Configuration#
PyPSA-Eur has several configuration options which are documented in this section.
Configuration Files#
Any PyPSA-Eur configuration can be set in a .yaml
file. The default configurations
config/config.default.yaml
and config/plotting.default.yaml
are maintained in
the repository and cover all the options that are used/ can be set.
To pass your own configuration, you can create a new file, e.g. my_config.yaml
,
and specify the options you want to change. They will override the default settings and
options which are not set, will be inherited from the defaults above.
Another way is to use the config/config.yaml
file, which does not exist in the
repository and is also not tracked by git. But snakemake will always use this file if
it exists. This way you can run snakemake with a custom config without having to
specify the config file each time.
Configuration order of precedence is as follows:
1. Command line options specified with --config
(optional)
2. Custom configuration file specified with --configfile
(optional)
3. The config/config.yaml
file (optional)
4. The default configuration files config/config.default.yaml
and config/plotting.default.yaml
To use your custom configuration file, you need to pass it to the snakemake
command
using the --configfile
option:
$ snakemake -call --configfile my_config.yaml
Warning
In a previous version of PyPSA-Eur (<=2025.04.0
), a full copy of the created config
was stored in the config/config.yaml
file. This is no longer the case. If the
file exists, snakemake will use it, but no new copy will be created.
Top-level configuration#
“Remote” indicates the address of a server used for data exchange, often for clusters and data pushing/pulling.
version: v2025.04.0
tutorial: false
logging:
level: INFO
format: '%(levelname)s:%(name)s:%(message)s'
remote:
ssh: ""
path: ""
Unit |
Values |
Description |
|
---|---|---|---|
version |
– |
0.x.x |
Version of PyPSA-Eur. Descriptive only. |
tutorial |
bool |
{true, false} |
Switch to retrieve the tutorial data set instead of the full data set. |
logging |
|||
– level |
– |
Any of {‘INFO’, ‘WARNING’, ‘ERROR’} |
Restrict console outputs to all infos, warning or errors only |
– format |
– |
Custom format for log messages. See LogRecord attributes. |
|
remote |
|||
– ssh |
– |
Optionally specify the SSH of a remote cluster to be synchronized. |
|
– path |
– |
Optionally specify the file path within the remote cluster to be synchronized. |
run
#
It is common conduct to analyse energy system optimisation models for multiple scenarios for a variety of reasons, e.g. assessing their sensitivity towards changing the temporal and/or geographical resolution or investigating how investment changes as more ambitious greenhouse-gas emission reduction targets are applied.
The run
section is used for running and storing scenarios with different configurations which are not covered by Wildcards. It determines the path at which resources, networks and results are stored. Therefore the user can run different configurations within the same directory. If a run with a non-empty name should use cutouts shared across runs, set shared_cutouts
to true.
run:
prefix: ""
name: ""
scenarios:
enable: false
file: config/scenarios.yaml
disable_progressbar: false
shared_resources:
policy: false
exclude: []
shared_cutouts: true
use_shadow_directory: false
Unit |
Values |
Description |
|
---|---|---|---|
name |
– |
str/list |
Specify a name for your run. Results will be stored under this name. If |
prefix |
– |
str |
Prefix for the run name which is used as a top-layer directory name in the results and resources folders. |
scenarios |
|||
– enable |
bool |
{true, false} |
Switch to select whether workflow should generate scenarios based on |
– file |
str |
Path to the scenario yaml file. The scenario file contains config overrides for each scenario. In order to be taken account, |
|
disable_progressbar |
bool |
{true, false} |
Switch to select whether progressbar should be disabled. |
shared_resources |
|||
– policy |
bool/str |
Boolean switch to select whether resources should be shared across runs. If a string is passed, this is used as a subdirectory name for shared resources. If set to ‘base’, only resources before creating the elec.nc file are shared. |
|
– exclude |
str |
For the case shared_resources=base, specify additional files that should not be shared across runs. |
|
shared_cutouts |
bool |
{true, false} |
Switch to select whether cutouts should be shared across runs. |
use_shadow_directory |
bool |
{true, false} |
Set to |
foresight
#
foresight: overnight
Unit |
Values |
Description |
|
---|---|---|---|
foresight |
string |
{overnight, myopic, perfect} |
See Foresight Options for detail explanations. |
Note
If you use myopic or perfect foresight, the planning horizon in The {planning_horizons} wildcard in scenario has to be set.
scenario
#
The scenario
section is an extraordinary section of the config file
that is strongly connected to the Wildcards and is designed to
facilitate running multiple scenarios through a single command
# for electricity-only studies
$ snakemake -call solve_elec_networks
# for sector-coupling studies
$ snakemake -call solve_sector_networks
For each wildcard, a list of values is provided. The rule
solve_all_elec_networks
will trigger the rules for creating
results/networks/base_s_{clusters}_elec_{opts}.nc
for all
combinations of the provided wildcard values as defined by Python’s
itertools.product(…) function
that snakemake’s expand(…) function
uses.
An exemplary dependency graph (starting from the simplification rules) then looks like this:

scenario:
clusters:
- 39
- 128
- 256
opts:
- ''
sector_opts:
- ''
planning_horizons:
# - 2020
# - 2030
# - 2040
- 2050
Unit |
Values |
Description |
|
---|---|---|---|
clusters |
– |
List of |
|
opts |
– |
List of |
|
sector_opts |
– |
List of |
|
planning_horizons |
– |
List of |
countries
#
countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK', 'XK']
Unit |
Values |
Description |
|
---|---|---|---|
countries |
– |
Subset of {‘AL’, ‘AT’, ‘BA’, ‘BE’, ‘BG’, ‘CH’, ‘CZ’, ‘DE’, ‘DK’, ‘EE’, ‘ES’, ‘FI’, ‘FR’, ‘GB’, ‘GR’, ‘HR’, ‘HU’, ‘IE’, ‘IT’, ‘LT’, ‘LU’, ‘LV’, ‘MD’, ‘ME’, ‘MK’, ‘NL’, ‘NO’, ‘PL’, ‘PT’, ‘RO’, ‘RS’, ‘SE’, ‘SI’, ‘SK’, ‘UA’, ‘XK’} |
European countries defined by their Two-letter country codes (ISO 3166-1) which should be included in the energy system model. |
snapshots
#
Specifies the temporal range to build an energy system model for as arguments to pandas.date_range
snapshots:
start: "2013-01-01"
end: "2014-01-01"
inclusive: 'left'
Unit |
Values |
Description |
|
---|---|---|---|
start |
– |
str or list of datetime-like; e.g. YYYY-MM-DD |
Left bound of date range |
end |
– |
str or list of datetime-like; e.g. YYYY-MM-DD |
Right bound of date range |
inclusive |
– |
One of {‘neither’, ‘both’, ‘left’, ‘right’} |
Make the time interval closed to the |
enable
#
Switches for some rules and optional features.
enable:
retrieve: auto
retrieve_databundle: true
retrieve_cost_data: true
build_cutout: false
retrieve_cutout: true
drop_leap_day: true
Unit |
Values |
Description |
|
---|---|---|---|
retrieve |
str or bool |
{auto, true, false} |
Switch to include (true) or exclude (false) the retrieve_* rules of snakemake into the workflow; ‘auto’ sets true|false based on availability of an internet connection to prevent issues with snakemake failing due to lack of internet connection. |
retrieve_databundle |
bool |
{true, false} |
Switch to retrieve databundle from zenodo via the rule |
retrieve_cost_data |
bool |
{true, false} |
Switch to retrieve technology cost data from technology-data repository. |
build_cutout |
bool |
{true, false} |
Switch to enable the building of cutouts via the rule |
retrieve_cutout |
bool |
{true, false} |
Switch to enable the retrieval of cutouts from zenodo with |
drop_leap_day |
bool |
{true, false} |
Switch to drop February 29 from all time-dependent data in leap years |
co2 budget
#
co2_budget:
2020: 0.720 # average emissions of 2019 to 2021 relative to 1990, CO2 excl LULUCF, EEA data, European Environment Agency. (2023a). Annual European Union greenhouse gas inventory 1990–2021 and inventory report 2023 - CRF Table. https://unfccc.int/documents/627830
2025: 0.648 # With additional measures (WAM) projection, CO2 excl LULUCF, European Environment Agency. (2023e). Member States’ greenhouse gas (GHG) emission projections 2023. https://www.eea.europa.eu/en/datahub/datahubitem-view/4b8d94a4-aed7-4e67-a54c-0623a50f48e8
2030: 0.450 # 55% reduction by 2030 (Ff55)
2035: 0.250
2040: 0.100 # 90% by 2040
2045: 0.050
2050: 0.000 # climate-neutral by 2050
Unit |
Values |
Description |
|
---|---|---|---|
co2_budget |
– |
Dictionary with planning horizons as keys. |
CO2 budget as a fraction of 1990 emissions. Overwritten if |
Note
this parameter is over-ridden if Co2Lx
or cb
is set in
sector_opts.
electricity
#
electricity:
voltages: [220., 300., 330., 380., 400., 500., 750.]
base_network: osm-prebuilt
osm-prebuilt-version: 0.6
gaslimit_enable: false
gaslimit: false
co2limit_enable: false
co2limit: 7.75e+7
co2base: 1.487e+9
operational_reserve:
activate: false
epsilon_load: 0.02
epsilon_vres: 0.02
contingency: 4000
max_hours:
battery: 6
H2: 168
extendable_carriers:
Generator: [solar, solar-hsat, onwind, offwind-ac, offwind-dc, offwind-float, OCGT, CCGT]
StorageUnit: [] # battery, H2
Store: [battery, H2]
Link: [] # H2 pipeline
powerplants_filter: (DateOut >= 2024 or DateOut != DateOut) and not (Country == 'Germany' and Fueltype == 'Nuclear')
custom_powerplants: false
everywhere_powerplants: []
conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
renewable_carriers: [solar, solar-hsat, onwind, offwind-ac, offwind-dc, offwind-float, hydro]
estimate_renewable_capacities:
enable: true
from_gem: true
year: 2020
expansion_limit: false
technology_mapping:
Offshore: offwind-ac
Onshore: onwind
PV: solar
autarky:
enable: false
by_country: false
transmission_limit: vopt
Unit |
Values |
Description |
|
---|---|---|---|
voltages |
kV |
Any subset of {220., 300., 330., 380., 400., 500., 750.} |
Voltage levels to consider |
base_network |
– |
Any value in {‘entsoegridkit’, ‘osm-prebuilt’, ‘osm-raw} |
Specify the underlying base network, i.e. GridKit (based on ENTSO-E web map extract, OpenStreetMap (OSM) prebuilt or raw (built from raw OSM data), takes longer. |
osm-prebuilt-version |
– |
float, any value in range 0.1-0.6 |
Choose the version of the prebuilt OSM network. Defaults to latest Zenodo release. |
gaslimit_enable |
bool |
true or false |
Add an overall absolute gas limit configured in |
gaslimit |
MWhth |
float or false |
Global gas usage limit |
co2limit_enable |
bool |
true or false |
Add an overall absolute carbon-dioxide emissions limit configured in |
co2limit |
\(t_{CO_2-eq}/a\) |
float |
Cap on total annual system carbon dioxide emissions |
co2base |
\(t_{CO_2-eq}/a\) |
float |
Reference value of total annual system carbon dioxide emissions if relative emission reduction target is specified in |
operational_reserve |
Settings for reserve requirements following GenX |
||
– activate |
bool |
true or false |
Whether to take operational reserve requirements into account during optimisation |
– epsilon_load |
– |
float |
share of total load |
– epsilon_vres |
– |
float |
share of total renewable supply |
– contingency |
MW |
float |
fixed reserve capacity |
max_hours |
|||
– battery |
h |
float |
Maximum state of charge capacity of the battery in terms of hours at full output capacity |
– H2 |
h |
float |
Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity |
extendable_carriers |
|||
– Generator |
– |
Any extendable carrier |
Defines existing or non-existing conventional and renewable power plants to be extendable during the optimization. Conventional generators can only be built/expanded where already existent today. If a listed conventional carrier is not included in the |
– StorageUnit |
– |
Any subset of {‘battery’,’H2’} |
Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. |
– Store |
– |
Any subset of {‘battery’,’H2’} |
Adds extendable storage units (battery and/or hydrogen) at every node/bus after clustering without capacity limits and with zero initial capacity. |
– Link |
– |
Any subset of {‘H2 pipeline’} |
Adds extendable links (H2 pipelines only) at every connection where there are lines or HVDC links without capacity limits and with zero initial capacity. Hydrogen pipelines require hydrogen storage to be modelled as |
powerplants_filter |
– |
use pandas.query strings here, e.g. |
Filter query for the default powerplant database. |
custom_powerplants |
– |
use pandas.query strings here, e.g. |
Filter query for the custom powerplant database. |
everywhere_powerplants |
– |
Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass} |
List of conventional power plants to add to every node in the model with zero initial capacity. To be used in combination with |
conventional_carriers |
– |
Any subset of {nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass} |
List of conventional power plants to include in the model from |
renewable_carriers |
– |
Any subset of {solar, onwind, offwind-ac, offwind-dc, offwind-float, hydro} |
List of renewable generators to include in the model. |
estimate_renewable_capacities |
|||
– enable |
bool |
Activate routine to estimate renewable capacities in rule |
|
– from_gem |
– |
bool |
Add renewable capacities from Global Energy Monitor’s Global Solar Power Tracker and Global Energy Monitor’s Global Wind Power Tracker. |
– year |
– |
bool |
Renewable capacities are based on existing capacities reported by IRENA (IRENASTAT) for the specified year |
– expansion_limit |
– |
float or false |
Artificially limit maximum IRENA capacities to a factor. For example, an |
– technology_mapping |
Mapping between PyPSA-Eur and powerplantmatching technology names |
||
– – Offshore |
– |
{onwind} |
PyPSA-Eur carrier that is considered for existing onshore wind capacities (IRENA, GEM). |
– – Offshore |
– |
Any of {offwind-ac, offwind-dc, offwind-float} |
PyPSA-Eur carrier that is considered for existing offshore wind technology (IRENA, GEM). |
– – PV |
– |
{solar} |
PyPSA-Eur carrier that is considered for existing solar PV capacities (IRENA, GEM). |
autarky |
|||
– enable |
bool |
true or false |
Require each node to be autarkic by removing all lines and links. |
– by_country |
bool |
true or false |
Require each country to be autarkic by removing all cross-border lines and links. |
transmission_limit |
str |
Values like ‘vopt’, ‘v1.25’, ‘copt’, ‘c1.25’ |
Limit on transmission expansion. The first part can be |
atlite
#
Define and specify the atlite.Cutout
used for calculating renewable potentials and time-series. All options except for features
are directly used as cutout parameters.
