Mobile Robotic Calibration for Multi-Surface Solar Field Alignment
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Solution Overview
Problem
Current solar tracking and calibration systems for photovoltaic and concentrated solar thermal systems are inefficient, requiring labor-intensive manual calibration and limiting flexibility and cost-effectiveness, especially for larger heliostats and smaller solar surfaces, due to the need for precise sun sensors and constrained installation processes.
Innovation Solution
A mobile robotic calibration system that uses onboard and external sensors, such as GPS, total stations, cameras, and light detection systems, to autonomously determine and align solar surfaces' positions and orientations in a global reference frame, optimizing calibration and reducing labor costs by enabling self-repositioning and data communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual calibration methods are used with single sensor systems, then device complexity is reduced, but calibration precision and efficiency deteriorate due to labor-intensive processes and mechanical linkage inaccuracies
Solution Approach 1:
The solar surface performs self-calibration by using its own dual-axis position data and orientation sensors to determine its geometric origin and calibration parameters, eliminating the need for external sensor systems and manual calibration procedures. The system serves itself by autonomously calculating its own calibration data through coordinate transformations between body-fixed and global reference frames.
Solution Approach 2:
The patent replaces mechanical calibration systems (physical sensor devices and manual measurement tools) with computational methods that use electronic sensors and mathematical coordinate transformations. The calibration process is substituted from a mechanical measurement task to an computational geometry problem solved through coordinate frame transformations.
2Productivity
If automated calibration systems with multiple sensors are deployed, then calibration efficiency improves, but device complexity and cost increase significantly
Solution Approach 1:
The orientation sensor serves multiple functions: it determines the solar surface's orientation in the global reference frame, enables calculation of the geometric origin, and provides data for both calibration and operational tracking. The dual-axis position mechanism also serves dual purposes by providing both operational positioning data and calibration reference data, eliminating the need for separate calibration mechanisms.
Solution Approach 2:
The system creates a computational model (copy) of the solar surface's geometric properties by calculating the geometric origin coordinates through coordinate transformations. This computational copy allows the system to determine calibration parameters without requiring physical measurement devices, replacing tactile measurement with mathematical modeling.
3Reliability
If mechanical linkage calibration is used for multiple solar surfaces, then device complexity is minimized, but calibration accuracy deteriorates due to cumulative mechanical errors
Solution Approach 1:
Each solar surface is calibrated independently through its own orientation sensor and position data, rather than being mechanically linked to a master reference. The calibration process is segmented into individual surface calculations, where each surface determines its own geometric origin and calibration parameters autonomously, eliminating cumulative mechanical errors from linkage chains.
Solution Approach 2:
The global reference frame serves as an intermediary coordinate system that connects each solar surface's local body-fixed frame to the overall system. By using coordinate transformations through this intermediate global frame, the system achieves accurate relative positioning between multiple solar surfaces without requiring direct mechanical linkages between them.
4Measurement precision
If traditional calibration approaches requiring accurate sun sensors are used, then measurement precision is maintained, but ease of operation deteriorates due to constrained installation processes
Solution Approach 1:
The solar surface determines its own orientation and position data through onboard orientation sensors and position mechanisms, eliminating the need for external sun sensors or manual alignment tools. The system performs self-calibration by calculating its geometric origin from its own operational data, making the installation process simpler and more flexible.
Solution Approach 2:
The patent replaces mechanical sun-sensing alignment systems with electronic orientation sensors and computational methods. Instead of using physical sun sensors to manually determine alignment, the system uses electronic sensors to measure orientation and calculates the required calibration parameters through mathematical transformations, improving ease of operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The mobile robotic system significantly reduces calibration labor and increases installation flexibility by autonomously aligning solar surfaces, improving efficiency and reducing costs through precise, automated calibration and data-driven optimization of solar field configurations.
Implementation Method 1
the mobile robotic controller may discover its position in a global or relative reference frame through the use of an onboard global positioning system or triangulation system
Implementation Method 2
the mobile robotic controller may discover its position in a global or relative reference frame through the use of an onboard global positioning system or triangulation system
Implementation Method 3
the mobile robotic controller may discover its position in a global or relative reference frame through the use of an external total station, distance sensing system, natural light camera system, or structured light camera system
Implementation Method 4
the mobile robotic controller may discover its position in a global or relative reference frame through the use of an external total station, distance sensing system, natural light camera system, or structured light camera system
Implementation Method 5
the mobile robotic controller may use its known orientation in a global 3-axis reference frame to determine the 3-axis orientation of a solar surface through the use of an onboard magnetic compass, gyrocompass, solid state compass, accelerometer, inclinometer, magnetometer, gyroscope, or solar sensor
Implementation Method 6
the mobile robotic controller may use its known orientation in a global 3-axis reference frame to determine the 3-axis orientation of a solar surface through the use of an onboard magnetic compass, gyrocompass, solid state compass, accelerometer, inclinometer, magnetometer, gyroscope, or solar sensor
Implementation Method 7
the mobile robotic controller may use an onboard light detection system in conjunction with a light tube or light guiding system to determine if a solar surface is aligned to the sun
Implementation Method 8
the mobile robotic controller may use instantaneous power output information from a PV cell or CPV module to determine if a solar surface is aligned to the sun
Data Source
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AI summary
A robotic controller for autonomous calibration and inspection of two or more solar surfaces wherein the robotic controller includes a drive system to position itself near a solar surface such that onboard sensors may be utilized to gather information about the solar surface. An onboard communication unit relays information to a central processing network, this processor combines new information with stored historical data to calibrate a solar surface and/or to determine its instantaneous health.