Merge remote-tracking branch 'origin/master' into multiyear

2023-07-26 10:23:32 +02:00 · 2023-07-26 10:23:32 +02:00 · ddd1840981
commit ddd1840981
parent e8772c3340 799f4f3731
93 changed files with 1712 additions and 1285 deletions
--- a/.github/ISSUE_TEMPLATE/config.yml
+++ b/.github/ISSUE_TEMPLATE/config.yml
@ -3,3 +3,6 @@ contact_links:
 - name: PyPSA Mailing List
  url: https://groups.google.com/forum/#!forum/pypsa
  about: Please ask and answer general usage questions here.
 - name: Stackoverflow
  url: https://stackoverflow.com/questions/tagged/pypsa
  about: Please ask and answer code-related questions here.
--- a/.github/workflows/ci.yaml
+++ b/.github/workflows/ci.yaml
@ -19,7 +19,6 @@ on:
  - cron: "0 5 * * TUE"
 env:
  CONDA_CACHE_NUMBER: 1 # Change this value to manually reset the environment cache
  DATA_CACHE_NUMBER: 2
 jobs:
@ -27,22 +26,12 @@ jobs:
    strategy:
      fail-fast: false
      max-parallel: 3
      matrix:
-        include:
+        os:
-          # Matrix required to handle caching with Mambaforge
+        - ubuntu-latest
-        - os: ubuntu-latest
+        - macos-latest
-          label: ubuntu-latest
+        - windows-latest
          prefix: /usr/share/miniconda3/envs/pypsa-eur
        - os: macos-latest
          label: macos-latest
          prefix: /Users/runner/miniconda3/envs/pypsa-eur
        - os: windows-latest
          label: windows-latest
          prefix: C:\Miniconda3\envs\pypsa-eur
    name: ${{ matrix.label }}
    runs-on: ${{ matrix.os }}
@ -60,24 +49,25 @@ jobs:
    - name: Add solver to environment
      run: |
        echo -e "- glpk\n- ipopt<3.13.3" >> envs/environment.yaml
-      if: ${{ matrix.label }} == 'windows-latest'
+      if: ${{ matrix.os }} == 'windows-latest'
    - name: Add solver to environment
      run: |
        echo -e "- glpk\n- ipopt" >> envs/environment.yaml
-      if: ${{ matrix.label }} != 'windows-latest'
+      if: ${{ matrix.os }} != 'windows-latest'
-    - name: Setup Mambaforge
+    - name: Setup micromamba
-      uses: conda-incubator/setup-miniconda@v2
+      uses: mamba-org/setup-micromamba@v1
      with:
-        miniforge-variant: Mambaforge
+        micromamba-version: latest
-        miniforge-version: latest
+        environment-file: envs/environment.yaml
-        activate-environment: pypsa-eur
+        log-level: debug
-        use-mamba: true
+        init-shell: bash
        cache-environment: true
        cache-downloads: true
    - name: Set cache dates
      run: |
        echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
        echo "WEEK=$(date +'%Y%U')" >> $GITHUB_ENV
    - name: Cache data and cutouts folders
@ -88,21 +78,8 @@ jobs:
          cutouts
        key: data-cutouts-${{ env.WEEK }}-${{ env.DATA_CACHE_NUMBER }}
    - name: Create environment cache
      uses: actions/cache@v3
      id: cache
      with:
        path: ${{ matrix.prefix }}
        key: ${{ matrix.label }}-conda-${{ env.DATE }}-${{ env.CONDA_CACHE_NUMBER }}
    - name: Update environment due to outdated or unavailable cache
      run: mamba env update -n pypsa-eur -f envs/environment.yaml
      if: steps.cache.outputs.cache-hit != 'true'
    - name: Test snakemake workflow
      run: |
        conda activate pypsa-eur
        conda list
        snakemake -call solve_elec_networks --configfile config/test/config.electricity.yaml --rerun-triggers=mtime
        snakemake -call all --configfile config/test/config.overnight.yaml --rerun-triggers=mtime
        snakemake -call all --configfile config/test/config.myopic.yaml --rerun-triggers=mtime
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@ -30,7 +30,7 @@ repos:
  # Find common spelling mistakes in comments and docstrings
 - repo: https://github.com/codespell-project/codespell
-  rev: v2.2.4
+  rev: v2.2.5
  hooks:
  - id: codespell
    args: ['--ignore-regex="(\b[A-Z]+\b)"', '--ignore-words-list=fom,appartment,bage,ore,setis,tabacco,berfore'] # Ignore capital case words, e.g. country codes
@ -39,7 +39,7 @@ repos:
  # Make docstrings PEP 257 compliant
 - repo: https://github.com/PyCQA/docformatter
-  rev: v1.6.3
+  rev: v1.7.5
  hooks:
  - id: docformatter
    args: ["--in-place", "--make-summary-multi-line", "--pre-summary-newline"]
@ -51,7 +51,7 @@ repos:
  # Formatting with "black" coding style
 - repo: https://github.com/psf/black
-  rev: 23.3.0
+  rev: 23.7.0
  hooks:
      # Format Python files
  - id: black
@ -67,7 +67,7 @@ repos:
  # Do YAML formatting (before the linter checks it for misses)
 - repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
-  rev: v2.8.0
+  rev: v2.10.0
  hooks:
  - id: pretty-format-yaml
    args: [--autofix, --indent, "2", --preserve-quotes]
@ -87,6 +87,6 @@ repos:
  # Check for FSFE REUSE compliance (licensing)
 - repo: https://github.com/fsfe/reuse-tool
-  rev: v1.1.2
+  rev: v2.1.0
  hooks:
  - id: reuse
--- a/.readthedocs.yml
+++ b/.readthedocs.yml
@ -4,8 +4,14 @@
 version: 2
 build:
  os: ubuntu-22.04
  tools:
    python: "3.11"
  apt_packages:
  - graphviz
 python:
  version: 3.8
  install:
  - requirements: doc/requirements.txt
-  system_packages: true
+  system_packages: false
--- a/README.md
+++ b/README.md
@ -11,6 +11,7 @@ SPDX-License-Identifier: CC-BY-4.0
 [![Zenodo PyPSA-Eur-Sec](https://zenodo.org/badge/DOI/10.5281/zenodo.3938042.svg)](https://doi.org/10.5281/zenodo.3938042)
 [![Snakemake](https://img.shields.io/badge/snakemake-≥5.0.0-brightgreen.svg?style=flat)](https://snakemake.readthedocs.io)
 [![REUSE status](https://api.reuse.software/badge/github.com/pypsa/pypsa-eur)](https://api.reuse.software/info/github.com/pypsa/pypsa-eur)
 [![Stack Exchange questions](https://img.shields.io/stackexchange/stackoverflow/t/pypsa)](https://stackoverflow.com/questions/tagged/pypsa)
 # PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy System
@ -90,6 +91,14 @@ to 50-200 nodes.
 Already-built versions of the model can be found in the accompanying [Zenodo
 repository](https://doi.org/10.5281/zenodo.3601881).
 # Contributing and Support
 We strongly welcome anyone interested in contributing to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on GitHub.
 -   In case of code-related **questions**, please post on [stack overflow](https://stackoverflow.com/questions/tagged/pypsa).
 -   For non-programming related and more general questions please refer to the [mailing list](https://groups.google.com/group/pypsa).
 -   To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the [discord server](https://discord.com/invite/AnuJBk23FU).
 -   For **bugs and feature requests**, please use the [PyPSA-Eur Github Issues page](https://github.com/PyPSA/pypsa-eur/issues).
 # Licence
 The code in PyPSA-Eur is released as free software under the
--- a/config/config.default.yaml
+++ b/config/config.default.yaml
@ -2,6 +2,7 @@
 #
 # SPDX-License-Identifier: CC0-1.0
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#top-level-configuration
 version: 0.8.0
 tutorial: false
@ -9,65 +10,52 @@ logging:
  level: INFO
  format: '%(levelname)s:%(name)s:%(message)s'
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#run
 run:
-  name: "" # use this to keep track of runs with different settings
+  name: ""
-  disable_progressbar: false # set to true to disable the progressbar
+  disable_progressbar: false
-  shared_resources: false # set to true to share the default resources across runs
+  shared_resources: false
-  shared_cutouts: true # set to true to share the default cutout(s) across runs
+  shared_cutouts: true
-foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented)
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#foresight
-# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
+foresight: overnight
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#scenario
 # Wildcard docs in https://pypsa-eur.readthedocs.io/en/latest/wildcards.html
 scenario:
  weather_year: [''] # for backwards compatibility
  simpl:
  - ''
-  ll:  # allowed transmission line volume expansion, can be any float >= 1.0 with a prefix v|c (today) or "copt"
+  ll:
  - v1.0
  - v1.5
-  clusters:  # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
+  clusters:
  - 37
  - 128
  - 256
  - 512
  - 1024
-  opts: # only relevant for PyPSA-Eur
+  opts:
  - ''
-  sector_opts: # this is where the main scenario settings are
+  sector_opts:
  - Co2L0-3H-T-H-B-I-A-solar+p3-dist1
-  # to really understand the options here, look in scripts/prepare_sector_network.py
+  planning_horizons:
  # 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
+  - 2050
  # for myopic foresight
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#countries
 countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK']
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#snapshots
 snapshots:
  start: "2013-01-01"
  end: "2014-01-01"
-  inclusive: 'left' # include start, not end
+  inclusive: 'left'
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#enable
 enable:
  retrieve: auto
  prepare_links_p_nom: false
  retrieve_databundle: true
  retrieve_sector_databundle: true
@ -81,9 +69,7 @@ enable:
  custom_busmap: false
  drop_leap_days: true
-# CO2 budget as a fraction of 1990 emissions
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#co2-budget
 # 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
@ -93,18 +79,19 @@ co2_budget:
  2045: 0.032
  2050: 0.000
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#electricity
 electricity:
  voltages: [220., 300., 380.]
-  gaslimit: false # global gas usage limit of X MWh_th
+  gaslimit: false
-  co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5
+  co2limit: 7.75e+7
  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
+  operational_reserve:
    activate: false
-    epsilon_load: 0.02 # share of total load
+    epsilon_load: 0.02
-    epsilon_vres: 0.02 # share of total renewable supply
+    epsilon_vres: 0.02
-    contingency: 4000 # fixed capacity in MW
+    contingency: 4000
  max_hours:
    battery: 6
@ -116,9 +103,7 @@ electricity:
    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]
@ -126,25 +111,19 @@ electricity:
  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]
-
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#atlite
 atlite:
  default_cutout: europe-2013-era5
  nprocesses: 4
-  show_progress: false # false saves time
+  show_progress: false
  cutouts:
    # use 'base' to determine geographical bounds and time span from config
    # base:
@ -167,20 +146,16 @@ atlite:
      sarah_dir:
      features: [influx, temperature]
-
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#renewable
 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
+    capacity_per_sqkm: 3
    # 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]
@ -193,13 +168,8 @@ renewable:
    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
+    capacity_per_sqkm: 2
    # 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
@ -213,13 +183,8 @@ renewable:
    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
+    capacity_per_sqkm: 2
    # 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
@ -236,14 +201,7 @@ renewable:
      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
+    capacity_per_sqkm: 1.7
    # 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
@ -260,10 +218,12 @@ renewable:
    eia_correct_by_capacity: false
    eia_approximate_missing: false
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#conventional
 conventional:
  nuclear:
    p_max_pu: "data/nuclear_p_max_pu.csv" # float of file name
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#lines
 lines:
  types:
    220.: "Al/St 240/40 2-bundle 220.0"
@ -271,28 +231,35 @@ lines:
    380.: "Al/St 240/40 4-bundle 380.0"
  s_max_pu: 0.7
  s_nom_max: .inf
  max_extension: .inf
  length_factor: 1.25
  under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#links
 links:
  p_max_pu: 1.0
  p_nom_max: .inf
  max_extension: .inf
  include_tyndp: true
  under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#transformers
 transformers:
  x: 0.1
  s_nom: 2000.
  type: ''
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#load
 load:
-  power_statistics: true # only for files from <2019; set false in order to get ENTSOE transparency data
+  power_statistics: true
-  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
+  interpolate_limit: 3
-  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from
+  time_shift_for_large_gaps: 1w
  manual_adjustments: true # false
  scaling_factor: 1.0
  fixed_year: false # false or year (e.g. 2013)
 # docs
 # TODO: PyPSA-Eur merge issue in prepare_sector_network.py
 # regulate what components with which carriers are kept from PyPSA-Eur;
 # some technologies are removed because they are implemented differently
 # (e.g. battery or H2 storage) or have different year-dependent costs
@ -313,12 +280,14 @@ pypsa_eur:
  - hydro
  Store: []
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#energy
 energy:
  energy_totals_year: 2011
  base_emissions_year: 1990
  eurostat_report_year: 2016
-  emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
+  emissions: CO2
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#biomass
 biomass:
  year: 2030
  scenario: ENS_Med
@ -344,14 +313,14 @@ biomass:
    - Manure solid, liquid
    - Sludge
-
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solar-thermal
 solar_thermal:
  clearsky_model: simple  # should be "simple" or "enhanced"?
  orientation:
    slope: 45.
    azimuth: 180.
-# only relevant for foresight = myopic or perfect
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#existing-capacities
 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
@ -362,37 +331,34 @@ existing_capacities:
  - oil
  - uranium
-
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#sector
 sector:
  district_heating:
-    potential: 0.6  # maximum fraction of urban demand which can be supplied by district heating
+    potential: 0.6
     # 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
+  cluster_heat_buses: false
-  bev_dsm_restriction_value: 0.75  #Set to 0 for no restriction on BEV DSM
+  bev_dsm_restriction_value: 0.75
-  bev_dsm_restriction_time: 7  #Time at which SOC of BEV has to be dsm_restriction_value
+  bev_dsm_restriction_time: 7
  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_lower_degree_factor: 0.375
  ICE_upper_degree_factor: 1.6
  EV_lower_degree_factor: 0.98
  EV_upper_degree_factor: 0.63
-  bev_dsm: true #turns on EV battery
+  bev_dsm: true
-  bev_availability: 0.5  #How many cars do smart charging
+  bev_availability: 0.5
-  bev_energy: 0.05  #average battery size in MWh
+  bev_energy: 0.05
-  bev_charge_efficiency: 0.9  #BEV (dis-)charging efficiency
+  bev_charge_efficiency: 0.9
-  bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
+  bev_plug_to_wheel_efficiency: 0.2
-  bev_charge_rate: 0.011 #3-phase charger with 11 kW
+  bev_charge_rate: 0.011
  bev_avail_max: 0.95
  bev_avail_mean: 0.8
-  v2g: true #allows feed-in to grid from EV battery
+  v2g: true
  #what is not EV or FCEV is oil-fuelled ICE
  land_transport_fuel_cell_share:
    2020: 0
    2030: 0.05
@ -412,12 +378,12 @@ sector:
  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_fuel_efficiency: 0.7
-  agriculture_machinery_electric_efficiency: 0.3 # electricity per use
+  agriculture_machinery_electric_efficiency: 0.3
-  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_MWh_H2: 0.8787
-  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_tCO2: 4.0321
-  MWh_MeOH_per_MWh_e: 3.6907 # in LHV, source: DECHEMA (2017): Low carbon energy and feedstock for the European chemical industry , pg. 64.
+  MWh_MeOH_per_MWh_e: 3.6907
-  shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
+  shipping_hydrogen_liquefaction: false
  shipping_hydrogen_share:
    2020: 0
    2030: 0
@ -433,18 +399,14 @@ sector:
    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_methanol_efficiency: 0.46
-  shipping_oil_efficiency: 0.40 #For conversion of fuel oil to propulsion in 2011
+  shipping_oil_efficiency: 0.40
-  aviation_demand_factor: 1. # relative aviation demand compared to today
+  aviation_demand_factor: 1.
-  HVC_demand_factor: 1. # relative HVC demand compared to today
+  HVC_demand_factor: 1.
-  time_dep_hp_cop: true #time dependent heat pump coefficient of performance
+  time_dep_hp_cop: true
-  heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
+  heat_pump_sink_T: 55.
-   # conservatively high to cover hot water and space heating in poorly-insulated buildings
+  reduce_space_heat_exogenously: true
-  reduce_space_heat_exogenously: true  # reduces space heat demand by a given factor (applied before losses in DH)
+  reduce_space_heat_exogenously_factor:
  # 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
@ -452,15 +414,15 @@ sector:
    2040: 0.16
    2045: 0.21
    2050: 0.29
-  retrofitting:   # co-optimises building renovation to reduce space heat demand
+  retrofitting:
-    retro_endogen: false  # co-optimise space heat savings
+    retro_endogen: false
-    cost_factor: 1.0   # weight costs for building renovation
+    cost_factor: 1.0
-    interest_rate: 0.04  # for investment in building components
+    interest_rate: 0.04
-    annualise_cost: true  # annualise the investment costs
+    annualise_cost: true
-    tax_weighting: false   # weight costs depending on taxes in countries
+    tax_weighting: false
-    construction_index: true   # weight costs depending on labour/material costs per country
+    construction_index: true
  tes: true
-  tes_tau: # 180 day time constant for centralised, 3 day for decentralised
+  tes_tau:
    decentral: 3
    central: 180
  boilers: true
@ -481,50 +443,48 @@ sector:
  hydrogen_turbine: false
  SMR: true
  regional_co2_sequestration_potential:
-    enable: false  # enable regionally resolved geological co2 storage potential
+    enable: false
    attribute: 'conservative estimate Mt'
-    include_onshore: false  # include onshore sequestration potentials
+    include_onshore: false
-    min_size: 3 # Gt, sites with lower potential will be excluded
+    min_size: 3
-    max_size: 25 # Gt, max sequestration potential for any one site, TODO research suitable value
+    max_size: 25
-    years_of_storage: 25 # years until potential exhausted at optimised annual rate
+    years_of_storage: 25
-  co2_sequestration_potential: 200  #MtCO2/a sequestration potential for Europe
+  co2_sequestration_potential: 200
-  co2_sequestration_cost: 10   #EUR/tCO2 for sequestration of CO2
+  co2_sequestration_cost: 10
  co2_spatial: false
  co2network: false
-  cc_fraction: 0.9  # default fraction of CO2 captured with post-combustion capture
+  cc_fraction: 0.9
  hydrogen_underground_storage: true
  hydrogen_underground_storage_locations:
    # - onshore  # more than 50 km from sea
  - nearshore    # within 50 km of sea
    # - offshore
-  ammonia: false # can be false (no NH3 carrier), true (copperplated NH3), "regional" (regionalised NH3 without network)
+  ammonia: false
-  min_part_load_fischer_tropsch: 0.9 # p_min_pu
+  min_part_load_fischer_tropsch: 0.9
-  min_part_load_methanolisation: 0.5 # p_min_pu
+  min_part_load_methanolisation: 0.5
  use_fischer_tropsch_waste_heat: true
  use_fuel_cell_waste_heat: true
  use_electrolysis_waste_heat: false
  electricity_distribution_grid: true
-  electricity_distribution_grid_cost_factor: 1.0  #multiplies cost in data/costs.csv
+  electricity_distribution_grid_cost_factor: 1.0
-  electricity_grid_connection: true  # only applies to onshore wind and utility PV
+  electricity_grid_connection: true
  H2_network: true
  gas_network: false
-  H2_retrofit: false  # if set to True existing gas pipes can be retrofitted to H2 pipes
+  H2_retrofit: false
-  # according to hydrogen backbone strategy (April, 2020) p.15
+  H2_retrofit_capacity_per_CH4: 0.6
-  # https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
+  gas_network_connectivity_upgrade: 1
  # 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
+  gas_distribution_grid_cost_factor: 1.0
-  biomass_spatial: false  # regionally resolve biomass (e.g. potentials)
+  biomass_spatial: false
-  biomass_transport: false  # allow transport of solid biomass between nodes
+  biomass_transport: false
-  conventional_generation: # generator : carrier
+  conventional_generation:
    OCGT: gas
  biomass_to_liquid: false
  biosng: false
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry
 industry:
-  St_primary_fraction:  # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
+  St_primary_fraction:
    2020: 0.6
    2025: 0.55
    2030: 0.5
@ -532,7 +492,7 @@ industry:
    2040: 0.4
    2045: 0.35
    2050: 0.3
-  DRI_fraction:  # fraction of the primary route converted to DRI + EAF
+  DRI_fraction:
    2020: 0
    2025: 0
    2030: 0.05
@ -540,9 +500,9 @@ industry:
    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
+  H2_DRI: 1.7
-  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
+  elec_DRI: 0.322
-  Al_primary_fraction:  # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
+  Al_primary_fraction:
    2020: 0.4
    2025: 0.375
    2030: 0.35
@ -550,35 +510,33 @@ industry:
    2040: 0.3
    2045: 0.25
    2050: 0.2
-  MWh_NH3_per_tNH3: 5.166 # LHV
+  MWh_NH3_per_tNH3: 5.166
-  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_CH4_per_tNH3_SMR: 10.8
-  MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
+  MWh_elec_per_tNH3_SMR: 0.7
-  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_H2_per_tNH3_electrolysis: 6.5
-  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_elec_per_tNH3_electrolysis: 1.17
  MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
-  NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
+  NH3_process_emissions: 24.5
-  petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
+  petrochemical_process_emissions: 25.5
-  HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
+  HVC_primary_fraction: 1.
-  HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
+  HVC_mechanical_recycling_fraction: 0.
-  HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
+  HVC_chemical_recycling_fraction: 0.
-  HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
+  HVC_production_today: 52.
-  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_mechanical_recycling: 0.547
-  MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
+  MWh_elec_per_tHVC_chemical_recycling: 6.9
-  chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
+  chlorine_production_today: 9.58
-  MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
+  MWh_elec_per_tCl: 3.6
-  MWh_H2_per_tCl: -0.9372  # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
+  MWh_H2_per_tCl: -0.9372
-  methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
+  methanol_production_today: 1.5
-  MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
+  MWh_elec_per_tMeOH: 0.167
-  MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
+  MWh_CH4_per_tMeOH: 10.25
  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
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#costs
 costs:
  year: 2030
-  version: v0.5.0
+  version: v0.6.0
  rooftop_share: 0.14  # based on the potentials, assuming  (0.1 kW/m2 and 10 m2/person)
  fill_values:
    FOM: 0
@ -602,14 +560,15 @@ costs:
    fuel cell: 0.
    battery: 0.
    battery inverter: 0.
-  emission_prices: # in currency per tonne emission, only used with the option Ep
+  emission_prices:
    co2: 0.
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#clustering
 clustering:
  simplify_network:
-    to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections)
+    to_substations: false
    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.
