This repository contains data related to the IEEE 118-bus Cyber-Physical Power System (CPPS) for evaluating diagnostic methodologies in smart grid research.
The IEEE 118-bus CPPS is a widely-used benchmark system in smart grid research that integrates physical components (generators, transformers, loads, transmission lines) with cyber components (protective relays, voltage regulators, controllers). This interaction is crucial for system stability and reliable power delivery.
The data collection involves simulating various fault scenarios in the IEEE 118-bus CPPS using PowerFactory. Faults are categorized into:
- Load-Loss (LL)
- Generator Outage (GO)
- Generator Ground (GG)
Each fault type is simulated as follows:
- LL/GO Faults: A breaker disconnects the load or generator from the bus for 25 ms.
- GG Faults: Three-phase short-circuit faults are simulated between generation units and the ground.
Data is collected for 25 ms at a sampling rate of 10 kHz, resulting in 250 samples per scenario. The simulated fault scenarios include:
- 31 LL faults
- 19 GO faults
- 19 GG faults
- 1 normal operational state
Six datasets are constructed based on different Signal-to-Noise Ratio (SNR) and Fault Resistance (FR) values. Each dataset is detailed in the table below:
| Dataset | SNR (dB) | FR (Ω) | # Samples | # Features |
|---|---|---|---|---|
| data_1ohm_50db | 50 | 1 | 17,500 | 354 |
| data_1ohm_55db | 55 | 1 | 17,500 | 354 |
| data_1ohm_60db | 60 | 1 | 17,500 | 354 |
| data_10ohm_50db | 50 | 10 | 17,500 | 354 |
| data_10ohm_55db | 55 | 10 | 17,500 | 354 |
| data_10ohm_60db | 60 | 10 | 17,500 | 354 |
The features collected from each bus include:
- Voltage: 1 to 118
- Frequency: 119 to 236
- Phase Angle: 237 to 354
This results in a total of 354 features per dataset. Labels (from 1 to 70) are included in column 355.
The data provided in this repository supports the research findings detailed in the following paper:
Hassani, H., Hallaji, E., Razavi-Far, R. et al. Learning from high-dimensional cyber-physical data streams: a case of large-scale smart grid. Int. J. Mach. Learn. & Cyber. (2024). https://doi.org/10.1007/s13042-024-02365-3
Please cite this paper if you use the data in your research.
This project is licensed under the MIT License - see the LICENSE file for details.
For further information, please contact Hossein Hassani.