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
February 7th, 2024

Two presentations at the WindEurope Annual Event in Bilbao in March 2024!

We are looking forward to two presentations at the WindEurope Annual Event in Bilbao in March 2024! Sarah Barber and Charlie Plumley will both be presenting the results of recent WeDoWind challenges!

Exploring variability in operational energy yield analysis: insights from open data analysis

Long-term energy yield estimates play a pivotal role in the wind industry and are essential for financial planning. Accuracy is King, particularly for estimates using operational data, as these are used to then validate pre-construction energy analyses. But different methodologies and models result in different estimates.
In this presentation, Charlie Plumley from Glenmont Partners in the UK shows that the results of a recent challenge, a benchmarking exercise to predict the long-term 20-year generation of the assets and associated uncertainties using operational data, highlight this issue… however, they also highlight an opportunity!
Through collaboration and the use of open data, we can identify not only where differences exist, but also why. This allows for discussion and refinement of industry models, improving overall accuracy. And the more people and companies involved, the better are estimates can become… hence, we need your help!
Summary of results from a recent WeDoWind challenge

Improving data sharing in practice - power curve benchmarking case study

In this presentation, Sarah Barber from the Eastern Switzerland University of Applied Sciences shows that “Challenge”-based collaborations can help the industry become more innovative, by providing a motivation and basis for sharing data, as well as for comparing and benchmarking different methods.
A new WeDoWind space was created together with Yu Ding, author of the book, Data Science for Wind Energy. A new WeDoWind “challenge” was then created in this space. The goal of this “challenge” was to benchmark and discuss data-driven power curve models. Different methods, including ..., were submitted. A preview of the results is shown below. A participant's survey allow us to develop some recommendations for improving data sharing in practice, including:
  • Data owners are more likely to share data if a concrete benefit is visible.
  • A benchmarking project with well-defined comparison metrics can help to achieve this.
  • Students can be encouraged to use the shared data by integrating a “challenge” into their course of studies.

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You can partipate in WeDoWind challenges by signing up at the link below. An overview of spaces is given here.

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You can also provide data for new challenges by getting in touch below!

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