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CORDIS

hybrid MOdel-Based optImal DesIgn and Control of energy systems​

Obiettivo

Energy systems are evolving into highly interconnected multi-carrier networks spanning individual processes and large-scale infrastructures. As complexity increases, model-based optimisation becomes essential for designing and operating such systems under dynamic and uncertain conditions. Physics-based models offer interpretability and physical consistency but are often too computationally demanding for real-time or system-level use. Data-driven models, while efficient at capturing complex behaviours, require extensive datasets and often suffer from limited generalisation and physical coherence. Hybrid modelling approaches that blend physical knowledge with machine learning therefore represent a promising path.

However, experts in energy systems typically master physics and engineering principles but lack advanced machine-learning skills. Conversely, data-science specialists excel in AI techniques but often lack the domain knowledge required to handle energy systems and their operational constraints.

MOBIDIC bridges this gap by training a new generation of researchers who operate at the interface between energy systems engineering and AI. The 15 doctoral candidates advance methodologies for modelling, optimisation, uncertainty handling, and integration, each working on a use case at process, microgrid, or network scale. MOBIDIC ultimately delivers a coherent toolbox of solutions to support the design and control of future energy systems.

By being trained at the intersection of physics-based modelling, numerical simulation, data analytics, optimisation, and uncertainty-aware decision-making, competences rarely combined in traditional curricula, and by working with industrial datasets and operational constraints, the MOBIDIC cohort will be able to bridge fundamental multiphysics modelling and deployable digital tools, ensuring immediate employability in academia, industrial R&D, and system operations.

Campo scientifico (EuroSciVoc)

Parole chiave

Programma(i)

Argomento(i)

Meccanismo di finanziamento

HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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(si apre in una nuova finestra) HORIZON-MSCA-2025-DN-01

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Coordinatore

INSTITUT MINES-TELECOM
Contributo netto dell'UE
€ 629 338,32
Indirizzo
19 PLACE MARGUERITE PEREY
91120 Palaiseau
Francia
Regione
Ile-de-France Ile-de-France Essonne
Tipo di attività
Higher or Secondary Education Establishments
Collegamenti
Costo totale
Nessun dato

Partecipanti (8)

Partner (4)