+    feature: solar+onwind-time
    exclude_carriers: []
    remove_stubs: true
    remove_stubs_across_borders: true
@ -619,7 +578,7 @@ clustering:
    exclude_carriers: []
  aggregation_strategies:
    generators:
-      p_nom_max: sum # use "min" for more conservative assumptions
+      p_nom_max: sum
      p_nom_min: sum
      p_min_pu: mean
      marginal_cost: mean
@ -628,12 +587,13 @@ clustering:
      ramp_limit_down: max
      efficiency: mean
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solving
 solving:
  #tmpdir: "path/to/tmp"
  options:
    formulation: kirchhoff
    clip_p_max_pu: 1.e-2
    load_shedding: false
    transmission_losses: 0
    noisy_costs: true
    skip_iterations: true
    track_iterations: false
@ -717,6 +677,7 @@ operations:
  co2_price: 500 # EUR/t
  co2_sequestation_limit: 200 # Mt/a
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#plotting
 plotting:
  map:
    boundaries: [-11, 30, 34, 71]
@ -731,48 +692,6 @@ plotting:
  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"
@ -813,6 +732,11 @@ plotting:
    solar: "#f9d002"
    solar PV: "#f9d002"
    solar thermal: '#ffbf2b'
    residential rural solar thermal: '#f1c069'
    services rural solar thermal: '#eabf61'
    residential urban decentral solar thermal: '#e5bc5a'
    services urban decentral solar thermal: '#dfb953'
    urban central solar thermal: '#d7b24c'
    solar rooftop: '#ffea80'
    # gas
    OCGT: '#e0986c'
@ -821,9 +745,15 @@ plotting:
    gas boiler: '#db6a25'
    gas boilers: '#db6a25'
    gas boiler marginal: '#db6a25'
    residential rural gas boiler: '#d4722e'
    residential urban decentral gas boiler: '#cb7a36'
    services rural gas boiler: '#c4813f'
    services urban decentral gas boiler: '#ba8947'
    urban central gas boiler: '#b0904f'
    gas: '#e05b09'
    fossil gas: '#e05b09'
    natural gas: '#e05b09'
    biogas to gas: '#e36311'
    CCGT: '#a85522'
    CCGT marginal: '#a85522'
    allam: '#B98F76'
@ -836,6 +766,11 @@ plotting:
    # oil
    oil: '#c9c9c9'
    oil boiler: '#adadad'
    residential rural oil boiler: '#a9a9a9'
    services rural oil boiler: '#a5a5a5'
    residential urban decentral oil boiler: '#a1a1a1'
    urban central oil boiler: '#9d9d9d'
    services urban decentral oil boiler: '#999999'
    agriculture machinery oil: '#949494'
    shipping oil: "#808080"
    land transport oil: '#afafaf'
@ -861,13 +796,20 @@ plotting:
    solid biomass for industry CC: '#47411c'
    solid biomass for industry co2 from atmosphere: '#736412'
    solid biomass for industry co2 to stored: '#47411c'
    urban central solid biomass CHP: '#9d9042'
    urban central solid biomass CHP CC: '#6c5d28'
    biomass boiler: '#8A9A5B'
    residential rural biomass boiler: '#a1a066'
    residential urban decentral biomass boiler: '#b0b87b'
    services rural biomass boiler: '#c6cf98'
    services urban decentral biomass boiler: '#dde5b5'
    biomass to liquid: '#32CD32'
    BioSNG: '#123456'
    # power transmission
    lines: '#6c9459'
    transmission lines: '#6c9459'
    electricity distribution grid: '#97ad8c'
    low voltage: '#97ad8c'
    # electricity demand
    Electric load: '#110d63'
    electric demand: '#110d63'
@ -878,24 +820,48 @@ plotting:
    # battery + EVs
    battery: '#ace37f'
    battery storage: '#ace37f'
    battery charger: '#88a75b'
    battery discharger: '#5d4e29'
    home battery: '#80c944'
    home battery storage: '#80c944'
    home battery charger: '#5e8032'
    home battery discharger: '#3c5221'
    BEV charger: '#baf238'
    V2G: '#e5ffa8'
    land transport EV: '#baf238'
    Li ion: '#baf238'
    # hot water storage
    water tanks: '#e69487'
    residential rural water tanks: '#f7b7a3'
    services rural water tanks: '#f3afa3'
    residential urban decentral water tanks: '#f2b2a3'
    services urban decentral water tanks: '#f1b4a4'
    urban central water tanks: '#e9977d'
    hot water storage: '#e69487'
-    hot water charging: '#e69487'
+    hot water charging: '#e8998b'
-    hot water discharging: '#e69487'
+    urban central water tanks charger: '#b57a67'
    residential rural water tanks charger: '#b4887c'
    residential urban decentral water tanks charger: '#b39995'
    services rural water tanks charger: '#b3abb0'
    services urban decentral water tanks charger: '#b3becc'
    hot water discharging: '#e99c8e'
    urban central water tanks discharger: '#b9816e'
    residential rural water tanks discharger: '#ba9685'
    residential urban decentral water tanks discharger: '#baac9e'
    services rural water tanks discharger: '#bbc2b8'
    services urban decentral water tanks discharger: '#bdd8d3'
    # heat demand
    Heat load: '#cc1f1f'
    heat: '#cc1f1f'
    heat demand: '#cc1f1f'
    rural heat: '#ff5c5c'
    residential rural heat: '#ff7c7c'
    services rural heat: '#ff9c9c'
    central heat: '#cc1f1f'
    urban central heat: '#d15959'
    decentral heat: '#750606'
    residential urban decentral heat: '#a33c3c'
    services urban decentral heat: '#cc1f1f'
    low-temperature heat for industry: '#8f2727'
    process heat: '#ff0000'
    agriculture heat: '#d9a5a5'
@ -903,14 +869,26 @@ plotting:
    heat pumps: '#2fb537'
    heat pump: '#2fb537'
    air heat pump: '#36eb41'
    residential urban decentral air heat pump: '#48f74f'
    services urban decentral air heat pump: '#5af95d'
    urban central air heat pump: '#6cfb6b'
    ground heat pump: '#2fb537'
    residential rural ground heat pump: '#48f74f'
    services rural ground heat pump: '#5af95d'
    Ambient: '#98eb9d'
    CHP: '#8a5751'
    urban central gas CHP: '#8d5e56'
    CHP CC: '#634643'
    urban central gas CHP CC: '#6e4e4c'
    CHP heat: '#8a5751'
    CHP electric: '#8a5751'
    district heating: '#e8beac'
    resistive heater: '#d8f9b8'
    residential rural resistive heater: '#bef5b5'
    residential urban decentral resistive heater: '#b2f1a9'
    services rural resistive heater: '#a5ed9d'
    services urban decentral resistive heater: '#98e991'
    urban central resistive heater: '#8cdf85'
    retrofitting: '#8487e8'
    building retrofitting: '#8487e8'
    # hydrogen
@ -922,13 +900,16 @@ plotting:
    SMR CC: '#4f1745'
    H2 liquefaction: '#d647bd'
    hydrogen storage: '#bf13a0'
    H2 Store: '#bf13a0'
    H2 storage: '#bf13a0'
    land transport fuel cell: '#6b3161'
    H2 pipeline: '#f081dc'
    H2 pipeline retrofitted: '#ba99b5'
    H2 Fuel Cell: '#c251ae'
    H2 fuel cell: '#c251ae'
    H2 turbine: '#991f83'
    H2 Electrolysis: '#ff29d9'
    H2 electrolysis: '#ff29d9'
    # ammonia
    NH3: '#46caf0'
    ammonia: '#46caf0'
@ -977,9 +958,11 @@ plotting:
    waste: '#e3d37d'
    other: '#000000'
    geothermal: '#ba91b1'
    AC: "#70af1d"
    AC-AC: "#70af1d"
    AC line: "#70af1d"
    links: "#8a1caf"
    HVDC links: "#8a1caf"
    DC: "#8a1caf"
    DC-DC: "#8a1caf"
    DC link: "#8a1caf"
--- a/config/test/config.myopic.yaml
+++ b/config/test/config.myopic.yaml
@ -31,6 +31,14 @@ snapshots:
  end: "2013-03-08"
 electricity:
  co2limit: 100.e+6
  extendable_carriers:
    Generator: [OCGT]
    StorageUnit: [battery]
    Store: [H2]
    Link: [H2 pipeline]
  renewable_carriers: [solar, onwind, offwind-ac, offwind-dc]
 atlite:
--- a/config/test/config.overnight.yaml
+++ b/config/test/config.overnight.yaml
@ -28,6 +28,14 @@ snapshots:
  end: "2013-03-08"
 electricity:
  co2limit: 100.e+6
  extendable_carriers:
    Generator: [OCGT]
    StorageUnit: [battery]
    Store: [H2]
    Link: [H2 pipeline]
  renewable_carriers: [solar, onwind, offwind-ac, offwind-dc]
 atlite:
--- a/data/override_component_attrs/buses.csv
+++ b/data/override_component_attrs/buses.csv
@ -1,3 +0,0 @@
 attribute,type,unit,default,description,status
 location,string,n/a,n/a,Reference to original electricity bus,Input (optional)
 unit,string,n/a,MWh,Unit of the bus (descriptive only), Input (optional)
--- a/data/override_component_attrs/generators.csv
+++ b/data/override_component_attrs/generators.csv
@ -1,4 +0,0 @@
 attribute,type,unit,default,description,status
 carrier,string,n/a,n/a,carrier,Input (optional)
 lifetime,float,years,inf,lifetime,Input (optional)
 build_year,int,year ,0,build year,Input (optional)
--- a/data/override_component_attrs/links.csv
+++ b/data/override_component_attrs/links.csv
@ -1,13 +0,0 @@
 attribute,type,unit,default,description,status
 bus2,string,n/a,n/a,2nd bus,Input (optional)
 bus3,string,n/a,n/a,3rd bus,Input (optional)
 bus4,string,n/a,n/a,4th bus,Input (optional)
 efficiency2,static or series,per unit,1,2nd bus efficiency,Input (optional)
 efficiency3,static or series,per unit,1,3rd bus efficiency,Input (optional)
 efficiency4,static or series,per unit,1,4th bus efficiency,Input (optional)
 p2,series,MW,0,2nd bus output,Output
 p3,series,MW,0,3rd bus output,Output
 p4,series,MW,0,4th bus output,Output
 carrier,string,n/a,n/a,carrier,Input (optional)
 lifetime,float,years,inf,lifetime,Input (optional)
 build_year,int,year ,0,build year,Input (optional)
--- a/data/override_component_attrs/loads.csv
+++ b/data/override_component_attrs/loads.csv
@ -1,2 +0,0 @@
 attribute,type,unit,default,description,status
 carrier,string,n/a,n/a,carrier,Input (optional)
--- a/data/override_component_attrs/stores.csv
+++ b/data/override_component_attrs/stores.csv
@ -1,4 +0,0 @@
 attribute,type,unit,default,description,status
 carrier,string,n/a,n/a,carrier,Input (optional)
 lifetime,float,years,inf,lifetime,Input (optional)
 build_year,int,year ,0,build year,Input (optional)
--- a/doc/conf.py
+++ b/doc/conf.py
@ -36,6 +36,7 @@ sys.path.insert(0, os.path.abspath("../scripts"))
 extensions = [
    #'sphinx.ext.autodoc',
    #'sphinx.ext.autosummary',
    "myst_parser",
    "sphinx.ext.autosectionlabel",
    "sphinx.ext.intersphinx",
    "sphinx.ext.todo",
--- a/doc/configtables/biomass.csv
+++ b/doc/configtables/biomass.csv
@ -0,0 +1,7 @@
 ,Unit,Values,Description
 year ,--,"{2010, 2020, 2030, 2040, 2050}",Year for which to retrieve biomass potential according to the assumptions of the `JRC ENSPRESO <https://data.jrc.ec.europa.eu/dataset/74ed5a04-7d74-4807-9eab-b94774309d9f>`_ .
 scenario ,--,"{""ENS_Low"", ""ENS_Med"", ""ENS_High""}",Scenario for which to retrieve biomass potential. The scenario definition can be seen in `ENSPRESO_BIOMASS <https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx>`_
 classes ,,,
 -- solid biomass,--,Array of biomass comodity,The comodity that are included as solid biomass
 -- not included,--,Array of biomass comodity,The comodity that are not included as a biomass potential
 -- biogas,--,Array of biomass comodity,The comodity that are included as biogas
--- a/doc/configtables/co2_budget.csv
+++ b/doc/configtables/co2_budget.csv
@ -0,0 +1,2 @@
 ,Unit,Values,Description
 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"doc/configtables/othertoplevel.csv
--- a/doc/configtables/countries.csv
+++ b/doc/configtables/countries.csv
@ -0,0 +1,2 @@
 ,Unit,Values,Description
 countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) <https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2>`_ which should be included in the energy system model."
--- a/doc/configtables/electricity.csv
+++ b/doc/configtables/electricity.csv
@ -1,11 +1,12 @@
 ,Unit,Values,Description
 voltages,kV,"Any subset of {220., 300., 380.}",Voltage levels to consider
-gaslimit,MWhth,"float or false",Global gas usage limit
+gaslimit,MWhth,float or false,Global gas usage limit
 co2limit,:math:`t_{CO_2-eq}/a`,float,Cap on total annual system carbon dioxide emissions
 co2base,:math:`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 <https://genxproject.github.io/GenX/dev/core/#Reserves>`_"
+operational_reserve,,,Settings for reserve requirements following `GenX <https://genxproject.github.io/GenX/dev/core/#Reserves>`_
-- activate,bool,"true or false","Whether to take operational reserve requirements into account during optimisation"
+,,,
 -- 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
@ -13,17 +14,23 @@ 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 <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_.
 -- 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 <https://pypsa.readthedocs.io/en/latest/components.html#storage-unit>`_.
 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."
+-- 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 <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. Country not in ['Germany']",Filter query for the default powerplant database.
+powerplants_filter,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ strings here, e.g. ``Country not in ['Germany']``",Filter query for the default powerplant database.
-custom_powerplants,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ 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."
+custom_powerplants,--,"use `pandas.query <https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.query.html>`_ 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"
+-- enable,,bool,Activate routine to estimate renewable capacities
-- from_opsd,--,bool,"Add capacities from OPSD data"
+-- from_opsd,--,bool,Add renewable capacities from `OPSD database <https://data.open-power-system-data.org/renewable_power_plants/2020-08-25>`_. The value is depreciated but still can be used.
-- year,--,bool,"Renewable capacities are based on existing capacities reported by IRENA for the specified year"
+-- year,--,bool,Renewable capacities are based on existing capacities reported by IRENA (IRENASTAT) for the specified year
-- expansion_limit,--,float or false,"Artificially limit maximum 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,--,float or false,"Artificially limit maximum IRENA capacities to a factor.  For example, an ``expansion_limit: 1.1`` means 110% of capacities . If false are chosen, the estimated renewable potentials determine by the workflow are used."
-- technology_mapping,,,"Mapping between powerplantmatching and PyPSA-Eur technology names"
+-- technology_mapping,,,Mapping between PyPSA-Eur and powerplantmatching technology names
 -- -- Offshore,--,"Any subset of {offwind-ac, offwind-dc}","List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) onshore technology."
 -- -- Offshore,--,{onwind},"List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) offshore technology."
 -- -- PV,--,{solar},"List of PyPSA-Eur carriers that is considered as (IRENA, OPSD) PV technology."
--- a/doc/configtables/enable.csv
+++ b/doc/configtables/enable.csv
@ -1,4 +1,5 @@
 ,Unit,Values,Description
 enable,str or bool,"{auto, true, false}","Switch to include (true) or exclude (false) the retrieve_* rules of snakemake into the workflow; 'auto' sets true|false based on availability of an internet connection to prevent issues with snakemake failing due to lack of internet connection."
 prepare_links_p_nom,bool,"{true, false}","Switch to retrieve current HVDC projects from `Wikipedia <https://en.wikipedia.org/wiki/List_of_HVDC_projects>`_"
 retrieve_databundle,bool,"{true, false}","Switch to retrieve databundle from zenodo via the rule :mod:`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 :mod:`retrieve_sector_databundle` or whether to keep a custom databundle located in the corresponding folder."
--- a/doc/configtables/energy.csv
+++ b/doc/configtables/energy.csv
@ -0,0 +1,7 @@
 ,Unit,Values,Description
 energy_totals_year ,--,"{1990,1995,2000,2005,2010,2011,…} ",The year for the sector energy use. The year must be avaliable in the Eurostat report
 base_emissions_year ,--,"YYYY; e.g. 1990","The base year for the sector emissions. See `European Environment Agency (EEA) <https://www.eea.europa.eu/data-and-maps/data/national-emissions-reported-to-the-unfccc-and-to-the-eu-greenhouse-gas-monitoring-mechanism-16>`_."
 eurostat_report_year ,--,"{2016,2017,2018}","The publication year of the Eurostat report. 2016 includes Bosnia and Herzegovina, 2017 does not"
 emissions ,--,"{CO2, All greenhouse gases - (CO2 equivalent)}","Specify which sectoral emissions are taken into account. Data derived from EEA. Currently only CO2 is implemented."
--- a/doc/configtables/existing_capacities.csv
+++ b/doc/configtables/existing_capacities.csv
@ -0,0 +1,6 @@
 ,Unit,Values,Description
 grouping_years_power ,--,A list of years,Intervals to group existing capacities for power
 grouping_years_heat ,--,A list of years below 2020,Intervals to group existing capacities for heat
 threshold_capacity ,MW,float,Capacities generators and links of below threshold are removed during add_existing_capacities
 conventional_carriers ,--,"Any subset of {uranium, coal, lignite, oil} ",List of conventional power plants to include in the sectoral network
--- a/doc/configtables/foresight.csv
+++ b/doc/configtables/foresight.csv
@ -0,0 +1,2 @@
 ,Unit,Values,Description
 foresight,string,"{overnight, myopic, perfect}","See :ref:`Foresight Options` for detail explanations."
--- a/doc/configtables/industry.csv
+++ b/doc/configtables/industry.csv
@ -0,0 +1,31 @@
 ,Unit,Values,Description
 St_primary_fraction,--,Dictionary with planning horizons as keys.,The fraction of steel produced via primary route versus secondary route (scrap+EAF). Current fraction is 0.6
 DRI_fraction,--,Dictionary with planning horizons as keys.,The fraction of the primary route DRI + EAF
 ,,,
 H2_DRI,--,float,The hydrogen consumption in Direct Reduced Iron (DRI)  Mwh_H2 LHV/ton_Steel from 51kgH2/tSt in `Vogl et al (2018) <https://doi.org/10.1016/j.jclepro.2018.08.279>`_
 elec_DRI,MWh/tSt,float,The electricity consumed in Direct Reduced Iron (DRI) shaft. From `HYBRIT brochure <https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf>`_
 Al_primary_fraction,--,Dictionary with planning horizons as keys.,The fraction of aluminium produced via the primary route versus scrap. Current fraction is 0.4
 MWh_NH3_per_tNH3,LHV,float,The energy amount per ton of ammonia.
 MWh_CH4_per_tNH3_SMR,--,float,The energy amount of methane needed to produce a ton of ammonia using steam methane reforming (SMR). Value derived from 2012's demand from `Center for European Policy Studies (2008) <https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf>`_
 MWh_elec_per_tNH3_SMR,--,float,"The energy amount of electricity needed to produce a ton of ammonia using steam methane reforming (SMR). same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3"
 Mwh_H2_per_tNH3 _electrolysis,--,float,"The energy amount of hydrogen needed to produce a ton of ammonia using Haber–Bosch process. From  `Wang et al (2018) <https://doi.org/10.1016/j.joule.2018.04.017>`_, Base value assumed around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)"
 Mwh_elec_per_tNH3 _electrolysis,--,float,"The energy amount of electricity needed to produce a ton of ammonia using Haber–Bosch process. From  `Wang et al (2018) <https://doi.org/10.1016/j.joule.2018.04.017>`_, Table 13 (air separation and HB)"
 Mwh_NH3_per_MWh _H2_cracker,--,float,The energy amount of amonia needed to produce an energy amount hydrogen using ammonia cracker
 NH3_process_emissions,MtCO2/a,float,The emission of ammonia production from steam methane reforming (SMR). From UNFCCC for 2015 for EU28
 petrochemical_process _emissions,MtCO2/a,float,The emission of petrochemical production. From UNFCCC for 2015 for EU28
 HVC_primary_fraction,--,float,The fraction of high value chemicals (HVC) produced via primary route
 HVC_mechanical_recycling _fraction,--,float,The fraction of high value chemicals (HVC) produced using mechanical recycling
 HVC_chemical_recycling _fraction,--,float,The fraction of high value chemicals (HVC) produced using chemical recycling
 ,,,
 HVC_production_today,MtHVC/a,float,"The amount of high value chemicals (HVC) produced. This includes ethylene, propylene and BTX. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, Figure 16, page 107"
 Mwh_elec_per_tHVC _mechanical_recycling,MWh/tHVC,float,"The energy amount of electricity needed to produce a ton of high value chemical (HVC) using mechanical recycling. From SI of `Meys et al (2020) <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,MWh/tHVC,float,"The energy amount of electricity needed to produce a ton of high value chemical (HVC) using chemical recycling. The default value is based on pyrolysis and electric steam cracking. From `Material Economics (2019) <https://materialeconomics.com/latest-updates/industrial-transformation-2050>`_, page 125"
 ,,,
 chlorine_production _today,MtCl/a,float,"The amount of chlorine produced. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, Table 7, page 43"
 MWh_elec_per_tCl,MWh/tCl,float,"The energy amount of electricity needed to produce a ton of chlorine. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, Table 6 page 43"
 MWh_H2_per_tCl,MWhH2/tCl,float,"The energy amount of hydrogen needed to produce a ton of chlorine. The value is negative since hydrogen produced in chloralkali process. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 43"
 methanol_production _today,MtMeOH/a,float,"The amount of methanol produced. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 62"
 MWh_elec_per_tMeOH,MWh/tMeOH,float,"The energy amount of electricity needed to produce a ton of methanol. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, Table 14, page 65"
 MWh_CH4_per_tMeOH,MWhCH4/tMeOH,float,"The energy amount of methane needed to produce a ton of methanol. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, Table 14, page 65"
 hotmaps_locate_missing,--,"{true,false}",Locate industrial sites without valid locations based on city and countries.
 reference_year,year,YYYY,The year used as the baseline for industrial energy demand and production. Data extracted from `JRC-IDEES 2015 <https://data.jrc.ec.europa.eu/dataset/jrc-10110-10001>`_
--- a/doc/configtables/lines.csv
+++ b/doc/configtables/lines.csv
@ -2,5 +2,6 @@
 types,--,"Values should specify a `line type in PyPSA <https://pypsa.readthedocs.io/en/latest/components.html#line-types>`_. 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 :math:`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."
 max_extension,MW,"float","Upper limit for the extended capacity of each extendable line."
 length_factor,--,float,"Correction factor to account for the fact that buses are *not* connected by lines through air-line distance."
 under_construction,--,"One of {'zero': set capacity to zero, 'remove': remove completely, 'keep': keep with full capacity}","Specifies how to handle lines which are currently under construction."
