Datasets
Standard Dataset
BESS-Set
- Citation Author(s):
-
Giovanni BattistaGaggero
University of GenovaAlessandroArmellinUniversity of Genova - Submitted by:
- Giovanni Battis...
- Last updated:
- Mon, 02/26/2024 - 08:48
- DOI:
- 10.21227/13qz-e261
- Data Format:
- License:
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- Keywords:
Abstract
Smart grids are nowadays featured by distributed energy resources, both renewables, traditional sources and storage systems. Generally, these components are characterized by different control technologies that interact with the generators through smart inverters. This exposes them to a variety of cyber threats. In this context, there is a need to develop datasets of attacks on these systems, in order to evaluate the risks and allow researchers to develop proper monitoring algorithms. This dataset addresses this need, presenting BESS-Set, an open-source dataset for cybersecurity analysis, of a Battery Energy Storage System (BESS). We also provide the Simulink model used to collect the dataset.
The aim is to help the scientific community to produce results in the field of cybersecurity of DERs; in particular, the dataset can be used to develop physics-based anomaly detection algorithms, that represent a promising field of research for enhancing the security of the Smart Grid
The zip folder contains both the dataset and the Simulink model. A README file describes the use of both.
Comments
If you use this model for scientific purposes, please cite in your paper:
- Giovanni Battista Gaggero, Alessandro Armellin, Giulio Ferro, Michela Robba, Paola Girdinio and Mario Marchese (2024). A Dataset for Cybersecurity Monitoring in a Battery Energy Storage System
- Gaggero, G. B., Caviglia, R., Armellin, A., Rossi, M., Girdinio, P., & Marchese, M. (2022). Detecting cyberattacks on electrical storage systems through neural network-based anomaly detection algorithm. Sensors, 22(10), 3933.