A High School Research Project by
What if quantum computers could help your home use solar energy more efficiently? I'm exploring this question by building both classical and quantum algorithms to optimize when residential batteries should charge and discharge.
Site Update: This site launched in July 2025 as a general energy exploration. Today I'm pivoting to document this focused quantum computing research project.
Homeowners with solar panels face a daily puzzle: when should they use their generated power, when should they store it in batteries, and when should they sell it back to the grid? With time-of-use electricity pricing, getting this wrong can cost hundreds of dollars per year.
This is a combinatorial optimization problem - and it's exactly the kind of challenge quantum computers might help solve.
I'm just beginning this research journey. Today I'm setting up the tools and data sources needed to build both classical and quantum optimizers.
Building a traditional Python algorithm to optimize battery scheduling
Learning quantum computing and implementing QAOA
Understanding what works and why
Follow my progress on the Research Journal page.
Millions of homes have solar + battery systems
Hands-on experience with emerging technology
Energy optimization affects everyone
Not just a theoretical exercise
This site documents my entire research journey - from learning quantum computing basics to implementing and comparing algorithms.
Learn more about the problem, methodology, and why I chose this project.
Learn More →New to residential energy systems? Start here for background.
Explore Basics →Follow my journey with regular updates, code, and findings.
View Progress →Questions? Want to collaborate? Reach out!
Contact Me →This site documents my entire research journey - from learning quantum computing basics to implementing and comparing algorithms. I'm sharing code, progress updates, challenges, and findings as I go.
Code Repository: Will be made public once the implementation is ready