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Multi-level approach for the up-scaling of ultra high temperature energy storage and conversion

Project description

Innovative modelling methodology for future energy storage

The rapid transition to renewable energy sources and their integration necessitates the development of novel and improved energy storage and conversion solutions. However, this progress also calls for innovative approaches in modelling and upscaling these high-temperature storage and conversion systems. With the support of the Marie Skłodowska-Curie Actions programme, the SHINE project will develop a comprehensive numerical methodology to enhance cost-efficient and sustainable energy production and storage at ultra-high temperatures. To achieve this goal, the project will use in-house code along with commercial software, integrating multi-physics models, artificial intelligence, and validation solutions. The ultimate outcome will be instrumental in upscaling efforts for renewable energy storage solutions, while also providing interdisciplinary expertise to the project team members.

Objective

The growing interest for the integration of renewable energy sources, as solar energy, in the global energy mix, increases the need of developing of new methods that will assist on the up-scaling and demonstration of efficient energy storage and conversion technologies. In this regard, advanced modelling methods can be an indispensable tool towards this effort. SHINE aims at developing a holistic numerical methodology – by using in-house codes coupled with commercial software– that will boost the cost-efficient and sustainable electricity production and storage at unprecedented ultra-high temperatures (> 1000 oC). The stepping stone for the modelling activities will be a compact latent heat thermophotovoltaic device recently patented in UPM targeted for energy storage and production at ultra-high temperatures. The core components in such a device are the latent heat thermal energy storage system and the thermophotovoltaic device. The modelling methodology will integrate rigorous multi-physics models (fluid dynamics, heat transfer and optoelectronics) targeted at a component level into a reduced order model (ROM) by using multi-variable polynomial functions. Key in the proposed methodology is the validation of the rigorous models through in-house measurements at ultra-high temperatures that will be undertaken at the host organisation. Key as well is the production of the multi-variable polynomials through artificial neural networks that will be undetaken during the Secondment phase. The whole project is highly interdisciplinary because it integrates highly interrelated diverse disciplines (physics, engineering, optoelectronics, thermo- and fluid-dynamics, photovoltaics and thermal storage, and artificial intelligence-AI) as well as know-how from experiments is a single holistic approach. Once developed the ROM will be used to predict the whole system's performance as being part of a solar-to-heat-to-power and a power-to-heat-to-power concepts.

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

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-PF-01

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Coordinator

UNIVERSIDAD POLITECNICA DE MADRID
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 165 312,96
Address
CALLE RAMIRO DE MAEZTU 7 EDIFICIO RECTORADO
28040 Madrid
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Higher or Secondary Education Establishments
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Total cost

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