(University of Texas at Dallas) This dataset is part of the PowerBench benchmark suite designed to support machine learning research in resilient and secure power distribution networks. It includes one out of the three types of cyberattacks modeled on IEEE 34-bus, 123-bus, and 8500-node test feeders: EVCS Attacks. It includes adversarial manipulation of the charging behavior of grid-connected electric vehicle charging stations (EVCS) and is suitable for learning-based intrusion detection and localization of compromised EVCSs. Each attack dataset contains .pkl simulation files, .gml grid topology, and scenario metadata. All simulations were generated using OpenDSS via OpenDSSDirect.py.
Link to Dataset
PowerBench Dataset – Part 3: Cyber Attacks on EVCS
Date last updated: May 14, 2025