Molecules to Circular Energy Generation at Scale

Informazioni relative al progetto

MoCEGS

ID dell’accordo di sovvenzione: 101064585

DOI

10.3030/101064585

Progetto chiuso

Data della firma CE 7 Giugno 2022

Data di avvio 1 Ottobre 2022

Data di completamento 28 Febbraio 2025

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 203 464,32

Coordinato da

STICHTING RADBOUD UNIVERSITEIT
Netherlands

Periodic Reporting for period 1 - MoCEGS (Molecules to Circular Energy Generation at Scale)

Periodo di rendicontazione: 2022-10-01 al 2025-02-28

Sintesi del contesto e degli obiettivi generali del progetto

The MoCEGS project uses a data-driven approach in providing a more circular and reliable multi-level energy planning framework for EU. In today's integrated global energy landscape, the connection between domestic energy planning and international energy planning and trading is essential. This highlights the essentially of macro-level considerations within the region. Furthermore, meso-level integration of energy systems with national energy planning is a crucial task that determines the future of a nation's energy landscape in terms of economic and environmental sustainability. Exploitation of knowledge at meso-level allows for more rapid and efficient reconciliation actions in energy systems. The micro-level considerations of how chemical fundamental impact energy systems also connects the complexity between molecules and systems. The needs to connect insights of different modelling level (micro to macro) is crucial in understanding EU's energy infrastructure, and the potential that it brings. the MoCEGS project capitalize chemometrics and process network analysis in tackling this interlinked energy challenge.

Lavoro eseguito dall’inizio del progetto fino alla fine del periodo coperto dalla relazione e principali risultati finora ottenuti

The MoCEGS project has successfully performed research in various parts of energy circularity. On the macro-scale, the MoCEGS project has provided a large-scale data reconciliation algorithm, domain adaptation zero-shot learning in sequence (DAZLS) to allow high resolution energy data for energy planning. On the meso-scale, various retrofit algorithms were developed such as graph theory based retrofit algorithm, automation of P-graph framework, multi-period multi-objective graph theory planning, Shapley-Shubik based superstructure modelling etc. These fundamental development allows for advanced planning for the circular economy. Furthermore, a digital twin based on such fundamental understanding and the combination of graph theory development and high resolution energy data within EU27 (considering neighbouring countries was developed). This digital twin may assist policy making in high time resolution for energy and circularity in Europe. Furthermore, the MoCEGS project also explores some promising technologies at the micro-scale, this is a part of wider collaborative research efforts which includes co-pyrolysis technologies, waste oil technologies, single atom catalysts, etc.

Progressi oltre lo stato dell’arte e potenziale impatto previsto (incluso l’impatto socioeconomico e le implicazioni sociali più ampie del progetto fino ad ora)

In the MoCEGS project, large-scale data reconciliation for energy data was proposed via domain adaptation with zero-shot learning, which is a new development of methodology which was demonstrated for real-world substations. Furthermore, the project also promotes further research of graph theory (P-graph) for large-scale circularity planning. Via such development, a digital twin for Europe's energy planning is develop to optimize regional energy flow in high temporal resolution, and being updatable in short-time scale.

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