atlite:
cutout_directory: cutouts
default_cutout: europe-2013-sarah3-era5
nprocesses: 4
show_progress: false
cutouts:
# use 'base' to determine geographical bounds and time span from config
# base:
# module: era5
europe-2013-sarah3-era5:
module: [sarah, era5] # in priority order
x: [-12., 42.]
y: [33., 72.]
dx: 0.3
dy: 0.3
time: ['2013', '2013']
Unit |
Values |
Description |
|
---|---|---|---|
cutout_directory |
– |
str |
Directory to store cutouts. |
default_cutout |
– |
str|list |
Defines a default cutout. Can refer to a single cutout or a list of cutouts. |
nprocesses |
– |
int |
Number of parallel processes in cutout preparation |
show_progress |
bool |
true/false |
Whether progressbar for atlite conversion processes should be shown. False saves time. |
cutouts |
|||
– {name} |
– |
Convention is to name cutouts like |
Name of the cutout netcdf file. The user may specify multiple cutouts under configuration |
– – module |
– |
Subset of {‘era5’,’sarah’} |
Source of the reanalysis weather dataset (e.g. ERA5 or SARAH-3) |
– – x |
° |
Float interval within [-180, 180] |
Range of longitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes. |
– – y |
° |
Float interval within [-90, 90] |
Range of latitudes to download weather data for. If not defined, it defaults to the spatial bounds of all bus shapes. |
– – dx |
° |
Larger than 0.25 |
Grid resolution for longitude |
– – dy |
° |
Larger than 0.25 |
Grid resolution for latitude |
– – time |
Time interval within [‘1979’, ‘2018’] (with valid pandas date time strings) |
Time span to download weather data for. If not defined, it defaults to the time interval spanned by the snapshots. |
|
– – features |
String or list of strings with valid cutout features (‘inlfux’, ‘wind’). |
When freshly building a cutout, retrieve data only for those features. If not defined, it defaults to all available features. |
renewable
#
onwind
#
renewable:
onwind:
cutout: default
resource:
method: wind
turbine: Vestas_V112_3MW
smooth: false
add_cutout_windspeed: true
resource_classes: 1
capacity_per_sqkm: 3
# correction_factor: 0.93
corine:
grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32]
distance: 1000
distance_grid_codes: [1, 2, 3, 4, 5, 6]
luisa: false
# grid_codes: [1111, 1121, 1122, 1123, 1130, 1210, 1221, 1222, 1230, 1241, 1242]
# distance: 1000
# distance_grid_codes: [1111, 1121, 1122, 1123, 1130, 1210, 1221, 1222, 1230, 1241, 1242]
natura: true
excluder_resolution: 100
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
str|list |
Specifies the weather data cutout file(s) to use. |
resource |
|||
– method |
– |
Must be ‘wind’ |
A superordinate technology type. |
– turbine |
– |
One of turbine types included in atlite. Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available. |
Specifies the turbine type and its characteristic power curve. |
– smooth |
– |
{True, False} |
Switch to apply a gaussian kernel density smoothing to the power curve. |
resource_classes |
– |
int |
Number of resource classes per clustered region. |
capacity_per_sqkm |
\(MW/km^2\) |
float |
Allowable density of wind turbine placement. |
corine |
|||
– grid_codes |
– |
Any subset of the CORINE Land Cover code list |
Specifies areas according to CORINE Land Cover codes which are generally eligible for wind turbine placement. |
– distance |
m |
float |
Distance to keep from areas specified in |
– distance_grid_codes |
– |
Any subset of the CORINE Land Cover code list |
Specifies areas according to CORINE Land Cover codes to which wind turbines must maintain a distance specified in the setting |
luisa |
|||
– grid_codes |
– |
Any subset of the LUISA Base Map codes in Annex 1 |
Specifies areas according to the LUISA Base Map codes which are generally eligible for wind turbine placement. |
– distance |
m |
float |
Distance to keep from areas specified in |
– distance_grid_codes |
– |
Any subset of the LUISA Base Map codes in Annex 1 |
Specifies areas according to the LUISA Base Map codes to which wind turbines must maintain a distance specified in the setting |
natura |
bool |
{true, false} |
Switch to exclude Natura 2000 natural protection areas. Area is excluded if |
clip_p_max_pu |
p.u. |
float |
To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero. |
correction_factor |
– |
float |
Correction factor for capacity factor time series. |
excluder_resolution |
m |
float |
Resolution on which to perform geographical elibility analysis. |
Note
Notes on capacity_per_sqkm
. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 30% fraction of the already restricted
area is available for installation of wind generators due to competing land use and likely public
acceptance issues.
Note
The default choice for corine grid_codes
was based on Scholz, Y. (2012). Renewable energy based electricity supply at low costs
development of the REMix model and application for Europe. ( p.42 / p.28)
offwind-x
#
offwind-ac:
cutout: default
resource:
method: wind
turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
smooth: false
add_cutout_windspeed: true
resource_classes: 1
capacity_per_sqkm: 2
correction_factor: 0.8855
corine: [44, 255]
luisa: false # [0, 5230]
natura: true
ship_threshold: 400
max_depth: 60
max_shore_distance: 30000
excluder_resolution: 200
clip_p_max_pu: 1.e-2
landfall_length: 10
offwind-dc:
cutout: default
resource:
method: wind
turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
smooth: false
add_cutout_windspeed: true
resource_classes: 1
capacity_per_sqkm: 2
correction_factor: 0.8855
corine: [44, 255]
luisa: false # [0, 5230]
natura: true
ship_threshold: 400
max_depth: 60
min_shore_distance: 30000
excluder_resolution: 200
clip_p_max_pu: 1.e-2
landfall_length: 10
offwind-float:
cutout: default
resource:
method: wind
turbine: NREL_ReferenceTurbine_5MW_offshore
smooth: false
add_cutout_windspeed: true
resource_classes: 1
# ScholzPhd Tab 4.3.1: 10MW/km^2
capacity_per_sqkm: 2
correction_factor: 0.8855
# proxy for wake losses
# from 10.1016/j.energy.2018.08.153
# until done more rigorously in #153
corine: [44, 255]
natura: true
ship_threshold: 400
excluder_resolution: 200
min_depth: 60
max_depth: 1000
clip_p_max_pu: 1.e-2
landfall_length: 10
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
str|list |
Specifies the weather data cutout file(s) to use. |
resource |
|||
– method |
– |
Must be ‘wind’ |
A superordinate technology type. |
– turbine |
– |
One of turbine types included in atlite. Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available. |
Specifies the turbine type and its characteristic power curve. |
– smooth |
– |
{True, False} |
Switch to apply a gaussian kernel density smoothing to the power curve. |
resource_classes |
– |
int |
Number of resource classes per clustered region. |
capacity_per_sqkm |
\(MW/km^2\) |
float |
Allowable density of wind turbine placement. |
correction_factor |
– |
float |
Correction factor for capacity factor time series. |
excluder_resolution |
m |
float |
Resolution on which to perform geographical elibility analysis. |
corine |
– |
Any realistic subset of the CORINE Land Cover code list |
Specifies areas according to CORINE Land Cover codes which are generally eligible for AC-connected offshore wind turbine placement. |
luisa |
– |
Any subset of the LUISA Base Map codes in Annex 1 |
Specifies areas according to the LUISA Base Map codes which are generally eligible for AC-connected offshore wind turbine placement. |
natura |
bool |
{true, false} |
Switch to exclude Natura 2000 natural protection areas. Area is excluded if |
ship_threshold |
– |
float |
Ship density threshold from which areas are excluded. |
max_depth |
m |
float |
Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential. |
min_shore_distance |
m |
float |
Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential. |
max_shore_distance |
m |
float |
Maximum distance to the shore above which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential. |
clip_p_max_pu |
p.u. |
float |
To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero. |
landfall_length |
km |
float |
Fixed length of the cable connection that is onshorelandfall in km. If ‘centroid’, the length is calculated as the distance to centroid of the onshore bus. |
Note
Notes on capacity_per_sqkm
. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 20% fraction of the already restricted
area is available for installation of wind generators due to competing land use and likely public
acceptance issues.
Note
Notes on correction_factor
. Correction due to proxy for wake losses
from 10.1016/j.energy.2018.08.153
until done more rigorously in #153
solar
#
solar:
cutout: default
resource:
method: pv
panel: CSi
orientation:
slope: 35.
azimuth: 180.
resource_classes: 1
capacity_per_sqkm: 5.1
# correction_factor: 0.854337
corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
luisa: false # [1111, 1121, 1122, 1123, 1130, 1210, 1221, 1222, 1230, 1241, 1242, 1310, 1320, 1330, 1410, 1421, 1422, 2110, 2120, 2130, 2210, 2220, 2230, 2310, 2410, 2420, 3210, 3320, 3330]
natura: true
excluder_resolution: 100
clip_p_max_pu: 1.e-2
solar-hsat:
cutout: default
resource:
method: pv
panel: CSi
orientation:
slope: 35.
azimuth: 180.
tracking: horizontal
resource_classes: 1
capacity_per_sqkm: 4.43 # 15% higher land usage acc. to NREL
corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
luisa: false # [1111, 1121, 1122, 1123, 1130, 1210, 1221, 1222, 1230, 1241, 1242, 1310, 1320, 1330, 1410, 1421, 1422, 2110, 2120, 2130, 2210, 2220, 2230, 2310, 2410, 2420, 3210, 3320, 3330]
natura: true
excluder_resolution: 100
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
str|list |
Specifies the weather data cutout file(s) to use. |
resource |
|||
– method |
– |
Must be ‘pv’ |
A superordinate technology type. |
– panel |
– |
One of {‘Csi’, ‘CdTe’, ‘KANENA’} as defined in atlite . Can be a string or a dictionary with years as keys which denote the year another turbine model becomes available. |
Specifies the solar panel technology and its characteristic attributes. |
– orientation |
|||
– – slope |
° |
Realistically any angle in [0., 90.] |
Specifies the tilt angle (or slope) of the solar panel. A slope of zero corresponds to the face of the panel aiming directly overhead. A positive tilt angle steers the panel towards the equator. |
– – azimuth |
° |
Any angle in [0., 360.] |
Specifies the azimuth orientation of the solar panel. South corresponds to 180.°. |
resource_classes |
– |
int |
Number of resource classes per clustered region. |
capacity_per_sqkm |
\(MW/km^2\) |
float |
Allowable density of solar panel placement. |
correction_factor |
– |
float |
A correction factor for the capacity factor (availability) time series. |
corine |
– |
Any subset of the CORINE Land Cover code list |
Specifies areas according to CORINE Land Cover codes which are generally eligible for solar panel placement. |
luisa |
– |
Any subset of the LUISA Base Map codes in Annex 1 |
Specifies areas according to the LUISA Base Map codes which are generally eligible for solar panel placement. |
natura |
bool |
{true, false} |
Switch to exclude Natura 2000 natural protection areas. Area is excluded if |
clip_p_max_pu |
p.u. |
float |
To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero. |
excluder_resolution |
m |
float |
Resolution on which to perform geographical elibility analysis. |
Note
Notes on capacity_per_sqkm
. ScholzPhd Tab 4.3.1: 170 MW/km^2 and assuming 1% of the area can be used for solar PV panels.
Correction factor determined by comparing uncorrected area-weighted full-load hours to those
published in Supplementary Data to Pietzcker, Robert Carl, et al. “Using the sun to decarbonize the power
sector – The economic potential of photovoltaics and concentrating solar
power.” Applied Energy 135 (2014): 704-720.
This correction factor of 0.854337 may be in order if using reanalysis data.
for discussion refer to this <issue PyPSA/pypsa-eur#285>
hydro
#
hydro:
cutout: default
carriers: [ror, PHS, hydro]
PHS_max_hours: 6
hydro_max_hours: "energy_capacity_totals_by_country" # one of energy_capacity_totals_by_country, estimate_by_large_installations or a float
flatten_dispatch: false
flatten_dispatch_buffer: 0.2
clip_min_inflow: 1.0
eia_norm_year: false
eia_correct_by_capacity: false
eia_approximate_missing: false
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
str|list |
Specifies the weather data cutout file(s) to use. |
carriers |
– |
Any subset of {‘ror’, ‘PHS’, ‘hydro’} |
Specifies the types of hydro power plants to build per-unit availability time series for. ‘ror’ stands for run-of-river plants, ‘PHS’ represents pumped-hydro storage, and ‘hydro’ stands for hydroelectric dams. |
PHS_max_hours |
h |
float |
Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity |
hydro_max_hours |
h |
Any of {float, ‘energy_capacity_totals_by_country’, ‘estimate_by_large_installations’} |
Maximum state of charge capacity of the pumped-hydro storage (PHS) in terms of hours at full output capacity |
flatten_dispatch |
bool |
{true, false} |
Consider an upper limit for the hydro dispatch. The limit is given by the average capacity factor plus the buffer given in |
flatten_dispatch_buffer |
– |
float |
If |
clip_min_inflow |
MW |
float |
To avoid too small values in the inflow time series, values below this threshold are set to zero. |
eia_norm_year |
– |
Year in EIA hydro generation dataset; or False to disable |
To specify a specific year by which hydro inflow is normed that deviates from the snapshots’ year |
eia_correct_by_capacity |
– |
boolean |
Correct EIA annual hydro generation data by installed capacity. |
eia_approximate_missing |
– |
boolean |
Approximate hydro generation data for years not included in EIA dataset through a regression based on annual runoff. |
conventional
#
Define additional generator attribute for conventional carrier types. If a scalar value is given it is applied to all generators. However if a string starting with “data/” is given, the value is interpreted as a path to a csv file with country specific values. Then, the values are read in and applied to all generators of the given carrier in the given country. Note that the value(s) overwrite the existing values.
