Description du projet
Mesurer les performances de charge, prévoir la production des éoliennes
Les éoliennes sont de plus en plus grandes et hautes. Et plus elles sont grandes, plus les extrémités des pales sont affectées par les turbulences de l’écoulement atmosphérique. Les ingénieurs doivent pouvoir mesurer les performances de charge et prévoir la production afin de procéder aux optimisations nécessaires à l’amélioration des performances. Dans ce contexte, le projet FLOW, financé par l’UE, développera de nouvelles méthodes de prévision pour les statistiques de production et les performances de charge des systèmes éoliens en mer et terrestres modernes à l’échelle du GW et d’une hauteur de 400 mètres. Il permettra d’améliorer notre connaissance de la physique des écoulements atmosphériques et des interactions entre les parcs éoliens (micro-échelle) et les processus à grande échelle (méso-échelle) tels que: le blocage global du parc éolien, l’interaction entre les parcs éoliens et la turbulence topographique et de sillage sur un terrain complexe. FLOW développera et validera des outils de simulation basés sur ces principes.
Objectif
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. FLOW’s 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.
Champ scientifique
- natural sciencescomputer and information sciencesdatabases
- social scienceseconomics and businesseconomicsproduction economicsproductivity
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energywind power
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencessoftwaresoftware applicationssimulation software
Programme(s)
Régime de financement
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinateur
2800 Kongens Lyngby
Danemark