Dataset for Electrical Line Fault Detection & Classification

The dataset consists of four cases (TL-1 to TL-4), each representing a distinct configuration of a three-phase distributed transmission line system simulated for both fault detection and fault classification.<b>Transmission Line Configurations</b><b>TL-1:</b><br>Comprised of one generating unit and one RLC load representing a distributed high-voltage transmission line (200 km) with faults at the load end.<b>TL-2:</b><br>Comprised of one generating unit and one RLC load representing a short-distance transmission line, used to study behavior under reduced propagation delay and impedance effects.<b>TL-3:</b><br>Comprised of two generating units and three RLC loads, representing a distributed high-voltage long transmission line (200 km) with faults at the load end.<b>TL-4:</b><br>Comprised of two generating units and three RLC loads, representing a distributed high-voltage long transmission line (200 km) with faults at the source end.Each case includes three-phase voltage and current waveform<b>s</b> under normal and faulted operating conditions.<b>Fault Detection Label</b>To indicate whether the system is under a fault condition:<code>1</code> → <b>No Fault</b><code>2</code> → <b>Fault Present</b><b>Fault Classification Labels</b>The detailed fault types correspond to the following numeric codes :CodeFault TypeDescription1NFNo Fault2ABCThree-phase fault3ABGDouble line-to-ground fault (A-B-Ground)4BCGDouble line-to-ground fault (B-C-Ground)5ACGDouble line-to-ground fault (A-C-Ground)6ABLine-to-line fault (A-B)7BCLine-to-line fault (B-C)8CALine-to-line fault (C-A)9AGSingle line-to-ground fault (A-Ground)10BGSingle line-to-ground fault (B-Ground)11CGSingle line-to-ground fault (C-Ground)<b>Structure</b>Each CSV file (e.g., <code>TL_1_fault_detection.csv</code>, <code>TL_2_fault_classification.csv</code>) contains:Time-series data of three-phase voltages and currents.A target column indicating fault detection (1 / 2) or fault classification (1 – 11).Together, these datasets provide a comprehensive basis for machine learning and deep learning studies on:Fault detection (binary classification).Fault type identification (multi-class classification).Fault location analysis in long vs. short, and source- vs. load-end fault scenarios.