Wind Generation Optimization While Protecting Endangered Birds
When endangered birds may be flying near wind turbines, operators must decide whether to stop production, continue operating or activate deterrent measures. If those decisions rely too heavily on manual judgement, each park or team may act differently. A more homogeneous, data-based approach helps reduce unnecessary stops, protect endangered species and generate reliable information for environmental reporting
This approach focuses on the operational moments when wind production and the protection of endangered birds intersect: turbine shutdowns, deterrent actions, control-room decisions and environmental reporting
Help operators avoid stopping turbines when the available risk indicators do not justify it, improving production without weakening the protection of endangered birds
Support better decisions around endangered-bird protection, helping reduce the impact associated with turbine blades and the potential social or regulatory consequences of bird mortality
Provide a homogeneous decision input across wind farms, so control-room teams can act with consistent criteria rather than relying only on individual interpretation
Homogenize data captured across wind farms to support environmental follow-up, government reporting and continuous model improvement
NTTデータのサポート体制は？
NTT DATA develops models adapted to each operating context to estimate the probability of endangered birds being in flight near turbines
NTT DATA builds computer vision solutions based on machine learning or generative AI to support the detection, interpretation and use of bird-risk signals
Model outputs are connected with control-room processes so operators can decide whether to stop a turbine, keep it running or activate approved deterrent measures
Each recommendation can be supported by data, helping teams make decisions based on evidence and review them afterwards when needed
NTT DATA helps structure and homogenize the data required for environmental monitoring, endangered-bird protection follow-up and government reporting requirements
Keep turbines active when risk is not present
Anticipate risky flight situations near wind turbines
Support operators with consistent, data-based risk signals
Standardize field information for reporting and model improvement
Improve production decisions with reliable biodiversity-risk insight
