Dataset for Transient Stability Assessment of IEEE 39-Bus System

This dataset contains 50 features and was generated through 12,852 time-domain simulations performed on the IEEE New England 39 bus system test case using DIgSILENT PowerFactory and Python automation. The simulations span diverse operating conditions by varying the generation/load profile from 80% to 120% in 5% increments. For each condition, three-phase short-circuit faults were applied at seven distinct locations (0%, 10%, 20%, 50%, 80%, 90%, 100%) along all transmission lines, with fault clearing times ranging from 0.1s to 0.3s.

Key features captured for each of the 10 generators (G02 is the reference machine) include:

P in MW - Active Power
ut in p.u. - Terminal Voltage
ie in p.u. - Excitation Current
xspeed in p.u. - Rotor Speed
firel in deg - Rotor Angle (relative to G02)

Simulations lasted 10 seconds to ensure accurate transient stability assessment. Post-fault data was sampled every 0.01s from fault clearance up to 0.6s afterward, labeling the stability state as 1 (stable) or 0 (unstable). The dataset generation process took 5,840 seconds. The dataset exhibits a class imbalance, with 42% of cases belonging to the unstable class. All simulation data were exported to .csv files and subsequently unified into a single pickle file (tsa_data.pkl).

Helper scripts are provided:

dataset_loader.py: Includes the load_tsa_data function to load the dataset.
usage.py: Demonstrates how to use the loader module.

This dataset serves as a comprehensive foundation for machine learning applications in transient stability assessment (TSA), offering insights into system behavior under dynamic conditions.