EnergiAI

Inspiration

I started working on EnergiAI because I kept thinking about how frustrating it is when power goes out unexpectedly or when energy bills suddenly spike. I wanted to see if I could use AI to make energy more reliable, efficient, and predictable. Right now, it’s more of an experiment and learning project, but the idea of using AI to solve real-world energy problems is what’s driving me to keep going.

What it does

At this stage, EnergiAI is mostly conceptual and in early testing. The goal is to eventually turn complicated energy data into insights that could help utility operators and consumers make smarter decisions. Right now, I’m focusing on understanding the data and figuring out which machine learning models might work best.

How we built it

I’ve been working on this solo, starting with basic data collection and analysis. I’m experimenting with Python scripts and machine learning libraries like Scikit-Learn and Pandas. I’ve also been trying to simulate small grid scenarios to see how my code handles different energy patterns. Since it’s still early, a lot of what I’m doing is trial and error.

Challenges we ran into

There have been quite a few hurdles so far. Collecting meaningful sample data is harder than I expected, and figuring out how to process it efficiently with AI is still a work in progress. Security and privacy concerns are also something I’m learning more about. Even though I haven’t solved everything yet, these challenges are teaching me a lot about how real smart grids work.

Accomplishments that we're proud of

Even though it’s early, I’m proud that I’ve set up the basic structure for the project and started testing AI models with sample data. Getting even a small part of the system to work correctly feels like progress, and it’s encouraging to see the concepts I’ve learned in class start to come alive in code.

What we learned

So far, I’ve learned a lot about handling energy data, setting up Python scripts for AI experiments, and troubleshooting problems on my own. I’ve also learned that projects like this take patience and iteration—it’s okay that it’s not fully functional yet, because each step is teaching me something new

What's next for EnergiAI

Next, I want to expand my experiments with larger datasets, refine the AI models, and start thinking about how this could actually connect to a real smart grid in the future. I’m also planning to explore ways to visualize the results so I can better understand the predictions the AI is making

Built With

• data
• python