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Inspiration

The inspiration for the SolarViz project came from a desire to optimize solar panel performance and aid in decision-making for future solar projects. ENGIE North America and the University of Iowa envisioned a tool that could harness data analytics to enhance solar installation efficiency, predict energy production, and provide valuable insights.

What it does and How we built it

The Solar Viz project was built using Python and various libraries to streamline the development process. Streamlit was chosen as the primary framework for creating an interactive and user-friendly interface. The application fetches data from an API using the requests library and processes it to calculate solar panel conversion efficiency. Altair was employed for data visualization, creating insightful graphs representing the conversion efficiency over time.

Challenges Faced

During the project we ran into issues accessing the NREL database using their API. We also ran into issues with the output from the solar energy generation API, with many KW/h outputs not making sense. We had to develop logic to filter out these bad data points.

Accomplishments we're proud of

We were able to get around the NREL database not working by parsing and modifying .csv files. We achieved key milestones we are proud of. We created a functional solar efficiency calculator utilizing solar irradiance and panel data, empowering efficient solar panel performance optimization. Integrating external APIs enabled real-time data access for accurate calculations and analyses. Our user-friendly interface, powered by Streamlit, ensures an intuitive user experience. We successfully implemented payback analysis, enhancing solar project decision-making. Solar Viz is a testament to our commitment to sustainable energy and technological advancement.