Energy transition is accompanied by a significant expansion of wind farms, raising major environmental issues, notably the protection of biodiversity. A new publication, in which the Tour du Valat took part, presents Eoldist, a web application designed to estimate the necessary detection distances for automatic bird detection systems approaching wind turbines, in order to limit collisions.
Automatic detection systems (ADS) are increasingly being used to limit the impact of wind turbines on birdlife. However, it is crucial to determine at what distance these systems should detect birds to enable effective shutdown of the turbines before the birds arrive. Eoldist responds to this problem by providing an estimate of the detection distance to be expected, based on several parameters:
- Birds’ speed of flight,
- The time needed to stop or slow down a turbine,
- The specific characteristics of the species concerned.
A comprehensive scientific database
The application is based on a comprehensive database containing the flight speeds of 168 bird species in the Western Palearctic, collected from scientific publications and unpublished GPS data. To estimate turbine stopping times, field tests carried out at seven wind farms determined that the average time required to slow turbines down to a rotation threshold of 3 or 2 revolutions per minute was 32.2 and 38.8 seconds respectively.
A useful tool for wind turbine operators
Eoldist allows the user to select a species from the database, the characteristics of the wind turbine and a rotation threshold (3 or 2 revolutions per minute); it then calculates the time needed to reach the selected threshold and provides a distribution curve for the detection distance needed to avoid collision. The application is available free of charge and should help the wind energy industry, ADS providers and environmental agencies to define bird detection requirements using ADS that are compatible with the biology of the target species.
This approach aims to contribute to a better cohabitation between the development of renewable energies and the preservation of biodiversity.
Fluhr J., Duriez O., Blary C., Chambert T., Almasi B., Byholm P., Buitendijk N.H., Champagnon J., Dagys M., Fiedler W., Francesiaz C., Jiguet F., Lee S., Millon A., Monti F., Morcelet L., Nathan R., Nolet B.A., Nuijten R., Pilard P., Ponchon C., Roulin A., Santos C.D., Spiegel O., Schalcher K., De Seynes A., Spanoghe G., Wikelski M., Žydelis R., Besnard A. 2025. Eoldist, a Web Application for Estimating Cautionary Detection Distance of Birds by Automatic Detection Systems to Reduce Collisions With Wind Turbines. Wind Energy 28:e2971. doi: 10.1002/we.2971