Tutorial 1 – Data Sharing & Cybersecurity in Smart Grids
Aim of the tutorial
The purpose of the tutorial is to present how do deal with privacy issues in smart distribution grids, regarding both data sharing in big data analytics and the cybersecurity aspects.
The first part of this tutorial will be dedicated on how to break the data barrier and promote data sharing. After giving a broad overview of new technologies for data sharing (blockchains, noise-injection techniques, etc.), efforts will be devoted to two aspects, i.e., i) privacy-preserving data analytical methods, and ii) data pricing or valuation approaches.
To that end, the relevant statistical methods and data-driven approaches in distribution systems will be introduced, along with recent advances in privacy-preserving settings (e.g., federated learning, differential privacy, etc.) to enable data sharing.
In complement, the data trading mechanisms and data value quantification methods in power and energy industries will be summarized and compared.
The second part of the tutorial is focused on the discussion of cybersecurity issues and techniques related to SCADA networks, intrusion detection, and the security of end and legacy devices. The objective is not only to understand the critical risks and technologies used today, but also to foresee innovations that can improve the cybersecurity and resilience of smart distribution networks of the future.
- Allyson Bessani (University of Lisbon, Portugal)
- Jean-François Toubeau (KULeuven, Belgium)
- Yi Wang (University of Hong Kong, Hong Kong)