Fault detection and location estimation for<scp>LVDC</scp>microgrid using self‐parametric measurements

Reddy, O. Yugeswar; Chatterjee, Soumesh; Chakraborty, Ajoy Kumar; Bhowmik, Arup Ratan

doi:10.1002/2050-7038.12499

Cited by 13 publications

(5 citation statements)

References 30 publications

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“…1(a) is simulated in PSCAD with a sampling frequency of 1 M Hz, meaning the sampled values are 1 µs apart. Rated system voltage is chosen to be 400 V, as it has been used in a number of papers for dc microgrids [18]- [21]. A 100 m long Yorkshire conductor [22] is chosen for the feeder.…”

Section: Validation Of the Proposed Theorymentioning

confidence: 99%

A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements

Gani

Brahma

2022

IEEE Open J. Power Energy

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Fault location on a dc microgrid feeder needs to be extremely fast to protect the circuit breaker and converter-source components. This paper develops a seminal theoretical foundation for fast fault location on a dc feeder that uses only singleended local measurements in time domain. The theory provides a closed-form deterministic solution for fault location, making the resulting fault location method agnostic to system-topology and immune to fault resistance. The theory is developed with ideal dc voltage sources, and extended to practical converter-sources. The performance of the resulting method is demonstrated by simulating a dc feeder with converters connected at both ends, modeled in PSCAD.

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Section: Validation Of the Proposed Theorymentioning

confidence: 99%

A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements

Gani

Brahma

2022

IEEE Open J. Power Energy

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“…Accurate detection of fault locations (FLs) in power transmission lines is one of the most important aspects of protection systems. The capability of protection systems to precisely detect FL and determine the corrective action and solve the problem can increase the reliability and reduce the power system operating costs 1‐4 …”

Section: Introductionmentioning

confidence: 99%

A fault‐location algorithm for parallel line based on the long short‐term memory model using the distributed parameter line model

Taheri

Salehimehr

Sedighizadeh

2021

Int Trans Electr Energ Syst

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Summary Parallel transmission lines are widely used in modern power systems due to their ability to increase power transmission and reliability of the power network. However, due to these networks' complexity, fault locating is a potential problem in these types of systems. Besides, when the wind farms enter these systems, a new challenge will be created for the fault location (FL) techniques; and the reason is that the impedance continuously varies in wind power plants. This paper proposes a novel FL algorithm for parallel transmission lines using the distributed parameter line model. This method uses long short‐term memory networks for estimating source impedance and other network parameters. The algorithm shows accurate performance during noisy conditions and precisely determines the fault distance during both three‐phase and single‐phase faults. The presented method is implemented using PSCAD and Python software. The simulation results illustrate the applicability of the proposed method to estimate FL in the presence of wind farms in the system.

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“…Results were quite promising and able to recognize various types of SFs. Reddy et al [ 15 ] had proposed self-parametric measurements to detect the fault and estimate its location for the LVDC micro-grid with OPAL-RT real-time simulator support. The results have been validated in a real-time environment.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic-SUGPDS Model for Faults Detection and Isolation of Underground Power Cable Based on Detection and Isolation Algorithm and Smart Sensors

Rajpoot

Pandey²,

Rajpoot³

et al. 2021

J. Electr. Eng. Technol.

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This paper proposes a SUGPDS model based on Detection and Isolation algorithm and smart sensors, namely micro phasor measurement unit, smart sensing and switching device, phasor data concentrator, and ZigBee technology, etc. for the identification, classification, and isolation of the various fault occurs in the underground power cable in the distribution system. The proposed SUGPDS is a quick and smart tool in supervising, managing, and controlling various faults and issues and maintaining the reliability, stability, and uninterrupted flow of electricity. First, the SUGPDS model is analyzed using a distributed parameter approach. Then, the proper arrangement of the system required for the implantation of SUGPDS is demonstrated using figures. The Phasor data concentrator plays an essential role in developing the detection and classification report for identification and classification. Finally, smart sensing and switching device installed at a different location isolated the faulty phase from a healthy network. This approach helps to decrease power consumption. Hence, SUGPDS has super abilities compared to the underground power distribution system. The effectiveness of the proposed method and model is demonstrated via figures and tables. Keywords Fault detection and isolation • Micro phasor measurement unit (µPMU) • Underground power cable • Phasor data concentrator (PDC) • Smart sensing and switching device (SSSD) • Smart underground power distribution system (SUGPDS) • Short-circuit fault • Open-circuit fault • Ground fault

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Fault detection and location estimation forLVDCmicrogrid using self‐parametric measurements

Cited by 13 publications

References 30 publications

A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements

A Closed-Form Mathematical Model and Method for Fast Fault Location on a Low Voltage DC Feeder Using Single-Ended Measurements

A fault‐location algorithm for parallel line based on the long short‐term memory model using the distributed parameter line model

A Dynamic-SUGPDS Model for Faults Detection and Isolation of Underground Power Cable Based on Detection and Isolation Algorithm and Smart Sensors

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