IEA Wind Task 52 - 18 m/s Hurdles report - Low Hanging Winds Team

In the context of the IEA Summer Games Task 52, our work focuses on the development of lidar-assisted controllers (LAC) for wind turbines, a technology that promises to revolutionise wind energy management. Since wind characteristics are dynamic and subject to sudden changes, conventional control systems often react with delay, which can affect turbine efficiency and performance. Our approach proposes an LAC system that uses advance information about wind conditions, allowing the turbine to proactively adapt to variations before they impact its operation. This approach not only improves efficiency, but also minimises mechanical wear and tear on the turbine, extending its lifetime. During the development of this work, we have used open source tools to implement lidar data processing algorithms, which facilitates accessibility and collaboration in the community. Through this research, we aim to contribute to the advancement of LAC technology and promote practices that simplify its application in industry. We hope that our work will inspire new ideas and collaborations during the Summer Games, and that together we can move towards a more efficient and sustainable future in wind energy.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-01
DOI
https://doi.org/10.5281/zenodo.13937131
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
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article

IEA Wind Task 52 - 18 m/s Hurdles report - Low Hanging Winds Team

Zenodo (CERN European Organization for Nuclear Research)
Wind Energy Research and Development
article

IEA Wind Task 52 - 18 m/s Hurdles report - Low Hanging Winds Team

article en

Abstract

In the context of the IEA Summer Games Task 52, our work focuses on the development of lidar-assisted controllers (LAC) for wind turbines, a technology that promises to revolutionise wind energy management. Since wind characteristics are dynamic and subject to sudden changes, conventional control systems often react with delay, which can affect turbine efficiency and performance. Our approach proposes an LAC system that uses advance information about wind conditions, allowing the turbine to proactively adapt to variations before they impact its operation. This approach not only improves efficiency, but also minimises mechanical wear and tear on the turbine, extending its lifetime. During the development of this work, we have used open source tools to implement lidar data processing algorithms, which facilitates accessibility and collaboration in the community. Through this research, we aim to contribute to the advancement of LAC technology and promote practices that simplify its application in industry. We hope that our work will inspire new ideas and collaborations during the Summer Games, and that together we can move towards a more efficient and sustainable future in wind energy.

Zenodo (CERN European Organization for Nuclear Research)
Universidad de la República de Uruguay (UY)
Openalex Percentile: Top 42%
Wind Energy Research and Development
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