A consecutive Vestas turbine accident in the US: Safety and monitoring in the spotlight

In the US state of Missouri, a Vestas turbine collapsed for the third time since April 2024. In wind energy sector, such incidents have reopened the debate on safety standards and monitoring Technologies in wind turbine.

High Prairie Renewable Energy Center: Wind Farm at the center of the accidents

High Prairie Renewable Energy Center, with the capacity of 400 MW and owned by Ameren Missouri in the state of Missouri, began operations in 2020. Three different Vestas turbines have collapsed since April 2024, with the last incident occurring on November 1, 2024. In these accidents, blades were shattered, sometimes resulting in severe structural damage to the turbine housing. Fortunately, no injuries were reported in these incidents. Following the incident, the plant was temporarily shut down and safety inspections were initiated.

Did other Wind Turbine manufacturers encounter such incidents?

Accidents in wind energy sectors are not limited to Vestas only. Leading manufacturers, such Siemens Gamesa and General Electric (GE) also experienced various accidents in the past. For instance, in 2019, Siemens Gamesa’s wind turbine blade was shattered in Germany, meanwhile GE wind turbine was collapsed in Oklahoma. Such failures and incidents highlight the need for more strengthened safety measures for the entire wind sector.

New methods to predict and prevent accidents in the wind turbines:

Sensor Technologies and Early Warning Systems

The sensors used in modern wind turbines monitor the wind turbine blades health by continuously measuring parameters such as vibration, temperature, wind speed and blade regression. This type of collected data from wind turbine blades is analyzed by using Machine Learning algorithms to detect anomalies and send early warning signals to maintenance teams.

Drone and AI-powered blade inspection systems

By using drone technology and artificial intelligence, high-resolution images of wind turbine blades are obtained and analyzed, enabling early detection of cracks and/or erosions. Windrover Technology, developed in Türkiye by Werover, helps detect blade related damages in early stage by collecting the sounds of the blades. This system reduces the maintenance time and significantly lowers the maintenance costs.

Prediction of incidents in early stage with AI-powered technology and big data analytics

AI-powered and big data-based analytics can predict future incidents by using previous performance of wind turbine blades and environmental factors. Machine learning algorithms, especially powered by large data sets of wind farms, can predict the probability of certain incidents with relatively high accuracy.

Lessons for Türkiye’s wind energy sector

While Türkiye is attracting significant attention in the world with its huge investments in wind energy sector, there are couple of lessons should be learnt from such incidents in the US. Turkey also needs to invest in AI-powered and sensor-based wind turbine blade health monitoring system for enhancing safe and sustainable energy.

The recent Vestas turbine incidents in the US have once again demonstrated the importance of safety standards and maintenance strategies in wind energy. Innovative solutions such as AI-powered health monitoring systems and prediction of incidents can play a critical role in preventing such incidents. Within this framework, it holds great importance for countries like Türkiye where rapid investments in the energy sector is being made to benefit from these technologies for reaching sustainable energy goals.

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