Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
Looking for the Swiss Wind Energy R&D Network? We’ve moved to www.windenergynetwork.ch
December 6th, 2023

WeDoWind meets Game Changers - hear from an intern!

In summer 2023, we at the Wind Energy Innovation Division at the Eastern Switzerland University of Applied Sciences ran the "WeDoWind meets Game Changers" internship programme together with the University of Strathclyde in Glasgow, UK. Find out what one of the interns has to say about the programme!

Game Changers

In order to nurture the next generation of researchers, an inclusive internship program was created to demystify research and ensure that the opportunities of academia are open to all. Over the past five years, Game Changers has hosted a total of 24 internships, recruited talented students from three universities, worked directly with renewable energy industry partners, and helped a total of five interns become PhD students in Strathclyde, while assisting others in securing graduate positions. The interns' research is not only a valuable experience, but also leads to significant outputs such as publications and industrially used software. The internship program includes involvement with a Strathclyde research team and participation in specially designed research skills workshops. The recruitment process has been intentionally designed to recruit a wide range of applicant:s. It is hoped that the best practices developed here will contribute to improvements in recruitment across the University.


WeDoWind is a framework that enables and motivates people from academia and industry, as well as other stakeholders, to collaborate and share and manage data and knowledge in a secure environment, creating a mutually beneficial win-win situation. The framework is based on industry-provided "Challenges" coordinated through digital "Spaces." Several digital "Spaces" form industry-specific ecosystems of collaborators. It provides added value to any person who wants to either define or solve a "Challenge". The former receive an innovative solution for a "Challenge". The latter have the opportunity to be part of an international community, to gain experience by working with complex data or to develop and test new methods on previously inaccessible data sets.

An exciting collaboration

With the project "WeDoWind meets GameChangers" we brought the "GameChangers" internship program together with WeDoWind for the first time. In this collaboration, which took place over the summer of 2023, two research-interested and motivated students worked together on a WeDoWind challenge. Each student worked at a different partner university and was supported by experts from the respective host institution to make a concrete contribution within the project. Besides the two partner universities OST and Strathclyde University in Glasgow, UK, the organisations Cubico Sustainable Investments, UK, and Texas A&M University, USA, accompanied this project.
The work carried out by the interns resulted in a new WeDowind challenge definition - the Static Yaw Misalignment Analysis Challenge. This challenge aims to harness the power of data science to optimise wind turbine performance by analysing static yaw misalignment. Contributed by Cubico Sustainable Investments, the datasets of two wind farms, Kelmarsh and Penmanshiel, offer an ideal base for innovative approaches to yaw analysis. As well as this, a code was developed for seamlessly reading in the Kelmarsh and Penmanshiel data and applying the static yaw misalignment module on the OpenOA wind plant operational assessment framework.

A chat with an intern

We had a brief chat with one of the interns, Anton Paris, and here's what he told us!

Anton Paris

The internship provided me with diverse insights, from industry to academia, and gave me practical experience in applying principles crucial for my future career goals.
Hi Anton! Please tell us who you are and what do you do!
I am Anton Paris, currently studying electrical engineering at the Eastern Switzerland University of Applied Sciences in Rapperswil, Switzerland. My studies focus on machine learning, digital signal processing, and computer vision. I have a strong interest in working with data in various forms.
Why did you apply for the programme?
I wanted apply the theoretical knowledge I've gained in my studies, expand my understanding of wind energy, connect with new people, and gain insights into research. I was also eager to get hands-on experience with real-world problems and contribute to finding solutions for pressing issues.
How did you benefit from the programme?
The internship provided me with valuable hands-on experience and exposure to advanced concepts. I had the opportunity to work with an open-source Framework, OpenOA. It was fascinating to understand its structure and build. The open-minded team and contacts I made helped me significantly in expanding a tool for estimating static yaw misalignment for wind turbines. This experience enhanced my skills in handling SCADA data and exposed me to new programming knowledge and concepts.
How did you particularly benefit from the “GameChangers” part of the programme?
The international cooperation aspect of the internship was particularly beneficial. It allowed me to connect with experts from the USA and the UK, providing valuable insights into research methodologies and the importance of knowledge exchange. The meetings with these experts were instructive, pleasant, and they were all very helpful and kind.
How did you particularly benefit from the “WeDoWind” part of the programme?
In the WeDoWind part of the internship, I focused on creating a baseline for a WeDoWind Challenge. This involved contacting various parties from industry and academia to understand their goals for the challenge. The process taught me the importance of being specific in formulating limitations to ensure that results are comparable and provide meaningful insights.
In general, what was particularly positive about the experience?
The experience can be summarised in two main aspects. Firstly, the opportunity to work with talented peers and the assistance they offered was incredible, especially the support from my supervisor who was always kind and helpful in tackling problems during the internship. I also learned the importance of asking questions to maximize the benefits from all interactions. Secondly, on the technical side, I expanded my knowledge in handling SCADA data and structuring code. Working with the OpenOA Framework taught me to write cleaner and more efficient code. Overall, it was a highly positive and beneficial experience for my professional growth.
What are you planning next in your career?
I plan to finish my degree and leverage the skills and knowledge I've gained to pursue a career in Machine Learning, focusing on developing innovative solutions that combine machine learning with computer vision.
How did the project help you in achieving this?
Since 80% of Machine Learning is based on working with Big Data, my experience with SCADA data during the internship was invaluable. It taught me how to handle large volumes of data, structure it, filter it, and develop a more critical approach to assessing data plausibility.
Any more comments?
I am grateful for the opportunity and the experiences I gained, and I look forward to applying the insights and skills I've acquired in my future endeavors.

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