--- a/doc/configtables/links.csv
+++ b/doc/configtables/links.csv
@ -1,5 +1,6 @@
 ,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."
 max_extension,MW,"float","Upper limit for the extended capacity of each extendable DC link."
 include_tyndp,bool,"{'true', 'false'}","Specifies whether to add HVDC link projects from the `TYNDP 2018 <https://tyndp.entsoe.eu/tyndp2018/projects/>`_ 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."
--- a/doc/configtables/plotting.csv
+++ b/doc/configtables/plotting.csv
@ -1,10 +1,10 @@
 ,Unit,Values,Description
 map,,,
-- boundaries,°,"[x1,x2,y1,y2]","Boundaries of the map plots in degrees latitude (y) and longitude (x)"
+-- 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_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."
+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_max,TWh,float,Upper y-axis limit in energy bar plots.
-energy_min,TWh,float,"Lower 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."
+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 <https://en.wikipedia.org/wiki/Web_colors#Hex_triplet>`_)."
+tech_colors,--,carrier -> HEX colour code,Mapping from network ``carrier`` to a colour (`HEX colour code <https://en.wikipedia.org/wiki/Web_colors#Hex_triplet>`_).
-nice_names,--,"str -> str","Mapping from network ``carrier`` to a more readable name."
+nice_names,--,str -> str,Mapping from network ``carrier`` to a more readable name.
--- a/doc/configtables/sector-opts.csv
+++ b/doc/configtables/sector-opts.csv
@ -1,5 +1,5 @@
 Trigger, Description, Definition, Status
-``nH``, i.e. ``2H``-``6H``, Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L110>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L146>`__), In active use
+``nH``, i.e. ``2H``-``6H``, "Resample the time-resolution by averaging over every ``n`` snapshots, ``prepare_network``: `average_every_nhours() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L110>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L146>`__)", In active use
 ``Co2L``, Add an overall absolute carbon-dioxide emissions limit configured in ``electricity: co2limit``. If a float is appended an overall emission limit relative to the emission level given in ``electricity: co2base`` is added (e.g. ``Co2L0.05`` limits emissisions to 5% of what is given in ``electricity: co2base``), ``prepare_network``: `add_co2limit() <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L19>`_ and its `caller <https://github.com/PyPSA/pypsa-eur/blob/6b964540ed39d44079cdabddee8333f486d0cd63/scripts/prepare_network.py#L154>`__, In active use
 ``carrier+{c|p|m}factor``,"Alter the capital cost (``c``), installable potential (``p``) or marginal costs (``m``) of a carrier by a factor. Example: ``solar+c0.5`` reduces the capital cost of solar to 50\% of original values.", ``prepare_network``, In active use
 ``T``,Add land transport sector,,In active use
--- a/doc/configtables/sector.csv
+++ b/doc/configtables/sector.csv
@ -0,0 +1,122 @@
 ,Unit,Values,Description
 district_heating,--,,`prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/prepare_sector_network.py>`_
 -- potential,--,float,maximum fraction of urban demand which can be supplied by district heating
 -- progress,--,Dictionary with planning horizons as keys., Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating
 -- district_heating_loss,--,float,Share increase in district heat demand in urban central due to heat losses
 cluster_heat_buses,--,"{true, false}",Cluster residential and service heat buses in `prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/prepare_sector_network.py>`_  to one to save memory.
 ,,,
 bev_dsm_restriction _value,--,float,Adds a lower state of charge (SOC) limit for battery electric vehicles (BEV) to manage its own energy demand (DSM). Located in `build_transport_demand.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_transport_demand.py>`_. Set to 0 for no restriction on BEV DSM
 bev_dsm_restriction _time,--,float,Time at which SOC of BEV has to be dsm_restriction_value
 transport_heating _deadband_upper,°C,float,"The maximum temperature in the vehicle. At higher temperatures, the energy required for cooling in the vehicle increases."
 transport_heating _deadband_lower,°C,float,"The minimum temperature in the vehicle. At lower temperatures, the energy required for heating in the vehicle increases."
 ,,,
 ICE_lower_degree_factor,--,float,Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the cold environment and the minimum temperature.
 ICE_upper_degree_factor,--,float,Share increase in energy demand in internal combustion engine (ICE) for each degree difference between the hot environment and the maximum temperature.
 EV_lower_degree_factor,--,float,Share increase in energy demand in electric vehicles (EV) for each degree difference between the cold environment and the minimum temperature.
 EV_upper_degree_factor,--,float,Share increase in energy demand in electric vehicles (EV) for each degree difference between the hot environment and the maximum temperature.
 bev_dsm,--,"{true, false}",Add the option for battery electric vehicles (BEV) to participate in demand-side management (DSM)
 ,,,
 bev_availability,--,float,The share for battery electric vehicles (BEV) that are able to do demand side management (DSM)
 bev_energy,--,float,The average size of battery electric vehicles (BEV) in MWh
 bev_charge_efficiency,--,float,Battery electric vehicles (BEV) charge and discharge efficiency
 bev_plug_to_wheel _efficiency,km/kWh,float,The distance battery electric vehicles (BEV) can travel in km per kWh of energy charge in battery.  Base value comes from `Tesla Model S <https://www.fueleconomy.gov/feg/>`_
 bev_charge_rate,MWh,float,The power consumption for one electric vehicle (EV) in MWh. Value derived from 3-phase charger with 11 kW.
 bev_avail_max,--,float,The maximum share plugged-in availability for passenger electric vehicles.
 bev_avail_mean,--,float,The average share plugged-in availability for passenger electric vehicles.
 v2g,--,"{true, false}",Allows feed-in to grid from EV battery
 land_transport_fuel_cell _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses fuel cells in a given year
 land_transport_electric _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses electric vehicles (EV) in a given year
 land_transport_ice _share,--,Dictionary with planning horizons as keys.,The share of vehicles that uses internal combustion engines (ICE) in a given year. What is not EV or FCEV is oil-fuelled ICE.
 transport_fuel_cell _efficiency,--,float,The H2 conversion efficiencies of fuel cells in transport
 transport_internal _combustion_efficiency,--,float,The oil conversion efficiencies of internal combustion engine (ICE) in transport
 agriculture_machinery _electric_share,--,float,The share for agricultural machinery that uses electricity
 agriculture_machinery _oil_share,--,float,The share for agricultural machinery that uses oil
 agriculture_machinery _fuel_efficiency,--,float,The efficiency of electric-powered machinery in the conversion of electricity to meet agricultural needs.
 agriculture_machinery _electric_efficiency,--,float,The efficiency of oil-powered machinery in the conversion of oil to meet agricultural needs.
 Mwh_MeOH_per_MWh_H2,LHV,float,"The energy amount of the produced methanol per energy amount of hydrogen. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 64."
 MWh_MeOH_per_tCO2,LHV,float,"The energy amount of the produced methanol per ton of CO2. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 64."
 MWh_MeOH_per_MWh_e,LHV,float,"The energy amount of the produced methanol per energy amount of electricity. From `DECHEMA (2017) <https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf>`_, page 64."
 shipping_hydrogen _liquefaction,--,"{true, false}",Whether to include liquefaction costs for hydrogen demand in shipping.
 ,,,
 shipping_hydrogen_share,--,Dictionary with planning horizons as keys.,The share of ships powered by hydrogen in a given year
 shipping_methanol_share,--,Dictionary with planning horizons as keys.,The share of ships powered by methanol in a given year
 shipping_oil_share,--,Dictionary with planning horizons as keys.,The share of ships powered by oil in a given year
 shipping_methanol _efficiency,--,float,The efficiency of methanol-powered ships in the conversion of methanol to meet shipping needs (propulsion). The efficiency increase from oil can be 10-15% higher according to the `IEA <https://www.iea-amf.org/app/webroot/files/file/Annex%20Reports/AMF_Annex_56.pdf>`_
 ,,,
 shipping_oil_efficiency,--,float,The efficiency of oil-powered ships in the conversion of oil to meet shipping needs (propulsion). Base value derived from 2011
 aviation_demand_factor,--,float,The proportion of demand for aviation compared to today's consumption
 HVC_demand_factor,--,float,The proportion of demand for high-value chemicals compared to today's consumption
 ,,,
 time_dep_hp_cop,--,"{true, false}",Consider the time dependent coefficient of performance (COP) of the heat pump
 heat_pump_sink_T,°C,float,The temperature heat sink used in heat pumps based on DTU / large area radiators. The value is conservatively high to cover hot water and space heating in poorly-insulated buildings
 reduce_space_heat _exogenously,--,"{true, false}",Influence on space heating demand by a certain factor (applied before losses in district heating).
 reduce_space_heat _exogenously_factor,--,Dictionary with planning horizons as keys.,"A positive factor can mean renovation or demolition of a building. If the factor is negative, it can mean an increase in floor area, increased thermal comfort, population growth. The default factors are determined by the `Eurocalc Homes and buildings decarbonization scenario <http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221>`_"
 retrofitting,,,
 -- retro_endogen,--,"{true, false}",Add retrofitting as an endogenous system which co-optimise space heat savings.
 -- cost_factor,--,float,Weight costs for building renovation
 -- interest_rate,--,float,The interest rate for investment in building components
 -- annualise_cost,--,"{true, false}",Annualise the investment costs of retrofitting
 -- tax_weighting,--,"{true, false}",Weight the costs of retrofitting depending on taxes in countries
 -- construction_index,--,"{true, false}",Weight the costs of retrofitting depending on labour/material costs per country
 tes,--,"{true, false}",Add option for storing thermal energy in large water pits associated with district heating systems and individual thermal energy storage (TES)
 tes_tau,,,The time constant used to calculate the decay of thermal energy in thermal energy storage (TES): 1- :math:`e^{-1/24τ}`.
 -- decentral,days,float,The time constant in decentralized thermal energy storage (TES)
 -- central,days,float,The time constant in centralized thermal energy storage (TES)
 boilers,--,"{true, false}",Add option for transforming electricity into heat using resistive heater
 oil_boilers,--,"{true, false}",Add option for transforming oil into heat using boilers
 biomass_boiler,--,"{true, false}",Add option for transforming biomass into heat using boilers
 chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP)
 micro_chp,--,"{true, false}",Add option for using Combined Heat and Power (CHP) for decentral areas.
 solar_thermal,--,"{true, false}",Add option for using solar thermal to generate heat.
 solar_cf_correction,--,float,The correction factor for the value provided by the solar thermal profile calculations
 marginal_cost_storage,currency/MWh ,float,The marginal cost of discharging batteries in distributed grids
 methanation,--,"{true, false}",Add option for transforming hydrogen and CO2 into methane using methanation.
 helmeth,--,"{true, false}",Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion)
 coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture
 dac,--,"{true, false}",Add option for Direct Air Capture (DAC)
 co2_vent,--,"{true, false}",Add option for vent out CO2 from storages to the atmosphere.
 allam_cycle,--,"{true, false}",Add option to include `Allam cycle gas power plants <https://en.wikipedia.org/wiki/Allam_power_cycle>`_
 hydrogen_fuel_cell,--,"{true, false}",Add option to include hydrogen fuel cell for re-electrification. Assuming OCGT technology costs
 hydrogen_turbine,--,"{true, false}",Add option to include hydrogen turbine for re-electrification. Assuming OCGT technology costs
 SMR,--,"{true, false}",Add option for transforming natural gas into hydrogen and CO2 using Steam Methane Reforming (SMR)
 regional_co2 _sequestration_potential,,,
 -- enable,--,"{true, false}",Add option for regionally-resolved geological carbon dioxide sequestration potentials based on `CO2StoP <https://setis.ec.europa.eu/european-co2-storage-database_en>`_.
 -- attribute,--,string,Name of the attribute for the sequestration potential
 -- include_onshore,--,"{true, false}",Add options for including onshore sequestration potentials
 -- min_size,Gt ,float,Any sites with lower potential than this value will be excluded
 -- max_size,Gt ,float,The maximum sequestration potential for any one site.
 -- years_of_storage,years,float,The years until potential exhausted at optimised annual rate
 co2_sequestration_potential,MtCO2/a,float,The potential of sequestering CO2 in Europe per year
 co2_sequestration_cost,currency/tCO2,float,The cost of sequestering a ton of CO2
 co2_spatial,--,"{true, false}","Add option to spatially resolve carrier representing stored carbon dioxide. This allows for more detailed modelling of CCUTS, e.g. regarding the capturing of industrial process emissions, usage as feedstock for electrofuels, transport of carbon dioxide, and geological sequestration sites."
 ,,,
 co2network,--,"{true, false}",Add option for planning a new carbon dioxide transmission network
 ,,,
 cc_fraction,--,float,The default fraction of CO2 captured with post-combustion capture
 hydrogen_underground _storage,--,"{true, false}",Add options for storing hydrogen underground. Storage potential depends regionally.
 hydrogen_underground _storage_locations,,"{onshore, nearshore, offshore}","The location where hydrogen underground storage can be located. Onshore, nearshore, offshore means it must be located more than 50 km away from the sea, within 50 km of the sea, or within the sea itself respectively."
 ,,,
 ammonia,--,"{true, false, regional}","Add ammonia as a carrrier. It can be either true (copperplated NH3), false (no NH3 carrier) or ""regional"" (regionalised NH3 without network)"
 min_part_load_fischer _tropsch,per unit of p_nom ,float,The minimum unit dispatch (``p_min_pu``) for the Fischer-Tropsch process
 min_part_load _methanolisation,per unit of p_nom ,float,The minimum unit dispatch (``p_min_pu``) for the methanolisation process
 ,,,
 use_fischer_tropsch _waste_heat,--,"{true, false}",Add option for using waste heat of Fischer Tropsch in district heating networks
 use_fuel_cell_waste_heat,--,"{true, false}",Add option for using waste heat of fuel cells in district heating networks
 use_electrolysis_waste _heat,--,"{true, false}",Add option for using waste heat of electrolysis in district heating networks
 electricity_distribution _grid,--,"{true, false}",Add a simplified representation of the exchange capacity between transmission and distribution grid level through a link.
 electricity_distribution _grid_cost_factor,,,Multiplies the investment cost of the electricity distribution grid
 ,,,
 electricity_grid _connection,--,"{true, false}",Add the cost of electricity grid connection for onshore wind and solar
 H2_network,--,"{true, false}",Add option for new hydrogen pipelines
 gas_network,--,"{true, false}","Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted `k-edge augmentation algorithm   <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>`_   can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well."
 H2_retrofit,--,"{true, false}",Add option for retrofiting existing pipelines to transport hydrogen.
 H2_retrofit_capacity _per_CH4,--,float,"The ratio for H2 capacity per original CH4 capacity of retrofitted pipelines. The `European Hydrogen Backbone (April, 2020) p.15 <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."
 gas_network_connectivity _upgrade ,--,float,The number of desired edge connectivity (k) in the length-weighted `k-edge augmentation algorithm <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>`_ used for the gas network
 gas_distribution_grid,--,"{true, false}",Add a gas distribution grid
 gas_distribution_grid _cost_factor,,,Multiplier for the investment cost of the gas distribution grid
 ,,,
 biomass_spatial,--,"{true, false}",Add option for resolving biomass demand regionally
 biomass_transport,--,"{true, false}",Add option for transporting solid biomass between nodes
 conventional_generation,,,Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel.
 biomass_to_liquid,--,"{true, false}",Add option for transforming solid biomass into liquid fuel with the same properties as oil
 biosng,--,"{true, false}",Add option for transforming solid biomass into synthesis gas with the same properties as natural gas
--- a/doc/configtables/solar-thermal.csv
+++ b/doc/configtables/solar-thermal.csv
@ -0,0 +1,6 @@
 ,Unit,Values,Description
 clearsky_model ,--,"{‘simple’, ‘enhanced’}",Type of clearsky model for diffuse irradiation
 orientation ,--,"{units of degrees, ‘latitude_optimal’}",Panel orientation with slope and azimuth
 -- azimuth,float,units of degrees,The angle between the North and the sun with panels on the local horizon
 -- slope,float,units of degrees,The angle between the ground and the panels
--- a/doc/configtables/solving.csv
+++ b/doc/configtables/solving.csv
@ -1,7 +1,7 @@
 ,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 <https://arxiv.org/abs/1704.01881>`_."
 -- load_shedding,bool/float,"{'true','false', float}","Add generators with very high marginal cost to simulate load shedding and avoid problem infeasibilities. If load shedding is a float, it denotes the marginal cost in EUR/kWh."
 -- transmission_losses,int,"[0-9]","Add piecewise linear approximation of transmission losses based on n tangents. Defaults to 0, which means losses are ignored."
 -- noisy_costs,bool,"{'true','false'}","Add random noise to marginal cost of generators by :math:`\mathcal{U}(0.009,0,011)` and capital cost of lines and links by :math:`\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."
--- a/doc/configtables/toplevel.csv
+++ b/doc/configtables/toplevel.csv
@ -4,6 +4,7 @@ tutorial,bool,"{true, false}","Switch to retrieve the tutorial data set instead
 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 <https://docs.python.org/3/library/logging.html#logging.LogRecord>`_ attributes."
 <<<<<<< HEAD
 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) <https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2>`_ 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``."
@ -20,3 +21,5 @@ enable,,,
 =======
 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"
 >>>>>>> master
 =======
 >>>>>>> origin/master
--- a/doc/configuration.rst
+++ b/doc/configuration.rst
@ -18,15 +18,16 @@ Top-level configuration
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
-   :lines: 5-11,18-19,62,80-90
+   :start-at: version:
   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/toplevel.csv
-.. _scenario:
+.. _run_cf:
 ``run``
 =======
@ -40,13 +41,34 @@ The ``run`` section is used for running and storing scenarios with different con
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: run:
-   :end-before: foresight:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/run.csv
 .. _foresight_cf:
 ``foresight``
 =============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: foresight:
   :end-at: foresight:
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/foresight.csv
 .. note::
    If you use myopic or perfect foresight, the planning horizon in
    :ref:`planning_horizons` in scenario has to be set.
 .. _scenario:
 ``scenario``
 ============
@ -83,13 +105,28 @@ An exemplary dependency graph (starting from the simplification rules) then look
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: scenario:
-   :end-before: countries:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/scenario.csv
 .. _countries:
 ``countries``
 =============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: countries:
   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/countries.csv
 .. _snapshots_cf:
 ``snapshots``
@ -100,11 +137,11 @@ Specifies the temporal range to build an energy system model for as arguments to
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: snapshots:
-   :end-before: enable:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/snapshots.csv
 .. _enable_cf:
@ -117,13 +154,32 @@ Switches for some rules and optional features.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: enable:
-   :end-before: co2_budget:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/enable.csv
 .. _CO2_budget_cf:
 ``co2 budget``
 ==============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: co2_budget:
   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/co2_budget.csv
 .. note::
    this parameter is over-ridden if ``CO2Lx`` or ``cb`` is set in
    sector_opts.
 .. _electricity_cf:
 ``electricity``
@ -132,11 +188,11 @@ Switches for some rules and optional features.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: electricity:
-   :end-before: atlite:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/electricity.csv
 .. _atlite_cf:
@ -149,11 +205,11 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: atlite:
-   :end-before: renewable:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/atlite.csv
 .. _renewable_cf:
@ -171,9 +227,18 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/onwind.csv
 .. note::
   Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 30% fraction of the already restricted
   area is available for installation of wind generators due to competing land use and likely public
   acceptance issues.
 .. note::
   The default choice for corine ``grid_codes`` was based on Scholz, Y. (2012). Renewable energy based electricity supply at low costs
   development of the REMix model and application for Europe. ( p.42 / p.28)
 ``offwind-ac``
 --------------
@ -184,9 +249,19 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/offwind-ac.csv
 .. note::
   Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 10MW/km^2 and assuming 20% fraction of the already restricted
   area is available for installation of wind generators due to competing land use and likely public
   acceptance issues.
 .. note::
   Notes on ``correction_factor``. Correction due to proxy for wake losses
   from 10.1016/j.energy.2018.08.153
   until done more rigorously in #153
 ``offwind-dc``
 ---------------
@ -197,9 +272,13 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/offwind-dc.csv
 .. note::
   both ``offwind-ac`` and ``offwind-dc`` have the same assumption on
   ``capacity_per_sqkm`` and ``correction_factor``.
 ``solar``
 ---------------
@ -210,20 +289,29 @@ Define and specify the ``atlite.Cutout`` used for calculating renewable potentia
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/solar.csv
 .. note::
   Notes on ``capacity_per_sqkm``. ScholzPhd Tab 4.3.1: 170 MW/km^2 and assuming 1% of the area can be used for solar PV panels.
   Correction factor determined by comparing uncorrected area-weighted full-load hours to those
   published in Supplementary Data to Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power
   sector -- The economic potential of photovoltaics and concentrating solar
   power." Applied Energy 135 (2014): 704-720.
   This correction factor of 0.854337 may be in order if using reanalysis data.
   for discussion refer to this <issue https://github.com/PyPSA/pypsa-eur/issues/285>
 ``hydro``
 ---------------
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at:   hydro:
-   :end-before: conventional:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/hydro.csv
 .. _lines_cf:
@ -241,11 +329,11 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at:   conventional:
-   :end-before: lines:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/conventional.csv
 ``lines``
@ -254,11 +342,11 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: lines:
-   :end-before: links:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/lines.csv
 .. _links_cf:
@ -269,11 +357,11 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: links:
-   :end-before: transformers:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/links.csv
 .. _transformers_cf:
@ -284,11 +372,11 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: transformers:
-   :end-before: load:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/transformers.csv
 .. _load_cf:
@ -299,45 +387,13 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-after:   type:
-   :end-at:   scaling_factor:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/load.csv
 .. _costs_cf:
 ``costs``
 =============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: costs:
   :end-before: clustering:
 .. csv-table::
   :header-rows: 1
   :widths: 25,7,22,30
   :file: configtables/costs.csv
 .. _clustering_cf:
 ``clustering``
 ==============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: clustering:
   :end-before: solving:
 .. csv-table::
   :header-rows: 1
   :widths: 25,7,22,30
   :file: configtables/clustering.csv
 .. _energy_cf:
 ``energy``
@ -346,14 +402,15 @@ overwrite the existing values.
