AHEAD | AI-informed Holistic EVs integration Approaches for Distribution grids

Summary
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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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/101160665
Start date: 01-06-2024
End date: 31-05-2028
Total budget - Public funding: 12 845 000,00 Euro - 10 997 750,00 Euro
Cordis data

Original 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.

Status

SIGNED

Call topic

HORIZON-CL5-2023-D3-03-03

Update Date

16-09-2024
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Horizon Europe
HORIZON.2 Global Challenges and European Industrial Competitiveness
HORIZON.2.5 Climate, Energy and Mobility
HORIZON.2.5.3 Energy Systems and Grids
HORIZON-CL5-2023-D3-03
HORIZON-CL5-2023-D3-03-03 System approach for grid planning and upgrade in support of a dominant electric mobility (vehicles and vessels) using AI tools