Wildcards

Wildcards#

It is easy to run PyPSA-Earth for multiple scenarios using the wildcards feature of snakemake. Wildcards allow to generalise a rule to produce all files that follow a regular expression pattern which e.g. defines one particular scenario. One can think of a wildcard as a parameter that shows up in the input/output file names of the Snakefile and thereby determines which rules to run, what data to retrieve and what files to produce.

Detailed explanations of how wildcards work in snakemake can be found in the relevant section of the documentation.

The {simpl} wildcard#

The {simpl} wildcard specifies number of buses a detailed network model should be pre-clustered to in the rule simplify_network (before cluster_network).

The {clusters} wildcard#

The {clusters} wildcard specifies the number of buses a detailed network model should be reduced to in the rule cluster_network. The number of clusters must be lower than the total number of nodes and higher than the number of countries. However, a country counts twice if it has two asynchronous subnetworks (e.g. Denmark or Italy).

If an m is placed behind the number of clusters (e.g. 100m), generators are only moved to the clustered buses but not aggregated by carrier; i.e. the clustered bus may have more than one e.g. wind generator.

If a flex is placed behind the number of clusters (e.g. 100flex), the number of clusters will be the minimum between the desired value of clusters and the actual number of buses.

The wildcard value all specifies that no clustering is executed and the whole buses are used.

The wildcard value min specifies that the network is clustered to the smallest network possible accounting for the topology of the network (e.g. not fully meshed networks, isolated areas, etc.).

The {ll} wildcard#

The {ll} wildcard specifies what limits on line expansion are set for the optimisation model. It is handled in the rule prepare_network.

The wildcard, in general, consists of two parts:

  1. The first part can be v (for setting a limit on line volume) or c (for setting a limit on line cost)

  2. The second part can be opt or a float bigger than one (e.g. 1.25).

    1. If opt is chosen line expansion is optimised according to its capital cost (where the choice v only considers overhead costs for HVDC transmission lines, while c uses more accurate costs distinguishing between overhead and underwater sections and including inverter pairs).

    2. v1.25 will limit the total volume of line expansion to 25 % of currently installed capacities weighted by individual line lengths; investment costs are neglected.

    3. c1.25 will allow to build a transmission network that costs no more than 25 % more than the current system.

The {opts} wildcard#

The {opts} wildcard triggers optional constraints, which are activated in either prepare_network or the solve_network step. It may hold multiple triggers separated by -, i.e. Co2L-3H contains the Co2L trigger and the 3H switch. There are currently:

The {country} wildcard#

The rules make_summary and plot_summary (generating summaries of all or a subselection of the solved networks) as well as plot_p_nom_map (for plotting the cumulative generation potentials for renewable technologies) can be narrowed to individual countries using the {country} wildcard.

If country=all, then the rule acts on the network for all countries defined in config.yaml. If otherwise country=DE or another 2-letter country code, then the network is narrowed to buses of this country for the rule. For example to get a summary of the energy generated in Germany (in the solution for Europe) use:

snakemake -j 1 results/summaries/elec_s_all_lall_Co2L-3H_DE

The {cutout} wildcard#

The {cutout} wildcard facilitates running the rule build_cutout for all cutout configurations specified under atlite: cutouts:. These cutouts will be stored in a folder specified by {cutout}.

The {technology} wildcard#

The {technology} wildcard specifies for which renewable energy technology to produce availability time series and potentials using the rule build_renewable_profiles. It can take the values onwind, offwind-ac, offwind-dc, and solar but not hydro (since hydroelectric plant profiles are created by a different rule).

The wildcard can moreover be used to create technology specific figures and summaries. For instance {technology} can be used to plot regionally disaggregated potentials with the rule plot_p_nom_max.

The {attr} wildcard#

The {attr} wildcard specifies which attribute is used for size representations of network components on a map plot produced by the rule plot_network. While it might be extended in the future, {attr} currently only supports plotting of p_nom.

The {ext} wildcard#

The {ext} wildcard specifies the file type of the figures the rule plot_network, plot_summary, and plot_p_nom_max produce. Typical examples are pdf and png. The list of supported file formats depends on the used backend. To query the supported file types on your system, issue:

import matplotlib.pyplot as plt

plt.gcf().canvas.get_supported_filetypes()
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