 .. note::
   Only used for sector-coupling studies.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: energy:
-   :end-before: biomass:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/energy.csv
 .. _biomass_cf:
@ -363,13 +420,35 @@ overwrite the existing values.
 .. note::
   Only used for sector-coupling studies.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: biomass:
-   :end-before: solar_thermal:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/biomass.csv
 The list of available biomass is given by the category in `ENSPRESO_BIOMASS <https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx>`_, namely:
 - Agricultural waste
 - Manure solid, liquid
 - Residues from landscape care
 - Bioethanol barley, wheat, grain maize, oats, other cereals and rye
 - Sugar from sugar beet
 - Miscanthus, switchgrass, RCG
 - Willow
 - Poplar
 - Sunflower, soya seed
 - Rape seed
 - Fuelwood residues
 - FuelwoodRW
 - C&P_RW
 - Secondary Forestry residues - woodchips
 - Sawdust
 - Municipal waste
 - Sludge
 .. _solar_thermal_cf:
@ -379,13 +458,15 @@ overwrite the existing values.
 .. note::
   Only used for sector-coupling studies.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: solar_thermal:
-   :end-before: existing_capacities:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/solar-thermal.csv
 .. _existing_capacities_cf:
@ -393,15 +474,17 @@ overwrite the existing values.
 =======================
 .. note::
-   Only used for sector-coupling studies.
+   Only used for sector-coupling studies. The value for grouping years are only used in myopic or perfect foresight scenarios.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: existing_capacities:
-   :end-before: sector:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/existing_capacities.csv
 .. _sector_cf:
@ -411,13 +494,15 @@ overwrite the existing values.
 .. note::
   Only used for sector-coupling studies.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: sector:
-   :end-before: industry:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/sector.csv
 .. _industry_cf:
@ -427,13 +512,57 @@ overwrite the existing values.
 .. note::
   Only used for sector-coupling studies.
 .. warning::
   More comprehensive documentation for this segment will be released soon.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: industry:
-   :end-before: costs:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/industry.csv
 .. _costs_cf:
 ``costs``
 =============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: costs:
   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/costs.csv
 .. note::
   ``rooftop_share:`` are based on the potentials, assuming
   (0.1 kW/m2 and 10 m2/person)
 .. _clustering_cf:
 ``clustering``
 ==============
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: clustering:
   :end-before: # docs
 .. csv-table::
   :header-rows: 1
   :widths: 22,7,22,33
   :file: configtables/clustering.csv
 .. note::
   ``feature:`` in ``simplify_network:``
   are only relevant if ``hac`` were chosen in ``algorithm``.
 .. tip::
   use ``min`` in ``p_nom_max:`` for more `
   conservative assumptions.
 .. _solving_cf:
@ -443,16 +572,11 @@ overwrite the existing values.
 .. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: solving:
-   :end-before: plotting:
+   :end-before: # docs
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/solving.csv
 .. csv-table::
   :header-rows: 1
   :widths: 25,7,22,30
   :file: configtables/solving.csv
 .. _plotting_cf:
@ -469,5 +593,5 @@ overwrite the existing values.
 .. csv-table::
   :header-rows: 1
-   :widths: 25,7,22,30
+   :widths: 22,7,22,33
   :file: configtables/plotting.csv
--- a/doc/costs.rst
+++ b/doc/costs.rst
@ -12,7 +12,7 @@ The database of cost assumptions is retrieved from the repository
 saved to a file ``data/costs_{year}.csv``. The ``config/config.yaml`` provides options
 to choose a reference year and use a specific version of the repository.
-.. literalinclude:: ../config.default.yaml
+.. literalinclude:: ../config/config.default.yaml
   :language: yaml
   :start-at: costs:
   :end-at:   version:
--- a/doc/foresight.rst
+++ b/doc/foresight.rst
@ -87,8 +87,12 @@ evolve with the myopic approach:
  vehicle-to-grid services.
 - The annual biomass potential (default year and scenario for which potential is
-  taken is 2030, defined `here
+  taken is 2030, as defined in config)
-  <https://github.com/PyPSA/pypsa-eur-sec/blob/413254e241fb37f55b41caba7264644805ad8e97/config.default.yaml#L109>`_)
+
 .. literalinclude:: ../config/test/config.myopic.yaml
   :language: yaml
   :start-at: biomass:
   :end-at: year:
 Configuration
@ -108,7 +112,7 @@ optimized. For a myopic optimization, this is equivalent to the investment year.
 To set the investment years which are sequentially simulated for the myopic
 investment planning, select for example:
-.. literalinclude:: ../test/config.myopic.yaml
+.. literalinclude:: ../config/test/config.myopic.yaml
   :language: yaml
   :start-at:   planning_horizons:
   :end-before: countries:
@ -203,6 +207,7 @@ The myopic code solves the network for the time steps included in
   network comprises additional generator, storage, and link capacities with
   p_nom_extendable=True. The non-solved network is saved in
   ``results/run_name/networks/prenetworks-brownfield``.
 The base year is the first element in ``planning_horizons``. Step 1 is
 implemented with the rule add_baseyear for the base year and with the rule
 add_brownfield for the remaining planning_horizons.
--- a/doc/index.rst
+++ b/doc/index.rst
@ -31,7 +31,9 @@ PyPSA-Eur: A Sector-Coupled Open Optimisation Model of the European Energy Syste
    :target: https://api.reuse.software/info/github.com/pypsa/pypsa-eur
    :alt: REUSE
-|
+.. image:: https://img.shields.io/stackexchange/stackoverflow/t/pypsa
   :target: https://stackoverflow.com/questions/tagged/pypsa
   :alt: Stackoverflow
 PyPSA-Eur is an open model dataset of the European energy system at the
 transmission network level that covers the full ENTSO-E area. It covers demand
@ -222,7 +224,10 @@ The included ``.nc`` files are PyPSA network files which can be imported with Py
    n = pypsa.Network(filename)
 Operating Systems
 =================
 The PyPSA-Eur workflow is continuously tested for Linux, macOS and Windows (WSL only).
 .. toctree::
@ -274,4 +279,5 @@ The included ``.nc`` files are PyPSA network files which can be imported with Py
   licenses
   limitations
   contributing
   support
   publications
--- a/doc/preparation.rst
+++ b/doc/preparation.rst
@ -89,7 +89,7 @@ Rule ``build_powerplants``
 .. _electricity_demand:
 Rule ``build_electricity_demand``
-=============================
+==================================
 .. automodule:: build_electricity_demand
--- a/doc/release_notes.rst
+++ b/doc/release_notes.rst
@ -10,19 +10,45 @@ Release Notes
 Upcoming Release
 ================
 * ``param:`` section in rule definition are added to track changed settings in ``config.yaml``. The goal is to automatically re-execute rules whose parameters have changed. See `Non-file parameters for rules <https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html#non-file-parameters-for-rules>`_ in the snakemake documentation.
 * **Important:** The configuration files are now located in the ``config`` directory. This counts for ``config.default.yaml``, ``config.yaml`` as well as the test configuration files which are now located in ``config/test``. Config files that are still in the root directory will be ignored.
 * Bugfix: Correct typo in the CPLEX solver configuration in ``config.default.yaml``.
 * Bugfix: Error in ``add_electricity`` where carriers were added multiple times to the network, resulting in a non-unique carriers error.
 * Renamed script file from PyPSA-EUR ``build_load_data`` to ``build_electricity_demand`` and ``retrieve_load_data`` to ``retrieve_electricity_demand``.
-
+* Fix docs readthedocs built
 * Add plain hydrogen turbine as additional re-electrification option besides
  hydrogen fuel cell. Add switches for both re-electrification options under
  ``sector: hydrogen_turbine:`` and ``sector: hydrogen_fuel_cell:``.
 * A new function named ``sanitize_carrier`` ensures that all unique carrier names are present in the network's carriers attribute, and adds nice names and colors for each carrier according to the provided configuration dictionary.
 * Additional tech_color are added to include previously unlisted carriers.
 * Remove ``vresutils`` dependency.
 * Added configuration option ``lines: max_extension:`` and ``links:
  max_extension:``` to control the maximum capacity addition per line or link in
  MW.
 * Add option to include a piecewise linear approximation of transmission losses,
  e.g. by setting ``solving: options: transmission_losses: 2`` for an
  approximation with two tangents.
 * Handling networks with links with multiple inputs/outputs no longer requires
  to override component attributes.
 * Added configuration option ``enable: retrieve:`` to control whether data
  retrieval rules from snakemake are enabled or not. Th default setting ``auto``
  will automatically detect and enable/disable the rules based on internet connectivity.
 PyPSA-Eur 0.8.0 (18th March 2023)
 =================================
--- a/doc/requirements.txt
+++ b/doc/requirements.txt
@ -2,12 +2,13 @@
 #
 # SPDX-License-Identifier: CC0-1.0
 setuptools
 sphinx
 sphinx_book_theme
 sphinxcontrib-bibtex
 myst-parser  # recommark is deprecated, https://stackoverflow.com/a/71660856/13573820
 pypsa
 vresutils>=0.3.1
 powerplantmatching>=0.5.5
 atlite>=0.2.9
 dask[distributed]
--- a/doc/supply_demand.rst
+++ b/doc/supply_demand.rst
@ -133,12 +133,12 @@ The coefficient of performance (COP) of air- and ground-sourced heat pumps depen
 For the sink water temperature Tsink we assume 55 °C [`Config <https://github.com/PyPSA/pypsa-eur-sec/blob/3daff49c9999ba7ca7534df4e587e1d516044fc3/config.default.yaml#L207>`_ file]. For the time- and location-dependent source temperatures Tsource, we rely on the `ERA5 <https://doi.org/10.1002/qj.3803>`_ reanalysis weather data. The temperature differences are converted into COP time series using results from a regression analysis performed in the study by `Stafell et al. <https://pubs.rsc.org/en/content/articlelanding/2012/EE/c2ee22653g>`_. For air-sourced heat pumps (ASHP), we use the function:
 .. math::
-   COP (\Delta T) = 6.81 + 0.121\Delta T + 0.000630\Delta T^2
+   COP (\Delta T) = 6.81 - 0.121\Delta T + 0.000630\Delta T^2
 for ground-sourced heat pumps (GSHP), we use the function:
 .. math::
-   COP(\Delta T) = 8.77 + 0.150\Delta T + 0.000734\Delta T^2
+   COP(\Delta T) = 8.77 - 0.150\Delta T + 0.000734\Delta T^2
 **Resistive heaters**
--- a/doc/support.rst
+++ b/doc/support.rst
@ -0,0 +1,14 @@
 ..
  SPDX-FileCopyrightText: 2019-2023 The PyPSA-Eur Authors
  SPDX-License-Identifier: CC-BY-4.0
 #######################
 Support
 #######################
 * In case of code-related **questions**, please post on `stack overflow <https://stackoverflow.com/questions/tagged/pypsa>`_.
 * For non-programming related and more general questions please refer to the `mailing list <https://groups.google.com/group/pypsa>`_.
 * To **discuss** with other PyPSA users, organise projects, share news, and get in touch with the community you can use the `discord server <https://discord.gg/AnuJBk23FU>`_.
 * For **bugs and feature requests**, please use the `issue tracker <https://github.com/PyPSA/pypsa-eur/issues>`_.
 * We strongly welcome anyone interested in providing **contributions** to this project. If you have any ideas, suggestions or encounter problems, feel invited to file issues or make pull requests on `Github <https://github.com/PyPSA/PyPSA>`_. For further information on how to contribute, please refer to :ref:`contributing`.
--- a/doc/tutorial.rst
+++ b/doc/tutorial.rst
@ -32,7 +32,7 @@ configuration, execute
 .. code:: bash
    :class: full-width
-    snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile test/config.electricity.yaml
+    snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile config/test/config.electricity.yaml
 This configuration is set to download a reduced data set via the rules :mod:`retrieve_databundle`,
 :mod:`retrieve_natura_raster`, :mod:`retrieve_cutout`.
@ -43,21 +43,21 @@ How to configure runs?
 The model can be adapted to only include selected countries (e.g. Belgium) instead of all European countries to limit the spatial scope.
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: countries:
   :end-before: snapshots:
 Likewise, the example's temporal scope can be restricted (e.g. to a single week).
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: snapshots:
   :end-before: electricity:
 It is also possible to allow less or more carbon-dioxide emissions. Here, we limit the emissions of Belgium to 100 Mt per year.
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: electricity:
   :end-before: extendable_carriers:
@ -65,7 +65,7 @@ It is also possible to allow less or more carbon-dioxide emissions. Here, we lim
 PyPSA-Eur also includes a database of existing conventional powerplants.
 We can select which types of existing powerplants we like to be extendable:
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: extendable_carriers:
   :end-before: renewable_carriers:
@ -74,7 +74,7 @@ To accurately model the temporal and spatial availability of renewables such as
 wind and solar energy, we rely on historical weather data. It is advisable to
 adapt the required range of coordinates to the selection of countries.
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: atlite:
   :end-before: renewable:
@ -83,7 +83,7 @@ We can also decide which weather data source should be used to calculate
 potentials and capacity factor time-series for each carrier. For example, we may
 want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: solar:
   :end-at: cutout:
@ -91,7 +91,7 @@ want to use the ERA-5 dataset for solar and not the default SARAH-2 dataset.
 Finally, it is possible to pick a solver. For instance, this tutorial uses the
 open-source solver GLPK.
-.. literalinclude:: ../test/config.electricity.yaml
+.. literalinclude:: ../config/test/config.electricity.yaml
   :language: yaml
   :start-at: solver:
   :end-before: plotting:
@ -115,7 +115,7 @@ clustered down to 6 buses and every 24 hours aggregated to one snapshot. The com
 .. code:: bash
-    snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile test/config.electricity.yaml
+    snakemake -call results/test-elec/networks/elec_s_6_ec_lcopt_Co2L-24H.nc --configfile config/test/config.electricity.yaml
 orders ``snakemake`` to run the rule :mod:`solve_network` that produces the solved network and stores it in ``results/networks`` with the name ``elec_s_6_ec_lcopt_Co2L-24H.nc``:
@ -288,18 +288,18 @@ You can produce any output file occurring in the ``Snakefile`` by running
 For example, you can explore the evolution of the PyPSA networks by running
-#. ``snakemake resources/networks/base.nc -call --configfile test/config.electricity.yaml``
+#. ``snakemake resources/networks/base.nc -call --configfile config/test/config.electricity.yaml``
-#. ``snakemake resources/networks/elec.nc -call --configfile test/config.electricity.yaml``
+#. ``snakemake resources/networks/elec.nc -call --configfile config/test/config.electricity.yaml``
-#. ``snakemake resources/networks/elec_s.nc -call --configfile test/config.electricity.yaml``
+#. ``snakemake resources/networks/elec_s.nc -call --configfile config/test/config.electricity.yaml``
-#. ``snakemake resources/networks/elec_s_6.nc -call --configfile test/config.electricity.yaml``
+#. ``snakemake resources/networks/elec_s_6.nc -call --configfile config/test/config.electricity.yaml``
-#. ``snakemake resources/networks/elec_s_6_ec_lcopt_Co2L-24H.nc -call --configfile test/config.electricity.yaml``
+#. ``snakemake resources/networks/elec_s_6_ec_lcopt_Co2L-24H.nc -call --configfile config/test/config.electricity.yaml``
 To run all combinations of wildcard values provided in the ``config/config.yaml`` under ``scenario:``,
 you can use the collection rule ``solve_elec_networks``.
 .. code:: bash
-    snakemake -call solve_elec_networks --configfile test/config.electricity.yaml
+    snakemake -call solve_elec_networks --configfile config/test/config.electricity.yaml
 If you now feel confident and want to tackle runs with larger temporal and
 spatial scope, clean-up the repository and after modifying the ``config/config.yaml`` file
--- a/doc/tutorial_sector.rst
+++ b/doc/tutorial_sector.rst
@ -35,7 +35,7 @@ configuration options. In the example below, we say that the gas network should
 be added and spatially resolved. We also say that the existing gas network may
 be retrofitted to transport hydrogen instead.
-.. literalinclude:: ../test/config.overnight.yaml
+.. literalinclude:: ../config/test/config.overnight.yaml
   :language: yaml
   :start-at: sector:
   :end-before: solving:
@ -45,7 +45,7 @@ Documentation for all options will be added successively to :ref:`config`.
 Scenarios can be defined like for electricity-only studies, but with additional
 wildcard options.
-.. literalinclude:: ../test/config.overnight.yaml
+.. literalinclude:: ../config/test/config.overnight.yaml
   :language: yaml
   :start-at: scenario:
   :end-before: countries:
@ -59,7 +59,7 @@ To run an overnight / greenfiled scenario with the specifications above, run
 .. code:: bash
-    snakemake -call --configfile test/config.overnight.yaml all
+    snakemake -call --configfile config/test/config.overnight.yaml all
 which will result in the following *additional* jobs ``snakemake`` wants to run
 on top of those already included in the electricity-only tutorial:
@ -294,7 +294,7 @@ Scenarios can be defined like for electricity-only studies, but with additional
 wildcard options. For the myopic foresight mode, the ``{planning_horizons}`` wildcard
 defines the sequence of investment horizons.
-.. literalinclude:: ../test/config.myopic.yaml
+.. literalinclude:: ../config/test/config.myopic.yaml
   :language: yaml
   :start-at: scenario:
   :end-before: countries:
@ -304,7 +304,7 @@ For allowed wildcard values, refer to :ref:`wildcards`.
 In the myopic foresight mode, you can tweak for instance exogenously given transition paths, like the one for
 the share of primary steel production we change below:
-.. literalinclude:: ../test/config.myopic.yaml
+.. literalinclude:: ../config/test/config.myopic.yaml
   :language: yaml
   :start-at: industry:
   :end-before: solving:
@ -318,7 +318,7 @@ To run a myopic foresight scenario with the specifications above, run
 .. code:: bash
-    snakemake -call --configfile test/config.myopic.yaml all
+    snakemake -call --configfile config/test/config.myopic.yaml all
 which will result in the following *additional* jobs ``snakemake`` wants to run:
--- a/doc/wildcards.rst
+++ b/doc/wildcards.rst
@ -117,6 +117,23 @@ The ``{sector_opts}`` wildcard
 .. warning::
    More comprehensive documentation for this wildcard will be added soon.
    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
 The ``{sector_opts}`` wildcard is only used for sector-coupling studies.
