Configuration

Configuration#

PyPSA-Eur has several configuration options which are documented in this section and are collected in a config.yaml file located in the root directory. Users should copy the provided default configuration (config.default.yaml) and amend their own modifications and assumptions in the user-specific configuration file (config.yaml); confer installation instructions at Handling Configuration Files.

Top-level configuration#

version: 0.8.0
tutorial: false

logging:
  level: INFO
  format: '%(levelname)s:%(name)s:%(message)s'

foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented)
# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
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']

# CO2 budget as a fraction of 1990 emissions
# this is over-ridden if CO2Lx is set in sector_opts
# this is also over-ridden if cb is set in sector_opts
co2_budget:
  2020: 0.701
  2025: 0.524
  2030: 0.297
  2035: 0.150
  2040: 0.071
  2045: 0.032

	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.
foresight	string	{overnight, myopic, perfect}	Defaults to overnight scenarios.
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.
focus_weights	–	Keys should be two-digit country codes (e.g. DE) and values should range between 0 and 1	Ratio of total clusters for particular countries. the remaining weight is distributed according to mean load. An example: `focus_weights: 'DE': 0.6 'FR': 0.2`.
co2_budget	–	Dictionary with planning horizons as keys.	CO2 budget as a fraction of 1990 emissions. Overwritten if `CO2Lx` or `cb` are set in `{sector_opts}` wildcard

`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: "" # use this to keep track of runs with different settings
  disable_progressbar: false # set to true to disable the progressbar
  shared_resources: false # set to true to share the default resources across runs
  shared_cutouts: true # set to true to share the default cutout(s) across runs

	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.

`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:  # allowed transmission line volume expansion, can be any float >= 1.0 with a prefix v|c (today) or "copt"
  - v1.0
  - v1.5
  clusters:  # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
  - 37
  - 128
  - 256
  - 512
  - 1024
  opts: # only relevant for PyPSA-Eur
  - ''
  sector_opts: # this is where the main scenario settings are
  - Co2L0-3H-T-H-B-I-A-solar+p3-dist1
  # to really understand the options here, look in scripts/prepare_sector_network.py
  # Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
  # Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
  # xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
  # single letters are sectors: T for land transport, H for building heating,
  # B for biomass supply, I for industry, shipping and aviation,
  # A for agriculture, forestry and fishing
  # solar+c0.5 reduces the capital cost of solar to 50\% of reference value
  # solar+p3 multiplies the available installable potential by factor 3
  # seq400 sets the potential of CO2 sequestration to 400 Mt CO2 per year
  # dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
  # for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
  # emissions throughout the transition path in the timeframe determined by the
  # planning_horizons), be:beta decay; ex:exponential decay
  # cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
  # decay with initial growth rate 0
  planning_horizons: # investment years for myopic and perfect; for overnight, year of cost assumptions can be different and is defined under 'costs'
  - 2050
  # for example, set to
  # - 2020
  # - 2030
  # - 2040
  # - 2050
  # for myopic foresight

	Unit	Values	Description
simpl	–	cf. The {simpl} wildcard	List of `{simpl}` wildcards to run.
clusters	–	cf. The {clusters} wildcard	List of `{clusters}` wildcards to run.
ll	–	cf. The {ll} wildcard	List of `{ll}` wildcards to run.
opts	–	cf. The {opts} wildcard	List of `{opts}` wildcards to run.
sector_opts	–	cf. The {sector_opts} wildcard	List of `{sector_opts}` wildcards to run.
planning_horizons	–	cf. The {planning_horizons} wildcard	List of `{planning_horizon}` wildcards to run.

`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' # include start, not end

	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 `left`, `right`, or both sides `both` or neither side `None`.

