Single axis solar tracker management method and solar plant implementing said method
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Solution Overview
Problem
Existing solar tracker systems face inefficiencies in maximizing power production due to unpredictable environmental conditions like clouds and terrain irregularities, which can lead to shading and suboptimal irradiance capture.
Innovation Solution
Equipping solar trackers with field sensors and irradiance forecast data to determine optimal positioning adjustments, ensuring that panels are positioned for maximum power generation by differentiating between horizontal and tracking plane irradiance levels and using an outpost tracker for verification and error detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional timer-based tracking systems are used to move panels with the sun, then the system structure is simple, but power production is reduced due to unpredictable cloud coverage and terrain shading
Solution Approach 1:
The system performs preliminary actions by predicting future cloud coverage and irradiance conditions before they occur. The irradiance prediction module forecasts future irradiance levels based on current sensor data and environmental models, allowing the tracker to pre-adjust panel orientation to maximize power capture when conditions change, rather than simply reacting to current sun position
Solution Approach 2:
The system implements feedback through sensor arrays that continuously monitor actual sunlight conditions, cloud coverage, and terrain shading. This real-time feedback is fed into control algorithms that adjust tracker movements to maximize performance, creating a closed-loop system that adapts to changing environmental conditions rather than following predetermined timer-based paths
2Productivity
If sensors and control systems are deployed to monitor sunlight and adjust each row individually, then power production is maximized, but device complexity and cost increase
Solution Approach 1:
The system achieves multi-functionality by using a single integrated control platform that performs multiple tasks: processing sensor data from various types of sensors (light sensors, cameras, weather stations), running irradiance prediction algorithms, executing backtracking calculations, and controlling tracker movements. This universal control system replaces multiple specialized subsystems, reducing overall complexity while maintaining the ability to maximize power production through individualized row adjustment
Solution Approach 2:
The system implements self-service through autonomous operation where the tracker monitors its own performance conditions, predicts future states, and automatically adjusts without human intervention. The control algorithms independently process sensor data, calculate optimal positions considering terrain shading and cloud coverage, and execute movements, making the system self-regulating and reducing the need for external control infrastructure
3Measurement precision
If backtracking is implemented to minimize shading between rows, then irradiance capture is optimized, but the system requires complex real-time calculations and control
Solution Approach 1:
The system performs preliminary backtracking calculations by predicting future sun positions and terrain shading conditions before they occur. The control algorithm pre-computes optimal tracker angles that will minimize shading during upcoming high-irradiance periods, allowing the system to proactively optimize irradiance capture rather than reactively adjusting after shading occurs
Solution Approach 2:
The system replaces complex mechanical coordination between multiple trackers with computational algorithms. Instead of using mechanical linkages or synchronized drive mechanisms to coordinate tracker movements, the system uses software-based irradiance prediction and optimization algorithms that calculate independent optimal positions for each tracker based on terrain data and predicted sun position, simplifying the mechanical control system while achieving precise irradiance optimization
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
Enhances energy production by accurately adjusting solar panel orientation based on real-time and predicted environmental conditions, minimizing shading and optimizing irradiance capture, while maintaining data accuracy through sensor verification and error handling.
Implementation Method 1
some of the solar trackers being furnished with sensors to measure irradiance on the tracking plane
Data Source
Figure 1
AI summary
In order to maximize power output production, a solar plant and single axis solar tracker management method is hereby provided. The object of the invention embraces a solar plant and a method accounting for readings being made by field sensors whilst weather forecast data are provided by third parties such as weather forecast companies collecting and broadcasting weather forecast data related to sun irradiance levels and climate conditions affecting sun irradiance levels, like clouds, pollution or fog. Some of the solar trackers of the plant are furnished with irradiance sensors, whilst the solar plant has a plurality of solar sensors arranged along; these solar sensors being configured to measure irradiance on a horizontal plane. The object of the invention envisages an outpost solar tracker configured to take radiation measurements in an inclined plane and, when it is necessary to verify the measurements of the horizontal sensors, they will go to 0° positions.