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Data · dataset · 2026

Distribution Network Fault Simulation Dataset for Novel Power Systems

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This dataset was generated through simulations on the MATLAB/SIMULINK platform, based on the IEEE 33-bus distribution network model integrated with two wind-based distributed generators.

Description

The simulation covers 32 fault locations, 10 fault types (including single-phase-to-ground faults, two-phase short circuits, two-phase-to-ground short circuits, and three-phase short circuits), 7 transition resistance values (ranging from 0.01 Ω to 2000 Ω), and 6 randomly generated fault inception angles (ranging from 1° to 180°).

For each fault event, three-phase currents, three-phase voltages, and zero-sequence voltages over one week before and after the fault were collected as raw features, resulting in a total of 13,440 samples. This dataset is suitable for research tasks such as distribution network fault recognition, deep learning model training, and condition monitoring in novel power systems.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Simulation 75%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.4383112 d agoJSON v1
FieldAssertionExtractorEvidence
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