`enable`#

Switches for some rules and optional features.

enable:
  prepare_links_p_nom: false
  retrieve_databundle: true
  retrieve_sector_databundle: true
  retrieve_cost_data: true
  build_cutout: false
  retrieve_irena: false
  retrieve_cutout: true
  build_natura_raster: false
  retrieve_natura_raster: true
  custom_busmap: false

# CO2 budget as a fraction of 1990 emissions
# this is over-ridden if CO2Lx is set in sector_opts
# this is also over-ridden if cb is set in sector_opts

	Unit	Values	Description
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_databundle` or whether to keep a custom databundle located in the corresponding folder.
retrieve_sector_databundle	bool	{true, false}	Switch to retrieve sector databundle from zenodo via the rule `retrieve_sector_databundle` or whether to keep a custom databundle located in the corresponding folder.
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 `build_cutout`.
retrieve_irena	bool	{true, false}	Switch to enable the retrieval of `existing_capacities` from IRENASTAT with `retrieve_irena`.
retrieve_cutout	bool	{true, false}	Switch to enable the retrieval of cutouts from zenodo with `retrieve_cutout`.
build_natura_raster	bool	{true, false}	Switch to enable the creation of the raster `natura.tiff` via the rule `build_natura_raster`.
retrieve_natura_raster	bool	{true, false}	Switch to enable the retrieval of `natura.tiff` from zenodo with `retrieve_natura_raster`.
custom_busmap	bool	{true, false}	Switch to enable the use of custom busmaps in rule `cluster_network`. If activated the rule looks for provided busmaps at `data/custom_busmap_elec_s{simpl}_{clusters}.csv` which should have the same format as `resources/busmap_elec_s{simpl}_{clusters}.csv`, i.e. the index should contain the buses of `networks/elec_s{simpl}.nc`.

`electricity`#

electricity:
  voltages: [220., 300., 380.]
  gaslimit: false # global gas usage limit of X MWh_th
  co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5
  co2base: 1.487e+9
  agg_p_nom_limits: data/agg_p_nom_minmax.csv

  operational_reserve: # like https://genxproject.github.io/GenX/dev/core/#Reserves
    activate: false
    epsilon_load: 0.02 # share of total load
    epsilon_vres: 0.02 # share of total renewable supply
    contingency: 4000 # fixed capacity in MW

  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

  # use pandas query strings here, e.g. Country not in ['Germany']
  powerplants_filter: (DateOut >= 2022 or DateOut != DateOut)
  # use pandas query strings here, e.g. Country in ['Germany']
  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
    # Add capacities from OPSD data
    from_opsd: true
    # Renewable capacities are based on existing capacities reported by IRENA
    year: 2020
    # Artificially limit maximum capacities to factor * (IRENA capacities),
    # i.e. 110% of <years>'s capacities => expansion_limit: 1.1
    # false: Use estimated renewable potentials determine by the workflow
    expansion_limit: false
    technology_mapping:
      # Wind is the Fueltype in powerplantmatching, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur
      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 `{opts}` wildcard.
agg_p_nom_limits	file	path	Reference to `.csv` file specifying per carrier generator nominal capacity constraints for individual countries if `'CCL'` is in `{opts}` wildcard. Defaults to `data/agg_p_nom_minmax.csv`.
operational_reserve			Settings for reserve requirements following like 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 `p_nom`. Cf. PyPSA documentation.
– H2	h	float	Maximum state of charge capacity of the hydrogen storage in terms of hours at full output capacity `p_nom`. Cf. PyPSA documentation.
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 `conventional_carriers` list, the lower limit of the capacity expansion is set to 0.
– 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 `Store`.
powerplants_filter	–	use pandas.query strings here, e.g. Country not in [‘Germany’]	Filter query for the default powerplant database.
custom_powerplants	–	use pandas.query strings here, e.g. Country in [‘Germany’]	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 `resources/powerplants.csv`. If an included carrier is also listed in extendable_carriers, the capacity is taken as a lower bound.
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 capacities from OPSD data
– year	–	bool	Renewable capacities are based on existing capacities reported by IRENA for the specified year
– expansion_limit	–	float or false	Artificially limit maximum capacities to factor * (IRENA capacities), i.e. 110% of <years>’s capacities => expansion_limit: 1.1 false: Use estimated renewable potentials determine by the workflow
– technology_mapping			Mapping between powerplantmatching and PyPSA-Eur technology names

