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A heterogeneous distributed prediction model for wind-solar energy production

Project description

Predicting both wind and solar energy together

The EU is eager to go green, but integrating more solar and wind energy causes problems for current energy systems. This is because existing methods focus on predicting either wind or solar energy individually, neglecting joint forecasting. This gap arises from data heterogeneity and isolated data silos across wind farms and solar PV plants. With the support of the Marie Skłodowska-Curie Actions (MSCA) programme, the ANSWER project has emerged, aiming to develop a distributed prediction model for combined wind-solar energy production. By fusing models from various sources and using a two-level structure, ANSWER promises to bolster innovation and collaboration in renewable energy research. This initiative not only advances forecasting capabilities, but also aligns with the EU’s ambitious climate objectives.

Objective

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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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-MSCA-2022-PF-01

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Coordinator

DANMARKS TEKNISKE UNIVERSITET
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 230 774,40
Address
ANKER ENGELUNDS VEJ 101
2800 KONGENS LYNGBY
Denmark

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Region
Danmark Hovedstaden Københavns omegn
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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