Configuration#
PyPSA-Eur has several configuration options which are documented in this section and are collected in a config/config.yaml
file located in the root directory. Users should copy the provided default configuration (config/config.default.yaml
) and amend their own modifications and assumptions in the user-specific configuration file (config/config.yaml
); confer installation instructions at Handling Configuration Files.
Top-level configuration#
“Private” refers to local, machine-specific settings or data meant for personal use, not to be shared. “Remote” indicates the address of a server used for data exchange, often for clusters and data pushing/pulling.
version: 0.8.1
tutorial: false
logging:
level: INFO
format: '%(levelname)s:%(name)s:%(message)s'
private:
keys:
entsoe_api:
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. |
|
private |
|||
– keys |
|||
– – entsoe_api |
– |
Optionally specify the ENTSO-E API key. See the guidelines to get ENTSO-E API key |
|
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:
name: ""
disable_progressbar: false
shared_resources: false
shared_cutouts: true
Unit |
Values |
Description |
|
---|---|---|---|
name |
– |
any string |
Specify a name for your run. Results will be stored under this name. |
disable_progrssbar |
bool |
{true, false} |
Switch to select whether progressbar should be disabled. |
shared_resources |
bool |
{true, false} |
Switch to select whether resources should be shared across runs. |
shared_cutouts |
bool |
{true, false} |
Switch to select whether cutouts should be shared across runs. |
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/elec_s{simpl}_{clusters}_ec_l{ll}_{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:
simpl:
- ''
ll:
- v1.5
clusters:
- 37
- 128
- 256
- 512
- 1024
opts:
- ''
sector_opts:
- Co2L0-3H-T-H-B-I-A-solar+p3-dist1
planning_horizons:
# - 2020
# - 2030
# - 2040
- 2050
Unit |
Values |
Description |
|
---|---|---|---|
simpl |
– |
List of |
|
clusters |
– |
List of |
|
ll |
– |
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']
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’, ‘ME’, ‘MK’, ‘NL’, ‘NO’, ‘PL’, ‘PT’, ‘RO’, ‘RS’, ‘SE’, ‘SI’, ‘SK’} |
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 datetime-like; e.g. YYYY-MM-DD |
Left bound of date range |
end |
– |
str or 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
prepare_links_p_nom: false
retrieve_databundle: true
retrieve_sector_databundle: true
retrieve_cost_data: true
build_cutout: false
retrieve_cutout: true
build_natura_raster: false
retrieve_natura_raster: true
custom_busmap: false
Unit |
Values |
Description |
|
---|---|---|---|
enable |
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. |
prepare_links_p_nom |
bool |
{true, false} |
Switch to retrieve current HVDC projects from Wikipedia |
retrieve_databundle |
bool |
{true, false} |
Switch to retrieve databundle from zenodo via the rule |
retrieve_sector_databundle |
bool |
{true, false} |
Switch to retrieve sector 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 |
build_natura_raster |
bool |
{true, false} |
Switch to enable the creation of the raster |
retrieve_natura_raster |
bool |
{true, false} |
Switch to enable the retrieval of |
custom_busmap |
bool |
{true, false} |
Switch to enable the use of custom busmaps in rule |
co2 budget
#
co2_budget:
2020: 0.701
2025: 0.524
2030: 0.297
2035: 0.150
2040: 0.071
2045: 0.032
2050: 0.000
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., 380.]
