We wanted to use an ancient cooling technique in a modern setting. The system makes ice at night during off peak and then uses the ice to cool the building during the day, avoiding energy use during peak hours. This avoids extra emissions and costs from using peak energy - which uses dirtier power plants.
What it does
Uses data analytics tools with a database of over 3000 buildings to pinpoint the best candidates for ice storage cooling techniques.
How we built it
Using Python to analyze the data and Tableau to visualize the dashboard and business case.
Challenges we ran into
Bugs in Python parsing code, issues with data visualization, difficulty finding financial data.
Accomplishments that we're proud of
A working business analytics tool and recommendations of which buildings to target for ice storage.
What we learned
Ice storage has a huge potential, analytics can help with financing decisions.
What's next for Ice Batteries
We've already spoken to energy financing companies about using our algorithm for their projects. We hope to keep working on improving the model and expanding its capabilities.