--- a/envs/environment.fixed.yaml
+++ b/envs/environment.fixed.yaml
@ -226,7 +226,7 @@ dependencies:
 - nspr=4.35
 - nss=3.88
 - numexpr=2.8.3
- numpy=1.23.5
+- numpy=1.24
 - openjdk=17.0.3
 - openjpeg=2.5.0
 - openpyxl=3.1.0
@ -378,4 +378,3 @@ dependencies:
  - highspy==1.5.0.dev0
  - pybind11==2.10.3
  - tsam==2.2.2
  - vresutils==0.3.1
--- a/envs/environment.yaml
+++ b/envs/environment.yaml
@ -10,7 +10,6 @@ dependencies:
 - python>=3.8
 - pip
 - pypsa>=0.21.3
 - atlite>=0.2.9
 - dask
@ -25,7 +24,7 @@ dependencies:
 - pytables
 - lxml
 - powerplantmatching>=0.5.5
- numpy<1.24
+- numpy
 - pandas>=1.4
 - geopandas>=0.11.0
 - xarray
@ -55,5 +54,5 @@ dependencies:
 - rasterio!=1.2.10
 - pip:
  - vresutils>=0.3.1
  - tsam>=1.1.0
  - git+https://github.com/PyPSA/PyPSA.git@master
--- a/rules/build_electricity.smk
+++ b/rules/build_electricity.smk
@ -21,12 +21,16 @@ if config["enable"].get("prepare_links_p_nom", False):
 if config["enable"].get("retrieve_opsd_load_data", True):
    rule build_electricity_demand:
        params:
            snapshots=config["snapshots"],
            countries=config["countries"],
            load=config["load"],
        input:
            ancient("data/load_raw.csv"),
        output:
-            RESOURCES + "load{weather_year}.csv",
+            RESOURCES + "load.csv",
        log:
-            LOGS + "build_electricity_demand{weather_year}.log",
+            LOGS + "build_electricity_demand.log",
        resources:
            mem_mb=5000,
        conda:
@ -52,7 +56,12 @@ if config["enable"].get("retrieve_artificial_load_data", False):
            "../scripts/build_artificial_load_data.py"
 rule build_powerplants:
    params:
        powerplants_filter=config["electricity"]["powerplants_filter"],
        custom_powerplants=config["electricity"]["custom_powerplants"],
        countries=config["countries"],
    input:
        base_network=RESOURCES + "networks/base.nc",
        custom_powerplants="data/custom_powerplants.csv",
@ -70,6 +79,9 @@ rule build_powerplants:
 rule base_network:
    params:
        countries=config["countries"],
        snapshots=config["snapshots"],
    input:
        eg_buses="data/entsoegridkit/buses.csv",
        eg_lines="data/entsoegridkit/lines.csv",
@ -98,6 +110,8 @@ rule base_network:
 rule build_shapes:
    params:
        countries=config["countries"],
    input:
        naturalearth=ancient("data/bundle/naturalearth/ne_10m_admin_0_countries.shp"),
        eez=ancient("data/bundle/eez/World_EEZ_v8_2014.shp"),
@ -123,6 +137,8 @@ rule build_shapes:
 rule build_bus_regions:
    params:
        countries=config["countries"],
    input:
        country_shapes=RESOURCES + "country_shapes.geojson",
        offshore_shapes=RESOURCES + "offshore_shapes.geojson",
@ -146,6 +162,9 @@ if config["enable"].get("build_cutout", False):
    ruleorder: build_cutout_year > build_cutout
    rule build_cutout:
        params:
            snapshots=config["snapshots"],
            cutouts=config["atlite"]["cutouts"],
        input:
            regions_onshore=RESOURCES + "regions_onshore.geojson",
            regions_offshore=RESOURCES + "regions_offshore.geojson",
@ -224,6 +243,8 @@ rule build_ship_raster:
 rule build_renewable_profiles:
    params:
        renewable=config["renewable"],
    input:
        base_network=RESOURCES + "networks/base.nc",
        corine=ancient("data/bundle/corine/g250_clc06_V18_5.tif"),
@ -273,6 +294,9 @@ rule build_renewable_profiles:
 rule build_hydro_profile:
    params:
        hydro=config["renewable"]["hydro"],
        countries=config["countries"],
    input:
        country_shapes=RESOURCES + "country_shapes.geojson",
        eia_hydro_generation="data/eia_hydro_annual_generation.csv",
@ -293,6 +317,14 @@ rule build_hydro_profile:
 rule add_electricity:
    params:
        length_factor=config["lines"]["length_factor"],
        scaling_factor=config["load"]["scaling_factor"],
        countries=config["countries"],
        renewable=config["renewable"],
        electricity=config["electricity"],
        conventional=config.get("conventional", {}),
        costs=config["costs"],
    input:
        **{
            f"profile_{tech}": RESOURCES + f"profile{weather_year}_{tech}.nc"
@ -328,6 +360,15 @@ rule add_electricity:
 rule simplify_network:
    params:
        simplify_network=config["clustering"]["simplify_network"],
        aggregation_strategies=config["clustering"].get("aggregation_strategies", {}),
        focus_weights=config.get("focus_weights", None),
        renewable_carriers=config["electricity"]["renewable_carriers"],
        max_hours=config["electricity"]["max_hours"],
        length_factor=config["lines"]["length_factor"],
        p_max_pu=config["links"].get("p_max_pu", 1.0),
        costs=config["costs"],
    input:
        network=RESOURCES + "networks/elec{weather_year}.nc",
        tech_costs=COSTS,
@ -355,6 +396,16 @@ rule simplify_network:
 rule cluster_network:
    params:
        cluster_network=config["clustering"]["cluster_network"],
        aggregation_strategies=config["clustering"].get("aggregation_strategies", {}),
        custom_busmap=config["enable"].get("custom_busmap", False),
        focus_weights=config.get("focus_weights", None),
        renewable_carriers=config["electricity"]["renewable_carriers"],
        conventional_carriers=config["electricity"].get("conventional_carriers", []),
        max_hours=config["electricity"]["max_hours"],
        length_factor=config["lines"]["length_factor"],
        costs=config["costs"],
    input:
        network=RESOURCES + "networks/elec{weather_year}_s{simpl}.nc",
        regions_onshore=RESOURCES
@ -390,6 +441,10 @@ rule cluster_network:
 rule add_extra_components:
    params:
        extendable_carriers=config["electricity"]["extendable_carriers"],
        max_hours=config["electricity"]["max_hours"],
        costs=config["costs"],
    input:
        network=RESOURCES + "networks/elec{weather_year}_s{simpl}_{clusters}.nc",
        tech_costs=COSTS,
@ -409,6 +464,14 @@ rule add_extra_components:
 rule prepare_network:
    params:
        links=config["links"],
        lines=config["lines"],
        co2base=config["electricity"]["co2base"],
        co2limit=config["electricity"]["co2limit"],
        gaslimit=config["electricity"].get("gaslimit"),
        max_hours=config["electricity"]["max_hours"],
        costs=config["costs"],
    input:
        RESOURCES + "networks/elec{weather_year}_s{simpl}_{clusters}_ec.nc",
        tech_costs=COSTS,
--- a/rules/build_sector.smk
+++ b/rules/build_sector.smk
@ -140,6 +140,8 @@ if not (config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]):
 rule build_heat_demands:
    params:
        snapshots=config["snapshots"],
    input:
        pop_layout=RESOURCES + "pop_layout{weather_year}_{scope}.nc",
        regions_onshore=RESOURCES + "regions_onshore_elec{weather_year}_s{simpl}_{clusters}.geojson",
@ -160,6 +162,8 @@ rule build_heat_demands:
 rule build_temperature_profiles:
    params:
        snapshots=config["snapshots"],
    input:
        pop_layout=RESOURCES + "pop_layout{weather_year}_{scope}.nc",
        regions_onshore=RESOURCES + "regions_onshore_elec{weather_year}_s{simpl}_{clusters}.geojson",
@ -181,6 +185,8 @@ rule build_temperature_profiles:
 rule build_cop_profiles:
    params:
        heat_pump_sink_T=config["sector"]["heat_pump_sink_T"],
    input:
        temp_soil_total=RESOURCES + "temp_soil_total_elec{weather_year}_s{simpl}_{clusters}.nc",
        temp_soil_rural=RESOURCES + "temp_soil_rural_elec{weather_year}_s{simpl}_{clusters}.nc",
@ -208,6 +214,9 @@ rule build_cop_profiles:
 rule build_solar_thermal_profiles:
    params:
        snapshots=config["snapshots"],
        solar_thermal=config["solar_thermal"],
    input:
        pop_layout=RESOURCES + "pop_layout{weather_year}_{scope}.nc",
        regions_onshore=RESOURCES + "regions_onshore_elec{weather_year}_s{simpl}_{clusters}.geojson",
@ -228,6 +237,9 @@ rule build_solar_thermal_profiles:
 rule build_energy_totals:
    params:
        countries=config["countries"],
        energy=config["energy"],
    input:
        nuts3_shapes=RESOURCES + "nuts3_shapes.geojson",
        co2="data/eea/UNFCCC_v23.csv",
@ -271,6 +283,8 @@ rule build_heat_totals:
 rule build_biomass_potentials:
    params:
        biomass=config["biomass"],
    input:
        enspreso_biomass=HTTP.remote(
            "https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx",
@ -333,6 +347,10 @@ if not config["sector"]["biomass_transport"]:
 if config["sector"]["regional_co2_sequestration_potential"]["enable"]:
    rule build_sequestration_potentials:
        params:
            sequestration_potential=config["sector"][
                "regional_co2_sequestration_potential"
            ],
        input:
            sequestration_potential=HTTP.remote(
                "https://raw.githubusercontent.com/ericzhou571/Co2Storage/main/resources/complete_map_2020_unit_Mt.geojson",
@ -386,6 +404,8 @@ rule build_salt_cavern_potentials:
 rule build_ammonia_production:
    params:
        countries=config["countries"],
    input:
        usgs="data/myb1-2017-nitro.xls",
    output:
@ -404,6 +424,9 @@ rule build_ammonia_production:
 rule build_industry_sector_ratios:
    params:
        industry=config["industry"],
        ammonia=config["sector"].get("ammonia", False),
    input:
        ammonia_production=RESOURCES + "ammonia_production.csv",
        idees="data/jrc-idees-2015",
@ -423,6 +446,9 @@ rule build_industry_sector_ratios:
 rule build_industrial_production_per_country:
    params:
        industry=config["industry"],
        countries=config["countries"],
    input:
        ammonia_production=RESOURCES + "ammonia_production.csv",
        jrc="data/jrc-idees-2015",
@ -444,6 +470,8 @@ rule build_industrial_production_per_country:
 rule build_industrial_production_per_country_tomorrow:
    params:
        industry=config["industry"],
    input:
        industrial_production_per_country=RESOURCES
        + "industrial_production_per_country.csv",
@ -468,6 +496,9 @@ rule build_industrial_production_per_country_tomorrow:
 rule build_industrial_distribution_key:
    params:
        hotmaps_locate_missing=config["industry"].get("hotmaps_locate_missing", False),
        countries=config["countries"],
    input:
        regions_onshore=RESOURCES + "regions_onshore_elec{weather_year}_s{simpl}_{clusters}.geojson",
        clustered_pop_layout=RESOURCES + "pop_layout_elec{weather_year}_s{simpl}_{clusters}.csv",
@ -542,6 +573,9 @@ rule build_industrial_energy_demand_per_node:
 rule build_industrial_energy_demand_per_country_today:
    params:
        countries=config["countries"],
        industry=config["industry"],
    input:
        jrc="data/jrc-idees-2015",
        ammonia_production=RESOURCES + "ammonia_production.csv",
@ -588,6 +622,9 @@ rule build_industrial_energy_demand_per_node_today:
 if config["sector"]["retrofitting"]["retro_endogen"]:
    rule build_retro_cost:
        params:
            retrofitting=config["sector"]["retrofitting"],
            countries=config["countries"],
        input:
            building_stock="data/retro/data_building_stock.csv",
            data_tabula="data/retro/tabula-calculator-calcsetbuilding.csv",
@ -658,6 +695,9 @@ rule build_shipping_demand:
 rule build_transport_demand:
    params:
        snapshots=config["snapshots"],
        sector=config["sector"],
    input:
        clustered_pop_layout=RESOURCES + "pop_layout_elec{weather_year}_s{simpl}_{clusters}.csv",
        pop_weighted_energy_totals=RESOURCES
@ -684,14 +724,27 @@ rule build_transport_demand:
 rule prepare_sector_network:
    params:
        co2_budget=config["co2_budget"],
        conventional_carriers=config["existing_capacities"]["conventional_carriers"],
        foresight=config["foresight"],
        costs=config["costs"],
        sector=config["sector"],
        industry=config["industry"],
        pypsa_eur=config["pypsa_eur"],
        length_factor=config["lines"]["length_factor"],
        planning_horizons=config["scenario"]["planning_horizons"],
        countries=config["countries"],
        emissions_scope=config["energy"]["emissions"],
        eurostat_report_year=config["energy"]["eurostat_report_year"],
        RDIR=RDIR,
    input:
        **build_retro_cost_output,
        **build_biomass_transport_costs_output,
        **gas_infrastructure,
        **build_sequestration_potentials_output,
        overrides="data/override_component_attrs",
        network=RESOURCES + "networks/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
        energy_totals_name=RESOURCES + "energy_totals.csv",
        eurostat=input_eurostat,
        pop_weighted_energy_totals=RESOURCES
        + "pop_weighted_energy_totals{weather_year}_s{simpl}_{clusters}.csv",
        pop_weighted_heat_totals=RESOURCES
--- a/rules/common.smk
+++ b/rules/common.smk
@ -23,6 +23,28 @@ def memory(w):
        return int(factor * (10000 + 195 * int(w.clusters)))
 # Check if the workflow has access to the internet by trying to access the HEAD of specified url
 def has_internet_access(url="www.zenodo.org") -> bool:
    import http.client as http_client
    # based on answer and comments from
    # https://stackoverflow.com/a/29854274/11318472
    conn = http_client.HTTPConnection(url, timeout=5)  # need access to zenodo anyway
    try:
        conn.request("HEAD", "/")
        return True
    except:
        return False
    finally:
        conn.close()
 def input_eurostat(w):
    # 2016 includes BA, 2017 does not
    report_year = config["energy"]["eurostat_report_year"]
    return f"data/eurostat-energy_balances-june_{report_year}_edition"
 def solved_previous_horizon(wildcards):
    planning_horizons = config["scenario"]["planning_horizons"]
    i = planning_horizons.index(int(wildcards.planning_horizons))
--- a/rules/postprocess.smk
+++ b/rules/postprocess.smk
@ -9,8 +9,10 @@ localrules:
 rule plot_network:
    params:
        foresight=config["foresight"],
        plotting=config["plotting"],
    input:
        overrides="data/override_component_attrs",
        network=RESULTS
        + "postnetworks/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
        regions=RESOURCES
@ -68,9 +70,12 @@ rule copy_conda_env:
 rule make_summary:
    params:
        foresight=config["foresight"],
        costs=config["costs"],
        snapshots=config["snapshots"],
        scenario=config["scenario"],
        RDIR=RDIR,
    input:
        overrides="data/override_component_attrs",
        networks=expand(
            RESULTS
            + "postnetworks/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
@ -115,6 +120,10 @@ rule make_summary:
 rule plot_summary:
    params:
        countries=config["countries"],
        planning_horizons=config["scenario"]["planning_horizons"],
        sector_opts=config["scenario"]["sector_opts"],
        plotting=config["plotting"],
        RDIR=RDIR,
    input:
        costs=RESULTS + "csvs/costs.csv",
--- a/rules/retrieve.smk
+++ b/rules/retrieve.smk
@ -2,7 +2,14 @@
 #
 # SPDX-License-Identifier: MIT
-if config["enable"].get("retrieve_databundle", True):
+if config["enable"].get("retrieve", "auto") == "auto":
    config["enable"]["retrieve"] = has_internet_access()
 if config["enable"]["retrieve"] is False:
    print("Datafile downloads disabled in config[retrieve] or no internet access.")
 if config["enable"]["retrieve"] and config["enable"].get("retrieve_databundle", True):
    datafiles = [
        "ch_cantons.csv",
        "je-e-21.03.02.xls",
@ -32,7 +39,7 @@ if config["enable"].get("retrieve_databundle", True):
            "../scripts/retrieve_databundle.py"
-if config["enable"].get("retrieve_cutout", True):
+if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True):
    rule retrieve_cutout:
        input:
@ -51,7 +58,7 @@ if config["enable"].get("retrieve_cutout", True):
            move(input[0], output[0])
-if config["enable"].get("retrieve_cost_data", True):
+if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", True):
    rule retrieve_cost_data:
        input:
@ -73,7 +80,9 @@ if config["enable"].get("retrieve_cost_data", True):
            move(input[0], output[0])
-if config["enable"].get("retrieve_natura_raster", True):
+if config["enable"]["retrieve"] and config["enable"].get(
    "retrieve_natura_raster", True
 ):
    rule retrieve_natura_raster:
        input:
@ -93,7 +102,9 @@ if config["enable"].get("retrieve_natura_raster", True):
            move(input[0], output[0])
-if config["enable"].get("retrieve_sector_databundle", True):
+if config["enable"]["retrieve"] and config["enable"].get(
    "retrieve_sector_databundle", True
 ):
    datafiles = [
        "data/eea/UNFCCC_v23.csv",
        "data/switzerland-sfoe/switzerland-new_format.csv",
@ -119,7 +130,9 @@ if config["enable"].get("retrieve_sector_databundle", True):
            "../scripts/retrieve_sector_databundle.py"
-if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]:
+if config["enable"]["retrieve"] and (
    config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]
 ):
    datafiles = [
        "IGGIELGN_LNGs.geojson",
        "IGGIELGN_BorderPoints.geojson",
@ -138,7 +151,7 @@ if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]:
        script:
            "../scripts/retrieve_gas_infrastructure_data.py"
-if config["enable"].get("retrieve_opsd_load_data", True):
+if config["enable"]["retrieve"] and config["enable"].get("retrieve_opsd_load_data", True):
    rule retrieve_electricity_demand:
        input:
@ -158,7 +171,7 @@ if config["enable"].get("retrieve_opsd_load_data", True):
            move(input[0], output[0])
-if config["enable"].get('retrieve_artificial_load_data', False):
+if config["enable"]["retrieve"] and config["enable"].get('retrieve_artificial_load_data', False):
    rule retrieve_artificial_load_data:
        input: HTTP.remote("https://zenodo.org/record/7070438/files/demand_hourly.csv", keep_local=True, static=True)
@ -169,7 +182,9 @@ if config["enable"].get('retrieve_artificial_load_data', False):
        run: move(input[0], output[0])
-rule retrieve_ship_raster:
+if config["enable"]["retrieve"]:
    rule retrieve_ship_raster:
        input:
            HTTP.remote(
                "https://zenodo.org/record/6953563/files/shipdensity_global.zip",
--- a/rules/solve_electricity.smk
+++ b/rules/solve_electricity.smk
@ -4,6 +4,13 @@
 rule solve_network:
    params:
        solving=config["solving"],
        foresight=config["foresight"],
        planning_horizons=config["scenario"]["planning_horizons"],
        co2_sequestration_potential=config["sector"].get(
            "co2_sequestration_potential", 200
        ),
    input:
        network=RESOURCES
        + "networks/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
@ -17,8 +24,6 @@ rule solve_network:
        ),
        python=LOGS
        + "solve_network/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}_python.log",
        memory=LOGS
        + "solve_network/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}_memory.log",
    benchmark:
        (
            BENCHMARKS
@ -36,6 +41,8 @@ rule solve_network:
 rule solve_operations_network:
    params:
        options=config["solving"]["options"],
    input:
        network=RESULTS
        + "networks/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}.nc",
@ -49,8 +56,6 @@ rule solve_operations_network:
        ),
        python=LOGS
        + "solve_operations_network/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_python.log",
        memory=LOGS
        + "solve_operations_network/elec{weather_year}_s{simpl}_{clusters}_ec_l{ll}_{opts}_op_memory.log",
    benchmark:
        (
            BENCHMARKS
--- a/rules/solve_myopic.smk
+++ b/rules/solve_myopic.smk
@ -4,8 +4,12 @@
 rule add_existing_baseyear:
    params:
        baseyear=config["scenario"]["planning_horizons"][0],
        sector=config["sector"],
        existing_capacities=config["existing_capacities"],
        costs=config["costs"],
    input:
        overrides="data/override_component_attrs",
        network=RESULTS
        + "prenetworks/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
        powerplants=RESOURCES + "powerplants.csv",
@ -45,8 +49,11 @@ rule add_existing_baseyear:
 rule add_brownfield:
    params:
        H2_retrofit=config["sector"]["H2_retrofit"],
        H2_retrofit_capacity_per_CH4=config["sector"]["H2_retrofit_capacity_per_CH4"],
        threshold_capacity=config["existing_capacities"]["threshold_capacity"],
    input:
        overrides="data/override_component_attrs",
        network=RESULTS
        + "prenetworks/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
        network_p=solved_previous_horizon,  #solved network at previous time step
@ -79,8 +86,14 @@ ruleorder: add_existing_baseyear > add_brownfield
 rule solve_sector_network_myopic:
    params:
        solving=config["solving"],
        foresight=config["foresight"],
        planning_horizons=config["scenario"]["planning_horizons"],
        co2_sequestration_potential=config["sector"].get(
            "co2_sequestration_potential", 200
        ),
    input:
        overrides="data/override_component_attrs",
        network=RESULTS
        + "prenetworks-brownfield/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
        costs="data/costs_{planning_horizons}.csv",
@ -95,8 +108,6 @@ rule solve_sector_network_myopic:
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log",
        python=LOGS
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log",
        memory=LOGS
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log",
    threads: 4
    resources:
        mem_mb=config["solving"]["mem"],
--- a/rules/solve_overnight.smk
+++ b/rules/solve_overnight.smk
@ -4,8 +4,14 @@
 rule solve_sector_network:
    params:
        solving=config["solving"],
        foresight=config["foresight"],
        planning_horizons=config["scenario"]["planning_horizons"],
        co2_sequestration_potential=config["sector"].get(
            "co2_sequestration_potential", 200
        ),
    input:
        overrides="data/override_component_attrs",
        network=RESULTS
        + "prenetworks/elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
        costs="data/costs_{}.csv".format(config["costs"]["year"]),
@ -21,8 +27,6 @@ rule solve_sector_network:
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_solver.log",
        python=LOGS
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_python.log",
        memory=LOGS
        + "elec{weather_year}_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}_memory.log",
    threads: config["solving"]["solver"].get("threads", 4)
    resources:
        mem_mb=config["solving"]["mem"],
--- a/scripts/_helpers.py
+++ b/scripts/_helpers.py
@ -72,92 +72,6 @@ def configure_logging(snakemake, skip_handlers=False):
    logging.basicConfig(**kwargs)
 def load_network(import_name=None, custom_components=None):
    """
    Helper for importing a pypsa.Network with additional custom components.
    Parameters
    ----------
    import_name : str
        As in pypsa.Network(import_name)
    custom_components : dict
        Dictionary listing custom components.
        For using ``snakemake.config['override_components']``
        in ``config/config.yaml`` define:
        .. code:: yaml
            override_components:
                ShadowPrice:
                    component: ["shadow_prices","Shadow price for a global constraint.",np.nan]
                    attributes:
                    name: ["string","n/a","n/a","Unique name","Input (required)"]
                    value: ["float","n/a",0.,"shadow value","Output"]
    Returns
    -------
    pypsa.Network
    """
    import pypsa
    from pypsa.descriptors import Dict
    override_components = None
    override_component_attrs = None
    if custom_components is not None:
        override_components = pypsa.components.components.copy()
        override_component_attrs = Dict(
            {k: v.copy() for k, v in pypsa.components.component_attrs.items()}
        )
        for k, v in custom_components.items():
            override_components.loc[k] = v["component"]
            override_component_attrs[k] = pd.DataFrame(
                columns=["type", "unit", "default", "description", "status"]
            )
            for attr, val in v["attributes"].items():
                override_component_attrs[k].loc[attr] = val
    return pypsa.Network(
        import_name=import_name,
        override_components=override_components,
        override_component_attrs=override_component_attrs,
    )
 def load_network_for_plots(fn, tech_costs, config, combine_hydro_ps=True):
    import pypsa
    from add_electricity import load_costs, update_transmission_costs
    n = pypsa.Network(fn)
    n.loads["carrier"] = n.loads.bus.map(n.buses.carrier) + " load"
    n.stores["carrier"] = n.stores.bus.map(n.buses.carrier)
    n.links["carrier"] = (
        n.links.bus0.map(n.buses.carrier) + "-" + n.links.bus1.map(n.buses.carrier)
    )
    n.lines["carrier"] = "AC line"
    n.transformers["carrier"] = "AC transformer"
    n.lines["s_nom"] = n.lines["s_nom_min"]
    n.links["p_nom"] = n.links["p_nom_min"]
    if combine_hydro_ps:
        n.storage_units.loc[
            n.storage_units.carrier.isin({"PHS", "hydro"}), "carrier"
        ] = "hydro+PHS"
    # if the carrier was not set on the heat storage units
    # bus_carrier = n.storage_units.bus.map(n.buses.carrier)
    # n.storage_units.loc[bus_carrier == "heat","carrier"] = "water tanks"
    Nyears = n.snapshot_weightings.objective.sum() / 8760.0
    costs = load_costs(tech_costs, config["costs"], config["electricity"], Nyears)
    update_transmission_costs(n, costs)
    return n
 def update_p_nom_max(n):
    # if extendable carriers (solar/onwind/...) have capacity >= 0,
    # e.g. existing assets from the OPSD project are included to the network,
@ -277,23 +191,6 @@ def progress_retrieve(url, file, disable=False):
            urllib.request.urlretrieve(url, file, reporthook=update_to)
 def get_aggregation_strategies(aggregation_strategies):
    # default aggregation strategies that cannot be defined in .yaml format must be specified within
    # the function, otherwise (when defaults are passed in the function's definition) they get lost
    # when custom values are specified in the config.
    import numpy as np
    from pypsa.networkclustering import _make_consense
    bus_strategies = dict(country=_make_consense("Bus", "country"))
    bus_strategies.update(aggregation_strategies.get("buses", {}))
    generator_strategies = {"build_year": lambda x: 0, "lifetime": lambda x: np.inf}
    generator_strategies.update(aggregation_strategies.get("generators", {}))
    return bus_strategies, generator_strategies
 def mock_snakemake(rulename, configfiles=[], **wildcards):
    """
    This function is expected to be executed from the 'scripts'-directory of '
@ -384,33 +281,6 @@ def mock_snakemake(rulename, configfiles=[], **wildcards):
    return snakemake
 def override_component_attrs(directory):
    """Tell PyPSA that links can have multiple outputs by
    overriding the component_attrs. This can be done for
    as many buses as you need with format busi for i = 2,3,4,5,....
