Free Thinkers

https://freethinkersnasa.github.io/web/

https://drive.google.com/file/d/1QKM-Ssa7Cqe-sc46bML7zqcu5ORn1udS/view

We enhanced the original NASA WorldWeather application with the ability to analyze and visualize numeric data from API sources in CSV and JSON formats. This allows us to aggregate data from multiple sources and offer recommendations to our users. In addition, we can present a more user-friendly and interactive interface.

Possible applications

To demonstrate the great potential of our project, we created an app that recommends the optimal area of placement of solar energy projects. We mined data from several disparate sources and performed analysis on the aggregate.

Our algorithm shows the combined effect of the factors affecting solar panel performance, thereby suggesting the most suitable locations for solar energy projects. We visualize the result in a chart-like way directly on the 3D representation of Earth.

While we were focused on solar energy for the demo, connecting data sources and creating analysis algorithms regarding other kinds of renewable projects has great potential - most particularly wind energy, but also geothermal or nuclear energy.

Our project also shows potential in other areas such as agriculture.

Factors affecting solar panel performance

The amount of energy that is converted into electricity is referred to as solar cell efficiency. Some of the factors that should be taken into consideration to gain optimal performance of the solar array are:

Temperature:

• When higher than 25 °C, every 1°C the efficiency decreases by ~0.258%
• When lower than 25 °C , every 1°C the efficiency increases by ~0.258%

Irradiance:

• According to research the overall energy is increased by about 179.06% with increasing irradiation level between 1000 to 3000 W/m^2
• Higher than 1kW/m^2 in a specific range - every 10W/m^2 the efficiency increases by ~0.9%
• Lower than 1kW/m^2 in a specific range - every 10W/m^2 the efficiency decreases by ~0.9%

Latitude-related recommendations:

• Winter: optimal solar panel tilt angle = (lat * 0.9) + 29 degrees
• Summer: optimal solar panel tilt angle = (lat * 0.9) – 23.5 degrees

We accessed data from 2 major sources:

• NASA POWER - Prediction Of Worldwide Energy Resources
• OpenWeatherMap

As a first step, we used the OpenWeatherMap to make a simple weather forecast app, since that is an almost essential human habit. Then we extracted data such as temperature, cloud overcast, wind speed and so on.

As a second step, we mined data such as solar irradiation or precipitation from the NASA Prediction Of Worldwide Energy Resources (NASA POWER) via the GeoJSON output.

Finally we aggregated the data and used the result in our algorithm to determine optimal placement areas of solar energy projects across the area of the Czech Republic.

While we tried to perform analysis for the entire world, we weren't able to parse and analyze the data in time for the demo - it's still running now!

We are software engineers who met on the first day of the hackathon and merged into a group after talking about our purpose of participation and about each person's ideas for solutions. We have a lot in common in terms of programming thinking as well as the way of thinking about solutions. Even though the time spent working together was not too long, each member of the team was active in the common work.

Our most difficult problem was the identification of the necessary data and retrieving them for parsing and analysis.

We hope that although the project must've been completed in a very short time, it shows the possible direction in the long run and brings new potential into every day practical applications thanks to the valuable and accurate data of NASA and other space agencies.

Data sources:

• NASA POWER - Prediction Of Worldwide Energy Resources
• OpenWeatherMap

Programming language and libraries:

• TypeScript
• React
• React-Globe.gl

#earthdata #earthdataanalysis #energy #solarenergy #renewableenergy #data