conventional:
unit_commitment: false
dynamic_fuel_price: false
nuclear:
p_max_pu: "data/nuclear_p_max_pu.csv" # float of file name
Unit |
Values |
Description |
|
---|---|---|---|
unit_commitment |
bool |
{true, false} |
Allow the overwrite of ramp_limit_up, ramp_limit_start_up, ramp_limit_shut_down, p_min_pu, min_up_time, min_down_time, and start_up_cost of conventional generators. Refer to the CSV file „unit_commitment.csv“. |
dynamic_fuel_price |
bool |
{true, false} |
Consider the monthly fluctuating fuel prices for each conventional generator. Refer to the CSV file “data/validation/monthly_fuel_price.csv”. |
{name} |
– |
string |
For any carrier/technology overwrite attributes as listed below. |
– {attribute} |
– |
string or float |
For any attribute, can specify a float or reference to a file path to a CSV file giving floats for each country (2-letter code). |
lines
#
lines:
types:
220.: "Al/St 240/40 2-bundle 220.0"
300.: "Al/St 240/40 3-bundle 300.0"
330.: "Al/St 240/40 3-bundle 300.0"
380.: "Al/St 240/40 4-bundle 380.0"
400.: "Al/St 240/40 4-bundle 380.0"
500.: "Al/St 240/40 4-bundle 380.0"
750.: "Al/St 560/50 4-bundle 750.0"
s_max_pu: 0.7
s_nom_max: .inf
max_extension: 20000 #MW
length_factor: 1.25
reconnect_crimea: true
under_construction: 'keep' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity for lines in grid extract
dynamic_line_rating:
activate: false
cutout: default
correction_factor: 0.95
max_voltage_difference: false
max_line_rating: false
Unit |
Values |
Description |
|
---|---|---|---|
types |
– |
Values should specify a line type in PyPSA. Keys should specify the corresponding voltage level (e.g. 220., 300. and 380. kV) |
Specifies line types to assume for the different voltage levels of the ENTSO-E grid extraction. Should normally handle voltage levels 220, 300, and 380 kV |
s_max_pu |
– |
Value in [0.,1.] |
Correction factor for line capacities ( |
s_nom_max |
MW |
float |
Global upper limit for the maximum capacity of each extendable line. |
max_extension |
MW |
float |
Upper limit for the extended capacity of each extendable line. |
length_factor |
– |
float |
Correction factor to account for the fact that buses are not connected by lines through air-line distance. |
under_construction |
– |
One of {‘zero’: set capacity to zero, ‘remove’: remove completely, ‘keep’: keep with full capacity} |
Specifies how to handle lines which are currently under construction. |
reconnect_crimea |
– |
true or false |
Whether to reconnect Crimea to the Ukrainian grid |
dynamic_line_rating |
|||
– activate |
bool |
true or false |
Whether to take dynamic line rating into account |
– cutout |
– |
str|list |
Specifies the weather data cutout file(s) to use. |
– correction_factor |
– |
float |
Factor to compensate for overestimation of wind speeds in hourly averaged wind data |
– max_voltage_difference |
deg |
float |
Maximum voltage angle difference in degrees or ‘false’ to disable |
– max_line_rating |
– |
float |
Maximum line rating relative to nominal capacity without DLR, e.g. 1.3 or ‘false’ to disable |
links
#
links:
p_max_pu: 1.0
p_min_pu: -1.0
p_nom_max: .inf
max_extension: 30000 #MW
length_factor: 1.25
under_construction: 'keep' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity for lines in grid extract
Unit |
Values |
Description |
|
---|---|---|---|
p_max_pu |
– |
Value in [0.,1.] |
Correction factor for link capacities |
p_min_pu |
– |
Value in [-1.,0.] |
Correction factor for link capacities |
p_nom_max |
MW |
float |
Global upper limit for the maximum capacity of each extendable DC link. |
max_extension |
MW |
float |
Upper limit for the extended capacity of each extendable DC link. |
length_factor |
– |
float |
Correction factor to account for the fact that buses are not connected by links through air-line distance. |
under_construction |
– |
One of {‘zero’: set capacity to zero, ‘remove’: remove completely, ‘keep’: keep with full capacity} |
Specifies how to handle lines which are currently under construction. |
transmission projects
#
Allows to define additional transmission projects that will be added to the base network, e.g., from the TYNDP 2020 dataset. The projects are read in from the CSV files in the subfolder of data/transmission_projects/
. New transmission projects, e.g. from TYNDP 2024, can be added in a new subfolder of transmission projects, e.g. data/transmission_projects/tyndp2024
while extending the list of transmission_projects
in the config.yaml
by tyndp2024
. The CSV files in the project folder should have the same columns as the CSV files in the template folder data/transmission_projects/template
.
transmission_projects:
enable: true
include:
tyndp2020: true
nep: true
manual: true
skip:
- upgraded_lines
- upgraded_links
status:
- under_construction
- in_permitting
- confirmed
#- planned_not_yet_permitted
#- under_consideration
new_link_capacity: zero #keep or zero
Unit |
Values |
Description |
|
---|---|---|---|
enable |
bool |
{true,false} |
Whether to integrate this transmission projects or not. |
include |
– |
Name of the transmission projects. They should be unique and have to be provided in the data/transmission_projects folder. |
|
– tyndp2020 |
bool |
{true,false} |
Whether to integrate the TYNDP 2020 dataset. |
– nep |
bool |
{true,false} |
Whether to integrate the German network development plan dataset. |
– manual |
bool |
{true,false} |
Whether to integrate the manually added transmission projects. They are taken from the previously existing links_tyndp.csv file. |
skip |
list |
Type of lines to skip from all transmission projects. Possible values are: |
|
status |
list or dict |
Status to include into the model as list or as dict with name of project and status to include. Possible values for status are |
|
new_link_capacity |
– |
{zero,keep} |
Whether to set the new link capacity to the provided capacity or set it to zero. |
transformers
#
transformers:
x: 0.1
s_nom: 2000.
type: ''
Unit |
Values |
Description |
|
---|---|---|---|
x |
p.u. |
float |
Series reactance (per unit, using |
s_nom |
MVA |
float |
Limit of apparent power which can pass through branch. Overwritten if |
type |
– |
Specifies transformer types to assume for the transformers of the ENTSO-E grid extraction. |
load
#
load:
fill_gaps:
enable: true
interpolate_limit: 3
time_shift_for_large_gaps: 1w
manual_adjustments: true # false
scaling_factor: 1.0
fixed_year: false # false or year (e.g. 2013)
supplement_synthetic: true
distribution_key:
gdp: 0.6
population: 0.4
Unit |
Values |
Description |
|
---|---|---|---|
fill_gaps |
– |
– |
Gaps filling strategy used. |
– enable |
bool |
{true, false} |
Whether to fill gaps using interpolation for small gaps and time shift for large gaps. |
– interpolate_limit |
hours |
integer |
Maximum gap size (consecutive nans) which interpolated linearly. |
– time_shift_for_large_gaps |
string |
string |
Periods which are used for copying time-slices in order to fill large gaps of nans. Have to be valid |
manual_adjustments |
bool |
{true, false} |
Whether to adjust the load data manually according to the function in |
scaling_factor |
– |
float |
Global correction factor for the load time series. |
fixed_year |
– |
Year or False |
To specify a fixed year for the load time series that deviates from the snapshots’ year |
supplement_synthetic |
bool |
{true, false} |
Whether to supplement missing data for selected time period should be supplemented by synthetic data from https://zenodo.org/records/10820928. |
distribution_key |
– |
– |
Distribution key for spatially disaggregating the per-country electricity demand data. |
– gdp |
float |
[0, 1] |
Weighting factor for the GDP data in the distribution key. |
– population |
float |
[0, 1] |
Weighting factor for the population data in the distribution key. |
energy
#
Note
Only used for sector-coupling studies.
energy:
energy_totals_year: 2019
base_emissions_year: 1990
emissions: CO2
Unit |
Values |
Description |
|
---|---|---|---|
energy_totals_year |
– |
{1990,1995,2000,2005,2010,2011,…} |
The year for the sector energy use. The year must be avaliable in the Eurostat report |
base_emissions_year |
– |
YYYY; e.g. 1990 |
The base year for the sector emissions. See European Environment Agency (EEA). |
emissions |
– |
{CO2, All greenhouse gases - (CO2 equivalent)} |
Specify which sectoral emissions are taken into account. Data derived from EEA. Currently only CO2 is implemented. |
biomass
#
Note
Only used for sector-coupling studies.
biomass:
year: 2030
scenario: ENS_Med
classes:
solid biomass:
- Agricultural waste
- Fuelwood residues
- Secondary Forestry residues - woodchips
- Sawdust
- Residues from landscape care
not included:
- Sugar from sugar beet
- Rape seed
- "Sunflower, soya seed "
- Bioethanol barley, wheat, grain maize, oats, other cereals and rye
- Miscanthus, switchgrass, RCG
- Willow
- Poplar
- FuelwoodRW
- C&P_RW
biogas:
- Manure solid, liquid
- Sludge
municipal solid waste:
- Municipal waste
share_unsustainable_use_retained:
2020: 1
2025: 0.66
2030: 0.33
2035: 0
2040: 0
2045: 0
2050: 0
share_sustainable_potential_available:
2020: 0
2025: 0.33
2030: 0.66
2035: 1
2040: 1
2045: 1
2050: 1
Unit |
Values |
Description |
|
---|---|---|---|
year |
– |
{2010, 2020, 2030, 2040, 2050} |
Year for which to retrieve biomass potential according to the assumptions of the JRC ENSPRESO . |
scenario |
– |
{“ENS_Low”, “ENS_Med”, “ENS_High”} |
Scenario for which to retrieve biomass potential. The scenario definition can be seen in ENSPRESO_BIOMASS |
classes |
|||
– solid biomass |
– |
Array of biomass comodity |
The comodity that are included as solid biomass |
– not included |
– |
Array of biomass comodity |
The comodity that are not included as a biomass potential |
– biogas |
– |
Array of biomass comodity |
The comodity that are included as biogas |
share_unsustainable_use_retained |
– |
Dictionary with planning horizons as keys. |
Share of unsustainable biomass use retained using primary production of Eurostat data as reference |
share_sustainable_potential_available |
– |
Dictionary with planning horizons as keys. |
Share determines phase-in of ENSPRESO biomass potentials |
The list of available biomass is given by the category in ENSPRESO_BIOMASS, namely:
Agricultural waste
Manure solid, liquid
Residues from landscape care
Bioethanol barley, wheat, grain maize, oats, other cereals and rye
Sugar from sugar beet
Miscanthus, switchgrass, RCG
Willow
Poplar
Sunflower, soya seed
Rape seed
Fuelwood residues
FuelwoodRW
C&P_RW
Secondary Forestry residues - woodchips
Sawdust
Municipal waste
Sludge
solar_thermal
#
Note
Only used for sector-coupling studies.
solar_thermal:
clearsky_model: simple # should be "simple" or "enhanced"?
orientation:
slope: 45.
azimuth: 180.
cutout: default
Unit |
Values |
Description |
|
---|---|---|---|
clearsky_model |
– |
{‘simple’, ‘enhanced’} |
Type of clearsky model for diffuse irradiation |
orientation |
– |
{units of degrees, ‘latitude_optimal’} |
Panel orientation with slope and azimuth |
– azimuth |
float |
units of degrees |
The angle between the North and the sun with panels on the local horizon |
– slope |
float |
units of degrees |
The angle between the ground and the panels |
existing_capacities
#
Note
Only used for sector-coupling studies. The value for grouping years are only used in myopic or perfect foresight scenarios.
existing_capacities:
grouping_years_power: [1920, 1950, 1955, 1960, 1965, 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025]
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # heat grouping years >= baseyear will be ignored
threshold_capacity: 10
default_heating_lifetime: 20
conventional_carriers:
- lignite
- coal
- oil
- uranium
Unit |
Values |
Description |
|
---|---|---|---|
grouping_years_power |
– |
A list of years |
Intervals to group existing capacities for power |
grouping_years_heat |
– |
A list of years below 2020 |
Intervals to group existing capacities for heat |
threshold_capacity |
MW |
float |
Capacities generators and links of below threshold are removed during add_existing_capacities |
default_heating_lifetime |
years |
int |
Default lifetime for heating technologies |
conventional_carriers |
– |
Any subset of {uranium, coal, lignite, oil} |
List of conventional power plants to include in the sectoral network |
sector
#
Note
Only used for sector-coupling studies.
sector:
transport: true
heating: true
biomass: true
industry: true
shipping: true
aviation: true
agriculture: true
fossil_fuels: true
district_heating:
potential: 0.6
progress:
2020: 0.0
2025: 0.15
2030: 0.3
2035: 0.45
2040: 0.6
2045: 0.8
2050: 1.0
district_heating_loss: 0.15
supply_temperature_approximation:
max_forward_temperature_baseyear:
FR: 110
DK: 75
DE: 109
CZ: 130
FI: 115
PL: 130
SE: 102
IT: 90
min_forward_temperature_baseyear:
DE: 82
return_temperature_baseyear:
DE: 58
lower_threshold_ambient_temperature: 0
upper_threshold_ambient_temperature: 10
rolling_window_ambient_temperature: 72
relative_annual_temperature_reduction: 0.01
ptes:
dynamic_capacity: true
supplemental_heating:
enable: false
booster_heat_pump: false
max_top_temperature: 90
min_bottom_temperature: 35
ates:
enable: false
suitable_aquifer_types: ['Highly productive porous aquifers']
aquifer_volumetric_heat_capacity: 2600
fraction_of_aquifer_area_available: 0.2
effective_screen_length: 20
dh_area_buffer: 1000
capex_as_fraction_of_geothermal_heat_source: 0.75
recovery_factor: 0.6
marginal_cost_charger: 0.035
ignore_missing_regions: false
heat_source_cooling: 6 #K
heat_pump_cop_approximation:
refrigerant: ammonia
heat_exchanger_pinch_point_temperature_difference: 5 #K
isentropic_compressor_efficiency: 0.8
heat_loss: 0.0
limited_heat_sources:
geothermal:
constant_temperature_celsius: 65
ignore_missing_regions: false
direct_utilisation_heat_sources:
- geothermal
temperature_limited_stores:
- ptes
heat_pump_sources:
urban central:
- air
- ptes
urban decentral:
- air
rural:
- air
- ground
cluster_heat_buses: true
heat_demand_cutout: default
bev_dsm_restriction_value: 0.75
bev_dsm_restriction_time: 7
transport_heating_deadband_upper: 20.
transport_heating_deadband_lower: 15.