    See https://pypsa.org/doc/components.html#link-with-multiple-outputs-or-inputs
    Parameters
    ----------
    directory : string
        Folder where component attributes to override are stored
        analogous to ``pypsa/component_attrs``, e.g. `links.csv`.
    Returns
    -------
    Dictionary of overridden component attributes.
    """
    attrs = Dict({k: v.copy() for k, v in component_attrs.items()})
    for component, list_name in components.list_name.items():
        fn = f"{directory}/{list_name}.csv"
        if os.path.isfile(fn):
            overrides = pd.read_csv(fn, index_col=0, na_values="n/a")
            attrs[component] = overrides.combine_first(attrs[component])
    return attrs
 def generate_periodic_profiles(dt_index, nodes, weekly_profile, localize=None):
    """
    Give a 24*7 long list of weekly hourly profiles, generate this for each
--- a/scripts/add_brownfield.py
+++ b/scripts/add_brownfield.py
@ -16,7 +16,7 @@ idx = pd.IndexSlice
 import numpy as np
 import pypsa
-from _helpers import override_component_attrs, update_config_with_sector_opts
+from _helpers import update_config_with_sector_opts
 from add_existing_baseyear import add_build_year_to_new_assets
@ -49,7 +49,7 @@ def add_brownfield(n, n_p, year):
            )
        ]
-        threshold = snakemake.config["existing_capacities"]["threshold_capacity"]
+        threshold = snakemake.params.threshold_capacity
        if not chp_heat.empty:
            threshold_chp_heat = (
@ -87,7 +87,7 @@ def add_brownfield(n, n_p, year):
        # deal with gas network
        pipe_carrier = ["gas pipeline"]
-        if snakemake.config["sector"]["H2_retrofit"]:
+        if snakemake.params.H2_retrofit:
            # drop capacities of previous year to avoid duplicating
            to_drop = n.links.carrier.isin(pipe_carrier) & (n.links.build_year != year)
            n.mremove("Link", n.links.loc[to_drop].index)
@ -98,7 +98,7 @@ def add_brownfield(n, n_p, year):
                & (n.links.build_year != year)
            ].index
            gas_pipes_i = n.links[n.links.carrier.isin(pipe_carrier)].index
-            CH4_per_H2 = 1 / snakemake.config["sector"]["H2_retrofit_capacity_per_CH4"]
+            CH4_per_H2 = 1 / snakemake.params.H2_retrofit_capacity_per_CH4
            fr = "H2 pipeline retrofitted"
            to = "gas pipeline"
            # today's pipe capacity
@ -148,12 +148,11 @@ if __name__ == "__main__":
    year = int(snakemake.wildcards.planning_horizons)
-    overrides = override_component_attrs(snakemake.input.overrides)
+    n = pypsa.Network(snakemake.input.network)
    n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
    add_build_year_to_new_assets(n, year)
-    n_p = pypsa.Network(snakemake.input.network_p, override_component_attrs=overrides)
+    n_p = pypsa.Network(snakemake.input.network_p)
    add_brownfield(n, n_p, year)
--- a/scripts/add_electricity.py
+++ b/scripts/add_electricity.py
@ -85,16 +85,18 @@ It further adds extendable ``generators`` with **zero** capacity for
 """
 import logging
 from itertools import product
 import geopandas as gpd
 import numpy as np
 import pandas as pd
 import powerplantmatching as pm
 import pypsa
 import scipy.sparse as sparse
 import xarray as xr
 from _helpers import configure_logging, update_p_nom_max
 from powerplantmatching.export import map_country_bus
-from vresutils import transfer as vtransfer
+from shapely.prepared import prep
 idx = pd.IndexSlice
@ -121,21 +123,71 @@ def calculate_annuity(n, r):
        return 1 / n
-def _add_missing_carriers_from_costs(n, costs, carriers):
+def add_missing_carriers(n, carriers):
-    missing_carriers = pd.Index(carriers).difference(n.carriers.index)
+    """
-    if missing_carriers.empty:
+    Function to add missing carriers to the network without raising errors.
-        return
+    """
    missing_carriers = set(carriers) - set(n.carriers.index)
    if len(missing_carriers) > 0:
        n.madd("Carrier", missing_carriers)
-    emissions_cols = (
+
-        costs.columns.to_series().loc[lambda s: s.str.endswith("_emissions")].values
+def sanitize_carriers(n, config):
    """
    Sanitize the carrier information in a PyPSA Network object.
    The function ensures that all unique carrier names are present in the network's
    carriers attribute, and adds nice names and colors for each carrier according
    to the provided configuration dictionary.
    Parameters
    ----------
    n : pypsa.Network
        A PyPSA Network object that represents an electrical power system.
    config : dict
        A dictionary containing configuration information, specifically the
        "plotting" key with "nice_names" and "tech_colors" keys for carriers.
    Returns
    -------
    None
        The function modifies the 'n' PyPSA Network object in-place, updating the
        carriers attribute with nice names and colors.
    Warnings
    --------
    Raises a warning if any carrier's "tech_colors" are not defined in the config dictionary.
    """
    for c in n.iterate_components():
        if "carrier" in c.df:
            add_missing_carriers(n, c.df.carrier)
    carrier_i = n.carriers.index
    nice_names = (
        pd.Series(config["plotting"]["nice_names"])
        .reindex(carrier_i)
        .fillna(carrier_i.to_series().str.title())
    )
-    suptechs = missing_carriers.str.split("-").str[0]
+    n.carriers["nice_name"] = n.carriers.nice_name.where(
-    emissions = costs.loc[suptechs, emissions_cols].fillna(0.0)
+        n.carriers.nice_name != "", nice_names
-    emissions.index = missing_carriers
+    )
-    n.import_components_from_dataframe(emissions, "Carrier")
+    colors = pd.Series(config["plotting"]["tech_colors"]).reindex(carrier_i)
    if colors.isna().any():
        missing_i = list(colors.index[colors.isna()])
        logger.warning(f"tech_colors for carriers {missing_i} not defined in config.")
    n.carriers["color"] = n.carriers.color.where(n.carriers.color != "", colors)
-def load_costs(tech_costs, config, elec_config, Nyears=1.0):
+def add_co2_emissions(n, costs, carriers):
    """
    Add CO2 emissions to the network's carriers attribute.
    """
    suptechs = n.carriers.loc[carriers].index.str.split("-").str[0]
    n.carriers.loc[carriers, "co2_emissions"] = costs.co2_emissions[suptechs].values
 def load_costs(tech_costs, config, max_hours, Nyears=1.0):
    # set all asset costs and other parameters
    costs = pd.read_csv(tech_costs, index_col=[0, 1]).sort_index()
@ -178,7 +230,6 @@ def load_costs(tech_costs, config, elec_config, Nyears=1.0):
            dict(capital_cost=capital_cost, marginal_cost=0.0, co2_emissions=0.0)
        )
    max_hours = elec_config["max_hours"]
    costs.loc["battery"] = costs_for_storage(
        costs.loc["battery storage"],
        costs.loc["battery inverter"],
@ -216,6 +267,21 @@ def load_powerplants(ppl_fn):
    )
 def shapes_to_shapes(orig, dest):
    """
    Adopted from vresutils.transfer.Shapes2Shapes()
    """
    orig_prepped = list(map(prep, orig))
    transfer = sparse.lil_matrix((len(dest), len(orig)), dtype=float)
    for i, j in product(range(len(dest)), range(len(orig))):
        if orig_prepped[j].intersects(dest[i]):
            area = orig[j].intersection(dest[i]).area
            transfer[i, j] = area / dest[i].area
    return transfer
 def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
    substation_lv_i = n.buses.index[n.buses["substation_lv"]]
    regions = gpd.read_file(regions).set_index("name").reindex(substation_lv_i)
@ -232,9 +298,7 @@ def attach_load(n, regions, load, nuts3_shapes, countries, scaling=1.0):
            return pd.DataFrame({group.index[0]: l})
        else:
            nuts3_cntry = nuts3.loc[nuts3.country == cntry]
-            transfer = vtransfer.Shapes2Shapes(
+            transfer = shapes_to_shapes(group, nuts3_cntry.geometry).T.tocsr()
                group, nuts3_cntry.geometry, normed=False
            ).T.tocsr()
            gdp_n = pd.Series(
                transfer.dot(nuts3_cntry["gdp"].fillna(1.0).values), index=group.index
            )
@ -295,57 +359,56 @@ def update_transmission_costs(n, costs, length_factor=1.0):
 def attach_wind_and_solar(
-    n, costs, input_profiles, technologies, extendable_carriers, line_length_factor=1
+    n, costs, input_profiles, carriers, extendable_carriers, line_length_factor=1
 ):
-    # TODO: rename tech -> carrier, technologies -> carriers
+    add_missing_carriers(n, carriers)
    _add_missing_carriers_from_costs(n, costs, technologies)
-    for tech in technologies:
+    for car in carriers:
-        if tech == "hydro":
+        if car == "hydro":
            continue
-        with xr.open_dataset(getattr(input_profiles, "profile_" + tech)) as ds:
+        with xr.open_dataset(getattr(input_profiles, "profile_" + car)) as ds:
            if ds.indexes["bus"].empty:
                continue
-            suptech = tech.split("-", 2)[0]
+            supcar = car.split("-", 2)[0]
-            if suptech == "offwind":
+            if supcar == "offwind":
                underwater_fraction = ds["underwater_fraction"].to_pandas()
                connection_cost = (
                    line_length_factor
                    * ds["average_distance"].to_pandas()
                    * (
                        underwater_fraction
-                        * costs.at[tech + "-connection-submarine", "capital_cost"]
+                        * costs.at[car + "-connection-submarine", "capital_cost"]
                        + (1.0 - underwater_fraction)
-                        * costs.at[tech + "-connection-underground", "capital_cost"]
+                        * costs.at[car + "-connection-underground", "capital_cost"]
                    )
                )
                capital_cost = (
                    costs.at["offwind", "capital_cost"]
-                    + costs.at[tech + "-station", "capital_cost"]
+                    + costs.at[car + "-station", "capital_cost"]
                    + connection_cost
                )
                logger.info(
                    "Added connection cost of {:0.0f}-{:0.0f} Eur/MW/a to {}".format(
-                        connection_cost.min(), connection_cost.max(), tech
+                        connection_cost.min(), connection_cost.max(), car
                    )
                )
            else:
-                capital_cost = costs.at[tech, "capital_cost"]
+                capital_cost = costs.at[car, "capital_cost"]
            n.madd(
                "Generator",
                ds.indexes["bus"],
-                " " + tech,
+                " " + car,
                bus=ds.indexes["bus"],
-                carrier=tech,
+                carrier=car,
-                p_nom_extendable=tech in extendable_carriers["Generator"],
+                p_nom_extendable=car in extendable_carriers["Generator"],
                p_nom_max=ds["p_nom_max"].to_pandas(),
                weight=ds["weight"].to_pandas(),
-                marginal_cost=costs.at[suptech, "marginal_cost"],
+                marginal_cost=costs.at[supcar, "marginal_cost"],
                capital_cost=capital_cost,
-                efficiency=costs.at[suptech, "efficiency"],
+                efficiency=costs.at[supcar, "efficiency"],
                p_max_pu=ds["profile"].transpose("time", "bus").to_pandas(),
            )
@ -356,11 +419,19 @@ def attach_conventional_generators(
    ppl,
    conventional_carriers,
    extendable_carriers,
-    conventional_config,
+    conventional_params,
    conventional_inputs,
 ):
-    carriers = set(conventional_carriers) | set(extendable_carriers["Generator"])
+    carriers = list(set(conventional_carriers) | set(extendable_carriers["Generator"]))
-    _add_missing_carriers_from_costs(n, costs, carriers)
+    add_missing_carriers(n, carriers)
    add_co2_emissions(n, costs, carriers)
    # Replace carrier "natural gas" with the respective technology (OCGT or
    # CCGT) to align with PyPSA names of "carriers" and avoid filtering "natural
    # gas" powerplants in ppl.query("carrier in @carriers")
    ppl.loc[ppl["carrier"] == "natural gas", "carrier"] = ppl.loc[
        ppl["carrier"] == "natural gas", "technology"
    ]
    ppl = (
        ppl.query("carrier in @carriers")
@ -393,17 +464,19 @@ def attach_conventional_generators(
        lifetime=(ppl.dateout - ppl.datein).fillna(np.inf),
    )
-    for carrier in conventional_config:
+    for carrier in conventional_params:
        # Generators with technology affected
        idx = n.generators.query("carrier == @carrier").index
-        for attr in list(set(conventional_config[carrier]) & set(n.generators)):
+        for attr in list(set(conventional_params[carrier]) & set(n.generators)):
-            values = conventional_config[carrier][attr]
+            values = conventional_params[carrier][attr]
            if f"conventional_{carrier}_{attr}" in conventional_inputs:
                # Values affecting generators of technology k country-specific
                # First map generator buses to countries; then map countries to p_max_pu
-                values = pd.read_csv(values, index_col=0).iloc[:, 0]
+                values = pd.read_csv(
                    snakemake.input[f"conventional_{carrier}_{attr}"], index_col=0
                ).iloc[:, 0]
                bus_values = n.buses.country.map(values)
                n.generators[attr].update(
                    n.generators.loc[idx].bus.map(bus_values).dropna()
@ -413,8 +486,9 @@ def attach_conventional_generators(
                n.generators.loc[idx, attr] = values
-def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **config):
+def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **params):
-    _add_missing_carriers_from_costs(n, costs, carriers)
+    add_missing_carriers(n, carriers)
    add_co2_emissions(n, costs, carriers)
    ppl = (
        ppl.query('carrier == "hydro"')
@ -468,9 +542,9 @@ def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **con
        )
    if "PHS" in carriers and not phs.empty:
-        # fill missing max hours to config value and
+        # fill missing max hours to params value and
        # assume no natural inflow due to lack of data
-        max_hours = config.get("PHS_max_hours", 6)
+        max_hours = params.get("PHS_max_hours", 6)
        phs = phs.replace({"max_hours": {0: max_hours}})
        n.madd(
            "StorageUnit",
@ -486,7 +560,7 @@ def attach_hydro(n, costs, ppl, profile_hydro, hydro_capacities, carriers, **con
        )
    if "hydro" in carriers and not hydro.empty:
-        hydro_max_hours = config.get("hydro_max_hours")
+        hydro_max_hours = params.get("hydro_max_hours")
        assert hydro_max_hours is not None, "No path for hydro capacities given."
@ -546,7 +620,8 @@ def attach_extendable_generators(n, costs, ppl, carriers):
    logger.warning(
        "The function `attach_extendable_generators` is deprecated in v0.5.0."
    )
-    _add_missing_carriers_from_costs(n, costs, carriers)
+    add_missing_carriers(n, carriers)
    add_co2_emissions(n, costs, carriers)
    for tech in carriers:
        if tech.startswith("OCGT"):
@ -628,7 +703,7 @@ def attach_OPSD_renewables(n, tech_map):
        buses = n.buses.loc[gens.bus.unique()]
        gens_per_bus = gens.groupby("bus").p_nom.count()
-        caps = map_country_bus(df.query("Fueltype == @fueltype"), buses)
+        caps = map_country_bus(df.query("Fueltype == @fueltype and lat == lat"), buses)
        caps = caps.groupby(["bus"]).Capacity.sum()
        caps = caps / gens_per_bus.reindex(caps.index, fill_value=1)
@ -636,16 +711,7 @@ def attach_OPSD_renewables(n, tech_map):
        n.generators.p_nom_min.update(gens.bus.map(caps).dropna())
-def estimate_renewable_capacities(n, config):
+def estimate_renewable_capacities(n, year, tech_map, expansion_limit, countries):
    year = config["electricity"]["estimate_renewable_capacities"]["year"]
    tech_map = config["electricity"]["estimate_renewable_capacities"][
        "technology_mapping"
    ]
    countries = config["countries"]
    expansion_limit = config["electricity"]["estimate_renewable_capacities"][
        "expansion_limit"
    ]
    if not len(countries) or not len(tech_map):
        return
@ -686,21 +752,6 @@ def estimate_renewable_capacities(n, config):
            )
 def add_nice_carrier_names(n, config):
    carrier_i = n.carriers.index
    nice_names = (
        pd.Series(config["plotting"]["nice_names"])
        .reindex(carrier_i)
        .fillna(carrier_i.to_series().str.title())
    )
    n.carriers["nice_name"] = nice_names
    colors = pd.Series(config["plotting"]["tech_colors"]).reindex(carrier_i)
    if colors.isna().any():
        missing_i = list(colors.index[colors.isna()])
        logger.warning(f"tech_colors for carriers {missing_i} not defined in config.")
    n.carriers["color"] = colors
 def drop_leap_day(n):
    if not n.snapshots.is_leap_year.any():
        return
@ -717,6 +768,8 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("add_electricity", weather_year="")
    configure_logging(snakemake)
    params = snakemake.params
    n = pypsa.Network(snakemake.input.base_network)
    weather_year = snakemake.wildcards.weather_year
@ -732,43 +785,26 @@ if __name__ == "__main__":
    costs = load_costs(
        snakemake.input.tech_costs,
-        snakemake.config["costs"],
+        params.costs,
-        snakemake.config["electricity"],
+        params.electricity["max_hours"],
        Nyears,
    )
    ppl = load_powerplants(snakemake.input.powerplants)
    if "renewable_carriers" in snakemake.config["electricity"]:
        renewable_carriers = set(snakemake.config["electricity"]["renewable_carriers"])
    else:
        logger.warning(
            "Missing key `renewable_carriers` under config entry `electricity`. "
            "In future versions, this will raise an error. "
            "Falling back to carriers listed under `renewable`."
        )
        renewable_carriers = snakemake.config["renewable"]
    extendable_carriers = snakemake.config["electricity"]["extendable_carriers"]
    if not (set(renewable_carriers) & set(extendable_carriers["Generator"])):
        logger.warning(
            "No renewables found in config entry `extendable_carriers`. "
            "In future versions, these have to be explicitly listed. "
            "Falling back to all renewables."
        )
    conventional_carriers = snakemake.config["electricity"]["conventional_carriers"]
    attach_load(
        n,
        snakemake.input.regions,
        snakemake.input.load,
        snakemake.input.nuts3_shapes,
-        snakemake.config["countries"],
+        params.countries,
-        snakemake.config["load"]["scaling_factor"],
+        params.scaling_factor,
    )
-    update_transmission_costs(n, costs, snakemake.config["lines"]["length_factor"])
+    update_transmission_costs(n, costs, params.length_factor)
    renewable_carriers = set(params.electricity["renewable_carriers"])
    extendable_carriers = params.electricity["extendable_carriers"]
    conventional_carriers = params.electricity["conventional_carriers"]
    conventional_inputs = {
        k: v for k, v in snakemake.input.items() if k.startswith("conventional_")
    }
@ -778,7 +814,7 @@ if __name__ == "__main__":
        ppl,
        conventional_carriers,
        extendable_carriers,
-        snakemake.config.get("conventional", {}),
+        params.conventional,
        conventional_inputs,
    )
@ -788,71 +824,36 @@ if __name__ == "__main__":
        snakemake.input,
        renewable_carriers,
        extendable_carriers,
-        snakemake.config["lines"]["length_factor"],
+        params.length_factor,
    )
    if "hydro" in renewable_carriers:
-        conf = snakemake.config["renewable"]["hydro"]
+        para = params.renewable["hydro"]
        attach_hydro(
            n,
            costs,
            ppl,
            snakemake.input.profile_hydro,
            snakemake.input.hydro_capacities,
-            conf.pop("carriers", []),
+            para.pop("carriers", []),
-            **conf,
+            **para,
        )
-    if "estimate_renewable_capacities" not in snakemake.config["electricity"]:
+    estimate_renewable_caps = params.electricity["estimate_renewable_capacities"]
        logger.warning(
            "Missing key `estimate_renewable_capacities` under config entry `electricity`. "
            "In future versions, this will raise an error. "
            "Falling back to whether ``estimate_renewable_capacities_from_capacity_stats`` is in the config."
        )
        if (
            "estimate_renewable_capacities_from_capacity_stats"
            in snakemake.config["electricity"]
        ):
            estimate_renewable_caps = {
                "enable": True,
                **snakemake.config["electricity"][
                    "estimate_renewable_capacities_from_capacity_stats"
                ],
            }
        else:
            estimate_renewable_caps = {"enable": False}
    else:
        estimate_renewable_caps = snakemake.config["electricity"][
            "estimate_renewable_capacities"
        ]
    if "enable" not in estimate_renewable_caps:
        logger.warning(
            "Missing key `enable` under config entry `estimate_renewable_capacities`. "
            "In future versions, this will raise an error. Falling back to False."
        )
        estimate_renewable_caps = {"enable": False}
    if "from_opsd" not in estimate_renewable_caps:
        logger.warning(
            "Missing key `from_opsd` under config entry `estimate_renewable_capacities`. "
            "In future versions, this will raise an error. "
            "Falling back to whether `renewable_capacities_from_opsd` is non-empty."
