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AHEAD

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AI informed Holistic EVs integration Approaches for Distribution grids

The AHEAD (AI-informed Holistic Electric Vehicles Integration Approaches for Distribution Grids) project will create a simulation environment capable of predicting the most convenient location to place the electric vehicle (EV) ch... see more

31/05/2028

unknown leader

13M€

Project Budget: 13M€

Project leader unknown leader

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 25 Participantes

Financing granted El organismo HORIZON EUROPE notifico la concesión del proyecto The day 2024-05-27

HORIZON-CL5-2023-D3-03-01: Increasing the efficiency of innova... Expected Outcome:Projects are expected to develop further the harvesting of renewable energy in area...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Private Information

No hay información privada compartida para este proyecto. Habla con el coordinador.

25 Participantes

EEM EMPRESA DE ELECTRICIDADE...

UNIVERSITETI POLITEKNIK I TI...

ENERGINET

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Project duration: 48 months Date Start: 2024-05-27
End date: 2028-05-31

Project leader unknown leader

Project Budget 13M€

participation deadline Sin fecha límite de participación.

Project description The AHEAD (AI-informed Holistic Electric Vehicles Integration Approaches for Distribution Grids) project will create a simulation environment capable of predicting the most convenient location to place the electric vehicle (EV) charging stations and optimise both the usage of the power grid resources, and the charging stations located in urban and rural areas. This simulation environment will exploit the unique features of currently available AI models and include two layers: the spatial mapping one (placing the chargers where the people need them to be), and the power grid one (placing the chargers where the grid can support them). Innovative smart charging algorithms will be designed and tested in the model, to minimise the impact of EV charging pools on the network, and ensure the consumers have economic benefits. Moreover, these smart charging algorithms will be tested in three demonstration sites, dedicated to assessing the technical and economic feasibility of smart charging light and heavy-duty EVs, and boats. To this end, AHEAD gathered relevant partners from all the EV value-chain: technology providers who want to test their equipment in the real world, grid operators, who want to optimise the usage of the grid resources and mitigate the EV charging impact, and research institutions, who aim at advancing the knowledge on the topic and producing value for society. Particular attention is going to be placed on the user experience and cybersecurity part of the demonstrators, with specific partners who focus their efforts on understanding how to minimize the impact of smart charging on the user experience and on creating a model to represent cyber-attacks on the chargers to suggest efficient defensive mechanisms for system protection.

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