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 Set Up the Default Configuration.

Top-level configuration

version: 0.4.0
tutorial: false

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

summary_dir: results
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']
enable:
  prepare_links_p_nom: false
  retrieve_databundle: true
  build_cutout: false
  retrieve_cutout: true
  build_natura_raster: false
  retrieve_natura_raster: true
  custom_busmap: false
  Unit Values Description
version – 0.x.x Version of PyPSA-Eur
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.
summary_dir – e.g. ‘results’ Directory into which results are written.
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.
enable      
– 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.
– build_cutout bool {true, false} Switch to enable the building of cutouts via the rule build_cutout.
– 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.

scenario

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 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

snakemake -j 1 solve_all_networks

For each wildcard, a list of values is provided. The rule solve_all_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:

_images/scenarios.png 
scenario:
  simpl: ['']
  ll: ['copt']
  clusters: [37, 128, 256, 512, 1024]
  opts: [Co2L-3H]
  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.

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"
  closed: 'left' # end is not inclusive
  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
closed – One of {None, ‘left’, ‘right’} Make the time interval closed to the left, right, or both sides None.

electricity

electricity:
  voltages: [220., 300., 380.]
  co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5
  co2base: 1.487e+9
  agg_p_nom_limits: data/agg_p_nom_minmax.csv

  extendable_carriers:
    Generator: []
    StorageUnit: [] # battery, H2
    Store: [battery, H2]
    Link: []

  max_hours:
    battery: 6
    H2: 168

  powerplants_filter: false # use pandas query strings here, e.g. Country not in ['Germany']
  custom_powerplants: false # use pandas query strings here, e.g. Country in ['Germany']
  conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
  renewable_capacities_from_OPSD: [] # onwind, offwind, solar

  # estimate_renewable_capacities_from_capacity_stats:
  #   # Wind is the Fueltype in ppm.data.Capacity_stats, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur
  #   Wind: [onwind, offwind-ac, offwind-dc]
  #   Solar: [solar]
  Unit Values Description
voltages kV Any subset of {220., 300., 380.} Voltage levels to consider when
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.
extendable_carriers      
– Generator – Any subset of {‘OCGT’,’CCGT’} Places extendable conventional power plants (OCGT and/or CCGT) where gas power plants are located today without capacity limits.
– 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.
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.
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.
renewable_capacities_from_OPSD   [solar, onwind, offwind] List of carriers (offwind-ac and offwind-dc are included in offwind) whose capacities ‘p_nom’ are aligned to the OPSD renewable power plant list
estimate_renewable_capacities_from_capacitiy_stats      
– Fueltype [ppm], e.g. Wind   list of fueltypes strings in PyPSA-Eur, e.g. [onwind, offwind-ac, offwind-dc] converts ppm Fueltype to PyPSA-EUR Fueltype

Warning

Carriers in conventional_carriers must not also be in extendable_carriers.

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:
  nprocesses: 4
  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
nprocesses – int Number of parallel processes in cutout preparation
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.
– – 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
    # 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
    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.
keep_all_available_areas bool {‘true’, ‘false’} Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed.

offwind-ac

  offwind-ac:
    cutout: europe-2013-era5
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_5MW_offshore
    capacity_per_sqkm: 2
    correction_factor: 0.8855
    # proxy for wake losses
    # from 10.1016/j.energy.2018.08.153
    # until done more rigorously in #153
    corine: [44, 255]
    natura: true
    max_depth: 50
    max_shore_distance: 30000
    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 – 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.
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.
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.
keep_all_available_areas bool {‘true’, ‘false’} Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed.

offwind-dc

  offwind-dc:
    cutout: europe-2013-era5
    resource:
      method: wind
      turbine: NREL_ReferenceTurbine_5MW_offshore
    # ScholzPhd Tab 4.3.1: 10MW/km^2
    capacity_per_sqkm: 2
    correction_factor: 0.8855
    # proxy for wake losses
    # from 10.1016/j.energy.2018.08.153
    # until done more rigorously in #153
    corine: [44, 255]
    natura: true
    max_depth: 50
    min_shore_distance: 30000
    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 – 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.
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.
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.
keep_all_available_areas bool {‘true’, ‘false’} Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed.

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
    # 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
    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.
keep_all_available_areas bool {‘true’, ‘false’} Use all availabe weather cells for renewable profile and potential generation. The default ignores weather cells where only less than 1 MW can be installed.

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.

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.

