Inspiration
With the ongoing global combat against climate change, there has been a need to use sustainable energy solutions. Kenya was privileged to host the Africa Summit and Africa Climate week between 4th to 6th September 2023, where declarations were made that, no country should ever choose between development and climate action. With the declaration, there was a clear need for optimizing renewable energy sources such as the solar energy which became the key inspiration for this project.
What it does
It leverages advanced machine learning models to predict solar radiation and wind turbine power generation based on critical weather parameters in Narok county, Kenya.
How we built it
We created visualizations for effective of solar irradiance data by use of time-series line plots to observe trends and patterns in diffused and global horizontal global irradiance. For weather related visualizations we used a line plot for observing how the weather patterns vary over time, and a Wind rose to visualize wind direction and identify the prevailing wind patterns. We plotted a line graph to compare the diffused horizontal irradiance and global horizontal irradiance measured by different methods over time, to help identify any discrepancies or patterns between the measurements. We then built a machine learning model to predict solar irradiance values from the given features, with an accuracy score of 85%.
Challenges we ran into
- Acquiring recent datasets on the topic from our country.
- Relying on the accuracy of the data.
Accomplishments that we're proud of
We are proud to have explored the intricate relationship between weather parameters and solar radiation and achieved an accuracy of 85% in prediction of the values of solar irradiance.
What we learned
- We have successfully learned and experienced the software development life cycle.
- We have learnt to successfully finish a project and overcome the various challenges encountered.
- The use of machine learning models to find patterns or make predictions from a dataset.
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