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.
Note
Detailed explanations of how wildcards work in snakemake
can be found in the
relevant section of the documentation.
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
, offwind-float
, and solar
but not hydro
(since hydroelectric plant profiles are created by a different rule)``
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).
The {opts}
wildcard#
The {opts}
wildcard is used for electricity-only studies. It 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 |
---|---|---|---|
|
Resample the time-resolution by averaging over every |
|
In active use |
|
Apply time series segmentation with tsam package to |
|
In active use |
|
Add an overall absolute carbon-dioxide emissions limit configured in |
|
In active use |
|
Add cost for a carbon-dioxide price configured in |
|
In active use |
|
Add monthly cost for a carbon-dioxide price based on historical values built by the rule |
In active use |
|
|
Add minimum and maximum levels of generator nominal capacity per carrier for individual countries. These can be specified in the file linked at |
|
In active use |
|
Require each country or node to on average produce a minimal share of its total consumption itself. Example: |
|
In active use |
|
Require each node to be autarkic. Example: |
|
In active use |
|
Add a per- |
|
Untested |
|
Add a capacity reserve margin of a certain fraction above the peak demand to which renewable generators and storage do not contribute. Ignores network. |
|
Untested |
|
Alter the capital cost ( |
|
In active use |
|
Add an overall absolute gas limit. If configured in |
|
In active use |
|
Add an overall transmission expansion limit relative to existing power transmission infrastructure based on volume ( |
|
In active use |
The {sector_opts}
wildcard#
Warning
More comprehensive documentation for this wildcard will be added soon. To really understand the options here, look in scripts/prepare_sector_network.py
The {sector_opts}
wildcard is only used for sector-coupling studies.
Trigger |
Description |
Definition |
Status |
---|---|---|---|
|
i.e. |
Resample the time-resolution by averaging over every |
In active use |
|
Add an overall absolute carbon-dioxide emissions limit of |
:mod: |
In active use |
|
Alter the capital cost ( |
|
In active use |
|
Add land transport sector |
In active use |
|
|
Add heating sector |
In active use |
|
|
Add biomass |
In active use |
|
|
Add industry sector |
In active use |
|
|
Add agriculture sector |
In active use |
|
|
Add distribution grid with investment costs of |
In active use |
|
|
Sets the CO2 sequestration potential to |
In active use |
The {planning_horizons}
wildcard#
Warning
More comprehensive documentation for this wildcard will be added soon.
The {planning_horizons}
wildcard is only used for sector-coupling studies.
It takes years as values, e.g. 2020, 2030, 2040, 2050.