H2020
Europeo
ExpectedOutcome: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 a...
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ExpectedOutcome: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.
Specific Topic Conditions:Activities are expected to achieve TRL 6-8 by the end of the project – see General Annex B.
[1]https://www.h2020-bridge.eu/
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Características del consorcio
:
La ayuda es de ámbito europeo, puede aplicar a esta linea cualquier empresa que forme parte de la Comunidad Europea.
Características del Proyecto
Características de la financiación
Para el presupuesto subvencionable la intensidad de la ayuda en formato fondo perdido podrá alcanzar desde un 70% hasta un 100%.
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