3.4 Tracking systems and sun-tracking algorithms

Solar tracking systems are crucial for maximizing energy capture in concentrated solar power. They rotate panels to follow the sun's path, increasing efficiency by up to 45% compared to fixed systems. Single-axis and dual-axis tracking offer different levels of precision and complexity.

Tracking algorithms calculate sun positions using mathematical models and geographic data. Control systems can be open-loop, relying on predetermined data, or closed-loop, using sensors for real-time adjustments. Accuracy, drive mechanisms, and optimization strategies all impact overall system performance.

Tracking Types

Single-Axis and Dual-Axis Tracking Systems

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• Single-axis tracking rotates solar panels around one axis, typically aligned north-south or east-west
  • Increases energy capture by ~25-35% compared to fixed systems
  • East-west alignment optimizes morning and afternoon sunlight collection
  • North-south alignment maximizes summer energy production
• Dual-axis tracking allows rotation around two perpendicular axes
  • Enables panels to follow the sun's exact position throughout the day and year
  • Boosts energy capture by ~35-45% compared to fixed systems
  • Provides higher efficiency but requires more complex and costly mechanisms

Azimuth-Elevation and Polar Tracking Methods

• Azimuth-elevation tracking uses two separate movements to follow the sun
  • Azimuth rotation adjusts the horizontal angle of panels (east to west)
  • Elevation rotation changes the vertical tilt of panels (up and down)
  • Offers precise sun-tracking but demands sophisticated control systems
• Polar tracking aligns the primary axis parallel to Earth's rotational axis
  • Requires only one motor to track daily sun movement
  • Second axis adjusts seasonally to account for changes in solar declination
  • Balances tracking accuracy with mechanical simplicity

Tracking Algorithms and Control

Sun Position Calculation and Open-Loop Systems

• Sun position algorithms calculate the sun's location based on time and geographic coordinates
  • Utilize mathematical models (NREL's SPA algorithm) to determine solar azimuth and elevation angles
  • Account for factors like atmospheric refraction and Earth's elliptical orbit
• Open-loop tracking systems rely on predetermined sun position data
  • Move solar collectors based on calculated sun positions without real-time feedback
  • Require accurate initial calibration and periodic adjustments
  • Vulnerable to mechanical misalignments or environmental disturbances

Closed-Loop and Sensor-Based Tracking Techniques

• Closed-loop tracking systems continuously adjust based on real-time feedback
  • Use sensors to measure actual sun position or collector alignment
  • Implement control algorithms to minimize tracking errors
  • Adapt to changing environmental conditions (cloud cover, wind)
• Sensor-based tracking employs light-sensitive devices to locate the sun
  • Photodiodes or photoresistors detect intensity differences to guide tracking
  • Can include auxiliary sensors for temperature, wind speed, and precipitation
  • Offers robust performance in varying weather conditions but may struggle with diffuse light

Tracking Performance

Accuracy Metrics and Error Sources

• Tracking accuracy measures how closely the system follows the sun's position
  • Typically expressed in degrees of angular deviation from ideal alignment
  • High-precision systems achieve accuracies of 0.1° or better
• Factors affecting tracking accuracy include:
  • Mechanical tolerances and backlash in drive components
  • Sensor resolution and calibration errors
  • Environmental influences (wind loads, thermal expansion)
  • Control system response time and algorithm precision

Drive Mechanisms and System Optimization

• Tracking drive mechanisms convert control signals into physical movement
  • Electric motors (DC or stepper motors) provide precise, controllable rotation
  • Hydraulic actuators offer high torque for large-scale installations
  • Gear reducers and slew drives enable smooth, low-speed rotation
• Optimizing tracking performance involves:
  • Balancing tracking frequency with energy consumption of drive systems
  • Implementing backtracking algorithms to minimize row-to-row shading
  • Incorporating stow positions for extreme weather protection
  • Utilizing predictive maintenance techniques to ensure long-term reliability