ICE_lower_degree_factor: 0.375
ICE_upper_degree_factor: 1.6
EV_lower_degree_factor: 0.98
EV_upper_degree_factor: 0.63
bev_dsm: true
bev_dsm_availability: 0.5
bev_energy: 0.05
bev_charge_efficiency: 0.9
bev_charge_rate: 0.011
bev_avail_max: 0.95
bev_avail_mean: 0.8
v2g: true
land_transport_fuel_cell_share:
2020: 0
2025: 0
2030: 0
2035: 0
2040: 0
2045: 0
2050: 0
land_transport_electric_share:
2020: 0
2025: 0.15
2030: 0.3
2035: 0.45
2040: 0.7
2045: 0.85
2050: 1
land_transport_ice_share:
2020: 1
2025: 0.85
2030: 0.7
2035: 0.55
2040: 0.3
2045: 0.15
2050: 0
transport_electric_efficiency: 53.19 # 1 MWh_el = 53.19*100 km
transport_fuel_cell_efficiency: 30.003 # 1 MWh_H2 = 30.003*100 km
transport_ice_efficiency: 16.0712 # 1 MWh_oil = 16.0712 * 100 km
agriculture_machinery_electric_share: 0
agriculture_machinery_oil_share: 1
agriculture_machinery_fuel_efficiency: 0.7
agriculture_machinery_electric_efficiency: 0.3
MWh_MeOH_per_MWh_H2: 0.8787
MWh_MeOH_per_tCO2: 4.0321
MWh_MeOH_per_MWh_e: 3.6907
shipping_hydrogen_liquefaction: false
shipping_hydrogen_share:
2020: 0
2025: 0
2030: 0
2035: 0
2040: 0
2045: 0
2050: 0
shipping_methanol_share:
2020: 0
2025: 0.15
2030: 0.3
2035: 0.5
2040: 0.7
2045: 0.85
2050: 1
shipping_oil_share:
2020: 1
2025: 0.85
2030: 0.7
2035: 0.5
2040: 0.3
2045: 0.15
2050: 0
shipping_methanol_efficiency: 0.46
shipping_oil_efficiency: 0.40
aviation_demand_factor: 1.
HVC_demand_factor: 1.
time_dep_hp_cop: true
heat_pump_sink_T_individual_heating: 55.
reduce_space_heat_exogenously: true
reduce_space_heat_exogenously_factor:
2020: 0.10 # this results in a space heat demand reduction of 10%
2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita
2030: 0.09
2035: 0.11
2040: 0.16
2045: 0.21
2050: 0.29
retrofitting:
retro_endogen: false
cost_factor: 1.0
interest_rate: 0.04
annualise_cost: true
tax_weighting: false
construction_index: true
tes: true
tes_tau:
decentral: 3
central: 180
boilers: true
resistive_heaters: true
oil_boilers: false
biomass_boiler: true
overdimension_heat_generators:
decentral: 1.1 #to cover demand peaks bigger than data
central: 1.0
chp:
enable: true
fuel:
- solid biomass # For solid biomass, CHP with and without CC are added
- gas # For all other fuels the same techno economic data from gas CHP is taken
micro_chp: false # Only gas is used for micro_chp
solar_thermal: true
solar_cf_correction: 0.788457 # = >>> 1/1.2683
methanation: true
coal_cc: false
dac: true
co2_vent: false
heat_vent:
urban central: true
urban decentral: true
rural: true
marginal_cost_heat_vent: 0.02
allam_cycle_gas: false
hydrogen_fuel_cell: true
hydrogen_turbine: false
SMR: true
SMR_cc: true
regional_oil_demand: false
regional_coal_demand: false
regional_co2_sequestration_potential:
enable: false
attribute:
- conservative estimate Mt
- conservative estimate GAS Mt
- conservative estimate OIL Mt
- conservative estimate aquifer Mt
include_onshore: false
min_size: 3
max_size: 25
years_of_storage: 25
co2_sequestration_potential:
2020: 0
2025: 0
2030: 50
2035: 100
2040: 200
2045: 200
2050: 200
co2_sequestration_cost: 10
co2_sequestration_lifetime: 50
co2_spatial: false
co2_network: false
co2_network_cost_factor: 1
cc_fraction: 0.9
hydrogen_underground_storage: true
hydrogen_underground_storage_locations:
# - onshore # more than 50 km from sea
- nearshore # within 50 km of sea
# - offshore
methanol:
regional_methanol_demand: false
methanol_reforming: false
methanol_reforming_cc: false
methanol_to_kerosene: false
methanol_to_power:
ccgt: false
ccgt_cc: false
ocgt: false
allam: false
biomass_to_methanol: false
biomass_to_methanol_cc: false
ammonia: false
min_part_load_fischer_tropsch: 0.5
min_part_load_methanolisation: 0.3
min_part_load_methanation: 0.3
use_fischer_tropsch_waste_heat: 0.25
use_haber_bosch_waste_heat: 0.25
use_methanolisation_waste_heat: 0.25
use_methanation_waste_heat: 0.25
use_fuel_cell_waste_heat: 0.25
use_electrolysis_waste_heat: 0.25
electricity_transmission_grid: true
electricity_distribution_grid: true
electricity_grid_connection: true
transmission_efficiency:
enable:
- DC
- H2 pipeline
- gas pipeline
- electricity distribution grid
DC:
efficiency_static: 0.98
efficiency_per_1000km: 0.977
H2 pipeline:
efficiency_per_1000km: 1 # 0.982
compression_per_1000km: 0.018
gas pipeline:
efficiency_per_1000km: 1 #0.977
compression_per_1000km: 0.01
electricity distribution grid:
efficiency_static: 0.97
H2_network: true
gas_network: false
H2_retrofit: false
H2_retrofit_capacity_per_CH4: 0.6
gas_network_connectivity_upgrade: 1
gas_distribution_grid: true
gas_distribution_grid_cost_factor: 1.0
biomass_spatial: false
biomass_transport: false
biogas_upgrading_cc: false
conventional_generation:
OCGT: gas
biomass_to_liquid: false
biomass_to_liquid_cc: false
electrobiofuels: false
biosng: false
biosng_cc: false
bioH2: false
municipal_solid_waste: false
limit_max_growth:
enable: false
# allowing 30% larger than max historic growth
factor: 1.3
max_growth: # unit GW
onwind: 16 # onshore max grow so far 16 GW in Europe https://www.iea.org/reports/renewables-2020/wind
solar: 28 # solar max grow so far 28 GW in Europe https://www.iea.org/reports/renewables-2020/solar-pv
offwind-ac: 35 # offshore max grow so far 3.5 GW in Europe https://windeurope.org/about-wind/statistics/offshore/european-offshore-wind-industry-key-trends-statistics-2019/
offwind-dc: 35
max_relative_growth:
onwind: 3
solar: 3
offwind-ac: 3
offwind-dc: 3
enhanced_geothermal:
enable: false
flexible: true
max_hours: 240
max_boost: 0.25
var_cf: true
sustainability_factor: 0.0025
solid_biomass_import:
enable: false
price: 54 #EUR/MWh
max_amount: 1390 # TWh
upstream_emissions_factor: .1 #share of solid biomass CO2 emissions at full combustion
imports:
enable: false
limit: .inf
limit_sense: <=
price:
H2: 74
NH3: 97
methanol: 121
gas: 122
oil: 125
Unit |
Values |
Description |
|
---|---|---|---|
transport |
– |
{true, false} |
Flag to include transport sector. |
heating |
– |
{true, false} |
Flag to include heating sector. |
biomass |
– |
{true, false} |
Flag to include biomass sector. |
industry |
– |
{true, false} |
Flag to include industry sector. |
shipping |
– |
{true, false} |
Flag to include shipping sector. |
aviation |
– |
{true, false} |
Flag to include aviation sector. |
agriculture |
– |
{true, false} |
Flag to include agriculture sector. |
fossil_fuels |
– |
{true, false} |
Flag to include imports of fossil fuels. |
district_heating |
– |
||
– potential |
– |
float |
maximum fraction of urban demand which can be supplied by district heating |
– progress |
– |
Dictionary with planning horizons as keys. |
Increase of today’s district heating demand to potential maximum district heating share. Progress = 0 means today’s district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating |
– district_heating_loss |
– |
float |
Share increase in district heat demand in urban central due to heat losses |
– supply_temperature_approximation |
|||
– – max_forward_temperature_baseyear |
C |
Dictionary with country codes as keys. One key must be ‘default’. |
Max. forward temperature in district heating in baseyear (if ambient temperature lower-or-equal lower_threshold_ambient_temperature) |
– – min_forward_temperature_baseyear |
C |
Dictionary with country codes as keys. One key must be ‘default’. |
Min. forward temperature in district heating in baseyear (if ambient temperature higher-or-equal upper_threshold_ambient_temperature) |
– – return_temperature_baseyear |
C |
Dictionary with country codes as keys. One key must be ‘default’. |
Return temperature in district heating in baseyear . Must be lower than forward temperature |
– – lower_threshold_ambient_temperature |
C |
float |
Assume max_forward_temperature if ambient temperature is below this threshold |
– – upper_threshold_ambient_temperature |
C |
float |
Assume min_forward_temperature if ambient temperature is above this threshold |
– – rolling_window_ambient_temperature |
h |
int |
Rolling window size for averaging ambient temperature when approximating supply temperature |
– – relative_annual_temperature_reduction |
float |
Relative annual reduction of district heating forward and return temperature - defaults to 0.01 (1%) |
|
– ptes |
|||
– – dynamic_capacity |
– |
{true, false} |
Add option for dynamic temperature-dependent energy capacity of pit storage in district heating |
– – supplemental_heating |
|||
– – – enable |
– |
{true, false} |
Add option to enable supplemental heating of pit storage in district heating |
– – – booster_heat_pump: true |
– |
{true, false} |
Add option to enable a booster heat pump for supplemental heating of pit storage in district heating |
– – max_top_temperature |
C |
float |
The maximum top temperature of the pit storage according to DEA technology catalogue (2018) |
– – min_bottom_temperature |
C |
float |
The minimum bottom temperature of the pit storage according to DEA technology catalogue (2018) |
– ates |
|||
– – enable |
– |
{true, false} |
Enable investments in aquifer thermal energy pit storage in district heating |
– – suitable_aquifer_types |
– |
List of aquifer types assumed suitable for ATES. Must be subset of [Highly productive porous aquifers’; |
|
‘Low and moderately productive porous aquifers’; |
|||
‘Highly productive fissured aquifers (including karstified rocks)’; |
|||
‘Low and moderately productive fissured aquifers (including karstified rocks)’; |
|||
‘Locally aquiferous rocks |
porous or fissured’; |
||
‘Practically non-aquiferous rocks |
porous or fissured’; |
||
‘Inland water’; ‘Snow field / ice field’] |
|||
– – aquifer_volumetric_heat_capacity |
kJ/m³/K |
float |
The volumetric heat capacity of the aquifer water |
– – fraction_of_aquifer_area_available |
float |
The fraction of the aquifer area available for ATES |
|
– – effective_screen_length |
m |
float |
The effective screen length of the aquifer well. Used to estimate its thermal radius. |
– – dh_area_buffer |
m |
float |
Suitable aquifers must be within this distance to district heating areas. |
– – capex_as_fraction_of_geothermal_heat_source |
float |
The capital expenditure of ATES chargers/dischargers as a fraction of the geothermal heat source per-MWh CAPEX. |
|
– – recovery_factor |
float |
The recovery factor of the aquifer (1- yearly_losses). |
|
– heat_source_cooling |
K |
float |
Cooling of heat source for heat pumps |
– heat_pump_cop_approximation |
|||
– – refrigerant |
– |
{ammonia, isobutane} |
Heat pump refrigerant assumed for COP approximation |
– – heat_exchanger_pinch_point_temperature_difference |
K |
float |
Heat pump pinch point temperature difference in heat exchangers assumed for approximation. |
– – isentropic_compressor_efficiency |
– |
float |
Isentropic efficiency of heat pump compressor assumed for approximation. Must be between 0 and 1. |
– – heat_loss |
– |
float |
Heat pump heat loss assumed for approximation. Must be between 0 and 1. |
– limited_heat_sources |
– |
Dictionary with names of limited heat sources (not air) for which data by Fraunhofer ISI (`Manz et al. 2024 <https://www.sciencedirect.com/science/article/pii/S0960148124001769>) is used |
|
– – geothermal |
Name of the heat source. Must be the same as in |
||
– – – constant_temperature_celsius |
°C |
heat source temperature |
|
– – – ignore_missing_regions |
– |
Boolean |
Ignore missing regions in the data and fill with zeros or raise an error |
– direct_utilisation_heat_sources |
– |
List of heat sources for direct heat utilisation in district heating. Must be in the keys of heat_utilisation_potentials (e.g. |
|
– temperature_limited_stores |
Dictionary with names for stores used as limited heat sources |
||
– – ptes |
Name of the heat source. Must be the same as in |
||
– heat_pump_sources |
– |
||
– – urban central |
– |
List of heat sources for heat pumps in urban central heating |
|
– – urban decentral |
– |
List of heat sources for heat pumps in urban decentral heating |
|
– – rural |
– |
List of heat sources for heat pumps in rural heating |
|
cluster_heat_buses |
– |
{true, false} |
Cluster residential and service heat buses in prepare_sector_network.py to one to save memory. |
bev_dsm_restriction _value |
– |
float |
Adds a lower state of charge (SOC) limit for battery electric vehicles (BEV) to manage its own energy demand (DSM). Located in build_transport_demand.py. Set to 0 for no restriction on BEV DSM |
bev_dsm_restriction _time |
– |
float |
Time at which SOC of BEV has to be dsm_restriction_value |
transport_heating _deadband_upper |
C |
float |
The maximum temperature in the vehicle. At higher temperatures, the energy required for cooling in the vehicle increases. |
transport_heating _deadband_lower |
C |
float |
The minimum temperature in the vehicle. At lower temperatures, the energy required for heating in the vehicle increases. |
ICE_lower_degree_factor |
– |
float |
Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the cold environment and the minimum temperature. |
ICE_upper_degree_factor |
– |
float |
Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the hot environment and the maximum temperature. |
EV_lower_degree_factor |
– |
float |
Share increase in energy demand in electric vehicles (EV) for each degree difference between the cold environment and the minimum temperature. |
EV_upper_degree_factor |
– |
float |
Share increase in energy demand in electric vehicles (EV) for each degree difference between the hot environment and the maximum temperature. |
bev_dsm |
– |
{true, false} |
Add the option for battery electric vehicles (BEV) to participate in demand-side management (DSM) |
bev_dsm_availability |
– |
float |
The share for battery electric vehicles (BEV) that are able to do demand side management (DSM) |
bev_energy |
– |
float |
The average size of battery electric vehicles (BEV) in MWh |
bev_charge_efficiency |
– |
float |
Battery electric vehicles (BEV) charge and discharge efficiency |
bev_charge_rate |
MWh |
float |
The power consumption for one electric vehicle (EV) in MWh. Value derived from 3-phase charger with 11 kW. |
bev_avail_max |
– |
float |
The maximum share plugged-in availability for passenger electric vehicles. |
bev_avail_mean |
– |
float |
The average share plugged-in availability for passenger electric vehicles. |
v2g |
– |
{true, false} |
Allows feed-in to grid from EV battery. This is only enabled if BEV demand-side management is enabled, and the share of vehicles participating is V2G is given by bev_dsm_availability. |
land_transport_fuel_cell _share |
– |
Dictionary with planning horizons as keys. |
The share of vehicles that uses fuel cells in a given year |
land_transport_electric _share |
– |
Dictionary with planning horizons as keys. |
The share of vehicles that uses electric vehicles (EV) in a given year |
land_transport_ice _share |
– |
Dictionary with planning horizons as keys. |
The share of vehicles that uses internal combustion engines (ICE) in a given year. What is not EV or FCEV is oil-fuelled ICE. |
transport_electric_efficiency |
MWh/100km |
float |
The conversion efficiencies of electric vehicles in transport |
transport_fuel_cell_efficiency |
MWh/100km |
float |
The H2 conversion efficiencies of fuel cells in transport |
transport_ice_efficiency |
MWh/100km |
float |
The oil conversion efficiencies of internal combustion engine (ICE) in transport |
agriculture_machinery _electric_share |
– |
float |
The share for agricultural machinery that uses electricity |
agriculture_machinery _oil_share |
– |
float |
The share for agricultural machinery that uses oil |
agriculture_machinery _fuel_efficiency |
– |
float |
