Introducing our new Turbine Performance Quantification Collaboration

In the first half of 2023, we successfully completed the Power Curve Modelling Benchmarking Challenge as part of our Data-Driven Turbine Performance Analysis space with Professor Yu Ding from Georgia Tech, author of the Data Science for Wind Energy book. The results of this challenge will be presented in March 2024 at the Wind Europe Annual Event in Bilbao. In the meantime, we are happy to announce our new Turbine Performance Quantification Collaboration within the same space, which starts in January 2024!

While it is highly important to develop new technologies for better designs/configurations/controls or materials/manufacturing of wind turbine blades and drive trains, an equally critical question is how one can be certain that a newly proposed technology could deliver the proposed/promised improvement in energy capture in a real-world, commercial operation environment, measured in terms of the percentage change in AEP.  It is not exaggerating to say that  quantifying a wind turbine's holistic, system-level power production efficiency in its commercial operating condition is one of the keys to reducing the levelized cost for energy of wind energy. 

With this collaboration, we would like to tackle the long-overdue question of how to best to quantify a wind turbine's holistic, system-level power production efficiency and detect a turbine's performance change under its commercial operating conditions.  Through our collective effort, we hope to produce better understandings of the issue, as well as methods and/or tools of a higher degree of credibility.

In this collaboration, we will use the Turbine Upgrade Dataset released through the publication of the book, Data Science for Wind Energy, to discuss, test, develop, and refine methods for the question posed above, i.e., how to quantify a wind turbine's holistic, system-level power production efficiency and detect a turbine's performance change under its commercial operating conditions.  

Join the WeDoWind Data-Driven Turbine Performance Analysis space by selecting it in the form at the link below. You will then automatically receive an invitation to the launch webinar at 15:00 CET on Monday, January 8th, 2024. If you are already part of the Data-Driven Turbine Performance Analysis space, you should have already received the Zoom invite. Even if you miss the launch webinar, a recording will be made available and you can join at any time!

WeDoWind is a framework for bringing asset owners together with researchers and model developers in a "win-win" situation, whereby asset owners get easy access to state-of-the-art data analytics and model developers get access to relevant asset data to train and validate their models.

It is based on industry-provided challenges, which are coordinated through digital spaces. Multiple digital spaces form branch-specific ecosystems of collaborators.

This space offers a safe discussion forum for the open data science solutions offered in connection with the book “Data Science for Wind Energy” and the author’s research team at Georgia Tech.

Get in touch with us here!