`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 # false saves time
  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 `<region>-<year>-<source>` (e.g. `europe-2013-era5`).	Name of the cutout netcdf file. The user may specify multiple cutouts under configuration `atlite: cutouts:`. Reference is used in configuration `renewable: {technology}: cutout:`. The cutout `base` may be used to automatically calculate temporal and spatial bounds of the network.
– – 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 # 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.
    # correction_factor: 0.93
    corine:
      # Scholz, Y. (2012). Renewable energy based electricity supply at low costs
      #  development of the REMix model and application for Europe. ( p.42 / p.28)
      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 `atlite: cutouts:` (e.g. ‘europe-2013-era5’) or reference an existing folder in the directory `cutouts`. Source module must be ERA5.	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`
– 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 `distance`.
natura	bool	{true, false}	Switch to exclude Natura 2000 natural protection areas. Area is excluded if `true`.
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.

`offwind-ac`#

  offwind-ac:
    cutout: europe-2013-era5
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_5MW_offshore
    capacity_per_sqkm: 2 # 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.
    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
    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 `atlite: cutouts:` (e.g. ‘europe-2013-era5’) or reference an existing folder in the directory `cutouts`. Source module must be ERA5.	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 `true`.
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.

`offwind-dc`#

  offwind-dc:
    cutout: europe-2013-era5
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_5MW_offshore
    capacity_per_sqkm: 2 # 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.
    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
    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 `atlite: cutouts:` (e.g. ‘europe-2013-era5’) or reference an existing folder in the directory `cutouts`. Source module must be ERA5.	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 `true`.
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.

`solar`#

  solar:
    cutout: europe-2013-sarah
    resource:
      method: pv
      panel: CSi
      orientation:
        slope: 35.
        azimuth: 180.
    capacity_per_sqkm: 1.7 # 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 https://github.com/PyPSA/pypsa-eur/pull/304
    # 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 `atlite: cutouts:` (e.g. ‘europe-2013-era5’) or reference an existing folder in the directory `cutouts`. Source module can be ERA5 or SARAH-2.	Specifies the directory where the relevant weather data ist stored that is specified at `atlite/cutouts` configuration. Both `sarah` and `era5` work.
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 `true`.
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.

`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
    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 `p_nom`. Cf. PyPSA documentation.
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 `p_nom` or heuristically determined. Cf. PyPSA documentation.
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:
  nuclear:
    p_max_pu: "data/nuclear_p_max_pu.csv" # float of file name

	Unit	Values	Description
{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
  length_factor: 1.25
  under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity

	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`) to approximate \(N-1\) security and reserve capacity for reactive power flows
s_nom_max	MW	float	Global upper limit for the maximum 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.

`links`#

links:
  p_max_pu: 1.0
  p_nom_max: .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`.
p_nom_max	MW	float	Global upper limit for the maximum 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` as base power of the transformer. Overwritten if `type` is specified.
s_nom	MVA	float	Limit of apparent power which can pass through branch. Overwritten if `type` is specified.
type	–	A transformer type in PyPSA.	Specifies transformer types to assume for the transformers of the ENTSO-E grid extraction.

`load`#

load:
  power_statistics: true # only for files from <2019; set false in order to get ENTSOE transparency data
  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from
  manual_adjustments: true # false
  scaling_factor: 1.0

	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 `pandas` period strings.
manual_adjustments	bool	{true, false}	Whether to adjust the load data manually according to the function in `manual_adjustment()`.
scaling_factor	–	float	Global correction factor for the load time series.

`costs`#

costs:
  year: 2030
  version: v0.5.0
  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: # in currency per tonne emission, only used with the option Ep
    co2: 0.

