Imagine trying to build a giant sail in the sky without knowing exactly how the wind gusts at different heights. This project creates a digital map and a set of tools to predict those wind patterns up to 1km high. It helps engineers build wind turbines and flying energy kites that are stronger and more efficient without wasting expensive materials.
Wind energy systems operating at high altitudes face unpredictable wind conditions that lead to over-engineering and wasted materials. Current tools lack the accuracy to predict unsteady inflow, resulting in inefficient plant layouts and higher costs.
An open-source tool chain and data hub for predicting wind loads and energy yield. This includes kite-as-a-sensor algorithms and high-fidelity simulation repositories.
If you are a wind farm developer dealing with unpredictable energy yields in complex terrains — this project developed a validated tool chain that increases plant efficiency and reduces material costs through less conservative design.
If you are an AWES manufacturer dealing with structural loads at altitudes above the surface layer — this project developed kite-as-a-sensor algorithms and inflow repositories that improve device durability.
If you are a consultant dealing with the certification of offshore wind arrays — this project developed a data hub and multiscale models to accurately assess loading and yield for individual and arrays of generators.
By providing more accurate load assessments, the tools allow for less conservative designs, which directly reduces the amount of material needed for construction.
Yes, the project aims to integrate tools usable in both academic and industrial contexts for individual turbines and large arrays of wind power generators.
Based on available project data, the tool chain is based on an open-source platform.
It uses a knowledge and data hub that allows users to access measurement and simulation data to perform site-specific analysis at any location.
The project is active from 2022-10-01 and is scheduled to conclude by 2026-09-30.
The consortium is well-balanced for commercial translation, featuring 12 partners across 6 countries. With an industry ratio of 42% (including 5 industrial partners and 4 SMEs), there is a strong bridge between the 5 participating universities and the actual market needs of the wind energy sector.
Contact the Technische Universiteit Delft (HES department)
Contact us to explore the open-source tool chain for your wind site analysis.
