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Artificial Intelligence-Driven Coordination Algorithms for Adaptive Fault Protection in Hybrid AC/DC Networks: Enhancing Grid Resilience and Blackout Prevention

Project description

AI-driven fault protection for hybrid AC/DC power systems

As power systems become more complex and less predictable, fault protection methods are struggling to keep pace. Supported by the Marie Skłodowska-Curie Actions programme, the Net-Zero project is developing an AI framework that can improve how faults are detected, classified and located in hybrid AC/DC power systems increasingly dominated by renewables and electric vehicles. It combines physics-informed neural networks with mathematical models of fault behaviour and validating them through real-time simulations. The project’s goal is to deliver more reliable, adaptive protection methods, along with open-access datasets and tools to support resilient, secure and efficient future energy networks. This will boost reliability of Europe’s clean energy transition.

Objective

The rapid integration of renewable energy, electric vehicles, and inverter-based resources is reshaping power systems into hybrid AC/DC networks. While these grids are central to Europe’s net-zero ambitions, their protection is increasingly uncertain. Conventional schemes rely on strong fault currents and synchronous machines, which are no longer dominant. As a result, today’s protection methods often fail to detect, classify, or locate faults accurately, exposing networks to instability and large-scale outages.
This research proposes an AI-driven adaptive fault protection framework tailored for hybrid integrated AC/DC networks. The research will combine advanced Physics-Informed Neural Networks (PINNs) with mathematically derived equations of the fault events to detect and classify faults quickly, even under converter-dominated and uncertain conditions. A dedicated fault database will be built to cover diverse operating scenarios, including disturbances from renewables and electric vehicles. Algorithms will be validated using real-time digital simulation, ensuring both novelty and practical applications.
Expected results include:
1. A unified modelling platform for hybrid AC/DC fault interactions.
2. Adaptive physics-based learning knowledge with formulated mathematical equations to reduce the data and improve the performances.
3. Open-access datasets and tools for researchers and system operators.
This research will advance fault protection beyond state-of-the-art to improve the resilience, reliability, and cyber-physical security of future energy networks to avoid blackouts. The outcomes will directly support Europe’s clean energy transition, digitalisation agenda, and the integration of renewables and e-mobility. The fellowship will also strengthen the researcher’s expertise at the intersection of power systems, artificial intelligence, and energy security, enhancing career prospects while delivering solutions of high value to academia, industry, and society.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

UNIVERSITY OF GLASGOW
Net EU contribution
€ 276 187,92
Address
UNIVERSITY AVENUE
G12 8QQ Glasgow
United Kingdom
Region
Scotland West Central Scotland Glasgow City
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data