The project focuses on increasing the efficieny of dual-axis solar tracking system by utilizing the UV sensor over the cliched LDR sensors. LDR reaches a saturation and lowers efficency in cloud effect; however on the other hand, UV sensors increases efficieny in cloud effect since UV radiations get
UV Sensor Based Dual-Axis Solar Tracking System: Implementation and Analysis
The project focuses on increasing the efficieny of dual-axis solar tracking system by utilizing the UV sensor over the cliched LDR sensors. LDR reaches a saturation and lowers efficency in cloud effect; however on the other hand, UV sensors increases efficieny in cloud effect since UV radiations gets entrapped and doesn't reach a saturation level as LDRs.
Bringing an innovation in the world of renewable power resources by overcoming the limitation of cliched LDR with a robust UV sensor, thus improved tracking movement and PV energy generation.
The project comprises of two modules; DAST with LDR sensor and DAST with UV sensor. Two Raspberry Pi modules are used along with its operating system (python programming) of the servomotors for daily and elevation angle adjustment from the output of UV sensors and LDR sensors. The two sensors are designated to elavation angle and other two to daily angle. If-else logic is used to compare the values and move the servomotors accordingly. PLA-F material is used for the 3D-designing of servo-case, axis-rotator, bottom case, and plate catcher on AUTODESK.
Static solar plates are less efficient than the single-axis solar tracking system (SAST). Similarly, SAST is less efficient than the dual-axis solar tracking system (DAST). However, DAST with LDR sesnors is less efficient than the DAST with UV sensors. Therefore, this project will help meet the need of power supply by utilizing the sun's energy to greater extend, overcoming the energy crisis in Pakistan.
This project can be implemented in Quaid-e-Azam Solar Park, the first ever utility scale solar power plant in the country, to further increase the efficiency.
The final delivery includes a 30-days output analysis between LDR sensor module and UV sensor muodule. The output will be in graphical form, deriving data from two models placed under the sunlight in Multan, Punjab, Pakistan. The model will remain at the position all day despite the weather change to ensure authenticity of results and avoid any biasing.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry Pi 3 | Equipment | 2 | 9500 | 19000 |
| PLA-F (3D-filament) | Equipment | 4 | 3000 | 12000 |
| BH-1750 UV Light sensor | Equipment | 4 | 450 | 1800 |
| LM-393 LDR Sensor | Equipment | 4 | 75 | 300 |
| 10 Watt Mono-crystalline Solar Plate | Equipment | 2 | 2500 | 5000 |
| SG-5010 Servomotors | Equipment | 4 | 800 | 3200 |
| 3D-Printing Cost | Miscellaneous | 2 | 2500 | 5000 |
| 16X2 Line LCD display | Equipment | 2 | 600 | 1200 |
| Total in (Rs) | 47500 |
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