A live journal documenting my journey building quantum and classical algorithms for home energy optimization
Date: January 18, 2025
When I launched this site back in July 2025, it was a broad exploration of energy systems - renewable technologies, sustainability metrics, global energy trends. I was trying to understand everything about our energy future.
But over the past few months, I kept coming back to one question: How do we actually optimize all this renewable energy? Solar and wind are great, but their variability creates real challenges. The more I researched, the more I realized energy optimization is a massive computational problem.
That's when I discovered quantum computing might be relevant here.
Today I'm transforming this site from a general energy information hub into documentation of an actual research project: Using quantum computing to optimize home solar + battery storage.
Here's why:
Can quantum computers help homeowners optimize their solar + battery systems better than traditional computers?
It's a real problem affecting millions of homes, it involves cutting-edge technology, and I can actually test it with free tools from IBM, NREL, and EIA.
Two programs that solve the same problem:
Traditional Python algorithms
IBM's quantum computers via Qiskit
Both will answer: "Given tomorrow's solar forecast and electricity prices, when should a home battery charge and discharge to minimize costs?"
Then I'll compare them and see what I learn.
Modeling a realistic home in Lawrenceville, NJ:
Why Lawrenceville? It's where I live, and I want to validate results against real-world intuition.
My first version will be intentionally simple:
I can add complexity later once the basics work.
I don't know what I'll find, but I'm curious about:
1. How hard is quantum computing to actually use?
2. Do quantum algorithms find better solutions?
3. When might quantum become practical for home energy?
4. What are current quantum hardware limitations?
I'm sharing everything - confusion, mistakes, dead ends - because:
This weekend I'm going to:
Then I'll start building and documenting what I learn.
How hard is it for a high school student to actually use quantum computers?
Do quantum algorithms find better battery schedules?
Which approach is faster for this problem size?
When would this actually help homeowners?
What can't you learn from textbooks alone?
Currently Private - Will be made public when implementation is ready
Will include:
Everything open source so others can replicate, learn from, or improve upon this work.
for updates as I make progress
via the contact page
once implementation is ready and tested
if you spot issues or suggestions
This is real research, which means things won't always work as expected. I'm committing to documenting the messy middle - bugs, wrong approaches, confusion.
That's part of learning, and I think it's valuable to show.
IBM Quantum - Free quantum computing access
NREL - Open solar data
EIA - Electricity market data
The Lawrenceville School - Supporting this research
Site originally launched: July 9, 2025 (general energy focus)
Pivoted to quantum research: January 18, 2025
Last updated: January 18, 2025
This journal is updated as I make progress. Updates might be frequent when things are moving, sparse when I'm stuck, but always honest about where the project stands.