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Front Page of Web App
Inspiration
Last year we did a project with our university looking to optimize the implementation of renewable energy sources for residential homes. Specifically, we determined the best designs for home turbines given different environments. In this project, we decided to take this idea of optimizing the implementation of home power further.
What it does
A web application allows users to enter an address and determine if installing a backyard wind turbine or solar panel is more profitable/productive for their location.
How we built it
Using an HTML front-end we send the user's address to a python flask back end where we use a combination of external APIs, web scraping, researched equations, and our own logic and math to predict how the selected piece of technology will perform.
Challenges we ran into
We were hoping to use Google's Earth Engine to gather climate data, but were never approved fro the $25 credit so we had to find alternatives. There aren't alot of good options to gather the nessesary solar and wind data, so we had to use a combination of API's and web scraping to gather the required data which ended up being a bit more convulted than we hoped. Also integrating the back-end with the front-end was very difficult because we don't have much experience with full-stack development working end to end.
Accomplishments that we're proud of
We spent a lot of time coming up with idea for EcoEnergy and we really think it has potential. Home renewable energy sources are quite an investment, so having a tool like this really highlights the benefits and should incentivize people to buy them. We also think it's a great way to try to popularize at-home wind turbine systems by directly comparing them to the output of a solar panel because depending on the location it can be a better investment.
What we learned
During this project we learned how to predict the power output of solar panels and wind turbines based on windspeed and sunlight duration. We learned how to combine a back-end built in python to a front-end built in HTML using flask. We learned even more random stuff about optimizing wind turbine placement so we could recommend different turbines depending on location.
What's next for EcoEnergy
The next step for EcoEnergy would be to improve the integration between the front and back end. As well as find ways to gather more location based climate data which would allow EcoEnergy to predict power generation with greater accuracy.
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