	Unit	Values	Description
year	–	YYYY; e.g. ‘2030’	Year for which to retrieve cost assumptions of `resources/costs.csv`.
version	–	vX.X.X; e.g. ‘v0.5.0’	Version of `technology-data` repository to use.
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 `resources/costs.csv`.
capital_cost	EUR/MW	Keys should be in the ‘technology’ column of `resources/costs.csv`. Values can be any float.	For the given technologies, assumptions about their capital investment costs are set to the corresponding value. Optional; overwrites cost assumptions from `resources/costs.csv`.
marginal_cost	EUR/MWh	Keys should be in the ‘technology’ column of `resources/costs.csv`. Values can be any float.	For the given technologies, assumptions about their marginal operating costs are set to the corresponding value. Optional; overwrites cost assumptions from `resources/costs.csv`.
emission_prices			Specify exogenous prices for emission types listed in `network.carriers` to marginal costs.
– 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 `Ep` in the `{opts}` wildcard only in the rule prepare_network`.

`clustering`#

clustering:
  simplify_network:
    to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections)
    algorithm: kmeans # choose from: [hac, kmeans]
    feature: solar+onwind-time # only for hac. choose from: [solar+onwind-time, solar+onwind-cap, solar-time, solar-cap, solar+offwind-cap] etc.
    exclude_carriers: []
    remove_stubs: true
    remove_stubs_across_borders: true
  cluster_network:
    algorithm: kmeans
    feature: solar+onwind-time
    exclude_carriers: []
  aggregation_strategies:
    generators:
      p_nom_max: sum # use "min" for more conservative assumptions
      p_nom_min: sum
      p_min_pu: mean
      marginal_cost: mean
      committable: any
      ramp_limit_up: max
      ramp_limit_down: max
      efficiency: mean

	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.
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.

`energy`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

energy:
  energy_totals_year: 2011
  base_emissions_year: 1990
  eurostat_report_year: 2016
  emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"

`biomass`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

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

`solar_thermal`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

solar_thermal:
  clearsky_model: simple  # should be "simple" or "enhanced"?
  orientation:
    slope: 45.
    azimuth: 180.

# only relevant for foresight = myopic or perfect

`existing_capacities`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

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
  exit_year:  # assuming phase out at the end of the year