gaslimit: false
co2limit: 7.75e+7
co2base: 1.487e+9
agg_p_nom_limits: data/agg_p_nom_minmax.csv
operational_reserve:
activate: false
epsilon_load: 0.02
epsilon_vres: 0.02
contingency: 4000
max_hours:
battery: 6
H2: 168
extendable_carriers:
Generator: [solar, onwind, offwind-ac, offwind-dc, OCGT]
StorageUnit: [] # battery, H2
Store: [battery, H2]
Link: [] # H2 pipeline
powerplants_filter: (DateOut >= 2022 or DateOut != DateOut)
custom_powerplants: false
conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
renewable_carriers: [solar, onwind, offwind-ac, offwind-dc, hydro]
estimate_renewable_capacities:
enable: true
from_opsd: true
year: 2020
expansion_limit: false
technology_mapping:
Offshore: [offwind-ac, offwind-dc]
Onshore: [onwind]
PV: [solar]
Unit |
Values |
Description |
|
---|---|---|---|
voltages |
kV |
Any subset of {220., 300., 380.} |
Voltage levels to consider |
gaslimit |
MWhth |
float or false |
Global gas usage limit |
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 |
agg_p_nom_limits |
file |
path |
Reference to |
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. |
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, hydro} |
List of renewable generators to include in the model. |
estimate_renewable_capacities |
|||
– enable |
bool |
Activate routine to estimate renewable capacities |
|
– from_opsd |
– |
bool |
Add renewable capacities from OPSD database. The value is depreciated but still can be used. |
– 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 |
– |
Any subset of {offwind-ac, offwind-dc} |
List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) onshore technology. |
– – Offshore |
– |
{onwind} |
List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) offshore technology. |
– – PV |
– |
{solar} |
List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) PV technology. |
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:
default_cutout: europe-2013-era5
nprocesses: 4
show_progress: false
cutouts:
# use 'base' to determine geographical bounds and time span from config
# base:
# module: era5
europe-2013-era5:
module: era5 # in priority order
x: [-12., 35.]
y: [33., 72]
dx: 0.3
dy: 0.3
time: ['2013', '2013']
europe-2013-sarah:
module: [sarah, era5] # in priority order
x: [-12., 45.]
y: [33., 65]
dx: 0.2
dy: 0.2
time: ['2013', '2013']
sarah_interpolate: false
sarah_dir:
features: [influx, temperature]
Unit |
Values |
Description |
|
---|---|---|---|
default_cutout |
– |
str |
Defines a default cutout. |
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-2) |
– – 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: europe-2013-era5
resource:
method: wind
turbine: Vestas_V112_3MW
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]
natura: true
excluder_resolution: 100
potential: simple # or conservative
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
Should be a folder listed in the configuration |
Specifies the directory where the relevant weather data ist stored. |
resource |
|||
– method |
– |
Must be ‘wind’ |
A superordinate technology type. |
– turbine |
– |
One of turbine types included in atlite |
Specifies the turbine type and its characteristic power curve. |
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 |
natura |
bool |
{true, false} |
Switch to exclude Natura 2000 natural protection areas. Area is excluded if |
potential |
– |
One of {‘simple’, ‘conservative’} |
Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles |
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-ac
#
offwind-ac:
cutout: europe-2013-era5
resource:
method: wind
turbine: NREL_ReferenceTurbine_5MW_offshore
capacity_per_sqkm: 2
correction_factor: 0.8855
corine: [44, 255]
natura: true
ship_threshold: 400
max_depth: 50
max_shore_distance: 30000
excluder_resolution: 200
potential: simple # or conservative
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
Should be a folder listed in the configuration |
Specifies the directory where the relevant weather data ist stored. |
resource |
|||
– method |
– |
Must be ‘wind’ |
A superordinate technology type. |
– turbine |
– |
One of turbine types included in atlite |
Specifies the turbine type and its characteristic power curve. |
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. |
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. |
potential |
– |
One of {‘simple’, ‘conservative’} |
Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles |
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. |
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
offwind-dc
#
offwind-dc:
cutout: europe-2013-era5
resource:
method: wind
turbine: NREL_ReferenceTurbine_5MW_offshore
capacity_per_sqkm: 2
correction_factor: 0.8855
corine: [44, 255]
natura: true
ship_threshold: 400
max_depth: 50
min_shore_distance: 30000
excluder_resolution: 200
potential: simple # or conservative
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
Should be a folder listed in the configuration |
Specifies the directory where the relevant weather data ist stored. |
resource |
|||
– method |
– |
Must be ‘wind’ |
A superordinate technology type. |
– turbine |
– |
One of turbine types included in atlite |
Specifies the turbine type and its characteristic power curve. |
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. |
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. |
max_shore_distance |
m |
float |
Maximum distance to the shore above which wind turbines cannot be build. |
potential |
– |
One of {‘simple’, ‘conservative’} |
Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles |
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. |
Note
both offwind-ac
and offwind-dc
have the same assumption on
capacity_per_sqkm
and correction_factor
.
