Energy Crisis Management System

Inspiration

Marlin comes from Srilanka and he personally and he personally knows the turmoil, sadness and despair of energy blackouts and how especially it mostly affects the most vulnerable groups of the population. Marlin noticed that during an energy blackout energy consumption was 0 as soon as the power was turned on the cosumption was almost at its maximum. So there has to be a more effective way to manage power consumption during an energy crisis. How could we regulate energy load to make it more uniform and less abrupt.

What it does

We created a system that looks at current energy consumption per region and intelligently identifies and makes decisions on what regions need to reduce their energy consumption to prevent a blackout.

How we built it

We used Foundry to build our system and utilised. We used the data pipelines and countour to transform the datasets and derive coloums to help drive our insights. We then used workshop to create a fronend for the user to interact and view the data. this includes interactive national heatmaps, identification of over consuming regions, and management of alert assignment and resolution. Finally using the scenarios tools we allowed the user to model the impact of reducing certain regions power draw without real world consequence. This results in more informed decicions. Our system fully used Foundry in every step of the process.

Challenges we ran into

Our main initial challenge was to understand how to use Foundry; however, we were quick on our feet and thanks to kind help and support of the Palantir team, we were able up and running and start creating a product that will truly revolutionize the future.

Accomplishments that we're proud of

We accomplished all the goals we initially set out. Altough daunting at first, we created an MVP and added more advanced supplementary features when we knew we had time.

What we learned

Over the course of the 24h we went from naving no knowledge of Foundry to having a functional app which met all of our intitial design criteria

What's next for Energy Crisis Management System

If the scope of our system were to be increased we would include a regression model which would be able to identify periods of over consuption in advance giving the user alerts in advance as well as live. This would move the system from reactive to proactive, as prevention is always better than cure.

Built With

• foundry
• python