Implementation of Voltage Sag Relative Location and Fault Type Identification Algorithm Using Real-Time Distribution System Data

Yalman, Yunus; Uyanık, Tayfun; Tan, Adnan; Bayındır, Kamil Çağatay; Terriche, Yacine; Su, Chun‐Lien; Guerrero, Josep M.

doi:10.3390/math10193537

Cited by 4 publications

(1 citation statement)

References 30 publications

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“…Most voltage sags occur under fault conditions [1][2][3][4][5][6][7], thus studies have been conducted to identify the relative location and types of faults that cause voltage sag [6] and to calculate the voltage sag [7]. Superconducting fault current limiters (SFCLs) play an important role in limiting fault currents and mitigating voltage sag in a power distribution system, and various studies have been conducted on these protection devices [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Voltage Sag Mitigation Effect Considering Failure Probability According to the Types of SFCL

2023

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The development of industrial technology is based on electronic devices that are sensitive to power quality. Thus, the demand for high-quality and reliable power supplies is increasing. Voltage sag results in severe problems in the manufacturing process of power quality-sensitive industrial loads. When a fault occurs in a multi-ground power distribution system, the magnitudes of the fault current and voltage sag in the faulted and nonfaulted feeders become high. Hence, installing a superconducting fault current limiter (SFCL) is an effective method of compensating for fault current limitation and voltage sag. This study evaluates the effects of improving the magnitude, duration, and frequency of the voltage sag according to the type of SFCL used. First, a fault in the power distribution system is analyzed using PSCAD/EMTDC, a power system simulation software, according to the fault current-limiting element (CLE) and the type of SFCL. Second, the expected voltage sag frequency caused by a feeder fault in the power distribution system is assessed. Finally, the voltage sag improvement effect according to the CLE and the type of SFCL are compared. The trigger-type SFCL with a resistor as a CLE has been evaluated and found to be effective in improving voltage sag.

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Section: Introductionmentioning

confidence: 99%

Voltage Sag Mitigation Effect Considering Failure Probability According to the Types of SFCL

2023

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Most influential feature form for supervised learning in voltage sag source localization

Mohammadi,

Polajžer,

Leborgne

et al. 2024

Engineering Applications of Artificial Intelligence

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A time-variant power distribution network voltage sag identification method based on the concept of inheritance

Li,

Yu,

et al. 2024

Front. Energy Res.

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The present paper introduces a novel method for identifying voltage sags in time-variant power distribution networks, effectively addressing the challenges arising from the temporal variability of network topology and data. The proposed method is founded on the concept of inheritance, which is bifurcated into breadth and depth inheritance strategies. The breadth inheritance strategy employs transfer learning to manage topological temporality, utilizing the Euclidean distance between samples to ascertain the sequence of sample migration, and implements multitask learning to share feature representations across different tasks. The depth inheritance strategy, on the other hand, utilizes incremental learning to handle data temporality, building upon the initial model parameters to learn new sample features, which in turn reduces the time required for model updates and enhances the accuracy of target tasks. Case study findings validate the suitability of the proposed methods for reconstructing fault identification models in scenarios characterized by topological temporal variability and for rapidly updating fault identification models in scenarios with data temporal variability. The approach presented herein holds significant implications for the enhancement of power supply reliability and the adaptability of electrical grids.

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Implementation of Voltage Sag Relative Location and Fault Type Identification Algorithm Using Real-Time Distribution System Data

Cited by 4 publications

References 30 publications

Voltage Sag Mitigation Effect Considering Failure Probability According to the Types of SFCL

Voltage Sag Mitigation Effect Considering Failure Probability According to the Types of SFCL

Most influential feature form for supervised learning in voltage sag source localization

A time-variant power distribution network voltage sag identification method based on the concept of inheritance

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