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Otary

AI for Wind Turbine Optimization: turbine underperformance analysis to reduce power loss

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TagsEnergy
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TagsEnergy

Otary, a Belgian partnership of eight companies, is driving offshore wind innovation through collaboration and sustainable energy projects. To further optimize their wind farms, Otary teamed up with ML6 to apply machine learning for smarter performance monitoring and prediction.

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Otary_View of offshore windfarm and service boat By imagesourcecurated_2_envato

Catch up quickly

Otary partnered with ML6 to build a machine learning model that predicts wind turbine power output more accurately than OEM models. By analyzing factors like wind speed, direction, and turbine location, the solution provides real-time insights into under-performance drivers. This empowers Otary to reduce costs, maximize energy production, and strengthen Belgium’s sustainable energy future.

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About this client

Otary is a unique partnership of eight Belgian companies committed to the development, financing, construction, and management of offshore wind farms. Their collaborative approach brings together a diverse range of expertise to drive innovation and advance sustainable energy solutions.

Impact

Otary, a Belgian partnership for sustainable offshore energy, is leveraging machine learning to optimize the performance of their existing wind turbines. This innovative approach helps Otary maximize energy production and reduce costs, contributing to a more sustainable energy future for Belgium.

otary_Windmill turbines at sea a huge winmill park in the Netherlands during winter By fokkebok 2_envato

Challenge

Otary sought to gain a deeper understanding of the performance of their wind turbines and identify factors contributing to both over- and under-performance. The model that was in place, as provided by OEM, wasn’t always able to accurately predict or explain the observed power output. In order to gain a better understanding and optimize their operations, Otaray needed to analyze vast amounts of data and develop a system for real-time monitoring and prediction of the energy production.

The results are very promising. We now have more insight into the behavior of our wind turbines. This will help us further reduce the cost of offshore wind energy
Benjamin
Benjamin ColbrandtCEO, Otary

Solution

Otary partnered with ML6 to build a machine learning model that boosts the accuracy of wind turbine power predictions. By analyzing vast datasets and making insights actionable, the solution empowers Otary to optimize operations and reduce the cost of offshore wind energy.

  • Improved Power Output Prediction

    A machine learning model integrates parameters such as wind speed, direction, and turbine location to deliver more accurate forecasts than existing OEM models.

  • Actionable Insights for Optimization

    The model makes predictions understandable, helping Otary identify causes of under-performance and take proactive steps to maximize energy output.

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The key to this project was linking the model's predictions to actionable insights for the business. We focused on making the predictions understandable, so Otary knows which factors can lead to under-performance and can take action.
ML6Team

Results

Through the implementation of a sophisticated machine learning model developed in collaboration with ML6, Otary has achieved a significant leap in understanding and optimizing the performance of their offshore wind turbines. This solution has resulted in more accurate power output predictions, surpassing existing OEM models, and provided critical insights into the factors influencing both over- and under-performance. By leveraging these insights, Otary is now empowered to make data-driven decisions that will reduce operational costs, maximize energy production, and contribute to a more sustainable energy future for Belgium, with the added benefit of real-time monitoring and prediction of energy production.

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Benjamin Praats
Benjamin PraatsClient Executive, ML6

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Benjamin Praats
Benjamin PraatsClient Executive, ML6

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