Assessing Avian-Wind Turbine Collision Risk:
A Novel Approach to Account For Site-specific Variability
http://www.HamerEnvironmental.com
Lars A. Holmstrom, Delphin Ruché, Erin M. Colclazier, Nathalie Denis, and Thomas E. Hamer
Hamer Environmental L.P., P.O. Box 2561, Mount Vernon, Washington, 98273, USA, Hamer@HamerEnvironmental.com
Azimut, 14 rue Picard, 44620 La Montagne, France, contact@azimut-radar.com
Abstract
The Hamer Risk of Collision Model includes significant additions and improvements from previous models by accounting for different angles of avian approach other than perpendicular or
parallel to the turbine rotor plane, and by taking into account the statistical distributions of wind, terrain, and avian flight characteristics at the wind resource area using Monte Carlo sampling.
We calculated a comparison of average collision probabilities across a single GE 1.5se wind turbine for different raptor flight path approach angles under varying weather conditions. We
demonstrate, using a case study of fall raptor migration data, that accounting for site-specific variables has a significant effect on the estimated collision probability.
Results
Introduction
Variability in terrain, wind patterns, and bird
flight patterns can make accurate preconstruction risk assessment problematic for
wind energy developments. Current models
assessing collision risk fail to account for these
site-specific factors, potentially decreasing the
accuracy of the predictions they provide. Our
objective was to improve on previous models by
Band (2007) and Tucker (1996) by building a
predictive model that is capable of accounting
for site-specific variation.
Methods
• Initially built using bird flight directions and
passage rates (collected via marine radar),
wind speed and direction, and turbine
characteristics from a proposed eastern
Washington wind park.
• Further refined using data collected on the
island of Kauai.
Our model then uses empirically
measured
distributions
of
the
following
model
variables
in
conjunction
with
Monte-Carlo
sampling techniques to simulate a
large number of probable flight paths
under probable weather conditions:
• Bird flight direction in relation to
the rotor plane ;
• Three-dimensional blade
characteristics and number of
blades;
• Different turbine avian avoidance
rates and wind park displacement
rates;
• Monopole dimensions, hub/turbine
height, and nacelle dimensions;
• Rotor speed and rotor pitch as a
function of wind speed;
• Precise point of entry into the rotor
plane;
• Site-specific variation in wind
speed & direction over time;
• Number of wind turbines and their
spatial configuration on the
landscape and;
• Variation in bird flight speeds,
height profiles and flight path
density.
• Accounting for avian flight angle of
approach has a significant effect on the
estimated collision probability.
• Avian Risk of collision also varies with
weather patterns and can be highly spatially
autocorrelated.
Figure 3. A comparison of average collision probabilities across a
single GE 1.5se wind turbine for different Sharp-shinned Hawk
flight approach angles relative to downwind, using the mean
recorded flight speed. Note the difference in collision probability
when compared with previous models (red line) which assumed
uniform angles of approach.
Figure 1. Workflow of the Monte Carlo simulation-based Hamer
model.
Figure 2. Gaussian Kernel density of flight paths within a radar
survey field illustrating the spatial variability within a single site.