`sector`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

sector:
  district_heating:
    potential: 0.6  # maximum fraction of urban demand which can be supplied by district heating
     # 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
    progress:
      2020: 0.0
      2030: 0.3
      2040: 0.6
      2050: 1.0
    district_heating_loss: 0.15
  cluster_heat_buses: false # cluster residential and service heat buses to one to save memory
  bev_dsm_restriction_value: 0.75  #Set to 0 for no restriction on BEV DSM
  bev_dsm_restriction_time: 7  #Time at which SOC of BEV has to be dsm_restriction_value
  transport_heating_deadband_upper: 20.
  transport_heating_deadband_lower: 15.
  ICE_lower_degree_factor: 0.375  #in per cent increase in fuel consumption per degree above deadband
  ICE_upper_degree_factor: 1.6
  EV_lower_degree_factor: 0.98
  EV_upper_degree_factor: 0.63
  bev_dsm: true #turns on EV battery
  bev_availability: 0.5  #How many cars do smart charging
  bev_energy: 0.05  #average battery size in MWh
  bev_charge_efficiency: 0.9  #BEV (dis-)charging efficiency
  bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
  bev_charge_rate: 0.011 #3-phase charger with 11 kW
  bev_avail_max: 0.95
  bev_avail_mean: 0.8
  v2g: true #allows feed-in to grid from EV battery
  #what is not EV or FCEV is oil-fuelled ICE
  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 # fuel oil per use
  agriculture_machinery_electric_efficiency: 0.3 # electricity per use
  MWh_MeOH_per_MWh_H2: 0.8787 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
  MWh_MeOH_per_tCO2: 4.0321 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
  MWh_MeOH_per_MWh_e: 3.6907 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
  shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
  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 # 10-15% higher https://www.iea-amf.org/app/webroot/files/file/Annex%20Reports/AMF_Annex_56.pdf, https://users.ugent.be/~lsileghe/documents/extended_abstract.pdf
  shipping_oil_efficiency: 0.40 #For conversion of fuel oil to propulsion in 2011
  aviation_demand_factor: 1. # relative aviation demand compared to today
  HVC_demand_factor: 1. # relative HVC demand compared to today
  time_dep_hp_cop: true #time dependent heat pump coefficient of performance
  heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
   # conservatively high to cover hot water and space heating in poorly-insulated buildings
  reduce_space_heat_exogenously: true  # reduces space heat demand by a given factor (applied before losses in DH)
  # this can represent e.g. building renovation, building demolition, or if
  # the factor is negative: increasing floor area, increased thermal comfort, population growth
  reduce_space_heat_exogenously_factor:  # per unit reduction in space heat demand
  # the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
    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:   # co-optimises building renovation to reduce space heat demand
    retro_endogen: false  # co-optimise space heat savings
    cost_factor: 1.0   # weight costs for building renovation
    interest_rate: 0.04  # for investment in building components
    annualise_cost: true  # annualise the investment costs
    tax_weighting: false   # weight costs depending on taxes in countries
    construction_index: true   # weight costs depending on labour/material costs per country
  tes: true
  tes_tau: # 180 day time constant for centralised, 3 day for decentralised
    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: true
  coal_cc: false
  dac: true
  co2_vent: false
  allam_cycle: false
  SMR: true
  SMR_cc: false
  regional_co2_sequestration_potential:
    enable: false  # enable regionally resolved geological co2 storage potential
    attribute: 'conservative estimate Mt'
    include_onshore: false  # include onshore sequestration potentials
    min_size: 3 # Gt, sites with lower potential will be excluded
    max_size: 25 # Gt, max sequestration potential for any one site, TODO research suitable value
    years_of_storage: 25 # years until potential exhausted at optimised annual rate
  co2_sequestration_potential: 200  #MtCO2/a sequestration potential for Europe
  co2_sequestration_cost: 10   #EUR/tCO2 for sequestration of CO2
  co2_spatial: false
  co2network: false
  cc_fraction: 0.9  # default fraction of CO2 captured with post-combustion capture
  hydrogen_underground_storage: true
  hydrogen_underground_storage_locations:
    # - onshore  # more than 50 km from sea
  - nearshore    # within 50 km of sea
    # - offshore
  ammonia: false # can be false (no NH3 carrier), true (copperplated NH3), "regional" (regionalised NH3 without network)
  min_part_load_fischer_tropsch: 0.9 # p_min_pu
  min_part_load_methanolisation: 0.5 # p_min_pu
  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  #multiplies cost in data/costs.csv
  electricity_grid_connection: true  # only applies to onshore wind and utility PV
  H2_network: true
  gas_network: false
  H2_retrofit: false  # if set to True existing gas pipes can be retrofitted to H2 pipes
  # according to hydrogen backbone strategy (April, 2020) p.15
  # https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
  # 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
  H2_retrofit_capacity_per_CH4: 0.6  # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
  gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
  gas_distribution_grid: true
  gas_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
  biomass_spatial: false  # regionally resolve biomass (e.g. potentials)
  biomass_transport: false  # allow transport of solid biomass between nodes
  conventional_generation: # generator : carrier
    OCGT: gas
  biomass_to_liquid: false
  biosng: false

`industry`#

Note

Only used for sector-coupling studies.

