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ISOBAR

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Artificial Intelligence Solutions to Meteo Based DCB Imbalances for Network Oper...

Artificial Intelligence Solutions to Meteo Based DCB Imbalances for Network Operations Planning ISOBAR aims at the provision of a service- and AI-based Network Operations Plan, by integrating enhanced convective weather forecasts for predicting imbalances between capacity and demand and exploiting AI to select mitigation mea... see more

30/11/2022

CENTRO DE REFERENC...

3M€

Project Budget: 3M€

Project leader

CENTRO DE REFERENCIA INVESTIGACION DESARROLLO... La creacion, desarrollo y explotacion de un centro para la identificacion, analisis y evaluacion de conceptos, procedimientos y sistemas de...

TRL 4-5 | 4M€

PARTICIPATION DEPralty Sin fecha límite de participación.

Ver 11 Participantes

Financing granted El organismo H2020 notifico la concesión del proyecto The day 2022-11-30

SESAR-ER4-16-2019: Innovation in Network Management Specific Challenge:This topic covers innovative network management application concepts that aim at...

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Cerrada does 5 years

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characteristics of the participant

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.

11 Participantes

CENTRO DE REFERENCIA INVESTI...

315.75K€ | Leader

UC3M

214.41K€ | participant

IQC GmbH

241.76K€ | participant

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Project duration: 31 months Date Start: 2020-04-17
End date: 2022-11-30

Project leader

CENTRO DE REFERENCIA INVESTIGACION DESARROLLO... La creacion, desarrollo y explotacion de un centro para la identificacion, analisis y evaluacion de conceptos, procedimientos y sistemas de...

TRL 4-5 | 4M€

Project Budget 3M€

participation deadline Sin fecha límite de participación.

Project description ISOBAR aims at the provision of a service- and AI-based Network Operations Plan, by integrating enhanced convective weather forecasts for predicting imbalances between capacity and demand and exploiting AI to select mitigation measures at local and network level in a collaborative ATFCM operations paradigm. To achieve this vision, four objectives are set: a) Reinforce collaborative ATFCM processes at pre-tactical and tactical levels into the LTM (local) and Network Management (network) roles integrating dynamic weather cells. b) Characterisation of demand and capacity imbalances at pre-tactical level [-1D, -30min] depending on the input of probabilistic weather cells by using applied AI methods and ATM and weather data integration. c) User-driven mitigation plan considering AUs priorities (and fluctuations in demand based on weather forecasts) and predicted effectiveness of ATFCM regulations, considering flow constraints and network effects. d) Develop an operational and technical roadmap for the integration of ancillary services (providing AI-based hotspot detection and adaptative mitigation measures) into the NM platform, by defining interfaces, functional and performance requirements.

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