The increasing presence of wind energy installations is faced with citizen and political resistance often founded on the potential damage these can impose on fauna such as birds. This resistance is an obstacle to the necessary introduction of more weather-based renewable electricity sources due to the consequences of fossil-fuel electricity generation. However, if the introduction of more wind energy installations is to continue, this must also not be at the expense of wildlife. This project seeked to verify the existence of bird-turbine collision risk and to identify high collision risk zones in the temporal and spatial scale for Afro-Palaearctic migratory birds flying through Europe.
Collision risk was assumed as the presence of birds through the swept area of turbines. The migratory movement of birds was obtained from an interpolation of a geostatistical model and data from 37 weather radars for the dates 13 February 2018 to 1 January 2019. The data is given as a volumetric flow across a 0.25° grid. The volumetric distribution of wind energy installations was derived from a database of 23145 installations and a self-sourced turbine database of 589 turbine models. This distribution is presented as both a high-resolution map covering the European continent and as a swept area density map. The volumetric bird flow was multiplied by the swept area density to obtain values for birds at risk of collision in a 0.25° grid cell. Birds were not considered at risk when the average wind speed in the cell was outside the cut-in and cut-out wind speed region for the turbines (i.e. not between 3 m/s and 24 m/s).
The potential electricity production per 0.25° grid cell was also estimated. This was achieved by assigning power curves from a database to the wind energy installations and assigning a mean power curve to the entries missing a specific turbine model. The wind velocities were hourly average values for the dates 13 February 2018 to 1 January 2019 from the ERA5 reanalysis. A calculation of energy per bird at risk in [TJ/bird] was also done.
Four high collision risk spatial zones were explored in detail by use of a map compiled in QGIS and their proximity to or overlay with protected bird habitat sites discussed. Temporally, date ranges when bird collision is highest were obtained for the four country sub-region in 2018. The possibility of curtailment is briefly discussed.