Assessing Avian-Wind Turbine Collision Risk:

1. Assessing Avian-Wind Turbine Collision Risk: A Novel Approach to Account For Site-specific Variability http://www.HamerEnvironmental.com Lars A. Holmstrom, DelphinRuché, 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 • 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,heightprofiles 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. Variability in terrain, wind patterns, and bird flight patterns can make accurate pre-construction 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 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. • 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. 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.