Cocoon: COoperative Cyber prOtectiON for modern power grids

computer screen cyber security
Alejandro Rojano, R&D Engineer at Cuerva
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Solving cyber security challenges in electric power systems

DatesSeptember 2023 - August 2026
Proyect websitewww.cyber-cocoon.eu
LeaderUniversity of Cyprus (Angelos Marnerides), Aristotle University of Thessaloniki (AUTH)
Reference101120221
Financing entity

Cocoon’s Project has received funding from the European Union´s Horizon Europe research and innovation programme under grant agreement No 101120221

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Context

The project focuses on addressing the issue of cybersecurity in Electric Power and Energy Systems (EPES) through an interdisciplinary approach.

The overall goal of the project is to provide a practical solution for cyber-physical systems in EPES by combining research in secure network systems with energy system engineering. This will enable compliance with the EU ACER NCCS requirements and the SGAM framework, benefiting various stakeholders such as energy communities, regional security centers, substations, and aggregators of distributed renewable energy sources (DRES) interacting with a Distribution System Operator (DSO). 

To tackle these challenges, cyber-physical protection mechanisms based on real-time data will be implemented. This includes cyber-physical anomaly diagnosis, vulnerability assessment and risk profiling, cyber threat mitigation, and reliable information exchange. An Early Warning System (EWS) and an Incident Reporting (IR) interface will be provided, accessible to operators through the "COCOON Toolset Dashboard (CTD)." These tools will enable interactive interfaces with visualizations of alarms, risk profiles, active vulnerabilities, and threat mitigation configuration parameters. 

Objetivos

  • Improve reliable information exchange among Transmission System Operators (TSOs), Distribution System Operators (DSOs), aggregators, and facilities of distributed renewable energy sources (DRES).
  • Develop a practical Early Warning System (EWS) that aids in collaborative cyber-physical protection and operator training in various energy system environments, including DRES generation, energy communities, and substation networks.
  • Enable real-time cyber-physical protection and enhance network stability by explicitly identifying vulnerabilities in operational technology (OT) used to control and monitor the network, in relation to information technology (IT).
  • Enable data-based detection of known and unknown (zero-day) threats in convergent IT/OT settings spanning operational and business functions in the electrical network entities.
  • Strengthen the resilience of diverse interactions between entities involved in network stability through Auxiliary Services (AS).

Cuerva´s role

In this project, Cuerva plays a crucial role as an aggregator of Distributed Renewable Energy Sources (DRES), closely collaborating with Distribution System Operators (DSOs). The project aims to demonstrate the success of this collaboration in four representative operational deployments, including the management of DRES by energy communities in partnership with DSOs. 

Additionally, algorithmic models will be implemented to enable verifiable orchestration of network-level control, monitoring, and measurements. An assessment of vulnerabilities, risk profiling, and cyber-physical anomaly diagnosis will be conducted, enabling effective threat mitigation in the electrical network. In summary, Cuerva plays an essential role in the successful implementation of cybersecurity measures in the context of DRES management and electrical network stability. 

About the author

Alejandro Rojano, R&D Engineer at Cuerva
Alejandro is a professional with a background in Physics who holds the position of R&D Engineer in the Innovation department. In addition to his role as an engineer managing projects, he is currently pursuing a PhD at the University of La Laguna in Tenerife. His research focuses on the design of the charging network infrastructure for future electric vehicles, with the aim of developing a methodology that can be applied in a way that can be extrapolated to different geographical locations.
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