The efficiency of electric-powered machinery in the conversion of electricity to meet agricultural needs. |
agriculture_machinery _electric_efficiency |
– |
float |
The efficiency of oil-powered machinery in the conversion of oil to meet agricultural needs. |
Mwh_MeOH_per_MWh_H2 |
LHV |
float |
The energy amount of the produced methanol per energy amount of hydrogen. From DECHEMA (2017), page 64. |
MWh_MeOH_per_tCO2 |
LHV |
float |
The energy amount of the produced methanol per ton of CO2. From DECHEMA (2017), page 66. |
MWh_MeOH_per_MWh_e |
LHV |
float |
The energy amount of the produced methanol per energy amount of electricity. From DECHEMA (2017), page 64. |
shipping_hydrogen _liquefaction |
– |
{true, false} |
Whether to include liquefaction costs for hydrogen demand in shipping. |
shipping_hydrogen_share |
– |
Dictionary with planning horizons as keys. |
The share of ships powered by hydrogen in a given year |
shipping_methanol_share |
– |
Dictionary with planning horizons as keys. |
The share of ships powered by methanol in a given year |
shipping_oil_share |
– |
Dictionary with planning horizons as keys. |
The share of ships powered by oil in a given year |
shipping_methanol _efficiency |
– |
float |
The efficiency of methanol-powered ships in the conversion of methanol to meet shipping needs (propulsion). The efficiency increase from oil can be 10-15% higher according to the IEA |
shipping_oil_efficiency |
– |
float |
The efficiency of oil-powered ships in the conversion of oil to meet shipping needs (propulsion). Base value derived from 2011 |
aviation_demand_factor |
– |
float |
The proportion of demand for aviation compared to today’s consumption |
HVC_demand_factor |
– |
float |
The proportion of demand for high-value chemicals compared to today’s consumption |
time_dep_hp_cop |
– |
{true, false} |
Consider the time dependent coefficient of performance (COP) of the heat pump |
heat_pump_sink_T |
°C |
float |
The temperature heat sink used in heat pumps based on DTU / large area radiators. The value is conservatively high to cover hot water and space heating in poorly-insulated buildings |
reduce_space_heat _exogenously |
– |
{true, false} |
Influence on space heating demand by a certain factor (applied before losses in district heating). |
reduce_space_heat _exogenously_factor |
– |
Dictionary with planning horizons as keys. |
A positive factor can mean renovation or demolition of a building. If the factor is negative, it can mean an increase in floor area, increased thermal comfort, population growth. The default factors are determined by the Eurocalc Homes and buildings decarbonization scenario |
retrofitting |
|||
– retro_endogen |
– |
{true, false} |
Add retrofitting as an endogenous system which co-optimise space heat savings. |
– cost_factor |
– |
float |
Weight costs for building renovation |
– interest_rate |
– |
float |
The interest rate for investment in building components |
– annualise_cost |
– |
{true, false} |
Annualise the investment costs of retrofitting |
– tax_weighting |
– |
{true, false} |
Weight the costs of retrofitting depending on taxes in countries |
– construction_index |
– |
{true, false} |
Weight the costs of retrofitting depending on labour/material costs per country |
tes |
– |
{true, false} |
Add option for storing thermal energy in large water pits associated with district heating systems and individual thermal energy storage (TES) |
tes_tau |
The time constant used to calculate the decay of thermal energy in thermal energy storage (TES): 1- \(e^{-1/24τ}\). |
||
– decentral |
days |
float |
The time constant in decentralized thermal energy storage (TES) |
– central |
days |
float |
The time constant in centralized thermal energy storage (TES) |
boilers |
– |
{true, false} |
Add option for transforming gas into heat using gas boilers |
resistive_heaters |
– |
{true, false} |
Add option for transforming electricity into heat using resistive heaters (independently from gas boilers) |
oil_boilers |
– |
{true, false} |
Add option for transforming oil into heat using boilers |
biomass_boiler |
– |
{true, false} |
Add option for transforming biomass into heat using boilers |
overdimension_heat_generators |
Add option for overdimensioning heating systems by a certain factor. This allows them to cover heat demand peaks e.g. 10% higher than those in the data with a setting of 1.1. |
||
– decentral |
– |
float |
The factor for overdimensioning (increasing CAPEX) decentral heating systems |
– central |
– |
float |
The factor for overdimensioning (increasing CAPEX) central heating systems |
chp |
– |
||
– enable |
– |
{true, false} |
Add option for using Combined Heat and Power (CHP) |
– fuel |
– |
list of fuels |
Possible options are all fuels which have an existing bus and their CO2 intensity is given in the technology data. Currently possible are “gas”, “oil”, “methanol”, “lignite”, “coal” as well as “solid biomass”. For all fuels except solid biomass, the techno-economic data from gas CHP is used. For the special case of solid biomass fuel, both CHP plants with and without carbon capture are added. |
– micro_chp |
– |
{true, false} |
Add option for using gas-fired Combined Heat and Power (CHP) for decentral areas. |
solar_thermal |
– |
{true, false} |
Add option for using solar thermal to generate heat. |
solar_cf_correction |
– |
float |
The correction factor for the value provided by the solar thermal profile calculations |
marginal_cost_heat_vent |
currency/MWh |
float |
The marginal cost of heat-venting in all heating systems |
methanation |
– |
{true, false} |
Add option for transforming hydrogen and CO2 into methane using methanation. |
coal_cc |
– |
{true, false} |
Add option for coal CHPs with carbon capture |
dac |
– |
{true, false} |
Add option for Direct Air Capture (DAC) |
co2_vent |
– |
{true, false} |
Add option for vent out CO2 from storages to the atmosphere. |
heat_vent |
– |
– |
– |
– urban central |
– |
{true, false} |
Allow heat-venting in central heating. |
– urban decentral |
– |
{true, false} |
Allow heat-venting in urban decentral heating. |
– rural |
– |
{true, false} |
Allow heat-venting in rural heating. |
allam_cycle_gas |
– |
{true, false} |
Add option to include Allam cycle gas power plants |
hydrogen_fuel_cell |
– |
{true, false} |
Add option to include hydrogen fuel cell for re-electrification. Assuming OCGT technology costs |
hydrogen_turbine |
– |
{true, false} |
Add option to include hydrogen turbine for re-electrification. Assuming OCGT technology costs |
SMR |
– |
{true, false} |
Add option for transforming natural gas into hydrogen and CO2 using Steam Methane Reforming (SMR) |
SMR CC |
– |
{true, false} |
Add option for transforming natural gas into hydrogen and CO2 using Steam Methane Reforming (SMR) and Carbon Capture (CC) |
regional_oil_demand |
– |
{true, false} |
Spatially resolve oil demand. Set to true if regional CO2 constraints needed. |
regional_co2 _sequestration_potential |
|||
– enable |
– |
{true, false} |
Add option for regionally-resolved geological carbon dioxide sequestration potentials based on CO2StoP. |
– attribute |
– |
string or list |
Name (or list of names) of the attribute(s) for the sequestration potential |
– include_onshore |
– |
{true, false} |
Add options for including onshore sequestration potentials |
– min_size |
Gt |
float |
Any sites with lower potential than this value will be excluded |
– max_size |
Gt |
float |
The maximum sequestration potential for any one site. |
– years_of_storage |
years |
float |
The years until potential exhausted at optimised annual rate |
co2_sequestration_potential |
– |
Dictionary with planning horizons as keys. |
The potential of sequestering CO2 in Europe per year and investment period |
co2_sequestration_cost |
currency/tCO2 |
float |
The cost of sequestering a ton of CO2 |
co2_sequestration_lifetime |
years |
int |
The lifetime of a CO2 sequestration site |
co2_spatial |
– |
{true, false} |
Add option to spatially resolve carrier representing stored carbon dioxide. This allows for more detailed modelling of CCUTS, e.g. regarding the capturing of industrial process emissions, usage as feedstock for electrofuels, transport of carbon dioxide, and geological sequestration sites. |
co2_network |
– |
{true, false} |
Add option for planning a new carbon dioxide transmission network |
co2_network_cost_factor |
p.u. |
float |
The cost factor for the capital cost of the carbon dioxide transmission network |
cc_fraction |
– |
float |
The default fraction of CO2 captured with post-combustion capture |
hydrogen_underground _storage |
– |
{true, false} |
Add options for storing hydrogen underground. Storage potential depends regionally. |
hydrogen_underground _storage_locations |
{onshore, nearshore, offshore} |
The location where hydrogen underground storage can be located. Onshore, nearshore, offshore means it must be located more than 50 km away from the sea, within 50 km of the sea, or within the sea itself respectively. |
|
methanol |
– |
– |
Add methanol as carrrier and add enabled methnol technologies |
– regional_methanol_demand |
– |
{true, false} |
Spatially resolve methanol demand. Set to true if regional CO2 constraints needed. |
– methanol_reforming |
– |
{true, false} |
|
– methanol_reforming_cc |
– |
{true, false} |
|
– methanol_to_kerosene |
– |
{true, false} |
|
– methanol_to_power |
– |
– |
|
– – ccgt |
– |
{true, false} |
|
– – ccgt_cc |
– |
{true, false} |
|
– – ocgt |
– |
{true, false} |
|
– – allam |
– |
{true, false} |
|
– – biomass_to_methanol |
– |
{true, false} |
|
– – biomass_to_methanol_cc |
– |
{true, false} |
|
ammonia |
– |
{true, false, regional} |
Add ammonia as a carrrier. It can be either true (copperplated NH3), false (no NH3 carrier) or “regional” (regionalised NH3 without network) |
min_part_load_fischer _tropsch |
per unit of p_nom |
float |
The minimum unit dispatch ( |
min_part_load _methanolisation |
per unit of p_nom |
float |
The minimum unit dispatch ( |
use_fischer_tropsch _waste_heat |
– |
{true, false} |
Add option for using waste heat of Fischer Tropsch in district heating networks |
use_fuel_cell_waste_heat |
– |
{true, false} |
Add option for using waste heat of fuel cells in district heating networks |
use_electrolysis_waste _heat |
– |
{true, false} |
Add option for using waste heat of electrolysis in district heating networks |
electricity_transmission _grid |
– |
{true, false} |
Switch for enabling/disabling the electricity transmission grid. |
electricity_distribution _grid |
– |
{true, false} |
Add a simplified representation of the exchange capacity between transmission and distribution grid level through a link. |
electricity_distribution _grid_cost_factor |
Multiplies the investment cost of the electricity distribution grid |
||
electricity_grid _connection |
– |
{true, false} |
Add the cost of electricity grid connection for onshore wind and solar |
transmission_efficiency |
Section to specify transmission losses or compression energy demands of bidirectional links. Splits them into two capacity-linked unidirectional links. |
||
– enable |
– |
list |
Switch to select the carriers for which transmission efficiency is to be added. Carriers not listed assume lossless transmission. |
– {carrier} |
– |
str |
The carrier of the link. |
– – efficiency_static |
p.u. |
float |
Length-independent transmission efficiency. |
– – efficiency_per_1000km |
p.u. per 1000 km |
float |
Length-dependent transmission efficiency ($eta^{text{length}}$) |
– – compression_per_1000km |
p.u. per 1000 km |
float |
Length-dependent electricity demand for compression ($eta cdot text{length}$) implemented as multi-link to local electricity bus. |
H2_network |
– |
{true, false} |
Add option for new hydrogen pipelines |
gas_network |
– |
{true, false} |
Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted k-edge augmentation algorithm can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well. |
H2_retrofit |
– |
{true, false} |
Add option for retrofiting existing pipelines to transport hydrogen. |
H2_retrofit_capacity _per_CH4 |
– |
float |
The ratio for H2 capacity per original CH4 capacity of retrofitted pipelines. The European Hydrogen Backbone (April, 2020) p.15 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity. |
gas_network_connectivity _upgrade |
– |
float |
The number of desired edge connectivity (k) in the length-weighted k-edge augmentation algorithm used for the gas network |
gas_distribution_grid |
– |
{true, false} |
Add a gas distribution grid |
gas_distribution_grid _cost_factor |
Multiplier for the investment cost of the gas distribution grid |
||
biomass_spatial |
– |
{true, false} |
Add option for resolving biomass demand regionally |
biomass_transport |
– |
{true, false} |
Add option for transporting solid biomass between nodes |
biogas_upgrading_cc |
– |
{true, false} |
Add option to capture CO2 from biomass upgrading |
conventional_generation |
Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel. |
||
biomass_to_liquid |
– |
{true, false} |
Add option for transforming solid biomass into liquid fuel with the same properties as oil |
biomass_to_liquid_cc |
– |
{true, false} |
Add option for transforming solid biomass into liquid fuel with the same properties as oil with carbon capture |
biosng |
– |
{true, false} |
Add option for transforming solid biomass into synthesis gas with the same properties as natural gas |
biosng_cc |
– |
{true, false} |
Add option for transforming solid biomass into synthesis gas with the same properties as natural gas with carbon capture |
bioH2 |
– |
{true, false} |
Add option for transforming solid biomass into hydrogen with carbon capture |
municipal_solid_waste |
– |
{true, false} |
Add option for municipal solid waste |
limit_max_growth |
|||
– enable |
– |
{true, false} |
Add option to limit the maximum growth of a carrier |
– factor |
p.u. |
float |
The maximum growth factor of a carrier (e.g. 1.3 allows 30% larger than max historic growth) |
– max_growth |
|||
– – {carrier} |
GW |
float |
The historic maximum growth of a carrier |
– max_relative_growth |
|||
– – {carrier} |
p.u. |
float |
The historic maximum relative growth of a carrier |
enhanced_geothermal |
|||
– enable |
– |
{true, false} |
Add option to include Enhanced Geothermal Systems |
– flexible |
– |
{true, false} |
Add option for flexible operation (see Ricks et al. 2024) |
– max_hours |
– |
int |
The maximum hours the reservoir can be charged under flexible operation |
– max_boost |
– |
float |
The maximum boost in power output under flexible operation |
– var_cf |
– |
{true, false} |
Add option for variable capacity factor (see Ricks et al. 2024) |
– sustainability_factor |
– |
float |
Share of sourced heat that is replenished by the earth’s core (see details in build_egs_potentials.py) |
solid_biomass_import |
|||
– enable |
– |
{true, false} |
Add option to include solid biomass imports |
– price |
currency/MWh |
float |
Price for importing solid biomass |
– max_amount |
Twh |
float |
Maximum solid biomass import potential |
– upstream_emissions_factor |
p.u. |
float |
Upstream emissions of solid biomass imports |
imports |
|||
– enable |
– |
{true, false} |
Add option to include renewable energy imports |
– limit |
TWh |
float |
Maximum allowed renewable energy imports |
– limit_sense |
– |
{==, <=, >=} |
Sense of the limit |
– price |
{H2, NH3, methanol, gas, oil} |
||
– – {carrier} |
currency/MWh |
float |
Price for importing renewable energy of carrier |
industry
#
Note
Only used for sector-coupling studies.
# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry
industry:
St_primary_fraction:
2020: 0.6
2025: 0.55
2030: 0.5
2035: 0.45
2040: 0.4
2045: 0.35
2050: 0.3
DRI_fraction:
2020: 0
2025: 0
2030: 0.05
2035: 0.2
2040: 0.4
2045: 0.7
2050: 1
H2_DRI: 1.7
elec_DRI: 0.322
Al_primary_fraction:
2020: 0.4
2025: 0.375
2030: 0.35
2035: 0.325
2040: 0.3
2045: 0.25
2050: 0.2
MWh_NH3_per_tNH3: 5.166
MWh_CH4_per_tNH3_SMR: 10.8
MWh_elec_per_tNH3_SMR: 0.7
MWh_H2_per_tNH3_electrolysis: 5.93
MWh_elec_per_tNH3_electrolysis: 0.2473
MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
NH3_process_emissions: 24.5
petrochemical_process_emissions: 25.5
#HVC primary/recycling based on values used in Neumann et al https://doi.org/10.1016/j.joule.2023.06.016, linearly interpolated between 2020 and 2050
#2020 recycling rates based on Agora https://static.agora-energiewende.de/fileadmin/Projekte/2021/2021_02_EU_CEAP/A-EW_254_Mobilising-circular-economy_study_WEB.pdf
#fractions refer to the total primary HVC production in 2020
#assumes 6.7 Mtplastics produced from recycling in 2020
HVC_primary_fraction:
2020: 1.0
2025: 0.9
2030: 0.8
2035: 0.7
2040: 0.6
2045: 0.5
2050: 0.4
HVC_mechanical_recycling_fraction:
2020: 0.12
2025: 0.15
2030: 0.18
2035: 0.21
2040: 0.24
2045: 0.27
2050: 0.30
HVC_chemical_recycling_fraction:
2020: 0.0
2025: 0.0
2030: 0.04
2035: 0.08
2040: 0.12
2045: 0.16
2050: 0.20
HVC_environment_sequestration_fraction: 0.
waste_to_energy: false
waste_to_energy_cc: false
sector_ratios_fraction_future:
2020: 0.0
2025: 0.1
2030: 0.3
2035: 0.5
2040: 0.7
2045: 0.9
2050: 1.0
basic_chemicals_without_NH3_production_today: 69. #Mt/a, = 86 Mtethylene-equiv - 17 MtNH3
HVC_production_today: 52.
MWh_elec_per_tHVC_mechanical_recycling: 0.547
MWh_elec_per_tHVC_chemical_recycling: 6.9
chlorine_production_today: 9.58
MWh_elec_per_tCl: 3.6
MWh_H2_per_tCl: -0.9372
methanol_production_today: 1.5
MWh_elec_per_tMeOH: 0.167
MWh_CH4_per_tMeOH: 10.25
MWh_MeOH_per_tMeOH: 5.528
hotmaps_locate_missing: false
reference_year: 2019
oil_refining_emissions: 0.013
Unit |
Values |
Description |
|
---|---|---|---|
St_primary_fraction |
– |
Dictionary with planning horizons as keys. |
The fraction of steel produced via primary route versus secondary route (scrap+EAF). Current fraction is 0.6 |
DRI_fraction |
– |
Dictionary with planning horizons as keys. |
The fraction of the primary route DRI + EAF |
H2_DRI |
– |
float |
The hydrogen consumption in Direct Reduced Iron (DRI) Mwh_H2 LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) |
elec_DRI |
MWh/tSt |
float |
The electricity consumed in Direct Reduced Iron (DRI) shaft. From HYBRIT brochure |
Al_primary_fraction |
– |
Dictionary with planning horizons as keys. |
The fraction of aluminium produced via the primary route versus scrap. Current fraction is 0.4 |
MWh_NH3_per_tNH3 |
LHV |
float |
The energy amount per ton of ammonia. |
MWh_CH4_per_tNH3_SMR |
– |
float |
The energy amount of methane needed to produce a ton of ammonia using steam methane reforming (SMR). Value derived from 2012’s demand from Center for European Policy Studies (2008) |
MWh_elec_per_tNH3_SMR |
– |
float |
The energy amount of electricity needed to produce a ton of ammonia using steam methane reforming (SMR). same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3 |
Mwh_H2_per_tNH3 _electrolysis |
– |
float |
The energy amount of hydrogen needed to produce a ton of ammonia using Haber–Bosch process. From Wang et al (2018), Base value assumed around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy) |
Mwh_elec_per_tNH3 _electrolysis |
– |
float |
The energy amount of electricity needed to produce a ton of ammonia using Haber–Bosch process. From Wang et al (2018), Table 13 (air separation and HB) |
Mwh_NH3_per_MWh _H2_cracker |
– |
float |
The energy amount of amonia needed to produce an energy amount hydrogen using ammonia cracker |
NH3_process_emissions |
MtCO2/a |
float |
The emission of ammonia production from steam methane reforming (SMR). From UNFCCC for 2015 for EU28 |
petrochemical_process _emissions |
MtCO2/a |
float |
The emission of petrochemical production. From UNFCCC for 2015 for EU28 |
HVC_primary_fraction |
– |
float |
The fraction of high value chemicals (HVC) produced via primary route |
HVC_mechanical_recycling _fraction |
– |
float |
The fraction of high value chemicals (HVC) produced using mechanical recycling |
HVC_chemical_recycling _fraction |
– |
float |
The fraction of high value chemicals (HVC) produced using chemical recycling |
HVC_environment_sequestration_fraction |
– |
float |
The fraction of high value chemicals (HVC) put into landfill resulting in additional carbon sequestration. The default value is 0. |
waste_to_energy |
– |
bool |
Switch to enable expansion of waste to energy CHPs for conversion of plastics. Default is false. |
waste_to_energy_cc |
– |
bool |
Switch to enable expansion of waste to energy CHPs for conversion of plastics with carbon capture. Default is false. |
sector_ratios_fraction_future |
– |
Dictionary with planning horizons as keys. |
The fraction of total progress in fuel and process switching achieved in the industry sector. |
basic_chemicals_without_NH3_production_today |
Mt/a |
float |
The amount of basic chemicals produced without ammonia (= 86 Mtethylene-equiv - 17 MtNH3). |
HVC_production_today |
MtHVC/a |
float |
The amount of high value chemicals (HVC) produced. This includes ethylene, propylene and BTX. From DECHEMA (2017), Figure 16, page 107 |
Mwh_elec_per_tHVC _mechanical_recycling |
MWh/tHVC |
float |
The energy amount of electricity needed to produce a ton of high value chemical (HVC) using mechanical recycling. From SI of Meys et al (2020), Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756. |
Mwh_elec_per_tHVC _chemical_recycling |
MWh/tHVC |
float |
The energy amount of electricity needed to produce a ton of high value chemical (HVC) using chemical recycling. The default value is based on pyrolysis and electric steam cracking. From Material Economics (2019), page 125 |
chlorine_production _today |
MtCl/a |
float |
The amount of chlorine produced. From DECHEMA (2017), Table 7, page 43 |
MWh_elec_per_tCl |
MWh/tCl |
float |
The energy amount of electricity needed to produce a ton of chlorine. From DECHEMA (2017), Table 6 page 43 |
MWh_H2_per_tCl |
MWhH2/tCl |
float |
The energy amount of hydrogen needed to produce a ton of chlorine. The value is negative since hydrogen produced in chloralkali process. From DECHEMA (2017), page 43 |
methanol_production _today |
MtMeOH/a |
float |
The amount of methanol produced. From DECHEMA (2017), page 62 |
MWh_elec_per_tMeOH |
MWh/tMeOH |
float |
The energy amount of electricity needed to produce a ton of methanol. From DECHEMA (2017), Table 14, page 65 |
MWh_CH4_per_tMeOH |
MWhCH4/tMeOH |
float |
The energy amount of methane needed to produce a ton of methanol. From DECHEMA (2017), Table 14, page 65 |
MWh_MeOH_per_tMeOH |
LHV |
float |
The energy amount per ton of methanol. From DECHEMA (2017), page 74. |
hotmaps_locate_missing |
– |
{true,false} |
Locate industrial sites without valid locations based on city and countries. |
reference_year |
year |
YYYY |
The year used as the baseline for industrial energy demand and production. Data extracted from JRC-IDEES 2015 |
oil_refining_emissions |
tCO2/MWh |
float |
The emissions from oil fuel processing (e.g. oil in petrochemical refinieries). The default value of 0.013 tCO2/MWh is based on DE statistics for 2019; the EU value is very similar. |
costs
#
costs:
year: 2030
version: v0.10.1
social_discountrate: 0.02
fill_values:
FOM: 0
VOM: 0
efficiency: 1
fuel: 0
investment: 0
lifetime: 25
"CO2 intensity": 0
"discount rate": 0.07
overwrites: {}
marginal_cost:
solar: 0.01
onwind: 0.015
offwind: 0.015
hydro: 0.
H2: 0.
electrolysis: 0.
fuel cell: 0.
battery: 0.
battery inverter: 0.
home battery storage: 0
water tank charger: 0.03
central water pit charger: 0.025
emission_prices:
enable: false
co2: 0.
co2_monthly_prices: false
Unit |
Values |
Description |
|
---|---|---|---|
year |
– |
YYYY; e.g. ‘2030’ |
Year for which to retrieve cost assumptions of |
version |
– |
vX.X.X or <user>/<repo>/vX.X.X; e.g. ‘v0.5.0’ |
Version of |
social_discountrate |
p.u. |
float |
Social discount rate to compare costs in different investment periods. 0.02 corresponds to a social discount rate of 2%. |
fill_values |
– |
float |
Default values if not specified for a technology in |
overwrites |
– |
Keys should be in the ‘parameter’ column of |
For the given parameters and technologies, assumptions about their parameter are overwritten the corresponding value of the technology. |
capital_cost |
EUR/MW |
Keys should be in the ‘technology’ column of |
For the given technologies, assumptions about their capital investment costs are set to the corresponding value. Optional; overwrites cost assumptions from |
marginal_cost |
EUR/MWh |
Keys should be in the ‘technology’ column of |
For the given technologies, assumptions about their marginal operating costs are set to the corresponding value. Optional; overwrites cost assumptions from |
emission_prices |
Specify exogenous prices for emission types listed in |
||
– enable |
bool |
true or false |
Add cost for a carbon-dioxide price configured in |
– co2 |
EUR/t |
float |
Exogenous price of carbon-dioxide added to the marginal costs of fossil-fuelled generators according to their carbon intensity. Added through the keyword |
– co2_monthly_price |
bool |
true or false |
Add monthly cost for a carbon-dioxide price based on historical values built by the rule |
clustering
#
clustering:
mode: busmap
administrative:
level: 1
focus_weights: false
copperplate_regions: []
build_bidding_zones:
remove_islands: false
aggregate_to_tyndp: false
simplify_network:
to_substations: false
remove_stubs: true
remove_stubs_across_borders: false
cluster_network:
algorithm: kmeans
hac_features:
- wnd100m
- influx_direct
exclude_carriers: []
consider_efficiency_classes: false
aggregation_strategies:
generators:
committable: any
ramp_limit_up: max
ramp_limit_down: max
temporal:
resolution_elec: false
resolution_sector: false
Tip
use min
in p_nom_max:
for more conservative assumptions.
