System and methods for determination of potential solar installable surface area
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Solution Overview
Problem
Existing methods for evaluating a structure's potential for solar panel installation are labor-intensive, prone to human error, and costly, often relying on expensive three-dimensional mapping data that requires significant computational resources.
Innovation Solution
A system and method that uses overhead images and pattern recognition to determine the potential solar panel-installable surface area by identifying surface outlines, analyzing sun path, and accounting for shading, leveraging globally available imagery to provide a cost-effective and efficient assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual evaluation methods with instruments and climbing are used to profile solar power potential, then measurement precision can be achieved, but labor intensity and time consumption increase significantly
Solution Approach 1:
The patent uses aerial images as a copy or representation of the physical structure surfaces, eliminating the need for physical inspection while maintaining assessment accuracy. The system processes these image copies to determine solar panel installation potential, shading, and surface characteristics without requiring evaluators to physically access the sites.
Solution Approach 2:
The patent replaces manual mechanical evaluation methods with an automated computer-based image processing system. The mechanical actions of climbing, instrument deployment, and manual measurement are substituted with automated algorithms that process aerial images to extract solar potential information.
2Reliability
If three dimensional mapping data is used to determine solar potential, then comprehensive analysis is achieved, but data generation cost and computational resource requirements increase
Solution Approach 1:
The patent extracts only the necessary solar-relevant information from aerial images rather than generating complete three-dimensional mapping data. The system identifies and extracts surface areas, shading patterns, and installation suitability directly from two-dimensional aerial views, eliminating the need for complex 3D data generation and processing.
Solution Approach 2:
The patent uses readily available, low-cost aerial images instead of expensive three-dimensional mapping data. These images can be obtained from various sources including satellite imagery, aerial photography, or drone captures, providing sufficient information for solar assessment at a fraction of the cost of comprehensive 3D mapping.
3Measurement precision
If manual operation is used for structure profiling, then detailed assessment is possible, but human error susceptibility increases and global coverage cannot be provided
Solution Approach 1:
The system performs self-service by automatically processing aerial images to determine solar installation potential without human intervention in the analysis phase. The computer algorithm independently identifies surfaces, calculates shading, and determines installation suitability, eliminating human error while maintaining consistent assessment standards across all evaluations.
Solution Approach 2:
The system incorporates feedback mechanisms where the computer processes image data, compares it against solar installation criteria, and generates assessments that can be verified and refined. This automated feedback loop ensures consistent application of evaluation standards while allowing for systematic improvement of the assessment algorithms.
Data Source
AI summary
An apparatus and method for determining a potential surface for installation of solar panels are provided. The method includes extracting, from a database of overhead images, at least one overhead image respective of a location; identifying a surface outline of at least one surface within the at least one overhead image; determining a pattern associated with the surface outline, the pattern comprising at least a facet; determining a potential installation area for solar panels based on the at least facet; and, displaying the potential installation area overlaid on the overhead image.