Wildcards

It is easy to run PyPSA-Eur 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.

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:

Trigger Description Definition Status
nH; i.e. 2H-6H Resample the time-resolution by averaging over every n snapshots prepare_network: average_every_nhours() and its caller) In active use
nSEG; e.g. 4380SEG Apply time series segmentation with tsam package to n adjacent snapshots of varying lengths based on capacity factors of varying renewables, hydro inflow and load. prepare_network: apply_time_segmentation() In active use
Co2L Add an overall absolute carbon-dioxide emissions limit configured in electricity: co2limit. If a float is appended an overall emission limit relative to the emission level given in electricity: co2base is added (e.g. Co2L0.05 limits emissisions to 5% of what is given in electricity: co2base) prepare_network: add_co2limit() and its caller In active use
Ep Add cost for a carbon-dioxide price configured in costs: emission_prices: co2 to marginal_cost of generators (other emission types listed in network.carriers possible as well) prepare_network: add_emission_prices() and its caller In active use
CCL Add minimum and maximum levels of generator nominal capacity per carrier for individual countries. These can be specified in the file linked at electricity: agg_p_nom_limits in the configuration. File defaults to data/agg_p_nom_minmax.csv. solve_network In active use
EQ Require each country or node to on average produce a minimal share of its total consumption itself. Example: EQ0.5c demands each country to produce on average at least 50% of its consumption; EQ0.5 demands each node to produce on average at least 50% of its consumption. solve_network In active use
ATK Require each node to be autarkic. Example: ATK removes all lines and links. ATKc removes all cross-border lines and links. prepare_network In active use
BAU Add a per-carrier minimal overall capacity; i.e. at least 40GW of OCGT in Europe; configured in electricity: BAU_mincapacities solve_network: add_opts_constraints() Untested
SAFE Add a capacity reserve margin of a certain fraction above the peak demand to which renewable generators and storage do not contribute. Ignores network. solve_network add_opts_constraints() Untested
carrier+{c|p}factor Alter the capital cost (c) or installable potential (p) of a carrier by a factor. Example: solar+c0.5 reduces the capital cost of solar to 50% of original values. prepare_network In active use

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 availablity 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()