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
url – string Link to open power system data time series data.
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
  discountrate: 0.07 # From a Lion Hirth paper, also reflects average of Noothout et al 2016
  USD2013_to_EUR2013: 0.7532 # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html
  marginal_cost: # EUR/MWh
    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 data/costs.csv.
discountrate – float Default discount rate if not specified for a technology in data/costs.csv.
USD2013_to_EUR2013 – float Exchange rate from USD \(_{2013}\) to EUR \(_{2013}\) from ECB
capital_cost EUR/MW Keys should be in the ‘technology’ column of data/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 data/costs.csv.
marginal_cost EUR/MWh Keys should be in the ‘technology’ column of data/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 data/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`.

Note

To change cost assumptions in more detail (i.e. other than marginal_cost and capital_cost), consider modifying cost assumptions directly in data/costs.csv as this is not yet supported through the config file. You can also build multiple different cost databases. Make a renamed copy of data/costs.csv (e.g. data/costs-optimistic.csv) and set the variable COSTS=data/costs-optimistic.csv in the Snakefile.

solving

options

solving:
  options:
    formulation: kirchhoff
    load_shedding: false
    noisy_costs: true
    min_iterations: 4
    max_iterations: 6
    clip_p_max_pu: 0.01
    skip_iterations: false
    track_iterations: false
    #nhours: 10
  Unit Values Description
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.
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)

solver

  solver:
    name: gurobi
    threads: 4
    method: 2 # barrier
    crossover: 0
    BarConvTol: 1.e-5
    FeasibilityTol: 1.e-6
    AggFill: 0
    PreDual: 0
    GURO_PAR_BARDENSETHRESH: 200
  # solver:
  #   name: cplex
  #   threads: 4
  #   lpmethod: 4 # barrier
  #   solutiontype: 2 # non basic solution, ie no crossover
  #   barrier.convergetol: 1.e-5
  #   feasopt.tolerance: 1.e-6
  Unit Values Description
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.
opts – Parameter list for Gurobi and CPLEX Solver specific parameter settings.

plotting

plotting:
  map:
    figsize: [7, 7]
    boundaries: [-10.2, 29, 35,  72]
    p_nom:
      bus_size_factor: 5.e+4
      linewidth_factor: 3.e+3

  costs_max: 800
  costs_threshold: 1

  energy_max: 15000.
  energy_min: -10000.
  energy_threshold: 50.

  vre_techs: ["onwind", "offwind-ac", "offwind-dc", "solar", "ror"]
  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"]
  tech_colors:
    "onwind" : "#235ebc"
    "onshore wind" : "#235ebc"
    'offwind' : "#6895dd"
    'offwind-ac' : "#6895dd"
    'offshore wind' : "#6895dd"
    'offshore wind ac' : "#6895dd"
    'offwind-dc' : "#74c6f2"
    'offshore wind dc' : "#74c6f2"
    "hydro" : "#08ad97"
    "hydro+PHS" : "#08ad97"
    "PHS" : "#08ad97"
    "hydro reservoir" : "#08ad97"
    'hydroelectricity' : '#08ad97'
    "ror" : "#4adbc8"
    "run of river" : "#4adbc8"
    'solar' : "#f9d002"
    'solar PV' : "#f9d002"
    'solar thermal' : '#ffef60'
    'biomass' : '#0c6013'
    'solid biomass' : '#06540d'
    'biogas' : '#23932d'
    'waste' : '#68896b'
    'geothermal' : '#ba91b1'
    "OCGT" : "#d35050"
    "gas" : "#d35050"
    "natural gas" : "#d35050"
    "CCGT" : "#b20101"
    "nuclear" : "#ff9000"
    "coal" : "#707070"
    "lignite" : "#9e5a01"
    "oil" : "#262626"
    "H2" : "#ea048a"
    "hydrogen storage" : "#ea048a"
    "battery" : "#b8ea04"
    "Electric load" : "#f9d002"
    "electricity" : "#f9d002"
    "lines" : "#70af1d"
    "transmission lines" : "#70af1d"
    "AC-AC" : "#70af1d"
    "AC line" : "#70af1d"
    "links" : "#8a1caf"
    "HVDC links" : "#8a1caf"
    "DC-DC" : "#8a1caf"
    "DC link" : "#8a1caf"
  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"
  Unit Values Description
map      
– figsize – [width, height]; e.g. [7,7] Figure size in inches.
– boundaries ° [x1,x2,y1,y2] Boundaries of the map plots in degrees latitude (y) and longitude (x)
– p_nom      
– – bus_size_factor – float Factor by which values determining bus sizes are scaled to fit well in the plot.
– – linewidth_factor – float Factor by which values determining bus sizes are scaled to fit well in the plot.
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.