Solar Panel Computer Vision for Shading and Soiling Detection
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Solution Overview
Problem
Solar farms face reduced energy output due to shading and soiling, which are typically addressed through labor-intensive visual inspections or reliance on sensors, lacking efficient automated solutions for combined analysis and action.
Innovation Solution
A computer-implemented method using computer vision to analyze satellite images for shading and soiling on solar panels, identifying affected areas, and automatically generating outputs or triggering actions to mitigate these issues, such as cleaning or vegetation removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If labor-intensive visual inspections are used to detect shading and soiling, then detection accuracy can be maintained, but productivity decreases and time consumption increases
Solution Approach 1:
The patent replaces manual visual inspection with an automated computer vision system that captures images of solar panels and uses image processing algorithms to detect shading and soiling. This substitution of mechanical/manual inspection with automated optical-digital inspection maintains detection accuracy while dramatically improving productivity and reducing time consumption.
Solution Approach 2:
The system creates digital copies (images) of the solar panels and performs detection on these copies rather than requiring direct physical inspection. This allows multiple panels to be inspected simultaneously through automated image processing, maintaining detection quality while enabling high-throughput inspection.
2Reliability
If separate analysis methods are used for shading and soiling, then analysis thoroughness is improved, but device complexity increases
Solution Approach 1:
The patent combines shading detection and soiling detection into a single integrated computer vision system. The system captures images and applies processing algorithms that simultaneously evaluate both shading patterns and soiling characteristics, maintaining comprehensive analysis capability while reducing system complexity compared to having separate dedicated systems for each detection type.
Solution Approach 2:
The image processing system is designed to perform multiple functions - detecting both shading and soiling - using a unified approach. This multi-functional design maintains thorough analysis capability while avoiding the complexity of multiple specialized systems, as the same hardware and software infrastructure serves both detection purposes.
3Productivity
If automated computer vision analysis is implemented, then productivity increases and time consumption decreases, but device complexity increases
Solution Approach 1:
The patent replaces complex manual inspection processes with an automated computer vision system. While the automated system introduces technological complexity, it eliminates the need for manual labor and provides consistent, scalable inspection capability. The complexity is concentrated in the software/algorithms rather than requiring complex hardware arrangements, enabling high productivity through automated image capture and processing.
Data Source
AI summary
A method and system for detecting one or both of soiling or shading on solar panels using computer vision is disclosed. Soiling and shading may decrease the amount of energy that may be generated by a solar farm. As such, computer vision may be used to determine whether or when to act to reduce the shading or soiling may in turn increase the energy generated. The computer vision for soiling and shading may be performed in combination, such as in terms of the results of the soiling and shading analysis may be used in combination, or in terms of the analysis itself being performed in combination.