Warning

More comprehensive documentation for this segment will be released soon.

industry:
  St_primary_fraction:  # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
    2020: 0.6
    2025: 0.55
    2030: 0.5
    2035: 0.45
    2040: 0.4
    2045: 0.35
    2050: 0.3
  DRI_fraction:  # fraction of the primary route converted to DRI + EAF
    2020: 0
    2025: 0
    2030: 0.05
    2035: 0.2
    2040: 0.4
    2045: 0.7
    2050: 1
  H2_DRI: 1.7   #H2 consumption in Direct Reduced Iron (DRI),  MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
  elec_DRI: 0.322   #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
  Al_primary_fraction:  # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
    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 # LHV
  MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
  MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
  MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)
  MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
  MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
  NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
  petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
  HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
  HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
  HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
  HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
  MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
  MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
  chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
  MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
  MWh_H2_per_tCl: -0.9372  # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
  methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
  MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
  MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
  hotmaps_locate_missing: false
  reference_year: 2015
  # references:
  # DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
  # Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050

`solving`#

solving:
  #tmpdir: "path/to/tmp"
  options:
    formulation: kirchhoff
    clip_p_max_pu: 1.e-2
    load_shedding: false
    noisy_costs: true
    skip_iterations: true
    track_iterations: false
    min_iterations: 4
    max_iterations: 6
    seed: 123

  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
      seed: 10              # Consistent seed for all plattforms
    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

	Unit	Values	Description
options
– formulation	–	Any of {‘angles’, ‘kirchhoff’, ‘cycles’, ‘ptdf’}	Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is ‘kirchhoff’. Explained in this article.
– load_shedding	bool	{‘true’,’false’}	Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities.
– 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 \(\mathcal{U}(0.09,0,11)\).
– min_iterations	–	int	Minimum number of solving iterations in between which resistance and reactence (`x/r`) are updated for branches according to `s_nom_opt` of the previous run.
– max_iterations	–	int	Maximum number of solving iterations in between which resistance and reactence (`x/r`) are updated for branches according to `s_nom_opt` of the previous run.
– nhours	–	int	Specifies the \(n\) first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging.
– 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.
– skip_iterations	bool	{‘true’,’false’}	Skip iterating, do not update impedances of branches. Defaults to true.
– track_iterations	bool	{‘true’,’false’}	Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in `network.lines['s_nom_opt_X']` (where `X` labels the iteration)
– seed	–	int	Random seed for increased deterministic behaviour.
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 `solver_options`.	Link to specific parameter settings.
solver_options		dict	Dictionaries with solver-specific parameter settings.
mem	MB	int	Estimated maximum memory requirement for solving networks.

	Unit	Values	Description
options
– formulation	–	Any of {‘angles’, ‘kirchhoff’, ‘cycles’, ‘ptdf’}	Specifies which variant of linearized power flow formulations to use in the optimisation problem. Recommended is ‘kirchhoff’. Explained in this article.
– load_shedding	bool	{‘true’,’false’}	Add generators with a prohibitively high marginal cost to simulate load shedding and avoid problem infeasibilities.
– 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 \(\mathcal{U}(0.09,0,11)\).
– min_iterations	–	int	Minimum number of solving iterations in between which resistance and reactence (`x/r`) are updated for branches according to `s_nom_opt` of the previous run.
– max_iterations	–	int	Maximum number of solving iterations in between which resistance and reactence (`x/r`) are updated for branches according to `s_nom_opt` of the previous run.
– nhours	–	int	Specifies the \(n\) first snapshots to take into account. Must be less than the total number of snapshots. Rather recommended only for debugging.
– 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.
– skip_iterations	bool	{‘true’,’false’}	Skip iterating, do not update impedances of branches. Defaults to true.
– track_iterations	bool	{‘true’,’false’}	Flag whether to store the intermediate branch capacities and objective function values are recorded for each iteration in `network.lines['s_nom_opt_X']` (where `X` labels the iteration)
– seed	–	int	Random seed for increased deterministic behaviour.
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 `solver_options`.	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.
  vre_techs:
  - onwind
  - offwind-ac
  - offwind-dc
  - solar
  - ror
  renewable_storage_techs:
  - PHS
  - hydro
  conv_techs:
  - OCGT
  - CCGT
  - Nuclear
  - Coal
  storage_techs:
  - hydro+PHS
  - battery
  - H2
  load_carriers:
  - AC load
  AC_carriers:
  - AC line
  - AC transformer
  link_carriers:
  - DC line
  - Converter AC-DC
  heat_links:
  - heat pump
  - resistive heater
  - CHP heat
  - CHP electric
  - gas boiler
  - central heat pump
  - central resistive heater
  - central CHP heat
  - central CHP electric
  - central gas boiler
  heat_generators:
  - gas boiler
  - central gas boiler
  - solar thermal collector
  - central solar thermal collector

