2026-10-15T06:10:53Z https://www.scidb.cn/oai

10.57760/sciencedb.43831 2026-07-28T17:18:50Z

2026-07-28 Distribution Network Fault Simulation Dataset for Novel Power Systems doi:10.57760/sciencedb.43831 en 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. 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. distribution network; fault recognition; IEEE 33-bus Gefei Duan Meili Rao PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset Science Data Bank