adjustments
#
manual_adjustments: true # false
scaling_factor: 1.0
fixed_year: false # false or year (e.g. 2013)
supplement_synthetic: true
distribution_key:
gdp: 0.6
population: 0.4
Unit |
Values |
Description |
|
---|---|---|---|
adjustments |
|||
– electricity |
bool or dict |
Parameter adjustments applied in |
|
– – factor |
Multiply original value with given factor |
||
– – absolute |
Set attribute to absolute value |
||
– – – {component} |
PyPSA component in |
||
– – – – {carrier} |
Any carrier of the network to which parameter adjustment factor should be applied. |
||
– – – – – {attr} |
float |
per-unit |
Attribute to which parameter adjustment factor should be applied. |
– sector |
bool or dict |
Parameter adjustments applied in |
|
– – factor |
Multiply original value with given factor |
||
– – absolute |
Set attribute to absolute value |
||
– – – {component} |
PyPSA component in |
||
– – – – {carrier} |
Any carrier of the network to which parameter adjustment factor should be applied. |
||
– – – – – {attr} |
Float or dict |
per-unit |
Attribute to which parameter adjustment factor should be applied. Can be also a dictionary with planning horizons as keys. |
solving
#
solving:
options:
clip_p_max_pu: 1.e-2
load_shedding: false
curtailment_mode: false
noisy_costs: true
skip_iterations: true
rolling_horizon: false
seed: 123
custom_extra_functionality: "../data/custom_extra_functionality.py"
# io_api: "direct" # Increases performance but only supported for the highs and gurobi solvers
# options that go into the optimize function
track_iterations: false
min_iterations: 2
max_iterations: 3
transmission_losses: 2
linearized_unit_commitment: true
horizon: 365
post_discretization:
enable: false
line_unit_size: 1700
line_threshold: 0.3
link_unit_size:
DC: 2000
H2 pipeline: 1200
gas pipeline: 1500
link_threshold:
DC: 0.3
H2 pipeline: 0.3
gas pipeline: 0.3
fractional_last_unit_size: false
keep_files: false
model_kwargs:
solver_dir: ""
agg_p_nom_limits:
agg_offwind: false
agg_solar: false
include_existing: false
file: data/agg_p_nom_minmax.csv
constraints:
CCL: false
EQ: false
BAU: false
SAFE: false
solver:
name: gurobi
options: gurobi-default
solver_options:
highs-default:
# refer to https://ergo-code.github.io/HiGHS/dev/options/definitions/
threads: 1
solver: "ipm"
run_crossover: "off"
small_matrix_value: 1e-6
large_matrix_value: 1e9
primal_feasibility_tolerance: 1e-5
dual_feasibility_tolerance: 1e-5
ipm_optimality_tolerance: 1e-4
parallel: "on"
random_seed: 123
highs-simplex:
solver: "simplex"
parallel: "on"
primal_feasibility_tolerance: 1e-5
dual_feasibility_tolerance: 1e-5
random_seed: 123
gurobi-default:
threads: 8
method: 2 # barrier
crossover: 0
BarConvTol: 1.e-6
Seed: 123
AggFill: 0
PreDual: 0
GURO_PAR_BARDENSETHRESH: 200
gurobi-numeric-focus:
NumericFocus: 3 # Favour numeric stability over speed
method: 2 # barrier
crossover: 0 # do not use crossover
BarHomogeneous: 1 # Use homogeneous barrier if standard does not converge
BarConvTol: 1.e-5
FeasibilityTol: 1.e-4
OptimalityTol: 1.e-4
ObjScale: -0.5
threads: 8
Seed: 123
gurobi-fallback: # Use gurobi defaults
crossover: 0
method: 2 # barrier
BarHomogeneous: 1 # Use homogeneous barrier if standard does not converge
BarConvTol: 1.e-5
FeasibilityTol: 1.e-5
OptimalityTol: 1.e-5
Seed: 123
threads: 8
cplex-default:
threads: 4
lpmethod: 4 # barrier
solutiontype: 2 # non basic solution, ie no crossover
barrier.convergetol: 1.e-5
feasopt.tolerance: 1.e-6
copt-default:
Threads: 8
LpMethod: 2
Crossover: 0
RelGap: 1.e-6
Dualize: 0
copt-gpu:
LpMethod: 6
GPUMode: 1
PDLPTol: 1.e-5
Crossover: 0
cbc-default: {} # Used in CI
glpk-default: {} # Used in CI
check_objective:
enable: false
expected_value: None
atol: 1_000_000
rtol: 0.01
mem_mb: 30000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
memory_logging_frequency: 30 # in seconds
runtime: 6h #runtime in humanfriendly style https://humanfriendly.readthedocs.io/en/latest/
Unit |
Values |
Description |
|
---|---|---|---|
options |
|||
– clip_p_max_pu |
p.u. |
float |
To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero. |
– load_shedding |
bool/float |
{‘true’,’false’, float} |
Add generators with very high marginal cost to simulate load shedding and avoid problem infeasibilities. If load shedding is a float, it denotes the marginal cost in EUR/kWh. |
– curtailment_mode |
bool/float |
{‘true’,’false’} |
Fixes the dispatch profiles of generators with time-varying p_max_pu by setting |
– noisy_costs |
bool |
{‘true’,’false’} |
Add random noise to marginal cost of generators by \(\mathcal{U}(0.009,0,011)\) and capital cost of lines and links by \(\mathcal{U}(0.09,0,11)\). |
– skip_iterations |
bool |
{‘true’,’false’} |
Skip iterating, do not update impedances of branches. Defaults to true. |
– rolling_horizon |
bool |
{‘true’,’false’} |
Switch for rule |
– seed |
– |
int |
Random seed for increased deterministic behaviour. |
– custom_extra_functionality |
– |
str |
Path to a Python file with custom extra functionality code to be injected into the solving rules of the workflow relative to |
– io_api |
string |
{‘lp’,’mps’,’direct’} |
Passed to linopy and determines the API used to communicate with the solver. With the |
– track_iterations |
bool |
{‘true’,’false’} |
Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in |
– min_iterations |
– |
int |
Minimum number of solving iterations in between which resistance and reactence ( |
– max_iterations |
– |
int |
Maximum number of solving iterations in between which resistance and reactence ( |
– transmission_losses |
int |
[0-9] |
Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored. |
– linearized_unit_commitment |
bool |
{‘true’,’false’} |
Whether to optimise using the linearized unit commitment formulation. |
– horizon |
– |
int |
Number of snapshots to consider in each iteration. Defaults to 100. |
– post_discretization |
|||
– – enable |
bool |
{‘true’,’false’} |
Switch to enable post-discretization of the network. Disabled by default. |
– – line_unit_size |
MW |
float |
Discrete unit size of lines in MW. |
– – line_threshold |
float |
The threshold relative to the discrete line unit size beyond which to round up to the next unit. |
|
– – link_unit_size |
MW |
float |
Discrete unit size of links in MW by carrier (given in dictionary style). |
– – – {carrier} |
|||
– – link_threshold |
float |
The threshold relative to the discrete link unit size beyond which to round up to the next unit by carrier (given in dictionary style). |
|
– – – {carrier} |
|||
– – fractional_last_unit_size |
bool |
{‘true’,’false’} |
When true, links and lines can be built up to p_nom_max. When false, they can only be built up to a multiple of the unit size. |
– model_kwargs |
|||
– – solver_dir |
str |
‘/tmp’’ |
Absolute path to the directory where linopy saves files. |
– keep_files |
bool |
False |
Whether to keep LPs and MPS files after solving. |
agg_p_nom_limits |
Configure per carrier generator nominal capacity constraints for individual countries if |
||
– agg_offwind |
bool |
{‘true’,’false’} |
Aggregate together all the types of offwind when writing the constraint. Default is false. |
– agg_solar |
bool |
{‘true’,’false’} |
Aggregate together all the types of electric solar when writing the constraint. Default is false. |
– include_existing |
bool |
{‘true’,’false’} |
Take existing capacities into account when writing the constraint. Default is false. |
– file |
file |
path |
Reference to |
constraints |
|||
– CCL |
bool |
{‘true’,’false’} |
Add minimum and maximum levels of generator nominal capacity per carrier for individual countries. These can be specified in the file linked at |
– EQ |
bool/string |
{‘false’,`n(c| )``; i.e. |
Require each country or node to on average produce a minimal share of its total consumption itself. Example: |
– BAU |
bool |
{‘true’,’false’} |
Add a per- |
– SAFE |
bool |
{‘true’,’false’} |
Add a capacity reserve margin of a certain fraction above the peak demand to which renewable generators and storage do not contribute. Ignores network. |
solver |
|||
– name |
– |
One of {‘gurobi’, ‘cplex’, ‘highs’, ‘cbc’, ‘glpk’}; potentially more possible |
Solver to use for optimisation problems in the workflow; e.g. clustering and linear optimal power flow. |
– options |
– |
Key listed under |
Link to specific parameter settings. |
solver_options |
dict |
Dictionaries with solver-specific parameter settings. |
|
mem |
MB |
int |
Estimated maximum memory requirement for solving networks. |
mem_logging_frequency |
s |
int |
Interval in seconds at which memory usage is logged. |
plotting
#
plotting:
map:
boundaries: [-11, 30, 34, 71]
color_geomap:
ocean: white
land: white
projection:
name: "EqualEarth"
# See https://scitools.org.uk/cartopy/docs/latest/reference/projections.html for alternatives, for example:
# name: "LambertConformal"
# central_longitude: 10.
# central_latitude: 50.
# standard_parallels: [35, 65]
eu_node_location:
x: -5.5
y: 46.
costs_max: 1000
costs_threshold: 1
energy_max: 20000
energy_min: -20000
energy_threshold: 50.
balance_timeseries:
max_threshold: 5 # GW
mean_threshold: 1 # GW
monthly: true
monthly_resolution:
annual: true
annual_resolution: D
carriers:
- H2
- NH3
- gas
- methanol
- oil
- solid biomass
- biogas
- co2 stored
- co2
carrier_groups:
electricity:
- AC
- low voltage
heat:
- urban central heat
- urban decentral heat
- rural heat
- residential urban decentral heat
- residential rural heat
- services urban decentral heat
- services rural heat
heatmap_timeseries:
marginal_price:
- AC
- H2
- NH3
- gas
- methanol
- oil
- co2 stored
- urban central heat
utilisation_rate:
- solar
- solar rooftop
- solar-hsat
- onwind
- offwind-dc
- offwind-ac
- offwind-float
- ror
- hydro
- PHS
- battery charger
- battery discharger
- H2 Electrolysis
- Fischer-Tropsch
- methanolisation
- Sabatier
- OCGT
- H2 Fuel Cell
- urban central CHP
- urban central CHP CC
- urban central solid biomass CHP
- urban central solid biomass CHP CC
- rural gas boiler
- urban central air heat pump
- DAC
soc:
- battery
- H2 Store
- co2 stored
- gas
- methanol
- oil
- urban central water tanks
balance_map:
bus_carriers:
- AC
- H2
- gas
- oil
- methanol
- co2 stored
- urban central heat
AC:
unit: TWh
unit_conversion: 1_000_000
cmap: Greens
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.002
branch_factor: 0.01
flow_factor: 100
bus_sizes:
- 200
- 100
branch_sizes:
- 100
- 20
gas:
unit: TWh
unit_conversion: 1_000_000
cmap: Purples
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.002
branch_factor: 0.05
flow_factor: 60
bus_sizes:
- 200
- 100
branch_sizes:
- 100
- 50
H2:
unit: TWh
unit_conversion: 1_000_000
cmap: Blues
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.002
branch_factor: 0.07
flow_factor: 50
bus_sizes:
- 50
- 25
branch_sizes:
- 40
- 20
co2 stored:
unit: Mt
unit_conversion: 1_000_000
cmap: Purples
vmin:
vmax:
region_unit: €/t_${CO_2}$
bus_factor: 0.03
branch_factor: 1
flow_factor: 2_000
bus_sizes:
- 50
- 10
branch_sizes:
- 5
- 2
urban central heat:
unit: TWh
unit_conversion: 1_000_000
cmap: Oranges
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.005
branch_factor: 0.1
flow_factor: 100
bus_sizes:
- 300
- 100
branch_sizes:
methanol:
unit: TWh
unit_conversion: 1_000_000
cmap: Greens
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.005
branch_factor: 0.1
flow_factor: 100
bus_sizes:
- 20
- 10
branch_sizes:
biogas:
unit: TWh
unit_conversion: 1_000_000
cmap: Greens
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.1
branch_factor: 0.1
flow_factor: 100
bus_sizes:
- 100
- 50
branch_sizes:
solid biomass:
unit: TWh
unit_conversion: 1_000_000
cmap: Greens
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.01
branch_factor: 0.1
flow_factor: 100
bus_sizes:
- 100
- 50
branch_sizes:
oil:
unit: TWh
unit_conversion: 1_000_000
cmap: Greys
vmin:
vmax:
region_unit: €/MWh
bus_factor: 0.002
branch_factor: 0.01
flow_factor: 100
bus_sizes:
- 200
- 100
branch_sizes:
nice_names:
OCGT: "Open-Cycle Gas"
CCGT: "Combined-Cycle Gas"
offwind-ac: "Offshore Wind (AC)"
offwind-dc: "Offshore Wind (DC)"
offwind-float: "Offshore Wind (Floating)"
onwind: "Onshore Wind"
solar: "Solar"
PHS: "Pumped Hydro Storage"
hydro: "Reservoir & Dam"
battery: "Battery Storage"
H2: "Hydrogen Storage"
lines: "Transmission Lines"
ror: "Run of River"
load: "Load Shedding"
ac: "AC"
dc: "DC"
tech_colors:
# wind
onwind: "#235ebc"
onshore wind: "#235ebc"
offwind: "#6895dd"
offshore wind: "#6895dd"
offwind-ac: "#6895dd"
offshore wind (AC): "#6895dd"
offshore wind ac: "#6895dd"
