RESPONDENT
Financiado
Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NE...
Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT
Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT.
Renewable energy sources (RES) play a major role to the EU’s aspiration to transform to a climate-neutral economy. Their integrati...
Renewable Energy Sources Power FOrecasting and SyNchronisation for Smart GriD NEtworks MaNagemenT.
Renewable energy sources (RES) play a major role to the EU’s aspiration to transform to a climate-neutral economy. Their integration into the power grid is pivotal to the green transition and to the decarbonisation of the energy sector. However, as the most commonly used RES (solar, wind and hydropower) are also weather-dependent, their power generation capacity varies according to the local microclimatic conditions. This power production variability makes RES difficult to integrate into the power grid and to provide seamless, stable and secure amounts of power. On the other hand, power demand also affects the power grid operation, since there must always be a supply/demand balance in the power grid. Grid power imbalances can cause frequency fluctuations and other unwanted transient phenomena, which can compromise grid stability and operation. For that matter, advanced grid monitoring techniques have been developed, employing phasor measurement units (PMUs) to measure the electrical signals in a precise and synchronised way, based on a reliable timing reference. Yet, currently, no Galileo-based applications on PMU timing exist.
In the above framework, RESPONDENT comes to address the challenges of RES power generation forecasting, demand forecasting and smart power grid monitoring and supply/demand balancing. An AI/ML RES power generation forecasting algorithm is proposed, exploiting both Copernicus EO and site-specific weather data, along with renewable energy power conversion models. Furthermore, an AI/ML – multiphysics model for power demand of certain communities is also developed. Lastly, RESPONDENT will build a Galileo-enabled PMU and develop a monitoring module, in order to test and verify the advantages offered from the Galileo timing and synchronization services in smart grid monitoring, power balancing and overall operation.
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Duración del proyecto: 30 meses
Fecha Inicio: 2022-10-17
Fecha Fin: 2025-04-30
Fecha Fin: 2025-04-30
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-10-17
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
3M€
Líder del proyecto
FUTURE INTELLIGENCE EREVNA TILEPIKINONIAKON K...
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
321.25K€ |
Participante
227.50K€ |
Participante