DC Fault Current Analyzing, Limiting, and Clearing in DC Microgrid Clusters

Bayati, Navid; Baghaee, Hamid Reza; Savaghebi, Mehdi; Hajizadeh, Amin; Soltani, Mohsen; Lin, Zhengyu

doi:10.3390/en14196337

Cited by 17 publications

(11 citation statements)

References 41 publications

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“…Therefore, it is necessary to improve the voltage sag to increase the time the DER could be connected to the LVDC system. In the capacitor-discharge stage, Equation (1) represents the peak fault current caused by the DC capacitors included in the converter [10,18,19]. I 0 and V 0 are the initial values of voltage across the capacitor and the line current before the the fault.…”

Section: Low-voltage Ride-throughmentioning

confidence: 99%

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Simulation of a Low-Voltage Direct Current System Using T-SFCL to Enhance Low Voltage Ride through Capability

et al. 2022

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Owing to the increasing penetration level of distributed energy resources (DER) and direct current (DC) load, the usage of low-voltage direct current (LVDC) systems has expanded to achieve efficient operations. However, because the LVDC system reaches the peak fault current at a faster rate than the alternating current (AC) system, a solution that protects the system components is necessary to maintain system integrity. It is required by the low-voltage ride-through (LVRT) that the DERs maintain their interconnections with the LVDC system and support fault recovery. In this study, a method is proposed to allow the application of the superconducting fault current limiter (SFCL) to reduce the fault current and enhance the LVRT capability. However, when the DER maintain a connection to support fault recovery, the conventional resistive-type SFCL must withstand the burden of high-temperature superconducting (HTSC) operation during fault state dependence on LVRT. Therefore, this study proposes a trigger-type SFCL to reduce the burden of the HTSC element and enhance the LVRT capability. The voltage sag related to the LVRT was improved owing to the SFCL. The proposed solution was confirmed using PSCAD/EMTDC, which is a commercial software.

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Section: Low-voltage Ride-throughmentioning

confidence: 99%

“…In the last stage (grid-side current feeding stage), after the capacitor and line inductance exhaust the source, current is received from the PV [18,19].…”

Section: Low-voltage Ride-throughmentioning

confidence: 99%

Simulation of a Low-Voltage Direct Current System Using T-SFCL to Enhance Low Voltage Ride through Capability

et al. 2022

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“…To lessen the financial burden and boost the dependability, numerous DC microgrids are linked to one another and/or the main AC grid in a DC microgrid cluster. In comparison to protecting a single DC microgrid, protecting a cluster of DC microgrids poses more challenges due to the increased number of coupling points, longer transmission lines, and higher penetration of RES [3]. This is because there are no established protection standards for DC systems.…”

Section: Introductionmentioning

confidence: 99%

Fault detection and classification in DC microgrid clusters

Pan

Mandal

2023

Eng. Res. Express

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With the rising popularity of DC microgrids, clusters of such grids are beginning to emerge as a practical and economical option. Short circuit problems in a DC microgrid clusters can cause overcurrent damage to power electronic devices. Protecting DC lines from large fault currents is essential. This paper presents a novel localized fault detection and classification technique for the protection of DC microgrid clusters. In this paper, a variational mode decomposition (VMD) and artificial neural network (ANN) based technique is proposed for accurate and effective fault detection and classification. This research aims to train an ANN that can detect and classify faults in DC microgrid clusters with multiple sources and loads by applying VMD to extract features of current signals. Different types of short circuit faults such as Pole to Pole and Pole to ground faults are considered under various grid operating conditions. The proposed method is capable of real-time fault detection and diagnosis, which can help prevent system failures and minimize downtime. The results indicate that the proposed approach is efficient and effective in detecting/classifying faults in DC microgrid clusters improving the reliability and system safety. The performance evaluation is carried out through rigorous case studies in MATLAB/Simulink environment to prove the efficacy of the proposed method. The VMD-ANN approach is shown to outperform other traditional signal processing techniques in terms of accuracy and robustness. Moreover, the proposed method is applicable to a wide range of DC microgrid clusters, making it a versatile and valuable tool for future research and development.

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“…The absence of phasor, frequency, and zero-crossing point in DC systems prevents the direct use of AC fault detection methods in DC systems. Therefore, differential, current rise rates, and overcurrent fault detection techniques are commonly implemented in DC microgrids [3,4]. However, due to the high sensitivity of DC microgrid response to the impedance of fault, fault detection in such a system is challenging [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

EMD/HT‐based local fault detection in DC microgrid clusters

et al. 2022

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DC faults can create serious damages if not detected and isolated in a short time. This paper proposes a fault detection technique for DC faults to enhance the protection of DC microgrid clusters. To detect such faults accurately and quickly, a DC fault detection scheme using empirical mode decomposition and Hilbert transform is proposed. Due to the strict time limits for fault interruption caused by fast high‐rising fault currents in DC systems, DC microgrid clusters' protection remains a challenging task. Furthermore, high impedance faults (HIFs) in DC systems cause a small change in the current, which can damage the power electronic converters if not detected in time. Therefore, this paper proposes a local scheme for the fast detection of faults including HIFs in DC microgrid clusters. Both simulation and experimental results using a scaled DC microgrid cluster prototype and considering several scenarios (such as low impedance faults, HIFs, noise, overload, and bad calibration of sensors) demonstrate the successful and fast detection (less than 2 ms) of DC faults by the proposed method. Compared with other techniques, the proposed scheme presents its merits from the viewpoints of accuracy and speed.

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DC Fault Current Analyzing, Limiting, and Clearing in DC Microgrid Clusters

Cited by 17 publications

References 41 publications

Simulation of a Low-Voltage Direct Current System Using T-SFCL to Enhance Low Voltage Ride through Capability

Simulation of a Low-Voltage Direct Current System Using T-SFCL to Enhance Low Voltage Ride through Capability

Fault detection and classification in DC microgrid clusters

EMD/HT‐based local fault detection in DC microgrid clusters

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