Resilient & Secure Digital Distribution Grid

Domain #1
Sensitive infrastructure protection

Challenge 1.1. Development of cybersecurity solutions for sensitive infrastructure protection



Open Call #2 laureate

Description of the project

The electricity distribution grid is facing severe challenges due to the energy transition. A timely and accurate view of the current and future electrical behaviour of the electricity distribution grid is provided by the digital twin, which connects to heterogeneous IoT data sources. The resilience and security of the digital twin is essential, while challenged by the heterogeneous IoT connectivity and through zero-day attacks.

The RS2DG project will showcase the accurate and fast detection of faults and attacks on the digital twin and therefore will contribute to a smooth and secure energy transition. Major reliability and efficiency benefits will be demonstrated for the grid operator, for the operator of the digital twin which translate into the security and efficiency of the future electricity distribution grid.

Mid-term project update

The RS2DG project is assuring robustness of the digital twin of the electricity grid via novel methods based on machine learning.
project has identified two main usecases for anomaly and threat detection for the digital twin:
  • Missing data detection addressing the challenge of heterogeneous data collection for the digital twin with different update frequencies;
  • Identification of anomalies in values of energy measurements machine learning approaches will identify that unusual energy consumption data is provided by measurement devices; reasons for the latter can be wrong mountings of equipment (such as current transformers) or else malicious attacks on the measurement collection infrastructure.

The anomalies and attacks will be detected by a Resilience and Security component, which has been designed and implemented. A preliminary assessment of its integrated behavior has been obtained. The preliminary assessments demonstrate the potential of the solution to achieve a high true positive rate and to significantly reduce time to detection and effort for recovery from anomalous situations of the digital twin.

Project consortium

GridData GmbH
GridData GmbH
ResilTech S.R.L
ResilTech S.R.L