Method for predictive control of the orientation of a solar tracker
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Solution Overview
Problem
Existing single-axis solar trackers face performance deficits in cloudy conditions due to frequent changes in optimal orientation, leading to increased electrical consumption and mechanical wear without sufficient productivity gains.
Innovation Solution
A method for controlling the orientation of single-axis solar trackers that forecasts the evolution of cloud cover to anticipate optimal tilt angles, reducing unnecessary changes in orientation by translating cloud cover observations into solar luminance maps and calculating future optimal angles, considering wear and energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the solar tracker orientation is frequently adjusted to follow optimal angles in cloudy conditions, then solar energy production is improved, but electrical consumption and mechanical wear increase
Solution Approach 1:
The system performs preliminary forecasting of cloud cover evolution using sky observation images and machine learning models to predict future optimal tilt angles. This allows the solar tracker to anticipate changes in solar radiation patterns and adjust orientation proactively rather than reactively, optimizing energy capture while minimizing unnecessary actuator operations and electrical consumption during transient cloudy periods
Solution Approach 2:
The system changes the control parameter from direct real-time tilt angle optimization to forecasted tilt angle optimization. By using predicted cloud cover patterns and calculated future optimal angles, the system adapts its orientation strategy to balance energy production gains against actuator wear and electrical consumption, particularly during rapidly changing cloudy conditions
2Productivity
If the solar tracker orientation is frequently adjusted to follow optimal angles in cloudy conditions, then solar energy production is improved, but mechanical wear increases
Solution Approach 1:
The system performs preliminary forecasting of cloud cover evolution using sky observation images and machine learning models to predict future optimal tilt angles. This allows the solar tracker to anticipate changes in solar radiation patterns and adjust orientation proactively rather than reactively, optimizing energy capture while minimizing unnecessary actuator operations and electrical consumption during transient cloudy periods
Solution Approach 2:
The system changes the control parameter from direct real-time tilt angle optimization to forecasted tilt angle optimization. By using predicted cloud cover patterns and calculated future optimal angles, the system adapts its orientation strategy to balance energy production gains against actuator wear and electrical consumption, particularly during rapidly changing cloudy conditions
3Adaptability or versatility
If real-time cloud cover observation and frequent orientation adjustments are implemented, then adaptation to cloudy conditions is improved, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical multi-axis tracking mechanisms with a simplified single-axis tilt adjustment system. By using machine learning-based cloud cover forecasting and optimal angle calculation algorithms, the system achieves adaptive performance comparable to complex multi-axis trackers while maintaining the mechanical simplicity of single-axis rotation, thereby reducing device complexity
Solution Approach 2:
The system uses sky observation images as digital copies of the actual sky state to infer cloud cover patterns and predict future solar radiation conditions. This digital representation allows the control system to analyze cloud evolution without requiring direct physical sensors throughout the sky, simplifying the measurement system while maintaining high adaptability to changing conditions
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
This approach optimizes solar energy production while minimizing electrical consumption and mechanical wear by anticipating changes in optimal orientation, ensuring efficient operation even under varying cloudy conditions.
Implementation Method 1
observing the evolution over time of the cloud cover above the single-axis solar tracker, by observing the cloud cover at several consecutive times
Implementation Method 2
translating each observation made by the observation system into a map of the solar luminance and determining the evolution over time of an optimal angle of inclination
Implementation Method 3
conventional to control the orientation of the solar tracker based on an astronomical calculation of the position of the sun, for real-time positioning opposite the sun
Data Source
Figure 1a~2
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Figure 6
AI summary
Method for controlling the orientation of a single-axis solar tracker (1) steerable around an axis of rotation (A), said method implementing the following steps: a) observing the evolution over time of the cloud cover above the solar tracker (1); b) determining the evolution over time of an optimal tilt angle of the solar tracker (1) corresponding substantially to a maximum of solar radiation on the solar tracker (1), as a function of the observed cloud cover; c) predicting the future evolution of the cloud cover based on the observed past evolution of the cloud cover; d) calculating the future evolution of the optimal tilt angle as a function of the prediction of the future evolution of the cloud cover; e) controlling the orientation of the solar tracker (1) as a function of the past evolution of the optimal tilt angle and as a function of the future evolution of the optimal tilt angle.The present invention finds application in the field of solar trackers.