Team: 4
School: Capital High
Area of Science: Artificial Intelligence
Proposal: Today, renewable energy is receiving more attention than it ever has before. However, the main argument against it is that most sources do not provide a consistent flow of energy. Solar panels do not function if it is dark or cloudy, which can be highly detrimental to an effective and economically viable renewable alternative. In this project, we would like to optimize the geographic location of solar panels in order to maximize their energy output.
With this project we plan to use Python in order to determine the best spots in the United States to place renewable energy sources such as solar panels. We plan to accomplish this using optimization algorithm(s) which will analyze variables such as sun exposure, cloud cover, day length, altitude, temperature, distance from major population centers, and other variables related to the cost and energy efficiency of renewable energy.
By optimizing the maximum energy output based on geographic location, there is a very real possibility that the results of our project could significantly augment the theoretical energy output of renewables.
Mentor: Drew Einhorn
Team Members:
Valentin Ornelas
Lucas Blakeslee
Ian Olson
Shrey Poshiya
Sponsoring Teacher: Irina Cislaru