Wind park lightning risk assessment with the Meteosat Third Generation Lightning Imager
Austria's ambitious goal to achieve climate neutrality by 2040 requires a significant shift to renewable energy sources, with wind energy playing a key role. However, as wind turbines increase in height, they become more susceptible to lightning strikes, in particular to upward lightning.
The project aims to assess the risk of (upward) lightning strikes on wind turbines for various locations and heights across Austria. Data-driven machine learning models will be used to analyze lightning risk, including upward lightning that ground-based networks cannot detect, but might be monitored by the space-based Meteosat MTG Lightning Imager.
The project will evaluate the detection efficiency and accuracy of the Meteosat Lightning Imager under different meteorological, seasonal, and diurnal conditions using novel machine learning models. Long-term changes in lightning risk for tall structures since 1979 and their seasonal variability will also be assessed. Further, the models will establish functional relationships between turbine height, terrain roughness, and meteorological factors to address the longstanding question of the "effective height" of wind turbines for upward lightning. Finally, the lightning risk results will be made easily accessible via an interactive online map for public use.
The project aims to assess the risk of (upward) lightning strikes on wind turbines for various locations and heights across Austria. Data-driven machine learning models will be used to analyze lightning risk, including upward lightning that ground-based networks cannot detect, but might be monitored by the space-based Meteosat MTG Lightning Imager.
The project will evaluate the detection efficiency and accuracy of the Meteosat Lightning Imager under different meteorological, seasonal, and diurnal conditions using novel machine learning models. Long-term changes in lightning risk for tall structures since 1979 and their seasonal variability will also be assessed. Further, the models will establish functional relationships between turbine height, terrain roughness, and meteorological factors to address the longstanding question of the "effective height" of wind turbines for upward lightning. Finally, the lightning risk results will be made easily accessible via an interactive online map for public use.
Project leader:
Georg Mayr
Members:
Isabell Stucke
External members:
Achim Zeileis (Department of Statistics, UIBK),
Funding Agencies:
The Austrian Research Promotion Agency FFG
Project duration:
15.06.2024 to 14.12.2026