offwind-dc: "#74c6f2"
offshore wind (DC): "#74c6f2"
offshore wind dc: "#74c6f2"
offwind-float: "#b5e2fa"
offshore wind (Float): "#b5e2fa"
offshore wind float: "#b5e2fa"
# water
hydro: '#298c81'
hydro reservoir: '#298c81'
ror: '#3dbfb0'
run of river: '#3dbfb0'
hydroelectricity: '#298c81'
PHS: '#51dbcc'
hydro+PHS: "#08ad97"
# solar
solar: "#f9d002"
solar PV: "#f9d002"
solar-hsat: "#fdb915"
solar thermal: '#ffbf2b'
residential rural solar thermal: '#f1c069'
services rural solar thermal: '#eabf61'
residential urban decentral solar thermal: '#e5bc5a'
services urban decentral solar thermal: '#dfb953'
urban central solar thermal: '#d7b24c'
solar rooftop: '#ffea80'
# gas
OCGT: '#e0986c'
OCGT marginal: '#e0986c'
OCGT-heat: '#e0986c'
gas boiler: '#db6a25'
gas boilers: '#db6a25'
gas boiler marginal: '#db6a25'
residential rural gas boiler: '#d4722e'
residential urban decentral gas boiler: '#cb7a36'
services rural gas boiler: '#c4813f'
services urban decentral gas boiler: '#ba8947'
urban central gas boiler: '#b0904f'
gas: '#e05b09'
fossil gas: '#e05b09'
natural gas: '#e05b09'
biogas to gas: '#e36311'
biogas to gas CC: '#e51245'
CCGT: '#a85522'
CCGT marginal: '#a85522'
allam: '#B98F76'
gas for industry co2 to atmosphere: '#692e0a'
gas for industry co2 to stored: '#8a3400'
gas for industry: '#853403'
gas for industry CC: '#692e0a'
gas pipeline: '#ebbca0'
gas pipeline new: '#a87c62'
# oil
oil: '#c9c9c9'
oil primary: '#d2d2d2'
oil refining: '#e6e6e6'
imported oil: '#a3a3a3'
oil boiler: '#adadad'
residential rural oil boiler: '#a9a9a9'
services rural oil boiler: '#a5a5a5'
residential urban decentral oil boiler: '#a1a1a1'
urban central oil boiler: '#9d9d9d'
services urban decentral oil boiler: '#999999'
agriculture machinery oil: '#949494'
shipping oil: "#808080"
land transport oil: '#afafaf'
# nuclear
Nuclear: '#ff8c00'
Nuclear marginal: '#ff8c00'
nuclear: '#ff8c00'
uranium: '#ff8c00'
# coal
Coal: '#545454'
coal: '#545454'
Coal marginal: '#545454'
coal for industry: '#343434'
solid: '#545454'
Lignite: '#826837'
lignite: '#826837'
Lignite marginal: '#826837'
# biomass
biogas: '#e3d37d'
biomass: '#baa741'
solid biomass: '#baa741'
municipal solid waste: '#91ba41'
solid biomass import: '#d5ca8d'
solid biomass transport: '#baa741'
solid biomass for industry: '#7a6d26'
solid biomass for industry CC: '#47411c'
solid biomass for industry co2 from atmosphere: '#736412'
solid biomass for industry co2 to stored: '#47411c'
urban central solid biomass CHP: '#9d9042'
urban central solid biomass CHP CC: '#6c5d28'
biomass boiler: '#8A9A5B'
residential rural biomass boiler: '#a1a066'
residential urban decentral biomass boiler: '#b0b87b'
services rural biomass boiler: '#c6cf98'
services urban decentral biomass boiler: '#dde5b5'
biomass to liquid: '#32CD32'
unsustainable solid biomass: '#998622'
unsustainable bioliquids: '#32CD32'
electrobiofuels: 'red'
BioSNG: '#123456'
BioSNG CC: '#45233b'
solid biomass to hydrogen: '#654321'
# power transmission
lines: '#6c9459'
transmission lines: '#6c9459'
electricity distribution grid: '#97ad8c'
low voltage: '#97ad8c'
# electricity demand
Electric load: '#110d63'
electric demand: '#110d63'
electricity: '#110d63'
industry electricity: '#2d2a66'
industry new electricity: '#2d2a66'
agriculture electricity: '#494778'
# battery + EVs
battery: '#ace37f'
battery storage: '#ace37f'
battery charger: '#88a75b'
battery discharger: '#5d4e29'
home battery: '#80c944'
home battery storage: '#80c944'
home battery charger: '#5e8032'
home battery discharger: '#3c5221'
BEV charger: '#baf238'
V2G: '#e5ffa8'
land transport EV: '#baf238'
land transport demand: '#38baf2'
EV battery: '#baf238'
# hot water storage
water tanks: '#e69487'
residential rural water tanks: '#f7b7a3'
services rural water tanks: '#f3afa3'
residential urban decentral water tanks: '#f2b2a3'
services urban decentral water tanks: '#f1b4a4'
urban central water tanks: '#e9977d'
hot water storage: '#e69487'
hot water charging: '#e8998b'
urban central water tanks charger: '#b57a67'
residential rural water tanks charger: '#b4887c'
residential urban decentral water tanks charger: '#b39995'
services rural water tanks charger: '#b3abb0'
services urban decentral water tanks charger: '#b3becc'
hot water discharging: '#e99c8e'
urban central water tanks discharger: '#b9816e'
residential rural water tanks discharger: '#ba9685'
residential urban decentral water tanks discharger: '#baac9e'
services rural water tanks discharger: '#bbc2b8'
services urban decentral water tanks discharger: '#bdd8d3'
water pits: "#cc826a"
water pits charger: "#b36a5e"
water pits discharger: "#b37468"
urban central water pits: "#d96f4c"
urban central water pits charger: "#a85d47"
urban central water pits discharger: "#b36452"
aquifer thermal energy storage: "#6d00fc"
aquifer thermal energy storage charger: "#6d00fc"
aquifer thermal energy storage discharger: "#6d00fc"
# heat demand
Heat load: '#cc1f1f'
heat: '#cc1f1f'
heat vent: '#aa3344'
heat demand: '#cc1f1f'
rural heat: '#ff5c5c'
residential rural heat: '#ff7c7c'
services rural heat: '#ff9c9c'
central heat: '#cc1f1f'
urban central heat: '#d15959'
urban central heat vent: '#a74747'
decentral heat: '#750606'
residential urban decentral heat: '#a33c3c'
services urban decentral heat: '#cc1f1f'
low-temperature heat for industry: '#8f2727'
process heat: '#ff0000'
agriculture heat: '#d9a5a5'
# heat supply
heat pumps: '#2fb537'
heat pump: '#2fb537'
air heat pump: '#36eb41'
residential urban decentral air heat pump: '#48f74f'
services urban decentral air heat pump: '#5af95d'
services rural air heat pump: '#5af95d'
urban central air heat pump: '#6cfb6b'
ptes heat pump: '#5dade2'
urban central ptes heat pump: '#3498db'
urban central geothermal heat pump: '#4f2144'
geothermal heat pump: '#4f2144'
geothermal heat direct utilisation: '#ba91b1'
ground heat pump: '#2fb537'
residential rural ground heat pump: '#4f2144'
residential rural air heat pump: '#48f74f'
services rural ground heat pump: '#5af95d'
Ambient: '#98eb9d'
CHP: '#8a5751'
urban central gas CHP: '#8d5e56'
CHP CC: '#634643'
urban central gas CHP CC: '#6e4e4c'
CHP heat: '#8a5751'
CHP electric: '#8a5751'
district heating: '#e8beac'
resistive heater: '#d8f9b8'
residential rural resistive heater: '#bef5b5'
residential urban decentral resistive heater: '#b2f1a9'
services rural resistive heater: '#a5ed9d'
services urban decentral resistive heater: '#98e991'
urban central resistive heater: '#8cdf85'
retrofitting: '#8487e8'
building retrofitting: '#8487e8'
# hydrogen
H2 for industry: "#f073da"
H2 for shipping: "#ebaee0"
H2: '#bf13a0'
hydrogen: '#bf13a0'
retrofitted H2 boiler: '#e5a0d9'
SMR: '#870c71'
SMR CC: '#4f1745'
H2 liquefaction: '#d647bd'
hydrogen storage: '#bf13a0'
H2 Store: '#bf13a0'
H2 storage: '#bf13a0'
land transport fuel cell: '#6b3161'
H2 pipeline: '#f081dc'
H2 pipeline retrofitted: '#ba99b5'
H2 Fuel Cell: '#c251ae'
H2 fuel cell: '#c251ae'
H2 turbine: '#991f83'
H2 Electrolysis: '#ff29d9'
H2 electrolysis: '#ff29d9'
# ammonia
NH3: '#46caf0'
ammonia: '#46caf0'
ammonia store: '#00ace0'
ammonia cracker: '#87d0e6'
Haber-Bosch: '#076987'
# syngas
Sabatier: '#9850ad'
methanation: '#c44ce6'
methane: '#c44ce6'
# synfuels
Fischer-Tropsch: '#25c49a'
liquid: '#25c49a'
kerosene for aviation: '#a1ffe6'
naphtha for industry: '#57ebc4'
methanol-to-kerosene: '#C98468'
methanol-to-olefins/aromatics: '#FFA07A'
Methanol steam reforming: '#FFBF00'
Methanol steam reforming CC: '#A2EA8A'
methanolisation: '#00FFBF'
biomass-to-methanol: '#EAD28A'
biomass-to-methanol CC: '#EADBAD'
allam methanol: '#B98F76'
CCGT methanol: '#B98F76'
CCGT methanol CC: '#B98F76'
OCGT methanol: '#B98F76'
methanol: '#FF7B00'
methanol transport: '#FF7B00'
shipping methanol: '#468c8b'
industry methanol: '#468c8b'
# co2
CC: '#f29dae'
CCS: '#f29dae'
CO2 sequestration: '#f29dae'
DAC: '#ff5270'
co2 stored: '#f2385a'
co2 sequestered: '#f2682f'
co2: '#f29dae'
co2 vent: '#ffd4dc'
CO2 pipeline: '#f5627f'
# emissions
process emissions CC: '#000000'
process emissions: '#222222'
process emissions to stored: '#444444'
process emissions to atmosphere: '#888888'
oil emissions: '#aaaaaa'
shipping oil emissions: "#555555"
shipping methanol emissions: '#666666'
land transport oil emissions: '#777777'
agriculture machinery oil emissions: '#333333'
# other
shipping: '#03a2ff'
power-to-heat: '#2fb537'
power-to-gas: '#c44ce6'
power-to-H2: '#ff29d9'
power-to-liquid: '#25c49a'
gas-to-power/heat: '#ee8340'
waste: '#e3d37d'
other: '#000000'
geothermal: '#ba91b1'
geothermal heat: '#ba91b1'
geothermal district heat: '#d19D00'
geothermal organic rankine cycle: '#ffbf00'
AC: "#70af1d"
AC-AC: "#70af1d"
AC line: "#70af1d"
links: "#8a1caf"
HVDC links: "#8a1caf"
DC: "#8a1caf"
DC-DC: "#8a1caf"
DC link: "#8a1caf"
load: "#dd2e23"
waste CHP: '#e3d37d'
waste CHP CC: '#e3d3ff'
non-sequestered HVC: '#8f79b5'
HVC to air: 'k'
import H2: '#db8ccd'
import gas: '#f7a572'
import NH3: '#e2ed74'
import oil: '#93eda2'
import methanol: '#87d0e6'
Unit |
Values |
Description |
|
---|---|---|---|
map |
|||
– boundaries |
° |
[x1,x2,y1,y2] |
Boundaries of the map plots in degrees latitude (y) and longitude (x) |
– color_geomap |
|||
– – ocean |
– |
str |
Color of the ocean in the geomap. |
– – land |
– |
str |
Color of the land in the geomap. |
projection |
|||
– name |
– |
Valid Cartopy projection name |
See https://scitools.org.uk/cartopy/docs/latest/reference/projections.html for list of available projections. |
– args |
– |
– |
Other entries under ‘projection’ are passed as keyword arguments to the projection constructor, e.g. |
eu_node_location |
|||
– x |
° |
float |
Longitude of the EU node location. |
– y |
° |
float |
Latitude of the EU node location. |
costs_max |
bn Euro |
float |
Upper y-axis limit in cost bar plots. |
costs_threshold |
bn Euro |
float |
Threshold below which technologies will not be shown in cost bar plots. |
energy_max |
TWh |
float |
Upper y-axis limit in energy bar plots. |
energy_min |
TWh |
float |
Lower y-axis limit in energy bar plots. |
energy_threshold |
TWh |
float |
Threshold below which technologies will not be shown in energy bar plots. |
balance_timeseries: |
|||
– max_threshold |
GW or kt/h for CO2 |
float |
Technologies with maximum absolute dispatch below this threshold are grouped to ‘other’. |
– mean_threshold |
GW or kt/h for CO2 |
float |
Technologies with mean absolute dispatch below this threshold are grouped to ‘other’. |
– monthly |
{True,False} |
bool |
Whether to plot monthly balance timeseries. |
– monthly_resolution |
e.g. 1h |
str |
Resolution of the monthly balance timeseries. Argument to pandas.DataFrame.resample. Defaults to ‘null’ which uses the model-native resolution. |
– annual |
{True,False} |
bool |
Whether to plot annual balance timeseries. |
– annual_resolution |
e.g. 1h |
str |
Resolution of the annual balance timeseries. Argument to pandas.DataFrame.resample. Defaults to ‘D’ which applies daily resampling. |
– carriers |
– |
list |
Subset of bus carriers to plot in the balance timeseries. |
– carrier_groups |
– |
dict |
Mapping from carrier group names to list of bus carriers. E.g. a key ‘electricity’ to include ‘AC’ and ‘low voltage’. |
heatmap_timeseries |
Plotting configuration for |
||
– marginal_price |
– |
list |
Subset of bus carriers to plot marginal prices heatmap time series for. |
– utilisation_rate |
– |
list |
Subset of carriers to plot utilisation rates heatmap time series for. |
– soc |
– |
list |
Subset of carriers to plot state of charge heatmap time series for. |
balance_map |
|||
– bus_carriers |
– |
[str] |
List of carriers to plot. |
– {bus_carrier} |
|||
– – unit |
– |
str |
Unit of the energy carrier like TWh for electricity with conversion factor of a million. |
– – unit_conversion |
– |
float |
Conversion factor for the energy carrier unit. |
– – cmap |
– |
str |
Colormap for the price of the regions. |
– – vmin |
– |
float |
Minimum value for the colormap. |
– – vmax |
– |
float |
Maximum value for the colormap. |
– – region_unit |
– |
str |
Unit for the price like €/MWh for electricity. |
– – bus_factor |
– |
float |
Factor for the bus sizes by which they are multiplied. |
– – branch_factor |
– |
float |
Factor for the branch sizes by which they are multiplied. |
– – flow_factor |
– |
float |
Factor for the flow sizes by which they are multiplied. |
– – bus_sizes |
– |
[float] |
Sizes for the buses in the legend. |
– – branch_sizes |
– |
[float] |
Sizes for the branches in the legend. |
tech_colors |
– |
carrier -> HEX colour code |
Mapping from network |
nice_names |
– |
str -> str |
Mapping from network |