Draft modular config structure

configs/config.costs.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+# TODO: Needs to be adjusted for Africa.
+costs:
+  year: 2030
+  version: v0.6.2
+  discountrate: [0.071] #, 0.086, 0.111]
+  # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html # noqa: E501
+  USD2013_to_EUR2013: 0.7532 # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html
+  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_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.
+  # investment: # EUR/MW
+  #   CCGT: 830000
+  # FOM: # %/year
+  #   CCGT: 3.35
+  # VOM: # EUR/MWh
+  #   CCGT: 4.2
+  # fuel: # EUR/MWh
+  #   gas: 10.1
+  # lifetime: # years
+  #   CCGT: 25.0
+  # efficiency: # per unit
+  #   CCGT: 0.58
+  lines:
+    length_factor: 1.25 #to estimate offwind connection costs

configs/config.elec.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+clean_osm_data_options: # osm = OpenStreetMap
+  names_by_shapes: true # Set the country name based on the extended country shapes
+  threshold_voltage: 51000 # [V] minimum voltage threshold to keep the asset (cable, line, generator, etc.) [V]
+  tag_substation: "transmission" # Filters only substations with 'transmission' tag, ('distribution' also available)
+  add_line_endings: true # When "True", then line endings are added to the dataset of the substations
+  generator_name_method: OSM # Methodology to specify the name to the generator. Options: OSM (name as by OSM dataset), closest_city (name by the closest city)
+  use_custom_lines: "OSM_only" # Use OSM (OSM_only), customized (custom_only), or both data sets (add_custom)
+  path_custom_lines: false # If exists, provide the specific absolute path of the custom file e.g. (...\data\custom_lines.geojson)
+  use_custom_substations: "OSM_only" # Use OSM (OSM_only), customized (custom_only), or both data sets (add_custom)
+  path_custom_substations: false # If exists, provide the specific absolute path of the custom file e.g. (...\data\custom_substations.geojson)
+  use_custom_cables: "OSM_only" # Use OSM (OSM_only), customized (custom_only), or both data sets (add_custom)
+  path_custom_cables: false # If exists, provide the specific absolute path of the custom file e.g. (...\data\custom_cables.geojson)
+
+build_osm_network: # Options of the build_osm_network script; osm = OpenStreetMap
+  group_close_buses: true # When "True", close buses are merged and guarantee the voltage matching among line endings
+  group_tolerance_buses: 5000 # [m] (default 5000) Tolerance in meters of the close buses to merge
+  split_overpassing_lines: true # When True, lines overpassing buses are splitted and connected to the bueses
+  overpassing_lines_tolerance: 1 # [m] (default 1) Tolerance to identify lines overpassing buses
+  force_ac: false # When true, it forces all components (lines and substation) to be AC-only. To be used if DC assets create problem.
+
+base_network:
+  min_voltage_substation_offshore: 51000 # [V] minimum voltage of the offshore substations
+  min_voltage_rebase_voltage: 51000 # [V] minimum voltage in base network
+
+electricity:
+  base_voltage: 380.
+  voltages: [132., 220., 300., 380., 500., 750.]
+  co2limit: 7.75e+7 # European default, 0.05 * 3.1e9*0.5, needs to be adjusted for Africa
+  co2base: 1.487e+9 # European default, adjustment to Africa necessary
+  agg_p_nom_limits: data/agg_p_nom_minmax.csv
+  hvdc_as_lines: false # should HVDC lines be modeled as `Line` or as `Link` component?
+  automatic_emission: false
+  automatic_emission_base_year: 1990 # 1990 is taken as default. Any year from 1970 to 2018 can be selected.
+
+  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: 0 # fixed capacity in MW
+
+
+lines:
+  ac_types:
+    132.: "243-AL1/39-ST1A 20.0"
+    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"
+    500.: "Al/St 240/40 4-bundle 380.0"
+    750.: "Al/St 560/50 4-bundle 750.0"
+  dc_types:
+    500.: "HVDC XLPE 1000"
+  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
+
+links:
+  p_max_pu: 1.0
+  p_nom_max: .inf
+  under_construction: "zero" # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
+
+transformers:
+  x: 0.1
+  s_nom: 2000.
+  type: ""