        )
        from_opsd = bool(
            snakemake.config["electricity"].get("renewable_capacities_from_opsd", False)
        )
        estimate_renewable_caps["from_opsd"] = from_opsd
    if estimate_renewable_caps["enable"]:
        tech_map = estimate_renewable_caps["technology_mapping"]
        expansion_limit = estimate_renewable_caps["expansion_limit"]
        year = estimate_renewable_caps["year"]
        if estimate_renewable_caps["from_opsd"]:
            tech_map = snakemake.config["electricity"]["estimate_renewable_capacities"][
                "technology_mapping"
            ]
            attach_OPSD_renewables(n, tech_map)
-        estimate_renewable_capacities(n, snakemake.config)
+        estimate_renewable_capacities(
            n, year, tech_map, expansion_limit, params.countries
        )
    update_p_nom_max(n)
-    add_nice_carrier_names(n, snakemake.config)
+    sanitize_carriers(n, snakemake.config)
    if snakemake.config["enable"].get("drop_leap_days", True):
        drop_leap_day(n)
--- a/scripts/add_existing_baseyear.py
+++ b/scripts/add_existing_baseyear.py
@ -21,7 +21,8 @@ import country_converter as coco
 import numpy as np
 import pypsa
 import xarray as xr
-from _helpers import override_component_attrs, update_config_with_sector_opts
+from _helpers import update_config_with_sector_opts
 from add_electricity import sanitize_carriers
 from prepare_sector_network import cluster_heat_buses, define_spatial, prepare_costs
 cc = coco.CountryConverter()
@ -128,10 +129,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
        "Oil": "oil",
        "OCGT": "OCGT",
        "CCGT": "CCGT",
        "Natural Gas": "gas",
        "Bioenergy": "urban central solid biomass CHP",
    }
    # Replace Fueltype "Natural Gas" with the respective technology (OCGT or CCGT)
    df_agg.loc[df_agg["Fueltype"] == "Natural Gas", "Fueltype"] = df_agg.loc[
        df_agg["Fueltype"] == "Natural Gas", "Technology"
    ]
    fueltype_to_drop = [
        "Hydro",
        "Wind",
@ -157,7 +162,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
    # Fill missing DateOut
    dateout = (
        df_agg.loc[biomass_i, "DateIn"]
-        + snakemake.config["costs"]["fill_values"]["lifetime"]
+        + snakemake.params.costs["fill_values"]["lifetime"]
    )
    df_agg.loc[biomass_i, "DateOut"] = df_agg.loc[biomass_i, "DateOut"].fillna(dateout)
@ -218,7 +223,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
        capacity = df.loc[grouping_year, generator]
        capacity = capacity[~capacity.isna()]
        capacity = capacity[
-            capacity > snakemake.config["existing_capacities"]["threshold_capacity"]
+            capacity > snakemake.params.existing_capacities["threshold_capacity"]
        ]
        suffix = "-ac" if generator == "offwind" else ""
        name_suffix = f" {generator}{suffix}-{grouping_year}"
@ -582,7 +587,7 @@ def add_heating_capacities_installed_before_baseyear(
            )
            # delete links with capacities below threshold
-            threshold = snakemake.config["existing_capacities"]["threshold_capacity"]
+            threshold = snakemake.params.existing_capacities["threshold_capacity"]
            n.mremove(
                "Link",
                [
@ -601,25 +606,26 @@ if __name__ == "__main__":
        snakemake = mock_snakemake(
            "add_existing_baseyear",
            weather_year="",
            configfiles="config/test/config.myopic.yaml",
            simpl="",
-            clusters="45",
+            clusters="5",
-            ll="v1.0",
+            ll="v1.5",
            opts="",
-            sector_opts="8760H-T-H-B-I-A-solar+p3-dist1",
+            sector_opts="24H-T-H-B-I-A-solar+p3-dist1",
-            planning_horizons=2020,
+            planning_horizons=2030,
        )
    logging.basicConfig(level=snakemake.config["logging"]["level"])
    update_config_with_sector_opts(snakemake.config, snakemake.wildcards.sector_opts)
-    options = snakemake.config["sector"]
+    options = snakemake.params.sector
    opts = snakemake.wildcards.sector_opts.split("-")
-    baseyear = snakemake.config["scenario"]["planning_horizons"][0]
+    baseyear = snakemake.params.baseyear
    n = pypsa.Network(snakemake.input.network)
    overrides = override_component_attrs(snakemake.input.overrides)
    n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
    # define spatial resolution of carriers
    spatial = define_spatial(n.buses[n.buses.carrier == "AC"].index, options)
    add_build_year_to_new_assets(n, baseyear)
@ -627,14 +633,12 @@ if __name__ == "__main__":
    Nyears = n.snapshot_weightings.generators.sum() / 8760.0
    costs = prepare_costs(
        snakemake.input.costs,
-        snakemake.config["costs"],
+        snakemake.params.costs,
        Nyears,
    )
-    grouping_years_power = snakemake.config["existing_capacities"][
+    grouping_years_power = snakemake.params.existing_capacities["grouping_years_power"]
-        "grouping_years_power"
+    grouping_years_heat = snakemake.params.existing_capacities["grouping_years_heat"]
    ]
    grouping_years_heat = snakemake.config["existing_capacities"]["grouping_years_heat"]
    add_power_capacities_installed_before_baseyear(
        n, grouping_years_power, costs, baseyear
    )
@ -651,7 +655,7 @@ if __name__ == "__main__":
            .to_pandas()
            .reindex(index=n.snapshots)
        )
-        default_lifetime = snakemake.config["costs"]["fill_values"]["lifetime"]
+        default_lifetime = snakemake.params.costs["fill_values"]["lifetime"]
        add_heating_capacities_installed_before_baseyear(
            n,
            baseyear,
@ -668,4 +672,6 @@ if __name__ == "__main__":
    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
    sanitize_carriers(n, snakemake.config)
    n.export_to_netcdf(snakemake.output[0])
--- a/scripts/add_extra_components.py
+++ b/scripts/add_extra_components.py
@ -56,22 +56,17 @@ import numpy as np
 import pandas as pd
 import pypsa
 from _helpers import configure_logging
-from add_electricity import (
+from add_electricity import load_costs, sanitize_carriers
    _add_missing_carriers_from_costs,
    add_nice_carrier_names,
    load_costs,
 )
 idx = pd.IndexSlice
 logger = logging.getLogger(__name__)
-def attach_storageunits(n, costs, elec_opts):
+def attach_storageunits(n, costs, extendable_carriers, max_hours):
-    carriers = elec_opts["extendable_carriers"]["StorageUnit"]
+    carriers = extendable_carriers["StorageUnit"]
    max_hours = elec_opts["max_hours"]
-    _add_missing_carriers_from_costs(n, costs, carriers)
+    n.madd("Carrier", carriers)
    buses_i = n.buses.index
@ -99,10 +94,10 @@ def attach_storageunits(n, costs, elec_opts):
        )
-def attach_stores(n, costs, elec_opts):
+def attach_stores(n, costs, extendable_carriers):
-    carriers = elec_opts["extendable_carriers"]["Store"]
+    carriers = extendable_carriers["Store"]
-    _add_missing_carriers_from_costs(n, costs, carriers)
+    n.madd("Carrier", carriers)
    buses_i = n.buses.index
    bus_sub_dict = {k: n.buses[k].values for k in ["x", "y", "country"]}
@ -162,6 +157,8 @@ def attach_stores(n, costs, elec_opts):
            marginal_cost=costs.at["battery", "marginal_cost"],
        )
        n.madd("Carrier", ["battery charger", "battery discharger"])
        n.madd(
            "Link",
            b_buses_i + " charger",
@ -187,11 +184,10 @@ def attach_stores(n, costs, elec_opts):
        )
-def attach_hydrogen_pipelines(n, costs, elec_opts):
+def attach_hydrogen_pipelines(n, costs, extendable_carriers):
-    ext_carriers = elec_opts["extendable_carriers"]
+    as_stores = extendable_carriers.get("Store", [])
    as_stores = ext_carriers.get("Store", [])
-    if "H2 pipeline" not in ext_carriers.get("Link", []):
+    if "H2 pipeline" not in extendable_carriers.get("Link", []):
        return
    assert "H2" in as_stores, (
@ -213,6 +209,8 @@ def attach_hydrogen_pipelines(n, costs, elec_opts):
    h2_links.index = h2_links.apply(lambda c: f"H2 pipeline {c.bus0}-{c.bus1}", axis=1)
    # add pipelines
    n.add("Carrier", "H2 pipeline")
    n.madd(
        "Link",
        h2_links.index,
@ -237,18 +235,19 @@ if __name__ == "__main__":
    configure_logging(snakemake)
    n = pypsa.Network(snakemake.input.network)
-    elec_config = snakemake.config["electricity"]
+    extendable_carriers = snakemake.params.extendable_carriers
    max_hours = snakemake.params.max_hours
    Nyears = n.snapshot_weightings.objective.sum() / 8760.0
    costs = load_costs(
-        snakemake.input.tech_costs, snakemake.config["costs"], elec_config, Nyears
+        snakemake.input.tech_costs, snakemake.params.costs, max_hours, Nyears
    )
-    attach_storageunits(n, costs, elec_config)
+    attach_storageunits(n, costs, extendable_carriers, max_hours)
-    attach_stores(n, costs, elec_config)
+    attach_stores(n, costs, extendable_carriers)
-    attach_hydrogen_pipelines(n, costs, elec_config)
+    attach_hydrogen_pipelines(n, costs, extendable_carriers)
-    add_nice_carrier_names(n, snakemake.config)
+    sanitize_carriers(n, snakemake.config)
    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
    n.export_to_netcdf(snakemake.output[0])
--- a/scripts/base_network.py
+++ b/scripts/base_network.py
@ -712,6 +712,7 @@ def base_network(
    n.name = "PyPSA-Eur"
    n.set_snapshots(pd.date_range(freq="h", **config["snapshots"]))
    n.madd("Carrier", ["AC", "DC"])
    n.import_components_from_dataframe(buses, "Bus")
    n.import_components_from_dataframe(lines, "Line")
--- a/scripts/build_ammonia_production.py
+++ b/scripts/build_ammonia_production.py
@ -30,7 +30,7 @@ if __name__ == "__main__":
    ammonia.index = cc.convert(ammonia.index, to="iso2")
    years = [str(i) for i in range(2013, 2018)]
-    countries = ammonia.index.intersection(snakemake.config["countries"])
+    countries = ammonia.index.intersection(snakemake.params.countries)
    ammonia = ammonia.loc[countries, years].astype(float)
    # convert from ktonN to ktonNH3
--- a/scripts/build_biomass_potentials.py
+++ b/scripts/build_biomass_potentials.py
@ -212,9 +212,9 @@ if __name__ == "__main__":
            "build_biomass_potentials", weather_year="", simpl="", clusters="5"
        )
-    config = snakemake.config["biomass"]
+    params = snakemake.params.biomass
-    year = config["year"]
+    year = params["year"]
-    scenario = config["scenario"]
+    scenario = params["scenario"]
    enspreso = enspreso_biomass_potentials(year, scenario)
@ -230,7 +230,7 @@ if __name__ == "__main__":
    df.to_csv(snakemake.output.biomass_potentials_all)
-    grouper = {v: k for k, vv in config["classes"].items() for v in vv}
+    grouper = {v: k for k, vv in params["classes"].items() for v in vv}
    df = df.groupby(grouper, axis=1).sum()
    df *= 1e6  # TWh/a to MWh/a
--- a/scripts/build_bus_regions.py
+++ b/scripts/build_bus_regions.py
@ -116,7 +116,7 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_bus_regions")
    configure_logging(snakemake)
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    n = pypsa.Network(snakemake.input.base_network)
--- a/scripts/build_cop_profiles.py
+++ b/scripts/build_cop_profiles.py
@ -40,7 +40,7 @@ if __name__ == "__main__":
        for source in ["air", "soil"]:
            source_T = xr.open_dataarray(snakemake.input[f"temp_{source}_{area}"])
-            delta_T = snakemake.config["sector"]["heat_pump_sink_T"] - source_T
+            delta_T = snakemake.params.heat_pump_sink_T - source_T
            cop = coefficient_of_performance(delta_T, source)
--- a/scripts/build_cutout.py
+++ b/scripts/build_cutout.py
@ -106,14 +106,14 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_cutout", cutout="europe-2013-era5")
    configure_logging(snakemake)
-    cutout_params = snakemake.config["atlite"]["cutouts"][snakemake.wildcards.cutout]
+    cutout_params = snakemake.params.cutouts[snakemake.wildcards.cutout]
    if hasattr(snakemake.wildcards, "weather_year"):
        time = snakemake.wildcards.weather_year
        cutout_params["time"] = [time, time]
    if "time" not in cutout_params:
-        snapshots = pd.date_range(freq="h", **snakemake.config["snapshots"])
+        snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
        cutout_params["time"] = [snapshots[0], snapshots[-1]]
    cutout_params["time"] = slice(*cutout_params["time"])
--- a/scripts/build_electricity_demand.py
+++ b/scripts/build_electricity_demand.py
@ -285,7 +285,7 @@ if __name__ == "__main__":
            start=weather_year, end=str(int(weather_year) + 1), inclusive="left"
        )
    else:
-        snapshots = snakemake.config["snapshots"]
+        snapshots = snakemake.params.snapshots
    snapshots = pd.date_range(freq="h", **snapshots)
    fixed_year = snakemake.config["load"].get("fixed_year", False)
@ -295,16 +295,17 @@ if __name__ == "__main__":
        else slice(snapshots[0], snapshots[-1])
    )
-    powerstatistics = snakemake.config["load"]["power_statistics"]
+    powerstatistics = snakemake.params.load["power_statistics"]
-    interpolate_limit = snakemake.config["load"]["interpolate_limit"]
+    interpolate_limit = snakemake.params.load["interpolate_limit"]
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
-    snapshots = pd.date_range(freq="h", **snakemake.config["snapshots"])
+    snapshots = pd.date_range(freq="h", **snakemake.params.snapshots)
    years = slice(snapshots[0], snapshots[-1])
-    time_shift = snakemake.config["load"]["time_shift_for_large_gaps"]
+    time_shift = snakemake.params.load["time_shift_for_large_gaps"]
    load = load_timeseries(snakemake.input[0], years, countries, powerstatistics)
-    if snakemake.config["load"]["manual_adjustments"]:
+    if snakemake.params.load["manual_adjustments"]:
        load = manual_adjustment(load, snakemake.input[0], powerstatistics)
    logger.info(f"Linearly interpolate gaps of size {interpolate_limit} and less.")
--- a/scripts/build_energy_totals.py
+++ b/scripts/build_energy_totals.py
@ -736,23 +736,26 @@ if __name__ == "__main__":
    logging.basicConfig(level=snakemake.config["logging"]["level"])
-    config = snakemake.config["energy"]
+    params = snakemake.params.energy
    data_year = int(config["energy_totals_year"])
    nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index("index")
    population = nuts3["pop"].groupby(nuts3.country).sum()
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    idees_countries = pd.Index(countries).intersection(eu28)
-    eurostat = build_eurostat(countries.difference(['CH']))
+    data_year = params["energy_totals_year"]
-    swiss = build_swiss()
+    report_year = snakemake.params.energy["eurostat_report_year"]
-    idees = build_idees(idees_countries)
+    input_eurostat = snakemake.input.eurostat
    eurostat = build_eurostat(input_eurostat, countries, report_year, data_year)
    swiss = build_swiss(data_year)
    idees = build_idees(idees_countries, data_year)
    energy = build_energy_totals(countries, eurostat, swiss, idees)
    energy.to_csv(snakemake.output.energy_name)
-    base_year_emissions = config["base_emissions_year"]
+    base_year_emissions = params["base_emissions_year"]
    emissions_scope = snakemake.params.energy["emissions"]
    eea_co2 = build_eea_co2(snakemake.input.co2, base_year_emissions, emissions_scope)
    eurostat_co2 = build_eurostat_co2(countries, eurostat, base_year_emissions)
--- a/scripts/build_heat_demand.py
+++ b/scripts/build_heat_demand.py
@ -35,7 +35,7 @@ if __name__ == "__main__":
        snapshots = dict(start=year, end=str(int(year) + 1), inclusive="left")
        cutout_name = cutout_name.format(weather_year=year)
    else:
-        snapshots = snakemake.config["snapshots"]
+        snapshots = snakemake.params.snapshots
    drop_leap_day = snakemake.config["atlite"].get("drop_leap_day", False)
    time = pd.date_range(freq="h", **snapshots)
--- a/scripts/build_hydro_profile.py
+++ b/scripts/build_hydro_profile.py
@ -169,10 +169,10 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_hydro_profile", weather_year="")
    configure_logging(snakemake)
-    config_hydro = snakemake.config["renewable"]["hydro"]
+    params_hydro = snakemake.params.hydro
    cutout = atlite.Cutout(snakemake.input.cutout)
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    country_shapes = (
        gpd.read_file(snakemake.input.country_shapes)
        .set_index("name")["geometry"]
@ -207,7 +207,7 @@ if __name__ == "__main__":
        normalize_using_yearly=eia_stats,
    )
-    if "clip_min_inflow" in config_hydro:
+    if "clip_min_inflow" in params_hydro:
-        inflow = inflow.where(inflow > config_hydro["clip_min_inflow"], 0)
+        inflow = inflow.where(inflow > params_hydro["clip_min_inflow"], 0)
    inflow.to_netcdf(snakemake.output.profile)
--- a/scripts/build_industrial_distribution_key.py
+++ b/scripts/build_industrial_distribution_key.py
@ -73,7 +73,7 @@ def prepare_hotmaps_database(regions):
    df[["srid", "coordinates"]] = df.geom.str.split(";", expand=True)
-    if snakemake.config["industry"].get("hotmaps_locate_missing", False):
+    if snakemake.params.hotmaps_locate_missing:
        df = locate_missing_industrial_sites(df)
    # remove those sites without valid locations
@ -144,7 +144,7 @@ if __name__ == "__main__":
    logging.basicConfig(level=snakemake.config["logging"]["level"])
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    regions = gpd.read_file(snakemake.input.regions_onshore).set_index("name")
--- a/scripts/build_industrial_energy_demand_per_country_today.py
+++ b/scripts/build_industrial_energy_demand_per_country_today.py
@ -101,8 +101,8 @@ def add_ammonia_energy_demand(demand):
    def get_ammonia_by_fuel(x):
        fuels = {
-            "gas": config["MWh_CH4_per_tNH3_SMR"],
+            "gas": params["MWh_CH4_per_tNH3_SMR"],
-            "electricity": config["MWh_elec_per_tNH3_SMR"],
+            "electricity": params["MWh_elec_per_tNH3_SMR"],
        }
        return pd.Series({k: x * v for k, v in fuels.items()})
@ -112,7 +112,7 @@ def add_ammonia_energy_demand(demand):
        index=demand.index, fill_value=0.0
    )
-    ammonia = pd.DataFrame({"ammonia": ammonia * config["MWh_NH3_per_tNH3"]}).T
+    ammonia = pd.DataFrame({"ammonia": ammonia * params["MWh_NH3_per_tNH3"]}).T
    demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0)
@ -178,9 +178,9 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_industrial_energy_demand_per_country_today")
-    config = snakemake.config["industry"]
+    params = snakemake.params.industry
-    year = config.get("reference_year", 2015)
+    year = params.get("reference_year", 2015)
-    countries = pd.Index(snakemake.config["countries"])
+    countries = pd.Index(snakemake.params.countries)
    demand = industrial_energy_demand(countries.intersection(eu28), year)
--- a/scripts/build_industrial_production_per_country.py
+++ b/scripts/build_industrial_production_per_country.py
@ -264,9 +264,9 @@ def separate_basic_chemicals(demand, year):
    # assume HVC, methanol, chlorine production proportional to non-ammonia basic chemicals
    distribution_key = demand["Basic chemicals"] / demand["Basic chemicals"].sum()
-    demand["HVC"] = config["HVC_production_today"] * 1e3 * distribution_key
+    demand["HVC"] = params["HVC_production_today"] * 1e3 * distribution_key
-    demand["Chlorine"] = config["chlorine_production_today"] * 1e3 * distribution_key
+    demand["Chlorine"] = params["chlorine_production_today"] * 1e3 * distribution_key
-    demand["Methanol"] = config["methanol_production_today"] * 1e3 * distribution_key
+    demand["Methanol"] = params["methanol_production_today"] * 1e3 * distribution_key
    demand.drop(columns=["Basic chemicals"], inplace=True)
@ -279,11 +279,11 @@ if __name__ == "__main__":
    logging.basicConfig(level=snakemake.config["logging"]["level"])
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
-    year = snakemake.config["industry"]["reference_year"]
+    year = snakemake.params.industry["reference_year"]
-    config = snakemake.config["industry"]
+    params = snakemake.params.industry
    jrc_dir = snakemake.input.jrc
    eurostat_dir = snakemake.input.eurostat
--- a/scripts/build_industrial_production_per_country_tomorrow.py
+++ b/scripts/build_industrial_production_per_country_tomorrow.py
@ -15,7 +15,7 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_industrial_production_per_country_tomorrow")
-    config = snakemake.config["industry"]
+    params = snakemake.params.industry
    investment_year = int(snakemake.wildcards.planning_horizons)
@ -25,8 +25,8 @@ if __name__ == "__main__":
    keys = ["Integrated steelworks", "Electric arc"]
    total_steel = production[keys].sum(axis=1)
-    st_primary_fraction = get(config["St_primary_fraction"], investment_year)
+    st_primary_fraction = get(params["St_primary_fraction"], investment_year)
-    dri_fraction = get(config["DRI_fraction"], investment_year)
+    dri_fraction = get(params["DRI_fraction"], investment_year)
    int_steel = production["Integrated steelworks"].sum()
    fraction_persistent_primary = st_primary_fraction * total_steel.sum() / int_steel
@ -51,7 +51,7 @@ if __name__ == "__main__":
    key_pri = "Aluminium - primary production"
    key_sec = "Aluminium - secondary production"
-    al_primary_fraction = get(config["Al_primary_fraction"], investment_year)
+    al_primary_fraction = get(params["Al_primary_fraction"], investment_year)
    fraction_persistent_primary = (
        al_primary_fraction * total_aluminium.sum() / production[key_pri].sum()
    )
@ -60,15 +60,15 @@ if __name__ == "__main__":
    production[key_sec] = total_aluminium - production[key_pri]
    production["HVC (mechanical recycling)"] = (
-        get(config["HVC_mechanical_recycling_fraction"], investment_year)
+        get(params["HVC_mechanical_recycling_fraction"], investment_year)
        * production["HVC"]
    )
    production["HVC (chemical recycling)"] = (
-        get(config["HVC_chemical_recycling_fraction"], investment_year)
+        get(params["HVC_chemical_recycling_fraction"], investment_year)
        * production["HVC"]
    )
-    production["HVC"] *= get(config["HVC_primary_fraction"], investment_year)
