doubly-fed induction wind turbines (DFIG) have mostly focused on the rotor side converter, while the reactive power compensation capability of the grid side converter and the impact of grid side converter current transients have often been ignored on the DC bus voltage and reactive power. Therefore, a control strategy based on grid side current dynamic change characteristics is proposed, which resets the reference values of the grid side active and reactive currents for wind turbine HVRT to ensure partial absorption of reactive power on the grid side. Secondly, the key parameter in the proposed control strategy is optimization to get the most suitable DC bus voltage value with the grey wolf algorithm. Finally, the grid-integrated wind turbine simulation model is built on the MATLAB/SIMULINK and RT-Lab platforms. The simulation test results show that the proposed HVRT control strategy and its parameter optimization method are effective, DFIG can achieve HVRT when the wind turbine voltage rises to 1.3 pu.
Keywords
current change rate, doubly-fed induction wind turbines, grey wolf algorithm, grid side current, high voltage ride through
Suggested Citation
Deng J, Qi Z, Xia N, Gao T, Zhang Y, Duan J. Control Strategy and Parameter Optimization Based on Grid Side Current Dynamic Change Rate for Doubly-Fed Wind Turbine High Voltage Ride Through. (2023). LAPSE:2023.8285
Author Affiliations
Deng J: Power Research Institute of State Grid Shaanxi Electric Power Company Limited, Xi’an 710100, China [ORCID]
Qi Z: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, China
Xia N: Power Research Institute of State Grid Shaanxi Electric Power Company Limited, Xi’an 710100, China
Gao T: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, China
Zhang Y: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, China
Duan J: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710000, China [ORCID]
Journal Name
Energies
Volume
15
Issue
21
First Page
7977
Year
2022
Publication Date
2022-10-27
ISSN
1996-1073
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PII: en15217977, Publication Type: Journal Article
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https://doi.org/10.3390/en15217977
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