Reducing bat fatalities at wind turbines in central Europe -How efficient are bat-friendly operation algorithms in a fieldbased experiment? - Behr, Oliver; Hochradel, Klaus; Mages, Jürgen; Nagy, Martina; Korner-Nievergelt, Fränzi; Niermann, Ivo; Simon, Ralph; Stiller, Florian; Weber, Natalie; Brinkmann, Robert (Conference on Wind Power and Environmental Impacts (CWE), 2013)
Reducing bat fatalities at wind turbines in central Europe – How efficient are bat-friendly operation algorithms in a field-based experiment? Here we present data from an ongoing field-test of ‘bat-friendly’ operational algorithms for wind turbines. The algorithms trade off the reduction in collision risk against the loss in revenue resulting from mitigation. Algorithms are turbine-specific and are based on data of acoustic bat activity, wind speed, month, and time of night that were previously recorded in 2008 and 2010 at 72 randomly selected turbines in Germany. 18 of these turbines are now part of the ongoing experiment. To develop the bat-friendly operational algorithms we first modelled acoustic bat activity from the month, time of night, wind speed, and a turbinespecific factor coding the level of bat activity. Next, we used a mixture model to estimate the collision risk from acoustic bat activity. Both models were combined to estimate the collision risk using only wind and time as predictive variables. During times of high collision risk, rotors are stopped to avoid bat fatalities. Times of high risk are defined by a turbine-specific cut-in wind speed that varies with month and time of night. We are currently running our bat-friendly algorithms in an experimental set-up at 16 wind turbines at 8 sites (2 turbines each) in 4 different geographical regions in Germany and at 2 turbines at one site in France. The two turbines within each site are running with and without algorithms in alternating one-week intervals from July to September of 2012. All turbines in the experiment are equipped with at least 2 of 3 different acoustic detectors at the nacelle (Anabat SD1, Avisoft Ultra Soundgate, and Batcorder) that sample acoustic bat activity continuously during the night. Additionally, the area under the turbines is searched for animal fatalities each day during the entire time of the experiment. We will quantify the long-term variability of bat activity comparing acoustic data from 2012 and 2008. From the fatality data we will be able to draw con- NATURVÅRDSVERKET RAPPORT 6546 Book of Abstracts 34 clusions on the effectiveness of the algorithms (loss in revenue per reduction in bat fatality) and on the total cost for their implementation. We will compare the number of bat fatalities predicted for the specific operational algorithm to the number of carcasses found after correcting for search biases. Finally, and most importantly we will develop guidelines and practical examples for the quantification and mitigation of bat fatalities by bat-friendly operation of wind turbines in central Europe.