solar
#
solar:
cutout: europe-2013-sarah
resource:
method: pv
panel: CSi
orientation:
slope: 35.
azimuth: 180.
capacity_per_sqkm: 1.7
# 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]
natura: true
excluder_resolution: 100
potential: simple # or conservative
clip_p_max_pu: 1.e-2
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
Should be a folder listed in the configuration |
Specifies the directory where the relevant weather data ist stored that is specified at |
resource |
|||
– method |
– |
Must be ‘pv’ |
A superordinate technology type. |
– panel |
– |
One of {‘Csi’, ‘CdTe’, ‘KANENA’} as defined in atlite |
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.°. |
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. |
natura |
bool |
{true, false} |
Switch to exclude Natura 2000 natural protection areas. Area is excluded if |
potential |
– |
One of {‘simple’, ‘conservative’} |
Method to compute the maximal installable potential for a node; confer Rule build_renewable_profiles |
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: europe-2013-era5
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
Unit |
Values |
Description |
|
---|---|---|---|
cutout |
– |
Must be ‘europe-2013-era5’ |
Specifies the directory where the relevant weather data ist stored. |
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. |
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"
380.: "Al/St 240/40 4-bundle 380.0"
s_max_pu: 0.7
s_nom_max: .inf
max_extension: .inf
length_factor: 1.25
under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
dynamic_line_rating:
activate: false
cutout: europe-2013-era5
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. |
dynamic_line_rating |
|||
– activate |
bool |
true or false |
Whether to take dynamic line rating into account |
– cutout |
– |
Should be a folder listed in the configuration |
Specifies the directory where the relevant weather data ist stored. |
– 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_nom_max: .inf
max_extension: .inf
include_tyndp: true
under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
Unit |
Values |
Description |
|
---|---|---|---|
p_max_pu |
– |
Value in [0.,1.] |
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. |
include_tyndp |
bool |
{‘true’, ‘false’} |
Specifies whether to add HVDC link projects from the TYNDP 2018 which are at least in permitting. |
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. |
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
#
Unit |
Values |
Description |
|
---|---|---|---|
power_statistics |
bool |
{true, false} |
Whether to load the electricity consumption data of the ENTSOE power statistics (only for files from 2019 and before) or from the ENTSOE transparency data (only has load data from 2015 onwards). |
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. |
energy
#
Note
Only used for sector-coupling studies.
energy:
energy_totals_year: 2011
base_emissions_year: 1990
eurostat_report_year: 2016
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). |
eurostat_report_year |
– |
{2016,2017,2018} |
The publication year of the Eurostat report. 2016 includes Bosnia and Herzegovina, 2017 does not |
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
- Municipal waste
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
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 |
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.
