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HORIZON-CL5-2023-D3-03-03
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
Expected Outcome:Project results are expected to contribute of the following expected outcomes:
Sólo fondo perdido 0 €
Europeo
Esta convocatoria está cerrada Esta línea ya está cerrada por lo que no puedes aplicar. Cerró el pasado día 10-10-2023.
Se espera una próxima convocatoria para esta ayuda, aún no está clara la fecha exacta de inicio de convocatoria.
Hace más de 17 mes(es) del cierre y aún no tenemos información sobre los proyectos financiados, no parece que se vaya a publicar esta información.
Presentación: Consorcio Consorcio: Esta ayuda está diseñada para aplicar a ella en formato consorcio.
Número mínimo de participantes.
Esta ayuda financia Proyectos:

Expected Outcome:Project results are expected to contribute of the following expected outcomes:

AI-based prediction of most convenient locations that optimize grid resources and upgrades around recharging pools for EVs and electric HDVs.Developing of spatial mapping models and software tool for location decision-making with a comprehensive focus, including major highways, industrial zones (depot charging), urban nodes (e.g., for overnight charging) and less-densely populated areas.Simulation, analysis, design, test and demonstration of smart and bidirectional charging schemes and their integration into flexibility markets that allow to minimise the impact on grid planning and connection of high-power recharging pools for recharging EVs, and especially HDVs on more cost-intensive locations, and that ensure benefits to consumers based on smart charging energy service models.Exploration of the impact of different charging methods, including cable-charging, wireless charging and electric road systems covering either catenary as inductive coils embedded in the road.Analysis, design, testing and developing of a cyber security model that can simulate and accurately represent... ver más

Expected Outcome:Project results are expected to contribute of the following expected outcomes:

AI-based prediction of most convenient locations that optimize grid resources and upgrades around recharging pools for EVs and electric HDVs.Developing of spatial mapping models and software tool for location decision-making with a comprehensive focus, including major highways, industrial zones (depot charging), urban nodes (e.g., for overnight charging) and less-densely populated areas.Simulation, analysis, design, test and demonstration of smart and bidirectional charging schemes and their integration into flexibility markets that allow to minimise the impact on grid planning and connection of high-power recharging pools for recharging EVs, and especially HDVs on more cost-intensive locations, and that ensure benefits to consumers based on smart charging energy service models.Exploration of the impact of different charging methods, including cable-charging, wireless charging and electric road systems covering either catenary as inductive coils embedded in the road.Analysis, design, testing and developing of a cyber security model that can simulate and accurately represent attack propagation from recharging infrastructure entry vectors, informing the development of efficient strategies and lines of defence to mitigate these vulnerabilities for the different relevant stakeholders. Scope:The activities are expected to include at least the following aspects:

Definition and development of new AI-based tools to predict, estimate and plan the deployment and associated challenge for utilities (from an EV recharging ecosystem viewpoint - CPO, DSO and TSO) on how to deal with the increasing upcoming demand in numerous new locations, particularly during peak periods.Understanding on how to effectively deploy the required grid connection (and power) in less densely populated areas, exploring the impact of installation of batteries to expand the grid in combination with renewables.Development of a coherent energy system planning for electric mobility, considering both the needs and impact for recharging of EVs and onshore power supply of vessels in maritime ports and inland waterways.Development of new services for consumers (EV and HDV owners, leasers, etc.) based on smart charging that valorise the flexibility in the wholesale, home optimisation and/or grid services markets. Integration of smart charging services with flexibility from other devices (e.g. demand response) would be an added value for the project.There is an increasing risk for the occurrence of a scenario where EVs and/or recharging stations could be hacked simultaneously, causing a disruption to grid operations, propagating rapidly with dire consequences, such as blackouts and overall affection of the frequency stability of the grid. The project should bridge the gap between recharging infrastructure operators, EVs and the grid (DSOs, TSOs), identify existing weaknesses and risks for attack spread.The developed solutions should assess their environmental impact in particular with regards to their energy consumption. The selected projects are expected to contribute to the BRIDGE initiative[1], actively participate to its activities and allocate up to 2% of their budgets to that end. Additional contributions to the ‘Alliance for Internet of Things Innovation’ (AIOTI) and other relevant activities (e.g. clusters of digital projects and coordinating actions) might be considered, when relevant.

[1] https://www.h2020-bridge.eu/

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Temáticas Obligatorias del proyecto: Temática principal:

Características del consorcio

Ámbito Europeo : La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Tipo y tamaño de organizaciones: El diseño de consorcio necesario para la tramitación de esta ayuda necesita de:

Características del Proyecto

Requisitos de diseño: *Presupuesto para cada participante en el proyecto
Requisitos técnicos: Expected Outcome:Project results are expected to contribute of the following expected outcomes: Expected Outcome:Project results are expected to contribute of the following expected outcomes:
Capítulos financiables: Los capítulos de gastos financiables para esta línea son:
Personnel costs.
Subcontracting costs.
Purchase costs.
Other cost categories.
Indirect costs.
Madurez tecnológica: La tramitación de esta ayuda requiere de un nivel tecnológico mínimo en el proyecto de TRL 6:. Se cuenta con prototipos piloto capaces de desarrollar todas las funciones necesarias dentro de un sistema determinado, habiendo superado pruebas de factibilidad en condiciones de operación o funcionamiento real. + info.
TRL esperado:

Características de la financiación

Intensidad de la ayuda: Sólo fondo perdido + info
Fondo perdido:
Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar desde un 70% hasta un 100%.
The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities. The funding rate for IA projects is 70 % for profit-making legal entities and 100 % for non-profit legal entities.
Garantías:
No exige Garantías
No existen condiciones financieras para el beneficiario.

Información adicional de la convocatoria

Efecto incentivador: Esta ayuda no tiene efecto incentivador. + info.
Respuesta Organismo: Se calcula que aproximadamente, la respuesta del organismo una vez tramitada la ayuda es de:
Meses de respuesta:
Muy Competitiva:
No Competitiva Competitiva Muy Competitiva
No conocemos el presupuesto total de la línea
Minimis: Esta línea de financiación NO considera una “ayuda de minimis”. Puedes consultar la normativa aquí.

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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
en consorcio: Expected Outcome:Project results are expected to contribute of the following expected outcomes: AI-based prediction of most convenient loca...
Cerrada hace 1 año | Próxima convocatoria prevista para el mes de