Imaging Array Detection for Species-Specific Wind Turbine Curtailment
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Solution Overview
Problem
Existing wind farm mitigation methods cannot specifically identify birds or bats, leading to unnecessary curtailment of wind turbines, resulting in energy loss and high capital costs.
Innovation Solution
An automated system using optical imaging sensors and controllers to detect and identify protected species like Golden Eagles or Bald Eagles, deploying deterrents and curtailment measures only when necessary, with overlapping camera fields and meteorological data for precise risk assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated optical imaging systems are deployed to identify protected species, then species identification accuracy is improved, but device complexity increases
Solution Approach 1:
The system divides the identification task into multiple stages: initial detection by wide-field cameras, followed by detailed examination by telephoto cameras only for detected objects. This segmentation allows high-precision identification to be applied selectively rather than continuously, improving accuracy while managing system complexity.
Solution Approach 2:
The controller serves multiple functions: it processes images from multiple camera types, performs species identification, determines curtailment necessity, and controls turbine operation. This multi-functionality consolidates what could be separate complex systems into a single coordinated controller, improving identification accuracy without proportionally increasing overall system complexity.
2Reliability
If wind turbines are curtailed more frequently to protect birds and bats, then reliability of protected species protection is improved, but productivity of wind farm decreases
Solution Approach 1:
The system replaces manual monitoring and decision-making with automated optical imaging and AI-based species identification. This substitution enables more frequent and accurate curtailment decisions, improving protection reliability while the automation efficiency helps minimize unnecessary productivity loss.
Solution Approach 2:
The system changes the parameter of curtailment decision-making from conservative blanket curtailment to targeted curtailment based on species identification. By changing how curtailment decisions are made (from time-based to species-based parameters), the system improves protection reliability for protected species while reducing unnecessary curtailment of non-protected species, thereby maintaining productivity.
3Loss of energy
If species-specific identification is implemented, then loss of energy from unnecessary curtailment is reduced, but difficulty of detecting and measuring increases
Solution Approach 1:
The system adds the dimension of telephoto imaging capability to the detection system. By incorporating cameras with different focal lengths (wide-field and telephoto), the system can detect objects at various distances and resolutions, reducing energy loss from unnecessary curtailment while managing the difficulty of species-specific detection through multi-dimensional observation.
Data Source
AI summary
An automated system for mitigating risk from a wind farm. The automated system may include an array of a plurality of image capturing devices independently mounted in a wind farm. The array may include a plurality of low resolution cameras and at least one high resolution camera. The plurality of low resolution cameras may be interconnected and may detect a spherical field surrounding the wind farm. A server is in communication with the array of image capturing devices. The server may automatically analyze images to classify an airborne object captured by the array of image capturing devices in response to receiving the images.