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: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2020, 2025, 2030]
grouping_years_heat: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019] # these should not extend 2020
threshold_capacity: 10
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 |
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:
district_heating:
potential: 0.6
progress:
2020: 0.0
2030: 0.3
2040: 0.6
2050: 1.0
district_heating_loss: 0.15
cluster_heat_buses: false
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_availability: 0.5
bev_energy: 0.05
bev_charge_efficiency: 0.9
bev_plug_to_wheel_efficiency: 0.2
bev_charge_rate: 0.011
bev_avail_max: 0.95
bev_avail_mean: 0.8
v2g: true
land_transport_fuel_cell_share:
2020: 0
2030: 0.05
2040: 0.1
2050: 0.15
land_transport_electric_share:
2020: 0
2030: 0.25
2040: 0.6
2050: 0.85
land_transport_ice_share:
2020: 1
2030: 0.7
2040: 0.3
2050: 0
transport_fuel_cell_efficiency: 0.5
transport_internal_combustion_efficiency: 0.3
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
2030: 0
2040: 0
2050: 0
shipping_methanol_share:
2020: 0
2030: 0.3
2040: 0.7
2050: 1
shipping_oil_share:
2020: 1
2030: 0.7
2040: 0.3
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: 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
oil_boilers: false
biomass_boiler: true
chp: true
micro_chp: false
solar_thermal: true
solar_cf_correction: 0.788457 # = >>> 1/1.2683
marginal_cost_storage: 0. #1e-4
methanation: true
helmeth: false
coal_cc: false
dac: true
co2_vent: false
allam_cycle: false
hydrogen_fuel_cell: true
hydrogen_turbine: false
SMR: true
regional_co2_sequestration_potential:
enable: false
attribute: 'conservative estimate Mt'
include_onshore: false
min_size: 3
max_size: 25
years_of_storage: 25
co2_sequestration_potential: 200
co2_sequestration_cost: 10
co2_spatial: false
co2network: false
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
ammonia: false
min_part_load_fischer_tropsch: 0.9
min_part_load_methanolisation: 0.5
use_fischer_tropsch_waste_heat: true
use_fuel_cell_waste_heat: true
use_electrolysis_waste_heat: false
electricity_distribution_grid: true
electricity_distribution_grid_cost_factor: 1.0
electricity_grid_connection: true
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
conventional_generation:
OCGT: gas
biomass_to_liquid: false
biosng: false
Unit |
Values |
Description |
|
---|---|---|---|
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 |
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_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_plug_to_wheel _efficiency |
km/kWh |
float |
The distance battery electric vehicles (BEV) can travel in km per kWh of energy charge in battery. Base value comes from Tesla Model S |
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 |
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_fuel_cell _efficiency |
– |
float |
The H2 conversion efficiencies of fuel cells in transport |
transport_internal _combustion_efficiency |
– |
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 64. |
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 electricity into heat using resistive heater |
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 |
chp |
– |
{true, false} |
Add option for using Combined Heat and Power (CHP) |
micro_chp |
– |
{true, false} |
Add option for using 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_storage |
currency/MWh |
float |
The marginal cost of discharging batteries in distributed grids |
methanation |
– |
{true, false} |
Add option for transforming hydrogen and CO2 into methane using methanation. |
helmeth |
– |
{true, false} |
Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion) |
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. |
allam_cycle |
– |
{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) |
regional_co2 _sequestration_potential |
|||
– enable |
– |
{true, false} |
Add option for regionally-resolved geological carbon dioxide sequestration potentials based on CO2StoP. |
– attribute |
– |
string |
Name of the attribute 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 |
MtCO2/a |
float |
The potential of sequestering CO2 in Europe per year |
co2_sequestration_cost |
currency/tCO2 |
float |
The cost of sequestering a ton of CO2 |
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. |
co2network |
– |
{true, false} |
Add option for planning a new 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. |
|
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_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 |
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 |
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 |
biosng |
– |
{true, false} |
Add option for transforming solid biomass into synthesis gas with the same properties as natural gas |
industry
#
Note
Only used for sector-coupling studies.
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: 6.5
MWh_elec_per_tNH3_electrolysis: 1.17
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_fraction: 1.
HVC_mechanical_recycling_fraction: 0.
HVC_chemical_recycling_fraction: 0.
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
hotmaps_locate_missing: false
reference_year: 2015
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_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 |
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 |
costs
#
costs:
year: 2030
version: v0.6.0
rooftop_share: 0.14 # based on the potentials, assuming (0.1 kW/m2 and 10 m2/person)
fill_values:
FOM: 0
VOM: 0
efficiency: 1
fuel: 0
investment: 0
lifetime: 25
"CO2 intensity": 0
"discount rate": 0.07
# Marginal and capital costs can be overwritten
# capital_cost:
# onwind: 500
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.
emission_prices:
co2: 0.
