His
message: "This semester I taught a new course at TU Berlin on energy
system modelling and data science, for which I built a small website
with energy-focused Python tutorials. The course offers many hands-on
introductions to various libraries that are useful for energy system
modelling and processing data more generally. It includes tutorials and
examples for getting started with Python, numpy, matplotlib, pandas,
geopandas, cartopy, rasterio, atlite, networkx, pyomo, pypsa, plotly,
hvplot, and streamlit. Topics covered include:
- time series analysis (e.g. wind and solar production) - tabular data (e.g. LNG terminals)
- geographical data (e.g. location of power plants)
- data visualisation
- converting weather data to renewable generation
- land eligibility analysis (e.g. where to build wind turbines)
- optimisation
- electricity market modelling
- power flow modelling (linearised)
- capacity expansion planning
- sector-coupling
- interactive visualisation and dashboarding"
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