Detection function of medium-voltage intelligent distribution cabinet
CN120414281A
The invention relates to the technical field of power distribution equipment, in particular to an intelligent power distribution cabinet system, a detection method and a detection...
Smart power distribution solutions
The units offer Fault Passage Indication (FPI) functionality and enables accurate current and voltage measurements from the medium-voltage network utilizing ABB''s lightweight sensor technology.
Intelligent Control of Medium and Low Voltage Distribution Network
The equipment in medium and low voltage distribution network are complicated, located at wide range of points and their switch conditions are variable. Restrict.
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This paper proposes a setting-less fault detection algorithm that determines fault locations by evaluating the rate of change in the difference between local and remote terminal currents.
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It is designed for real-time monitoring of power distribution lines, performing fault detection, fault waveform recording, fault section pinpointing, risk alerting, and power quality analysis.
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This study presents a scalable, cost-effective, and real-time fault detection framework designed to operate within the constraints of existing SCADA infrastructure in medium voltage (MV) urban
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This paper presents a method to detect and classify the high impedance fault that occur in the medium voltage (MV) distribution network using discrete wavelet transform (DWT) and
High-impedance fault detection in medium-voltage distribution network
This paper presents the high-impedance fault (HIF) detection and identification in medium-voltage distribution network of 13.8 kV using discrete wavelet transform (DWT) and
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Through the intelligent terminal installed in the power distribution cabinet, the electric data of the cabinet can be automatically collected and analyzed, and the parameters such as humidity and temperature
Convolutional neural network approach for fault detection and
In summary, this research presents a novel approach to identifying and characterizing faults in medium-voltage networks. The integration of CNN and PFPT allows for precise fault type
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