Unit |
Values |
Description |
|
---|---|---|---|
year |
– |
YYYY; e.g. ‘2030’ |
Year for which to retrieve cost assumptions of |
version |
– |
vX.X.X; e.g. ‘v0.5.0’ |
Version of |
rooftop_share |
– |
float |
Share of rooftop PV when calculating capital cost of solar (joint rooftop and utility-scale PV). |
fill_values |
– |
float |
Default values if not specified for a technology in |
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 |
||
– 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 |
Note
rooftop_share:
are based on the potentials, assuming
(0.1 kW/m2 and 10 m2/person)
clustering
#
clustering:
simplify_network:
to_substations: false
algorithm: kmeans # choose from: [hac, kmeans]
feature: solar+onwind-time
exclude_carriers: []
remove_stubs: true
remove_stubs_across_borders: true
cluster_network:
algorithm: kmeans
feature: solar+onwind-time
exclude_carriers: []
consider_efficiency_classes: false
aggregation_strategies:
generators:
committable: any
ramp_limit_up: max
ramp_limit_down: max
Unit |
Values |
Description |
|
---|---|---|---|
simplify_network |
|||
– to_substations |
bool |
{‘true’,’false’} |
Aggregates all nodes without power injection (positive or negative, i.e. demand or generation) to electrically closest ones |
– algorithm |
str |
One of {‘kmeans’, ‘hac’, ‘modularity‘} |
|
– feature |
str |
Str in the format ‘carrier1+carrier2+…+carrierN-X’, where CarrierI can be from {‘solar’, ‘onwind’, ‘offwind’, ‘ror’} and X is one of {‘cap’, ‘time’}. |
|
– exclude_carriers |
list |
List of Str like [ ‘solar’, ‘onwind’] or empy list [] |
List of carriers which will not be aggregated. If empty, all carriers will be aggregated. |
– remove stubs |
bool |
{‘true’,’false’} |
Controls whether radial parts of the network should be recursively aggregated. Defaults to true. |
– remove_stubs_across_borders |
bool |
{‘true’,’false’} |
Controls whether radial parts of the network should be recursively aggregated across borders. Defaults to true. |
cluster_network |
|||
– algorithm |
str |
One of {‘kmeans’, ‘hac’} |
|
– feature |
str |
Str in the format ‘carrier1+carrier2+…+carrierN-X’, where CarrierI can be from {‘solar’, ‘onwind’, ‘offwind’, ‘ror’} and X is one of {‘cap’, ‘time’}. |
|
– exclude_carriers |
list |
List of Str like [ ‘solar’, ‘onwind’] or empy list [] |
List of carriers which will not be aggregated. If empty, all carriers will be aggregated. |
– consider_efficiency_classes |
bool |
{‘true’,’false’} |
Aggregated each carriers into the top 10-quantile (high), the bottom 90-quantile (low), and everything in between (medium). |
aggregation_strategies |
|||
– generators |
|||
– – {key} |
str |
{key} can be any of the component of the generator (str). It’s value can be any that can be converted to pandas.Series using getattr(). For example one of {min, max, sum}. |
Aggregates the component according to the given strategy. For example, if sum, then all values within each cluster are summed to represent the new generator. |
– buses |
|||
– – {key} |
str |
{key} can be any of the component of the bus (str). It’s value can be any that can be converted to pandas.Series using getattr(). For example one of {min, max, sum}. |
Aggregates the component according to the given strategy. For example, if sum, then all values within each cluster are summed to represent the new bus. |
Note
feature:
in simplify_network:
are only relevant if hac
were chosen in algorithm
.
