May 5th, 2025
New WeDoWind Hill of Towie Power Prediction Challenge from RES
We are happy to announce our new WeDoWind Hill of Towie Power Prediction Challenge by the UK-based renewable energy company RES!
The Hill of Towie Data Space
The aim of this space is to foster collaboration in connection with the new Hill of Towie data set provided by RES. The Hill of Towie wind farm open dataset provides over eight years of comprehensive operational data from a commercial wind farm in Scotland suitable for various wind energy research topics. The dataset has been released by RES on behalf of TRIG under a CC-BY-4.0 open data license and is provided on Zenodo here.
The Hill of Towie Power Prediction Challenge
Predicting power at a turbine in the absence of reliable wind measurements (e.g. power performance mast or LiDAR) is very challenging but increasingly necessary. One application of power prediction is in measurement of the effectiveness of a turbine upgrade. Upgrading existing wind farms is a highly effective way to unlock additional clean energy without requiring large-scale infrastructure investments. Transparent and reliable measurement of upgrade value is key to scaling these activities and supporting the rapid expansion of wind energy. Increasing the accuracy of wind turbine power modelling is fundamental to this goal.
The goal of the first challenge in this space is therefore to predict power as accurately as possible for one turbine at Hill of Towie given the data from the nearby turbines. The goal is to minimise Mean Absolute Error or the 10-minute predicted active power time series. It will be run on the Kaggle platform. The challenge starts on June 4th, 2025 and ends on November 3rd, 2025.
About the challenge providers
RES is the world’s largest independent renewable energy company and has been an industry innovator for over 40 years. RES’ retrofit upgrade products such as AeroUp and TuneUp have been developed using expertise from deep knowledge of the industry. TRIG, the owner of Hill of Towie, was one of the first investment companies investing in renewable energy infrastructure projects listed on the London Stock Exchange and is now a member of the FTSE-250 index.
Alex Clerc is a Senior Controls Engineer at RES where he works in a team developing new products to improve operational wind farms and other renewable assets. He has been working in technical roles in the renewable energy industry since 2010. Prior to that he completed a BSc in electrical engineering at Rose-Hulman (Indiana, USA) and a MSc in electrical engineering at the University of Warwick (UK). Alex is a supporter of open science, and he recently led a RES team that won the Predict the Wind Speed competition as part of the WeDoWind Open Data Exploration space, took part in the EAWE Data Science Challenge 2024-2025 (results currently under evaluation), and presented an open source analysis in the WeDoWind Data Science for Wind Energy space. He also open-sourced RES' Wind-Up Python tool.
Why participate?
- Access real SCADA data from operating wind turbines. Learn about "real" problems from the industry.
- Receive a WeDoWind Challenge participation certificate.
- Work together with other researchers, students and professionals from all over the world.
- Learn about state-of-the-art analysis and machine learning techniques and evaluation methods.
- Make new connections, develop new ideas, and get creative!
- Be part of our WeDoWind ecosystem, consisting of more than 100 people from 30+ countries, where you can access other challenges and teaching resources on a range of wind energy related topics.
Attend the launch webinar
You can sign up for the launch webinar on June 4th, 2025 below:
Access the WeDoWind space
Read more about the challenge and register to participate here:
Find out about previous challenges
In WeDoWind's collaborative problem-solving community, you can access our previous challenges, including:
You can access a summary of the results and publications here: