This repository hosts the codebase for the Automated Solar Tracking System 2022 senior project at Missouri University of Science and Technology (Missouri S&T).
Group Members
Matt Bowie, Electrical Engineering - Team Lead/Software Engineer
Jeremy Long, Electrical Engineering - Software Engineer/Hardware Design
Bronson Tavenner, Electrical Engineering - Physical design and construction
Aaron Ivie, Electrical Engineering - Physical design and construction
Technical Advisor
Dr. Tayo Obafemi-Ajayi - Professor of Electrical Engineering, Missouri S&T/Missouri State University
Special Thanks
Dr. Doug Carroll - Director, Missouri S&T/Missouri State University Cooperative Engineering Program
Project Presentation: https://youtu.be/HawqlIfnLps
Abstract
Due to the increasing world population and the depletion of many natural resources, there is a larger need for renewable energy than ever before. Solar energy is a popular alternative to the burning of fossil fuels due to its near infinitely renewable nature. As better technology develops, solar energy can become the best source of renewable energy. The goal of this project was to design an automated solar tracking system that follows the sun as it moves through the sky, increasing the efficiency of energy production when compared to a stationary solar panel. A Raspberry Pi Zero is being used as the system controller. It handles the calculations for the sun’s location via a mathematical model, driving of the two axis motors, and processing of the data collected by the power sensor. To start the program the user will need to insert a flash drive with the coordinates of their current location and flip three switches on the front panel. Once that has been done, the system runs itself with no need for human interface. The system consists of two motors that allow the solar panel to twist and tilt to track the sun based on the mathematical model. The declination angle, latitude, longitude, and hour angle are all factors that play a role into the mathematical model of the sun. The efficiency of a tracking system could greatly impact the future of renewable energy sources.
Software Components
Day_of_Year.py - Reads day of year (1-365) from system date
excel.py - Writes data to xlsx file
Lat_Long_Read.py - Reads latitude and longitude from parameters file
Motor_Control29.py - Contains motor control components
Motor_Control291.py - Contains motor control components for simulation
Parameters.txt - Plain text file for entering lat/long coordinates
Simulation_to_Run.py - Runs system through a simulated day. Useful for demos.
Sun_Model.py - Main file for normal operation. System should run this file on startup.
Sunrise_Sunset.py - Calculates sunrise and sunset time
Time.py - Reads current time from system time and converts to decimal
twist_tilt.py - Calculates number of steps for motors to move
Notes
System should run Sun_Model.py on startup for system to function normally.
Filepath for flash drive should be changed to match the correct destination in excel.py, Lat_Long_Read.py, and Sun_Model.py.