Descripción del proyecto
Ciencia de datos para la predicción de las fuentes de energía renovables (FER)
El desarrollo de la ciencia de datos, junto con el aumento de la cantidad de datos disponibles, brinda nuevas oportunidades para la predicción de las fuentes de energía renovables (FER). El proyecto Smart4RES, financiado con fondos europeos, se propone mejorar significativamente todo el marco y la cadena de valor de la predicción de FER mediante el desarrollo de la nueva generación de modelos de predicción de FER. El proyecto se dedicará a la mejora de la predicción meteorológica, y prestará especial atención a las necesidades del sector de las FER. Para ello, aprovechará predicciones meteorológicas de muy alta resolución y una amplia gama de datos de diferentes áreas geográficas y fuentes, respetando las limitaciones de privacidad y confidencialidad. Los objetivos de Smart4RES incluyen proporcionar predicciones extraordinariamente precisas que supongan mayores beneficios cuando se utilicen en aplicaciones como la gestión del almacenamiento, y que respalden el funcionamiento de la red y la participación de las FER en los mercados de la electricidad.
Objetivo
The Smart4RES project aims to bring substantial performance improvements to the whole model and value chain in renewable energy (RES) forecasting, with particular emphasis placed on optimizing synergies with storage and to support power system operation and participation in electricity markets. For that, it concentrates on a number of disruptive proposals to support ambitious objectives for the future of renewable energy forecasting. This is thought of in a context with steady increase in the quantity of data being collected and computational capabilities. And, this comes in combination with recent advances in data science and approaches to meteorological forecasting. Smart4RES concentrates on novel developments towards very high-resolution and dedicated weather forecasting solutions. It makes optimal use of varied and distributed sources of data e.g. remote sensing (sky imagers, satellites, etc), power and meteorological measurements, as well as high-resolution weather forecasts, to yield high-quality and seamless approaches to renewable energy forecasting. The project accommodates the fact that all these sources of data are distributed geographically and in terms of ownership, with current restrictions preventing sharing. Novel alternative approaches are to be developed and evaluated to reach optimal forecast accuracy in that context, including distributed and privacy-preserving learning and forecasting methods, as well as the advent of platform-enabled data-markets, with associated pricing strategies. Smart4RES places a strong emphasis on maximizing the value from the use of forecasts in applications through advanced decision making and optimization approaches. This also goes through approaches to streamline the definition of new forecasting products balancing the complexity of forecast information and the need of forecast users. Focus is on developing models for applications involving storage, the provision of ancillary services, as well as market participation.
Ámbito científico
- natural sciencescomputer and information sciencesdata science
- natural sciencesearth and related environmental sciencesatmospheric sciencesmeteorology
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energy
- engineering and technologymechanical engineeringvehicle engineeringaerospace engineeringsatellite technology
- engineering and technologyenvironmental engineeringremote sensing
Palabras clave
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-LC-SC3-2019-ES-SCC
Régimen de financiación
RIA - Research and Innovation actionCoordinador
75272 Paris
Francia