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| Funder | European Commission |
|---|---|
| Recipient Organization | Imperial College of Science Technology and Medicine |
| Country | United Kingdom |
| Start Date | Oct 01, 2021 |
| End Date | Sep 30, 2023 |
| Duration | 729 days |
| Number of Grantees | 1 |
| Roles | Coordinator |
| Data Source | European Commission |
| Grant ID | 101026657 |
The data manipulation and disruption in the energy service and control process will damage the stable and secure operation of the microgrid (MG) systems. This proposal, cyber resilience of MGs (CRMG), investigates this problem from the system and control perspective.
In particular, the MGs with distributed secondary control challenged by communication latency and denial-of-service (DoS) attacks will be studied. The objective is to provide holistic analysis and countermeasures for MGs under this cyber-attack scenario.
The system model will be developed and analysed, while a model-based resilient framework to mitigate the influence of cyber-attacks will be provided.
Besides, a data-driven cyber-resilient control based on deep reinforcement learning (DRL) will be proposed to provide online optimal control of MGs under unknown attack scenarios.
The controller hardware-in-the-loop (HIL) experiment will be conducted to provide a realistic validation of the proposed method.The CRMG project will bridge the research limitations and provide solutions for cyber-resilience enhancement of MGs.
The proposed research is important and timely, as the cyber-resilience of the electricity grid is an emerging and urgent concern for many European countries.
The rapid development of renewable energy and IoT technologies transform the traditional power systems into distributed power and energy systems.
The analysis and countermeasures of MGs under cyber-attacks will be investigated from system and control perspective, which can create both scientific and practical values.
A software package with the proposed control tools will be provided, which includes a resilient framework to protect the MG from communication malfunctions by attackers, and a data-driven controller to enhance the system resilience.
The research outcome would contribute to the cyber-resilience of the electricity grid and future MG development in Europe.
Imperial College of Science Technology and Medicine
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