We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier. For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
y: [46., 56.]
corine: [44, 255]
natura: true
Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solvers CBC and Ipopt and does not rely on the commercial solvers Gurobi or CPLEX (for which free academic licenses are available).
algorithm: kmeans # choose from: [hac, kmeans]
p_nom_min: sum
p_min_pu: mean
PyPSA-Eur documentation: https://pypsa-eur.readthedocs.io/en/latest/tutorial.html
These parts are not aligned well:
We can also decide which weather data source should be used to calculate potentials and capacity factor time-series for each carrier. For example, we may want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
Finally, it is possible to pick a solver. For instance, this tutorial uses the open-source solvers CBC and Ipopt and does not rely on the commercial solvers Gurobi or CPLEX (for which free academic licenses are available).