configs/config.geometry.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+# definition of the Coordinate Reference Systems
+crs:
+  geo_crs: EPSG:4326 # general geographic projection, not used for metric measures. "EPSG:4326" is the standard used by OSM and google maps
+  distance_crs: EPSG:3857 # projection for distance measurements only. Possible recommended values are "EPSG:3857" (used by OSM and Google Maps)
+  area_crs: ESRI:54009 # projection for area measurements only. Possible recommended values are Global Mollweide "ESRI:54009"
+
+cluster_options:
+  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
+    p_threshold_drop_isolated: 20 # [MW] isolated buses are being discarded if bus mean power is below the specified threshold
+    p_threshold_merge_isolated: 300 # [MW] isolated buses are being merged into a single isolated bus if a bus mean power is below the specified threshold
+    s_threshold_fetch_isolated: 0.05 # [-] a share of the national load for merging an isolated network into a backbone network
+  cluster_network:
+    algorithm: kmeans
+    feature: solar+onwind-time
+    exclude_carriers: []
+  alternative_clustering: false # "False" use Voronoi shapes, "True" use GADM shapes
+  distribute_cluster: ["load"] # Distributes cluster nodes per country according to ['load'],['pop'] or ['gdp']
+  out_logging: true # When "True", logging is printed to console
+  aggregation_strategies:
+    generators: # use "min" for more conservative assumptions
+      p_nom: sum
+      p_nom_max: sum
+      p_nom_min: sum
+      p_min_pu: mean
+      marginal_cost: mean
+      committable: any
+      ramp_limit_up: max
+      ramp_limit_down: max
+      efficiency: mean
+
+build_shape_options:
+  gadm_layer_id: 1 # GADM level area used for the gadm_shapes. Codes are country-dependent but roughly: 0: country, 1: region/county-like, 2: municipality-like
+  update_file: false # When true, all the input files are downloaded again and replace the existing files
+  out_logging: true # When true, logging is printed to console
+  year: 2020 # reference year used to derive shapes, info on population and info on GDP
+  nprocesses: 3 # number of processes to be used in build_shapes
+  worldpop_method: "standard" # "standard" pulls from web 1kmx1km raster, "api" pulls from API 100mx100m raster,
+  # false (not "false") no pop addition to shape which is useful when generating only cutout
+  gdp_method: "standard" # "standard" pulls from web 1x1km raster, false (not "false") no gdp addition to shape which useful when generating only cutout
+  contended_flag: "set_by_country" # "set_by_country" assigns the contended areas to the countries according to the GADM database, "drop" drops these contended areas from the model

configs/config.heating.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+sector:
+  district_heating:
+    potential: 0.3 #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: 1
+    # 2020: 0.0
+    # 2030: 0.3
+    # 2040: 0.6
+    # 2050: 1.0
+    district_heating_loss: 0.15
+  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: 0.29 # 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
+
+  tes: true
+  tes_tau: # 180 day time constant for centralised, 3 day for decentralised
+    decentral: 3
+    central: 180
+  boilers: true
+  oil_boilers: false
+  chp: true
+  micro_chp: false
+  solar_thermal: true
+  heat_pump_sink_T: 55 #Celsius, based on DTU / large area radiators; used un build_cop_profiles.py
+  time_dep_hp_cop: true #time dependent heat pump coefficient of performance
+  solar_cf_correction: 0.788457 # = >>>1/1.2683

configs/config.hydrogen.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+sector:
+  hydrogen:
+    network: true
+    H2_retrofit_capacity_per_CH4: 0.6
+    network_limit: 2000 #GWkm
+    network_routes: gas # "gas or "greenfield". If "gas"  ->  the network data are fetched from ["sector"]["gas"]["network_data"]. If "greenfield"  -> the network follows the topology of electrical transmission lines
+    gas_network_repurposing: true # If true -> ["sector"]["gas"]["network"] is automatically false
+    underground_storage: false
+    hydrogen_colors: false
+    set_color_shares: false
+    blue_share: 0.40
+    pink_share: 0.05
+
+  hydrogen_underground_storage: true
+  shipping_hydrogen_liquefaction: false
+  shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
+
+  gadm_level: 1
+  h2_cavern: true
+  marginal_cost_storage: 0
+  methanation: true
+  helmeth: true
+  dac: true
+  SMR: true
+  SMR CC: true
+  cc_fraction: 0.9
+  cc: true
+  airport_sizing_factor: 3
+
+  min_part_load_fischer_tropsch: 0.9

configs/config.monte-carlo.yaml

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+# SPDX-FileCopyrightText:  PyPSA-Earth and PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.1
+
+monte_carlo:
+  # Description: Specify Monte Carlo sampling options for uncertainty analysis.
+  # Define the option list for Monte Carlo sampling.
+  # Make sure add_to_snakefile is set to true to enable Monte-Carlo
+  options:
+    add_to_snakefile: false # When set to true, enables Monte Carlo sampling
+    samples: 9 # number of optimizations. Note that number of samples when using scipy has to be the square of a prime number
+    sampling_strategy: "chaospy" # "pydoe2", "chaospy", "scipy", packages that are supported
+    seed: 42 # set seedling for reproducibilty
+  # Uncertanties on any PyPSA object are specified by declaring the specific PyPSA object under the key 'uncertainties'.
+  # For each PyPSA object, the 'type' and 'args' keys represent the type of distribution and its argument, respectively.
+  # Supported distributions types are uniform, normal, lognormal, triangle, beta and gamma.
+  # The arguments of the distribution are passed using the key 'args'  as follows, tailored by distribution type
+  # normal: [mean, std], lognormal: [mean, std], uniform: [lower_bound, upper_bound],
+  # triangle: [mid_point (between 0 - 1)], beta: [alpha, beta], gamma: [shape, scale]
+  # More info on the distributions are documented in the Chaospy reference guide...
+  # https://chaospy.readthedocs.io/en/master/reference/distribution/index.html
+  # An abstract example is as follows:
+  # {pypsa network object, e.g. "loads_t.p_set"}:
+  # type: {any supported distribution among the previous: "uniform", "normal", ...}
+  # args: {arguments passed as a list depending on the distribution, see the above and more at https://pypsa.readthedocs.io/}
+  uncertainties:
+    loads_t.p_set:
+      type: uniform
+      args: [0, 1]
+    generators_t.p_max_pu.loc[:, n.generators.carrier == "onwind"]:
+      type: lognormal
+      args: [1.5]
+    generators_t.p_max_pu.loc[:, n.generators.carrier == "solar"]:
+      type: beta
+      args: [0.5, 2]