  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"

  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'
    solar rooftop: '#ffea80'
    # gas
    OCGT: '#e0986c'
    OCGT marginal: '#e0986c'
    OCGT-heat: '#e0986c'
    gas boiler: '#db6a25'
    gas boilers: '#db6a25'
    gas boiler marginal: '#db6a25'
    gas: '#e05b09'
    fossil gas: '#e05b09'
    natural gas: '#e05b09'
    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'
    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'
    biomass boiler: '#8A9A5B'
    biomass to liquid: '#32CD32'
    BioSNG: '#123456'
    # power transmission
    lines: '#6c9459'
    transmission lines: '#6c9459'
    electricity distribution grid: '#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'
    home battery: '#80c944'
    home battery storage: '#80c944'
    BEV charger: '#baf238'
    V2G: '#e5ffa8'
    land transport EV: '#baf238'
    Li ion: '#baf238'
    # hot water storage
    water tanks: '#e69487'
    hot water storage: '#e69487'
    hot water charging: '#e69487'
    hot water discharging: '#e69487'
    # heat demand
    Heat load: '#cc1f1f'
    heat: '#cc1f1f'
    heat demand: '#cc1f1f'
    rural heat: '#ff5c5c'
    central heat: '#cc1f1f'
    decentral heat: '#750606'
    low-temperature heat for industry: '#8f2727'
    process heat: '#ff0000'
    agriculture heat: '#d9a5a5'
    # heat supply
    heat pumps: '#2fb537'
    heat pump: '#2fb537'
    air heat pump: '#36eb41'
    ground heat pump: '#2fb537'
    Ambient: '#98eb9d'
    CHP: '#8a5751'
    CHP CC: '#634643'
    CHP heat: '#8a5751'
    CHP electric: '#8a5751'
    district heating: '#e8beac'
    resistive heater: '#d8f9b8'
    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 storage: '#bf13a0'
    H2 Store: '#bf13a0'
    land transport fuel cell: '#6b3161'
    H2 pipeline: '#f081dc'
    H2 pipeline retrofitted: '#ba99b5'
    H2 Fuel Cell: '#c251ae'
    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-AC: "#70af1d"
    AC line: "#70af1d"
    links: "#8a1caf"
    HVDC links: "#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 `carrier` to a colour (HEX colour code).
nice_names	–	str -> str	Mapping from network `carrier` to a more readable name.

Configuration

Contents

Configuration#

Top-level configuration#

run#

scenario#

snapshots#

enable#

electricity#

atlite#

renewable#

onwind#

offwind-ac#

offwind-dc#

solar#

hydro#

conventional#

lines#

links#

transformers#

load#

costs#

clustering#

energy#

biomass#

solar_thermal#

existing_capacities#

sector#

industry#

solving#

plotting#

`run`#

`scenario`#

`snapshots`#

`enable`#

`electricity`#

`atlite`#

`renewable`#

`onwind`#

`offwind-ac`#

`offwind-dc`#

`solar`#

`hydro`#

`conventional`#

`lines`#

`links`#

`transformers`#

`load`#

`costs`#

`clustering`#

`energy`#

`biomass`#

`solar_thermal`#

`existing_capacities`#

`sector`#

`industry`#

`solving`#

`plotting`#