Prediction of Bird Collision Risks in Offshore Wind Farms Based on the Interaction Between Bird Behavior and Wind Turbine Parameters

To address the conflict between offshore wind farm development and bird conservation, this study establishes a risk prediction model based on bird behavior-wind turbine parameter interactions, revealing spatiotemporal patterns of bird activity and collision mechanisms, thereby providing scientific decision-making support for eco-friendly wind power development.

Focusing on a coastal wind farm, we conducted 12-month bird activity monitoring using direct counting, high-definition photogrammetry, and GIS technology, and documented population dynamics and habitat preferences of 36 waterbird species. A Poisson distribution-based bird collision probability model was developed to quantify the interaction between season, flight altitude, and turbine operation parameters, and a risk stratification evaluation method was proposed.

The results show that, 1) Bird activity has significant seasonal variations, and summer is the high-risk period (540 egrets and 18 plovers in total) showing >50% collision probability concentrated at 20-50 m area in the middle and bottom part of the blade; 2) The flight altitude is negatively correlated with body weight (R²=0.87), except for high-altitude flying behavior in migration period, which causes risk distribution shifts; 3) The Poisson model can effectively quantify risk intensity coefficients (Σλ=749), and accurately identify high-risk periods (August) and key species (egrets contributing 97%).

This study provides quantitative tools for environmental impact assessment of offshore wind power projects, facilitating synergistic development of energy exploitation and biodiversity conservation.