Tip
use min
in p_nom_max:
for more `
conservative assumptions.
solving
#
solving:
#tmpdir: "path/to/tmp"
options:
clip_p_max_pu: 1.e-2
load_shedding: false
noisy_costs: true
skip_iterations: true
rolling_horizon: false
seed: 123
# options that go into the optimize function
track_iterations: false
min_iterations: 4
max_iterations: 6
transmission_losses: 0
linearized_unit_commitment: true
horizon: 365
solver:
name: gurobi
options: gurobi-default
solver_options:
highs-default:
# refer to https://ergo-code.github.io/HiGHS/options/definitions.html#solver
threads: 4
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
gurobi-default:
threads: 4
method: 2 # barrier
crossover: 0
BarConvTol: 1.e-6
Seed: 123
AggFill: 0
PreDual: 0
GURO_PAR_BARDENSETHRESH: 200
gurobi-numeric-focus:
name: gurobi
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
name: gurobi
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
cbc-default: {} # Used in CI
glpk-default: {} # Used in CI
mem: 30000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
walltime: "12:00:00"
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. |
– 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’} |
Whether to optimize the network in a rolling horizon manner, where the snapshot range is split into slices of size horizon which are solved consecutively. |
– seed |
– |
int |
Random seed for increased deterministic behaviour. |
– 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. |
solver |
|||
– name |
– |
One of {‘gurobi’, ‘cplex’, ‘cbc’, ‘glpk’, ‘ipopt’}; 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. |
plotting
#
Warning
More comprehensive documentation for this segment will be released soon.
plotting:
map:
boundaries: [-11, 30, 34, 71]
color_geomap:
ocean: white
land: white
eu_node_location:
x: -5.5
y: 46.
costs_max: 1000
costs_threshold: 1
energy_max: 20000
energy_min: -20000
energy_threshold: 50.
nice_names:
OCGT: "Open-Cycle Gas"
CCGT: "Combined-Cycle Gas"
offwind-ac: "Offshore Wind (AC)"
offwind-dc: "Offshore Wind (DC)"
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"
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"
# water
hydro: '#298c81'
hydro reservoir: '#298c81'
ror: '#3dbfb0'
run of river: '#3dbfb0'
hydroelectricity: '#298c81'
PHS: '#51dbcc'
hydro+PHS: "#08ad97"
wave: '#a7d4cf'
# solar
solar: "#f9d002"
solar PV: "#f9d002"
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'
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 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'
solid: '#545454'
Lignite: '#826837'
lignite: '#826837'
Lignite marginal: '#826837'
# biomass
biogas: '#e3d37d'
biomass: '#baa741'
solid biomass: '#baa741'
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'
BioSNG: '#123456'
# 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'
Li ion: '#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'
# heat demand
Heat load: '#cc1f1f'
heat: '#cc1f1f'
heat demand: '#cc1f1f'
rural heat: '#ff5c5c'
residential rural heat: '#ff7c7c'
services rural heat: '#ff9c9c'
central heat: '#cc1f1f'
urban central heat: '#d15959'
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'
urban central air heat pump: '#6cfb6b'
ground heat pump: '#2fb537'
residential rural ground 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'
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'
helmeth: '#e899ff'
# synfuels
Fischer-Tropsch: '#25c49a'
liquid: '#25c49a'
kerosene for aviation: '#a1ffe6'
naphtha for industry: '#57ebc4'
methanolisation: '#83d6d5'
methanol: '#468c8b'
shipping methanol: '#468c8b'
# co2
CC: '#f29dae'
CCS: '#f29dae'
CO2 sequestration: '#f29dae'
DAC: '#ff5270'
co2 stored: '#f2385a'
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'
AC: "#70af1d"
AC-AC: "#70af1d"
AC line: "#70af1d"
links: "#8a1caf"
HVDC links: "#8a1caf"
DC: "#8a1caf"
DC-DC: "#8a1caf"
DC link: "#8a1caf"
Unit |
Values |
Description |
|
---|---|---|---|
map |
|||
– boundaries |
° |
[x1,x2,y1,y2] |
Boundaries of the map plots in degrees latitude (y) and longitude (x) |
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. |
tech_colors |
– |
carrier -> HEX colour code |
Mapping from network |
nice_names |
– |
str -> str |
Mapping from network |