SOURCE-LINKED INTELLIGENCE
Multi-timescale Reinforcement Security on Cyber-Physical Smart Grids: Design, Monitoring, and Operation
urity on Cyber-Physical Smart Grids (MRSSG), proposes a novel three-tier security framework spanning long-, mid-, and short-term timescales. At the cyber level, the project will design spatiotemporal deep learning algorithms to detect heterogeneous attacks—including stealth, denial-of-service, replay, and false data injection—by capturing both dynamic power flow variations and network topology features. At the operational level, distributed attack-resilient control with adaptive laws will be developed to mitigate real-time disturbances and preserve reliable grid operations without reliance on centralized structures. At the physical level, a canonical self-disciplined stabilization controller will be established to guarantee large-signal stability across diverse DER converters, enabling autonomous plug-and-play resilience without disclosing sensitive system parameters. By addressing critical knowledge gaps in multi-timescale detection, mitigation, and stabilization, MRSSG will strengthen the security and reliability of European smart grids under extensive cyber-physical risks. The out
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 260347.92
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T04:21:15.460Z. This is not the publication date.