WeDoWind

📢 Do data analysts in your organisation or community still waste 80% of their time with data wrangling? Turn this 80% to 20% and transform your efficiency and boost your productivity by joining our new-look WeDoWind ecosystem at our launch event in January! 📢 The new-look WeDoWind expands on our current "challenge"-based platform, and helps you exploit the full value of data by: 👉 Connecting you with open data, code, lecture material, information models, best practices and guidelines for using and publishing code and data. 👉 Providing you with opportunities to develop code and reference methods collaboratively or in competition with each other, to co-create information models and to work on best practices and guidelines collaboratively. 👉 Connecting you with like-minded people, and potential project partners, employees or employers. Sign up for the launch webinar on Jan. 17th and find out more here: https://lnkd.in/e3RRVNfh #windeenergy #digitalisation #datasharing #wedowind OST – Eastern Switzerland University of Applied Sciences Departement Technik OST IET Institut für Energietechnik

Have you recently published wind energy data sets and want more people to access and use them? Or are you thinking about publishing some data but not sure the best way to do it? WeDoWind helps you make your data FAIR (Findable, Accessible, Interoperable and Resuable) and brings together teams of researchers and data scientists from around the world to solve "challenges" using your data. Use the power of the community to get the best solutions! Recent examples include: 👉 Development of fault detection methods using SCADA data from EDP Renewables with Sofia Ganilha 👉 Development of gearbox fault detection methods using SCADA data from WinJi with Dimitrios Anagnostos 👉 Comparison of power curve prediction methods using data from Cubico Sustainable Investments with Yu Ding 👉 Comparison of static yaw misaligment methods using data from Cubico Sustainable Investments with Charlie Plumley 👉 Development of structural health monitoring methods using vibration data from RTDT Laboratories AG with Imad Abdallah and Eleni Chatzi Find out more here: https://www.wedowind.ch/ Get in touch with Sarah Barber if you want to share data or create a WeDoWind challenge!! #fairdata #datasharing #collaboration #windenergy #digitalisation OST – Eastern Switzerland University of Applied Sciences Departement Technik OST IET Institut für Energietechnik

If you are into wind turbine control and want to test and develop methods for identifying controller settings from operational data, and get your efforts rewarded, then don't miss our EAWE Data Science Challenge 2024-2025, a collaboration with the European Academy of Wind Energy, OST – Eastern Switzerland University of Applied Sciences and Chalmers University of Technology! Last week we held November's monthly meeting this challenge, answering some questions about the data and the challenge requirements. The goal of the challenge is to develop new methods for identifying controller settings from operational 20 Hz data provided by Chalmers University of Technology. The challenge deadline in March 19th, 2025, so there's plenty of time to join! Find out more and sign up here: https://lnkd.in/gzdeae-W #datasharing #collaboration #windenergy #wedowind OST – Eastern Switzerland University of Applied Sciences Departement Technik OST IET Institut für Energietechnik

In the WeDoWind Open Data Exploration Space monthly meeting last week with Charlie Plumley, we had fun discussing the solutions submitted so far for the Kaggle mini-challenge "Predict the wind speed at a wind turbine", which is part of the Static Yaw Misalignment Analysis Challenge. See the leaderboard below! Join us here: https://lnkd.in/egyii8v7

We have extended our ASCE-EMI Structural Health Monitoring for Wind Energy Challenge deadline until Feb. 3rd, so if you are looking for an exciting project over Christmas, then it's not too late to join us! https://lnkd.in/e-hM9XFg #wedowind #collaboration #structuralhealthmonitoring #windenergy

Interested in comparing and benchmarking wind turbine performance quantification methods? In the last two monthly meetings of Yu Ding's WeDoWind Turbine Performance Quantification Collaboration, we heard from Ahmad Chokhachian from Texas A&M University about “Analysis of leading edge protection application on wind turbine performance through energy and power decomposition approaches.”, and discussed the advantages and challenges of the approaches. Get involved here: https://lnkd.in/gfb-A3TV

Did you see our new Kaggle mini-challenge "Wind speed predictions" within the WeDoWind Open Data Exploration space, run by Charlie Plumley? The aim is to determine the wind speed at a target turbine, only using data from neighbouring wind turbines. It forms part of the Static Yaw Misalignment Analysis Challenge, which can be signed up for here: https://lnkd.in/egyii8v7 #datasharing #wedowind #collaboration OST – Eastern Switzerland University of Applied Sciences Departement Technik OST

Looking for creative name ideas! 💡 In collaboration with IEA Wind Task 43, we are expanding WeDoWind to "an inclusive human-centred open innovation ecosystem", which can be applied to any sector to foster interdisciplinary cooperation between people from different backgrounds and an open exchange of data and code. The aim is to help organisations, communities, and entire sectors boost their data analysis efficiency by turning "80% of your time data wrangling" to "80% of your time doing value-adding analytics". We want to do this by, for example, creating data standards and common ontologies and frameworks, developing best practices for open and FAIR data and code, developing common code for data cleaning, and working collaboratively on WeDoWind challenges. All in one ecosystem! So let's try some open innovation right now! We are trying to think of a new name for this general "inclusive human-centred open innovation ecosystem". Any ideas? It should be applicable to any sector, so we don't want the word "wind" in there. But any similarity to "WeDoWind" would be a bonus, like WeDoData or WeCoCreate etc. The winner gets nothing but awe and respect from the WeDoWind team and beyond. Get in touch if you want to know more! https://www.wedowind.ch/ OST – Eastern Switzerland University of Applied Sciences Departement Technik OST IET Institut für Energietechnik #wedowind #digitalisation #datasharing #collaboration

We are excited to announce a new mini-challenge "Wind speed predictions" within the WeDoWind Open Data Exploration space, run by Charlie Plumley! During the Static Yaw Misalignment Analysis Challenge, we identified that a true wind speed measurment independent of yaw misalignment would be useful. In addition, this independent measurement could be useful for validating changes in turbine performance, which also might impact the nacelle mounted anemometer measured wind speed, and for calculating lost energy when a the target turbine is down and other data unavailable. Therefore, this challenge is to determine the wind speed at a target turbine (Kelmarsh 1), only using data from neighbouring wind turbines. We are trying out this mini-challenge on Kaggle, so sign up at "Join this space" on this page to get involved immediately! https://lnkd.in/egyii8v7 #datasharing #wedowind #collaboration OST – Eastern Switzerland University of Applied Sciences Departement Technik OST

At the WeDoWind Open Data Exploration space monthly meeting today, we had the pleasure of hearing Brian Kramak talking about DNV's analysis of the turbine interactions at the Kelmarsh open data site. This work is contributing to the currently running "Static Yaw Misalignment Analysis Challenge". Find out more and register to participate and view the recordings here: https://lnkd.in/egyii8v7 Thanks to Charlie Plumley for organising this space and to Brian for his entertaining and insightful presentation! #wedowind #datasharing #collaboration