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| Funder | European Commission |
|---|---|
| Recipient Organization | Danmarks Tekniske Universitet |
| Country | Denmark |
| Start Date | Jan 01, 2023 |
| End Date | Dec 31, 2026 |
| Duration | 1,460 days |
| Number of Grantees | 11 |
| Roles | Participant; Coordinator |
| Data Source | European Commission |
| Grant ID | 101084205 |
The objective of the FLOW project is to develop new and innovative prediction methods for production statistics and load performance of modern GW-scale and 400-metre tall offshore and onshore wind energy systems.
Our project will develop more accurate methods as regards the present state of the art (SOTA) and with high confidence, thereby reducing uncertainties, increasing productivity and grid stability, lowering Levelised Cost of Energy (LCoE), while establishing an open-source knowledge hub that will benefit the entire renewable energy sector and enable joint optimization between developers and OEMs.
To reach these ambitions, FLOW will improve the knowledge of atmospheric flow physics and the interplay between wind farm (microscale) and large-scale (mesoscale) processes such as: wind farm global blockage, farm-farm interaction, and topographic and wake-added turbulence in complex terrain.
Based on these principles, FLOW will develop and validate simulation tools that can be readily adopted by industry to lower economic uncertainties and enhance system reliability and power production, with wide economic and societal impacts.
The proposed modelling framework will make extensive use of public experimental datasets to validate and train models within a FAIR data hub.
The New European Wind Atlas (NEWA) database is the foundation to grow this innovative open-source ecosystem that links experimental data, flow models, and validation datasets for benchmarking and training.
Industry adoption will be facilitated through a computationally efficient modular framework that allows scalability in a production environment.
FLOWs industrial partners, comprised of VESTAS, SGRE, GE, and EDF, will verify compliance with operational processes and test the framework using private datasets to extend the validation range and demonstrate the added value of our results at a wide European scale.
Dnv Denmark As; Vestas Wind Systems A/S; Electricite de France; Fraunhofer Gesellschaft Zur Forderung Der Angewandten Forschung Ev; Uppsala Universitet; Siemens Gamesa Renewable Energy Innovation & Technology S.L.; General Electric Renovables Espana; Danmarks Tekniske Universitet; Inova+ - Innovation Services, Sa; Carl Von Ossietzky Universitaet Oldenburg; Katholieke Universiteit Leuven
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