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ANSWER

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A heterogeneous distributed prediction model for wind-solar energy production

To achieve the European Union's green transition goal, solar photovoltaic (PV) and wind energy are widely adopted, which pose great challenges to the reliability and safety of existing energy systems. The state-of-the-art methods... ver más

31/01/2026

TECHNICAL UNIVERSI...

231K€

Presupuesto del proyecto: 231K€

Líder del proyecto

DANMARKS TEKNISKE UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-07-13

HORIZON-MSCA-2022-PF-01-01: MSCA Postdoctoral Fellowships 2022 ExpectedOutcome:

I+D

Cerrada hace 2 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

1 Participantes

TECHNICAL UNIVERSITY OF DENM...

230.77K€ | Lider

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Duración del proyecto: 30 meses Fecha Inicio: 2023-07-13
Fecha Fin: 2026-01-31

Líder del proyecto

DANMARKS TEKNISKE UNIVERSITET No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 231K€

Descripción del proyecto To achieve the European Union's green transition goal, solar photovoltaic (PV) and wind energy are widely adopted, which pose great challenges to the reliability and safety of existing energy systems. The state-of-the-art methods mainly concentrate on the prediction of a single energy form, either wind or solar. There is limited research on joint forecasting for wind-solar energy due to the challenges of data heterogeneity and data silos for different wind farms and solar PV plants. This project develops a heterogeneous distributed prediction model for joint wind-solar energy production (ANSWER), based on heterogeneous data sources at different wind farms and solar PV plants. A global model will be generated by the fusion of heterogeneous models from all wind farms and solar PV plants, coordinated by a central server. To achieve the research goal, this project proposes four work packages, including 1) development of model specifications, which use a two-level structure:client-level and server-level, 2) development of a generic seamless forecasting client model that supports multiple time-scale and -horizon prediction, 3) model aggregatioin for heterogeneous client models, and 4) model deployment and evaluation in a living lab for the robustness of the proposed ANSWER model. This proposal ANSWER specifies the resources needed for this project, including the quality and capacity of the host university, mentors, data, and experimental facilities. This project will enhance the scientific skills and innovation capability, expand research horizons, and establish research collaborations of the applicant. A two-way knowledge transfer approach in energy big data, distributed modeling and energy system analysis is proposed to ensure benefits between the applicant and the host university. The proposed model will make a significant contribution to the state of the art in renewable energy (wind and solar) production forecasting and the EU climate goals.

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