Solar Irradiance GUI with UAV Ray-Path Modeling
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Solution Overview
Problem
Current methods for assessing solar irradiance on rooftops are inaccurate due to outdated imaging data and lack of detailed spatial and temporal analysis, often failing to account for obstructions and future changes, which affects the optimal placement and efficiency of solar panels.
Innovation Solution
A system utilizing an unmanned aerial vehicle (UAV) for capturing high-resolution images and performing detailed scans, combined with ray-path modeling and graphical user interfaces, to create accurate three-dimensional models and heatmaps of solar irradiance, accounting for obstructions and future changes, thereby optimizing solar panel placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution UAV imaging and detailed ray-path modeling are used, then measurement precision of solar irradiance is improved, but device complexity and computational requirements increase
Solution Approach 1:
The system segments the solar irradiance assessment into distinct functional modules: UAV-based image capture, three-dimensional model generation, ray-path modeling, obstruction detection, and heatmap visualization. Each module handles a specific aspect of the analysis, allowing complex computations to be broken down into manageable steps that can be processed sequentially or in parallel, thus maintaining measurement precision while managing system complexity.
Solution Approach 2:
The system performs preliminary actions by capturing high-resolution images and generating three-dimensional models of the rooftop environment before conducting solar irradiance calculations. Obstructions are identified and modeled in advance, and ray-path trajectories are pre-calculated based on the three-dimensional model. This preliminary preparation enables accurate real-time or near-real-time solar irradiance assessment without requiring complex computations during the actual measurement phase.
2Reliability
If detailed spatial and temporal analysis is performed, then reliability of solar panel placement is improved, but loss of time for data processing increases
Solution Approach 1:
The system performs detailed spatial analysis by generating three-dimensional models and identifying obstructions in advance. Temporal analysis is conducted by calculating solar ray-path trajectories for different times of day and seasons before actual panel placement decisions are made. This preliminary analysis ensures reliable placement decisions while reducing the time required during the actual installation planning phase.
Solution Approach 2:
The system dynamically adjusts the level of analysis based on specific project requirements. The ray-path modeling can be configured to analyze specific time periods, seasonal variations, or particular obstruction scenarios. This dynamic approach allows the system to provide comprehensive reliability assessment when needed while offering faster, simplified analysis for less critical applications, thus balancing reliability with processing time.
3Manufacturing precision
If three-dimensional modeling and ray-path analysis are implemented, then manufacturing precision of solar irradiance maps is improved, but device complexity increases
Solution Approach 1:
The three-dimensional modeling process is segmented into distinct stages: image capture from multiple angles, point cloud generation, surface reconstruction, and model refinement. Each stage produces intermediate results that can be validated and adjusted independently. The ray-path analysis is similarly segmented into solar position calculation, trajectory modeling, and irradiance computation. This segmentation enables precise solar irradiance mapping while managing computational complexity through modular processing.
Solution Approach 2:
The system creates accurate digital three-dimensional copies of the physical rooftop environment, including obstructions and surface features. These digital models serve as virtual replicas that can be manipulated and analyzed without requiring physical prototypes or scale models. The ray-path trajectories are also represented as digital copies of actual solar paths, enabling precise irradiance calculation while avoiding the complexity of physical experimentation.
4Productivity
If comprehensive obstruction analysis is performed, then productivity of solar panel installation is improved, but loss of time for analysis increases
Solution Approach 1:
The system performs comprehensive obstruction analysis in advance by identifying all objects that may block solar rays, modeling their three-dimensional geometry, and calculating their impact on different rooftop locations. This preliminary obstruction analysis is integrated into the three-dimensional model generation phase, so that when solar panel placement is planned, the obstruction data is already available. This enables rapid productivity optimization without requiring time-consuming analysis during the installation planning meeting.
Solution Approach 2:
The system automatically performs obstruction detection and analysis without requiring manual input or intervention. The ray-path modeling automatically identifies obstructions based on the three-dimensional model, and the heatmap generation automatically highlights optimal placement areas. This self-service capability reduces the time investment required from analysts while providing comprehensive obstruction analysis, thus improving overall productivity of the solar panel installation process.
Data Source
AI summary
Systems, methods, and computer-readable media are described herein to model divergent beam ray paths between locations on a roof (e.g., of a structure) and modeled locations of the sun at different times of the day and different days during a week, month, year, or another time period. A graphical user interface allows for visualization of the modeled ray paths and graphical manipulation of the resolution and parameters of the modeling process.