Artificial intelligence for the prevention of collisions between birds and wind turbines

AI-driven flight prediction enables real-time decisions to reduce bird collisions while improving wind farm availability and minimizing unnecessary operational stops

Bird protection

Reduced collision risk through predictive flight models

Real-time decisions

Autonomous, data-driven operational control

Higher availability

Fewer unnecessary turbine stops

Energy efficiency

Reduced losses through optimized stop control

AI enables safer wind operations with smarter, real-time decisions

AI for sustainable wind operations

Objectives

Minimize bird collisions and operational impact

Opportunity

Use predictive analytics to balance environmental protection and energy efficiency

Environmental Risk Management and Operational Efficiency in Wind Farms

Risk of collisions with protected bird species and regulatory exposure due to incidents, in a context of reactive operations and manual decision-making. This leads to inefficiencies and unnecessary turbine shutdowns, increasing the risk of penalties.

Key Challenges