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Identification of Control Parameters in Doubly Fed Induction Generators via Adaptive Differential Evolution.

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Název: Identification of Control Parameters in Doubly Fed Induction Generators via Adaptive Differential Evolution.
Autoři: Deng, Jun, Wang, Yu, Liu, Yao, Zheng, Tianyue, Xia, Nan, Li, Ziang, Wang, Tong
Zdroj: Energies (19961073); Sep2025, Vol. 18 Issue 18, p4979, 18p
Témata: DIFFERENTIAL evolution, INDUCTION generators, PARAMETER estimation, STABILITY of linear systems, ELECTRIC transients, TRANSIENT analysis, RENEWABLE energy sources
Abstrakt: With the increasing penetration of renewable energy generation, analysis of the transient characteristics of doubly fed induction generators, as the mainstream wind turbine configuration, is made highly significant both theoretically and practically. However, manufacturers treat the control parameters as confidential commercial secrets, rendering them a "black box". Parameter identification is fundamental for studying transient characteristics and system stability. Existing identification methods achieve accurate results only under moderate or severe voltage dip faults. To address this limitation, this paper proposes a control parameter identification method based on the adaptive differential evolution algorithm, suitable for DFIG time-domain simulation models. This method enables accurate parameter identification even during mild voltage dips. Firstly, a trajectory sensitivity analysis is employed to evaluate the difficulty of identifying each parameter, establishing the identification sequence accordingly. Secondly, based on the control loop where each parameter resides, the time-domain expressions are discretized to formulate the fitness function. Finally, the identified control parameters are compared against their true values. The results demonstrate that the proposed identification method achieves high accuracy and robustness while maintaining a rapid identification rate. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
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  Group: Ti
  Data: Identification of Control Parameters in Doubly Fed Induction Generators via Adaptive Differential Evolution.
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  Data: <searchLink fieldCode="AR" term="%22Deng%2C+Jun%22">Deng, Jun</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Yu%22">Wang, Yu</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Yao%22">Liu, Yao</searchLink><br /><searchLink fieldCode="AR" term="%22Zheng%2C+Tianyue%22">Zheng, Tianyue</searchLink><br /><searchLink fieldCode="AR" term="%22Xia%2C+Nan%22">Xia, Nan</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Ziang%22">Li, Ziang</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Tong%22">Wang, Tong</searchLink>
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  Data: Energies (19961073); Sep2025, Vol. 18 Issue 18, p4979, 18p
– Name: Subject
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  Group: Su
  Data: <searchLink fieldCode="DE" term="%22DIFFERENTIAL+evolution%22">DIFFERENTIAL evolution</searchLink><br /><searchLink fieldCode="DE" term="%22INDUCTION+generators%22">INDUCTION generators</searchLink><br /><searchLink fieldCode="DE" term="%22PARAMETER+estimation%22">PARAMETER estimation</searchLink><br /><searchLink fieldCode="DE" term="%22STABILITY+of+linear+systems%22">STABILITY of linear systems</searchLink><br /><searchLink fieldCode="DE" term="%22ELECTRIC+transients%22">ELECTRIC transients</searchLink><br /><searchLink fieldCode="DE" term="%22TRANSIENT+analysis%22">TRANSIENT analysis</searchLink><br /><searchLink fieldCode="DE" term="%22RENEWABLE+energy+sources%22">RENEWABLE energy sources</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: With the increasing penetration of renewable energy generation, analysis of the transient characteristics of doubly fed induction generators, as the mainstream wind turbine configuration, is made highly significant both theoretically and practically. However, manufacturers treat the control parameters as confidential commercial secrets, rendering them a "black box". Parameter identification is fundamental for studying transient characteristics and system stability. Existing identification methods achieve accurate results only under moderate or severe voltage dip faults. To address this limitation, this paper proposes a control parameter identification method based on the adaptive differential evolution algorithm, suitable for DFIG time-domain simulation models. This method enables accurate parameter identification even during mild voltage dips. Firstly, a trajectory sensitivity analysis is employed to evaluate the difficulty of identifying each parameter, establishing the identification sequence accordingly. Secondly, based on the control loop where each parameter resides, the time-domain expressions are discretized to formulate the fitness function. Finally, the identified control parameters are compared against their true values. The results demonstrate that the proposed identification method achieves high accuracy and robustness while maintaining a rapid identification rate. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.3390/en18184979
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 18
        StartPage: 4979
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      – SubjectFull: DIFFERENTIAL evolution
        Type: general
      – SubjectFull: INDUCTION generators
        Type: general
      – SubjectFull: PARAMETER estimation
        Type: general
      – SubjectFull: STABILITY of linear systems
        Type: general
      – SubjectFull: ELECTRIC transients
        Type: general
      – SubjectFull: TRANSIENT analysis
        Type: general
      – SubjectFull: RENEWABLE energy sources
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    Titles:
      – TitleFull: Identification of Control Parameters in Doubly Fed Induction Generators via Adaptive Differential Evolution.
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            NameFull: Deng, Jun
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            – D: 15
              M: 09
              Text: Sep2025
              Type: published
              Y: 2025
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