Short-Circuit Modeling of DFIG-Based WTG in Sequence Domain Considering Various Fault- Ride-Through Requirements and Solutions

Chang, Yuanzhu; Koçar, Ilhan; Farantatos, Evangelos; Haddadi, Aboutaleb; Patel, Manish

doi:10.1109/tpwrd.2023.3235985

Cited by 16 publications

(6 citation statements)

References 35 publications

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“…, and finally convert it into a two-dimensional matrix through matrix transformation. That is, the grayscale image matrix can be expressed as formula (8).…”

Section: Data Preprocessingmentioning

confidence: 99%

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Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator

Zhu,

Tao,

2023

AETR

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Recently, deep learning has provided a new opportunity to achieve high precision and real-time parameter identification of the doubly-fed induction generator (DFIG) in the event of short-circuit fault. However, deep learning algorithms based on data training are facing the challenge of relying on a large amount of training data and poor generalization performance. In order to improve these shortcomings, we embed the forward calculation model of three-phase short-circuit current (SCC) into the neural network, and propose an unsupervised neural network which can realize high-precision parameter identification. The network only needs to convert the short circuit current curve into a two-dimensional gray level map to complete the precise training of the network without real labels, which effectively improves the fitting ability of the network for inverse problems. The simulation results show that the proposed method can achieve high precision identification of DFIG parameters both within and outside the domain, and verify the high precision identification and generalization ability of unsupervised networks.

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“…, and finally convert it into a two-dimensional matrix through matrix transformation. That is, the grayscale image matrix can be expressed as formula (8).…”

Section: Data Preprocessingmentioning

confidence: 99%

“…Accurate SCC calculation and control of wind turbines depend on accurate model parameters of wind turbines. Effective identification of turbine parameters is of great significance for improving the performance of wind turbines [8][9] [10].…”

Section: Introductionmentioning

confidence: 99%

Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator

Zhu,

Tao,

2023

AETR

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“…In view of the asymmetric nature of faults, references [7,8] also pointed out that a DG only provides positive sequence components under positive and negative sequence separation control, which can be equivalent to a positive-sequence-controlled current source. In addition to the characteristics of industrial frequency, reference [9] considered two strategies consisting of excitation control and crowbar input, respectively, and deduced that the short-circuit current of a DG has an attenuation component and a DC component. The existing research fully demonstrates that the addition of DGs causes a fundamental change in the fault characteristics of a distribution network.…”

Section: Introduction 1backgroundmentioning

confidence: 99%

A Section Location Method of Single-Phase Short-Circuit Faults for Distribution Networks Containing Distributed Generators Based on Fusion Fault Confidence of Short-Circuit Current Vectors

Xu,

Ouyang,

Chen

et al. 2024

Electronics

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To ensure safe and stable operation, accurate fault localization within active distribution networks is required, and this has attracted much attention. Influenced by many factors such as the control strategy, control performance, initial state of the distributed generators, and distribution network topology, it is still difficult to reliably locate complex and variable single-phase short-circuit faults relying only on a single feature quantity, while localization methods incorporating intelligent algorithms are affected by the choice of a priori samples and the fact that the solution process is a black-box model. To address this challenge, in this work, an expression for the single-phase short-circuit current vector of a distribution network containing distributed generators is derived, and the differences in magnitude and phase angle of the short-circuit current vectors upstream and downstream of the fault point are analyzed. Based on measurement theory, a fault confidence distribution function that reacts to the relative size of the current magnitude difference and phase angle difference is established, and the fusion fault confidence of the short-circuit current vector is constructed with the help of evidence theory. Finally, a method of locating single-phase short-circuit faults in distribution networks that contain distributed generators is proposed. The simulation results show that the ratio of the fusion fault confidence of the short-circuit current vector between faulted and non-faulted sections under the influence of different distributed generator capacities, fault locations, and transition resistances differ significantly. The proposed single-phase short-circuit fault localization method is both adaptive and physically interpretable and has clear boundaries, sound sensitivity, and engineering practicability.

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“…In addition to encountering parameter disturbances arising from operational changes in system parameters, as well as transient disturbances caused by external aerodynamics, unmodeled factors, and grid faults [16]. The primary objective of designing a control strategy for DFIG is to effectively harness the maximum wind energy while ensuring compliance with faultride-through (FRT) benchmark capability [17]. However, the aforementioned disturbances, which are almost impossible to measure, pose significant challenges in achieving these control objectives.…”

Section: Introductionmentioning

confidence: 99%

Single-Loop Robust Decoupling Control Base on Perturbation Estimation for DC-Based DFIG

Sun,

Yang,

Zhang

2024

IEEE Access

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This paper presents a perturbation observer based single-loop robust decoupling control scheme (RDC-PO) for DC-based DFIG with dual voltage source converters to enhance maximum power point tracking (MPPT) and improve fault-ride-through (FRT) capability. The unknown nonlinear effects caused by aerodynamic and modeling uncertainties are aggregated into a perturbation term, which is estimated by a sliding-mode perturbation observer. Then, a single-loop linear feedback controller with no intermediate link is designed to quickly compensate disturbance estimation in real time. Furthermore, the control algorithm does not necessitate a precise DFIG model. Additionally, the incorporation of nonlinear robust control compensates for the inherent limitations of linear control, thereby endowing the proposed control algorithm with the advantages of facile implementation akin to traditional linear control and global consistency characteristic of nonlinear robust control. Simulation results show that RDC-PO has superior transient and steady-state performance compared with double-loop feedback controller (DFC) and single-loop feedback control (SFC) in MPPT and FRT. Finally, Experiment verifies the practical operability of the proposed strategy. INDEX TERMS DC-based DFIG, perturbation observer, single-loop controller, MPPT, FRT

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Short-Circuit Modeling of DFIG-Based WTG in Sequence Domain Considering Various Fault- Ride-Through Requirements and Solutions

Cited by 16 publications

References 35 publications

Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator

Short-circuit Current-based Parametrically Identification for Doubly Fed Induction Generator

A Section Location Method of Single-Phase Short-Circuit Faults for Distribution Networks Containing Distributed Generators Based on Fusion Fault Confidence of Short-Circuit Current Vectors

Single-Loop Robust Decoupling Control Base on Perturbation Estimation for DC-Based DFIG

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