+    production["HVC"] *= get(params["HVC_primary_fraction"], investment_year)
    fn = snakemake.output.industrial_production_per_country_tomorrow
    production.to_csv(fn, float_format="%.2f")
--- a/scripts/build_industry_sector_ratios.py
+++ b/scripts/build_industry_sector_ratios.py
@ -185,10 +185,10 @@ def iron_and_steel():
    df[sector] = df["Electric arc"]
    # add H2 consumption for DRI at 1.7 MWh H2 /ton steel
-    df.at["hydrogen", sector] = config["H2_DRI"]
+    df.at["hydrogen", sector] = params["H2_DRI"]
    # add electricity consumption in DRI shaft (0.322 MWh/tSl)
-    df.at["elec", sector] += config["elec_DRI"]
+    df.at["elec", sector] += params["elec_DRI"]
    ## Integrated steelworks
    # could be used in combination with CCS)
@ -383,19 +383,19 @@ def chemicals_industry():
    assert s_emi.index[0] == sector
    # convert from MtHVC/a to ktHVC/a
-    s_out = config["HVC_production_today"] * 1e3
+    s_out = params["HVC_production_today"] * 1e3
    # tCO2/t material
    df.loc["process emission", sector] += (
        s_emi["Process emissions"]
-        - config["petrochemical_process_emissions"] * 1e3
+        - params["petrochemical_process_emissions"] * 1e3
-        - config["NH3_process_emissions"] * 1e3
+        - params["NH3_process_emissions"] * 1e3
    ) / s_out
    # emissions originating from feedstock, could be non-fossil origin
    # tCO2/t material
    df.loc["process emission from feedstock", sector] += (
-        config["petrochemical_process_emissions"] * 1e3
+        params["petrochemical_process_emissions"] * 1e3
    ) / s_out
    # convert from ktoe/a to GWh/a
@ -405,18 +405,18 @@ def chemicals_industry():
    # subtract ammonia energy demand (in ktNH3/a)
    ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0)
    ammonia_total = ammonia.loc[ammonia.index.intersection(eu28), str(year)].sum()
-    df.loc["methane", sector] -= ammonia_total * config["MWh_CH4_per_tNH3_SMR"]
+    df.loc["methane", sector] -= ammonia_total * params["MWh_CH4_per_tNH3_SMR"]
-    df.loc["elec", sector] -= ammonia_total * config["MWh_elec_per_tNH3_SMR"]
+    df.loc["elec", sector] -= ammonia_total * params["MWh_elec_per_tNH3_SMR"]
    # subtract chlorine demand
-    chlorine_total = config["chlorine_production_today"]
+    chlorine_total = params["chlorine_production_today"]
-    df.loc["hydrogen", sector] -= chlorine_total * config["MWh_H2_per_tCl"]
+    df.loc["hydrogen", sector] -= chlorine_total * params["MWh_H2_per_tCl"]
-    df.loc["elec", sector] -= chlorine_total * config["MWh_elec_per_tCl"]
+    df.loc["elec", sector] -= chlorine_total * params["MWh_elec_per_tCl"]
    # subtract methanol demand
-    methanol_total = config["methanol_production_today"]
+    methanol_total = params["methanol_production_today"]
-    df.loc["methane", sector] -= methanol_total * config["MWh_CH4_per_tMeOH"]
+    df.loc["methane", sector] -= methanol_total * params["MWh_CH4_per_tMeOH"]
-    df.loc["elec", sector] -= methanol_total * config["MWh_elec_per_tMeOH"]
+    df.loc["elec", sector] -= methanol_total * params["MWh_elec_per_tMeOH"]
    # MWh/t material
    df.loc[sources, sector] = df.loc[sources, sector] / s_out
@ -427,37 +427,37 @@ def chemicals_industry():
    sector = "HVC (mechanical recycling)"
    df[sector] = 0.0
-    df.loc["elec", sector] = config["MWh_elec_per_tHVC_mechanical_recycling"]
+    df.loc["elec", sector] = params["MWh_elec_per_tHVC_mechanical_recycling"]
    # HVC chemical recycling
    sector = "HVC (chemical recycling)"
    df[sector] = 0.0
-    df.loc["elec", sector] = config["MWh_elec_per_tHVC_chemical_recycling"]
+    df.loc["elec", sector] = params["MWh_elec_per_tHVC_chemical_recycling"]
    # Ammonia
    sector = "Ammonia"
    df[sector] = 0.0
-    if snakemake.config["sector"].get("ammonia", False):
+    if snakemake.params.ammonia:
-        df.loc["ammonia", sector] = config["MWh_NH3_per_tNH3"]
+        df.loc["ammonia", sector] = params["MWh_NH3_per_tNH3"]
    else:
-        df.loc["hydrogen", sector] = config["MWh_H2_per_tNH3_electrolysis"]
+        df.loc["hydrogen", sector] = params["MWh_H2_per_tNH3_electrolysis"]
-        df.loc["elec", sector] = config["MWh_elec_per_tNH3_electrolysis"]
+        df.loc["elec", sector] = params["MWh_elec_per_tNH3_electrolysis"]
    # Chlorine
    sector = "Chlorine"
    df[sector] = 0.0
-    df.loc["hydrogen", sector] = config["MWh_H2_per_tCl"]
+    df.loc["hydrogen", sector] = params["MWh_H2_per_tCl"]
-    df.loc["elec", sector] = config["MWh_elec_per_tCl"]
+    df.loc["elec", sector] = params["MWh_elec_per_tCl"]
    # Methanol
    sector = "Methanol"
    df[sector] = 0.0
-    df.loc["methane", sector] = config["MWh_CH4_per_tMeOH"]
+    df.loc["methane", sector] = params["MWh_CH4_per_tMeOH"]
-    df.loc["elec", sector] = config["MWh_elec_per_tMeOH"]
+    df.loc["elec", sector] = params["MWh_elec_per_tMeOH"]
    # Other chemicals
@ -1465,10 +1465,10 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_industry_sector_ratios")
-    # TODO make config option
+    # TODO make params option
    year = 2015
-    config = snakemake.config["industry"]
+    params = snakemake.params.industry
    df = pd.concat(
        [
--- a/scripts/build_powerplants.py
+++ b/scripts/build_powerplants.py
@ -98,13 +98,15 @@ def add_custom_powerplants(ppl, custom_powerplants, custom_ppl_query=False):
 def replace_natural_gas_technology(df):
-    mapping = {"Steam Turbine": "OCGT", "Combustion Engine": "OCGT"}
+    mapping = {"Steam Turbine": "CCGT", "Combustion Engine": "OCGT"}
-    tech = df.Technology.replace(mapping).fillna("OCGT")
+    tech = df.Technology.replace(mapping).fillna("CCGT")
-    return df.Technology.where(df.Fueltype != "Natural Gas", tech)
+    return df.Technology.mask(df.Fueltype == "Natural Gas", tech)
 def replace_natural_gas_fueltype(df):
-    return df.Fueltype.where(df.Fueltype != "Natural Gas", df.Technology)
+    return df.Fueltype.mask(
        (df.Technology == "OCGT") | (df.Technology == "CCGT"), "Natural Gas"
    )
 if __name__ == "__main__":
@ -115,7 +117,7 @@ if __name__ == "__main__":
    configure_logging(snakemake)
    n = pypsa.Network(snakemake.input.base_network)
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    ppl = (
        pm.powerplants(from_url=True)
@ -134,12 +136,12 @@ if __name__ == "__main__":
    ppl = ppl.query('not (Country in @available_countries and Fueltype == "Bioenergy")')
    ppl = pd.concat([ppl, opsd])
-    ppl_query = snakemake.config["electricity"]["powerplants_filter"]
+    ppl_query = snakemake.params.powerplants_filter
    if isinstance(ppl_query, str):
        ppl.query(ppl_query, inplace=True)
    # add carriers from own powerplant files:
-    custom_ppl_query = snakemake.config["electricity"]["custom_powerplants"]
+    custom_ppl_query = snakemake.params.custom_powerplants
    ppl = add_custom_powerplants(
        ppl, snakemake.input.custom_powerplants, custom_ppl_query
    )
@ -149,6 +151,7 @@ if __name__ == "__main__":
        logging.warning(f"No powerplants known in: {', '.join(countries_wo_ppl)}")
    substations = n.buses.query("substation_lv")
    ppl = ppl.dropna(subset=["lat", "lon"])
    ppl = map_country_bus(ppl, substations)
    bus_null_b = ppl["bus"].isnull()
--- a/scripts/build_renewable_profiles.py
+++ b/scripts/build_renewable_profiles.py
@ -64,7 +64,7 @@ Inputs
 - ``resources/offshore_shapes.geojson``: confer :ref:`shapes`
 - ``resources/regions_onshore.geojson``: (if not offshore wind), confer :ref:`busregions`
 - ``resources/regions_offshore.geojson``: (if offshore wind), :ref:`busregions`
- ``"cutouts/" + config["renewable"][{technology}]['cutout']``: :ref:`cutout`
+- ``"cutouts/" + params["renewable"][{technology}]['cutout']``: :ref:`cutout`
 - ``networks/base.nc``: :ref:`base`
 Outputs
@ -188,7 +188,7 @@ import geopandas as gpd
 import numpy as np
 import xarray as xr
 from _helpers import configure_logging
-from dask.distributed import Client, LocalCluster
+from dask.distributed import Client
 from pypsa.geo import haversine
 from shapely.geometry import LineString
@ -206,20 +206,23 @@ if __name__ == "__main__":
    nprocesses = int(snakemake.threads)
    noprogress = snakemake.config["run"].get("disable_progressbar", True)
-    config = snakemake.config["renewable"][snakemake.wildcards.technology]
+    noprogress = noprogress or not snakemake.config["atlite"]["show_progress"]
-    resource = config["resource"]  # pv panel config / wind turbine config
+    params = snakemake.params.renewable[snakemake.wildcards.technology]
-    correction_factor = config.get("correction_factor", 1.0)
+    resource = params["resource"]  # pv panel params / wind turbine params
-    capacity_per_sqkm = config["capacity_per_sqkm"]
+    correction_factor = params.get("correction_factor", 1.0)
-    p_nom_max_meth = config.get("potential", "conservative")
+    capacity_per_sqkm = params["capacity_per_sqkm"]
    p_nom_max_meth = params.get("potential", "conservative")
-    if isinstance(config.get("corine", {}), list):
+    if isinstance(params.get("corine", {}), list):
-        config["corine"] = {"grid_codes": config["corine"]}
+        params["corine"] = {"grid_codes": params["corine"]}
    if correction_factor != 1.0:
        logger.info(f"correction_factor is set as {correction_factor}")
-    cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
+    if nprocesses > 1:
-    client = Client(cluster, asynchronous=True)
+        client = Client(n_workers=nprocesses, threads_per_worker=1)
    else:
        client = None
    cutout = atlite.Cutout(snakemake.input.cutout)
    regions = gpd.read_file(snakemake.input.regions)
@ -231,13 +234,13 @@ if __name__ == "__main__":
    regions = regions.set_index("name").rename_axis("bus")
    buses = regions.index
-    res = config.get("excluder_resolution", 100)
+    res = params.get("excluder_resolution", 100)
    excluder = atlite.ExclusionContainer(crs=3035, res=res)
-    if config["natura"]:
+    if params["natura"]:
        excluder.add_raster(snakemake.input.natura, nodata=0, allow_no_overlap=True)
-    corine = config.get("corine", {})
+    corine = params.get("corine", {})
    if "grid_codes" in corine:
        codes = corine["grid_codes"]
        excluder.add_raster(snakemake.input.corine, codes=codes, invert=True, crs=3035)
@ -248,28 +251,28 @@ if __name__ == "__main__":
            snakemake.input.corine, codes=codes, buffer=buffer, crs=3035
        )
-    if "ship_threshold" in config:
+    if "ship_threshold" in params:
        shipping_threshold = (
-            config["ship_threshold"] * 8760 * 6
+            params["ship_threshold"] * 8760 * 6
        )  # approximation because 6 years of data which is hourly collected
        func = functools.partial(np.less, shipping_threshold)
        excluder.add_raster(
            snakemake.input.ship_density, codes=func, crs=4326, allow_no_overlap=True
        )
-    if config.get("max_depth"):
+    if params.get("max_depth"):
        # lambda not supported for atlite + multiprocessing
        # use named function np.greater with partially frozen argument instead
        # and exclude areas where: -max_depth > grid cell depth
-        func = functools.partial(np.greater, -config["max_depth"])
+        func = functools.partial(np.greater, -params["max_depth"])
        excluder.add_raster(snakemake.input.gebco, codes=func, crs=4326, nodata=-1000)
-    if "min_shore_distance" in config:
+    if "min_shore_distance" in params:
-        buffer = config["min_shore_distance"]
+        buffer = params["min_shore_distance"]
        excluder.add_geometry(snakemake.input.country_shapes, buffer=buffer)
-    if "max_shore_distance" in config:
+    if "max_shore_distance" in params:
-        buffer = config["max_shore_distance"]
+        buffer = params["max_shore_distance"]
        excluder.add_geometry(
            snakemake.input.country_shapes, buffer=buffer, invert=True
        )
@ -291,6 +294,7 @@ if __name__ == "__main__":
    potential = capacity_per_sqkm * availability.sum("bus") * area
    func = getattr(cutout, resource.pop("method"))
    if client is not None:
        resource["dask_kwargs"] = {"scheduler": client}
    capacity_factor = correction_factor * func(capacity_factor=True, **resource)
    layout = capacity_factor * area * capacity_per_sqkm
@ -360,13 +364,13 @@ if __name__ == "__main__":
    # select only buses with some capacity and minimal capacity factor
    ds = ds.sel(
        bus=(
-            (ds["profile"].mean("time") > config.get("min_p_max_pu", 0.0))
+            (ds["profile"].mean("time") > params.get("min_p_max_pu", 0.0))
-            & (ds["p_nom_max"] > config.get("min_p_nom_max", 0.0))
+            & (ds["p_nom_max"] > params.get("min_p_nom_max", 0.0))
        )
    )
-    if "clip_p_max_pu" in config:
+    if "clip_p_max_pu" in params:
-        min_p_max_pu = config["clip_p_max_pu"]
+        min_p_max_pu = params["clip_p_max_pu"]
        ds["profile"] = ds["profile"].where(ds["profile"] >= min_p_max_pu, 0)
    ds.to_netcdf(snakemake.output.profile)
--- a/scripts/build_retro_cost.py
+++ b/scripts/build_retro_cost.py
@ -305,7 +305,7 @@ def prepare_building_stock_data():
    u_values.set_index(["country_code", "subsector", "bage", "type"], inplace=True)
    #  only take in config.yaml specified countries into account
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    area_tot = area_tot.loc[countries]
    return u_values, country_iso_dic, countries, area_tot, area
@ -513,7 +513,7 @@ def prepare_cost_retro(country_iso_dic):
 def prepare_temperature_data():
    """
-    returns the temperature dependent data for each country:
+    Returns the temperature dependent data for each country:
    d_heat             : length of heating season pd.Series(index=countries) [days/year]
                         on those days, daily average temperature is below
@ -621,7 +621,7 @@ def calculate_costs(u_values, l, cost_retro, window_assumptions):
 def calculate_new_u(u_values, l, l_weight, window_assumptions, k=0.035):
    """
-    calculate U-values after building retrofitting, depending on the old
+    Calculate U-values after building retrofitting, depending on the old
    U-values (u_values). This is for simple insulation measuers, adding an
    additional layer of insulation.
@ -682,7 +682,7 @@ def map_tabula_to_hotmaps(df_tabula, df_hotmaps, column_prefix):
 def get_solar_gains_per_year(window_area):
    """
-    returns solar heat gains during heating season in [kWh/a] depending on the
+    Returns solar heat gains during heating season in [kWh/a] depending on the
    window area [m^2] of the building, assuming a equal distributed window
    orientation (east, south, north, west)
    """
@ -698,8 +698,8 @@ def get_solar_gains_per_year(window_area):
 def map_to_lstrength(l_strength, df):
    """
-    renames column names from a pandas dataframe to map tabula retrofitting
+    Renames column names from a pandas dataframe to map tabula retrofitting
-    strengths [2 = moderate, 3 = ambitious] to l_strength
+    strengths [2 = moderate, 3 = ambitious] to l_strength.
    """
    middle = len(l_strength) // 2
    map_to_l = pd.MultiIndex.from_arrays(
@ -718,7 +718,7 @@ def map_to_lstrength(l_strength, df):
 def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor):
    """
-    calculates total annual heat losses Q_ht for different insulation
+    Calculates total annual heat losses Q_ht for different insulation
    thicknesses (l_strength), depending on current insulation state (u_values),
    standard building topologies and air ventilation from TABULA (data_tabula)
    and the accumulated difference between internal and external temperature
@ -840,7 +840,7 @@ def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor)
 def calculate_heat_gains(data_tabula, heat_transfer_perm2, d_heat):
    """
-    calculates heat gains Q_gain [W/m^2], which consititure from gains by:
+    Calculates heat gains Q_gain [W/m^2], which consititure from gains by:
    (1) solar radiation (2) internal heat gains
    """
@ -885,7 +885,7 @@ def calculate_space_heat_savings(
    u_values, data_tabula, l_strength, temperature_factor, d_heat
 ):
    """
-    calculates space heat savings (dE_space [per unit of unrefurbished state])
+    Calculates space heat savings (dE_space [per unit of unrefurbished state])
    through retrofitting of the thermal envelope by additional insulation
    material (l_strength[m])
    """
@ -1040,7 +1040,7 @@ if __name__ == "__main__":
    #  ********  config  *********************************************************
-    retro_opts = snakemake.config["sector"]["retrofitting"]
+    retro_opts = snakemake.params.retrofitting
    interest_rate = retro_opts["interest_rate"]
    annualise_cost = retro_opts["annualise_cost"]  # annualise the investment costs
    tax_weighting = retro_opts[
--- a/scripts/build_sequestration_potentials.py
+++ b/scripts/build_sequestration_potentials.py
@ -41,7 +41,7 @@ if __name__ == "__main__":
            "build_sequestration_potentials", simpl="", clusters="181"
        )
-    cf = snakemake.config["sector"]["regional_co2_sequestration_potential"]
+    cf = snakemake.params.sequestration_potential
    gdf = gpd.read_file(snakemake.input.sequestration_potential[0])
--- a/scripts/build_shapes.py
+++ b/scripts/build_shapes.py
@ -234,6 +234,7 @@ def nuts3(country_shapes, nuts3, nuts3pop, nuts3gdp, ch_cantons, ch_popgdp):
    manual = gpd.GeoDataFrame(
        [["BA1", "BA", 3871.0], ["RS1", "RS", 7210.0], ["AL1", "AL", 2893.0]],
        columns=["NUTS_ID", "country", "pop"],
        geometry=gpd.GeoSeries(),
    )
    manual["geometry"] = manual["country"].map(country_shapes)
    manual = manual.dropna()
@ -254,13 +255,11 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("build_shapes")
    configure_logging(snakemake)
-    country_shapes = countries(
+    country_shapes = countries(snakemake.input.naturalearth, snakemake.params.countries)
        snakemake.input.naturalearth, snakemake.config["countries"]
    )
    country_shapes.reset_index().to_file(snakemake.output.country_shapes)
    offshore_shapes = eez(
-        country_shapes, snakemake.input.eez, snakemake.config["countries"]
+        country_shapes, snakemake.input.eez, snakemake.params.countries
    )
    offshore_shapes.reset_index().to_file(snakemake.output.offshore_shapes)
--- a/scripts/build_solar_thermal_profiles.py
+++ b/scripts/build_solar_thermal_profiles.py
@ -28,7 +28,7 @@ if __name__ == "__main__":
    cluster = LocalCluster(n_workers=nprocesses, threads_per_worker=1)
    client = Client(cluster, asynchronous=True)
-    config = snakemake.config["solar_thermal"]
+    config = snakemake.params.solar_thermal
    cutout_name = snakemake.input.cutout
    year = snakemake.wildcards.weather_year
@ -37,7 +37,7 @@ if __name__ == "__main__":
        snapshots = dict(start=year, end=str(int(year) + 1), inclusive="left")
        cutout_name = cutout_name.format(weather_year=year)
    else:
-        snapshots = snakemake.config["snapshots"]
+        snapshots = snakemake.params.snapshots
    time = pd.date_range(freq="h", **snapshots)
    if snakemake.config["atlite"].get("drop_leap_day", False):
--- a/scripts/build_temperature_profiles.py
+++ b/scripts/build_temperature_profiles.py
@ -34,7 +34,7 @@ if __name__ == "__main__":
        snapshots = dict(start=year, end=str(int(year) + 1), inclusive="left")
        cutout_name = cutout_name.format(weather_year=year)
    else:
-        snapshots = snakemake.config["snapshots"]
+        snapshots = snakemake.params.snapshots
    time = pd.date_range(freq="h", **snapshots)
    if snakemake.config["atlite"].get("drop_leap_day", False):
--- a/scripts/build_transport_demand.py
+++ b/scripts/build_transport_demand.py
@ -176,13 +176,13 @@ if __name__ == "__main__":
        snakemake.input.pop_weighted_energy_totals, index_col=0
    )
-    options = snakemake.config["sector"]
+    options = snakemake.params.sector
    year = snakemake.wildcards.weather_year
    snapshots = (
        dict(start=year, end=str(int(year) + 1), inclusive="left")
        if year
-        else snakemake.config["snapshots"]
+        else snakemake.params.snapshots
    )
    snapshots = pd.date_range(freq="h", **snapshots, tz="UTC")
    if snakemake.config["atlite"].get("drop_leap_day", False):
--- a/scripts/cluster_network.py
+++ b/scripts/cluster_network.py
@ -89,7 +89,7 @@ Description
    **Is it possible to run the model without the** ``simplify_network`` **rule?**
        No, the network clustering methods in the PyPSA module
-        `pypsa.networkclustering <https://github.com/PyPSA/PyPSA/blob/master/pypsa/networkclustering.py>`_
+        `pypsa.clustering.spatial <https://github.com/PyPSA/PyPSA/blob/master/pypsa/clustering/spatial.py>`_
        do not work reliably with multiple voltage levels and transformers.
 .. tip::
@ -133,8 +133,8 @@ import pandas as pd
 import pyomo.environ as po
 import pypsa
 import seaborn as sns
-from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max
+from _helpers import configure_logging, update_p_nom_max
-from pypsa.networkclustering import (
+from pypsa.clustering.spatial import (
    busmap_by_greedy_modularity,
    busmap_by_hac,
    busmap_by_kmeans,
@ -186,7 +186,7 @@ def get_feature_for_hac(n, buses_i=None, feature=None):
    if "offwind" in carriers:
        carriers.remove("offwind")
        carriers = np.append(
-            carriers, network.generators.carrier.filter(like="offwind").unique()
+            carriers, n.generators.carrier.filter(like="offwind").unique()
        )
    if feature.split("-")[1] == "cap":
@ -395,10 +395,6 @@ def clustering_for_n_clusters(
    extended_link_costs=0,
    focus_weights=None,
 ):
    bus_strategies, generator_strategies = get_aggregation_strategies(
        aggregation_strategies
    )
    if not isinstance(custom_busmap, pd.Series):
        busmap = busmap_for_n_clusters(
            n, n_clusters, solver_name, focus_weights, algorithm, feature
@ -406,15 +402,20 @@ def clustering_for_n_clusters(
    else:
        busmap = custom_busmap
    line_strategies = aggregation_strategies.get("lines", dict())
    generator_strategies = aggregation_strategies.get("generators", dict())
    one_port_strategies = aggregation_strategies.get("one_ports", dict())
    clustering = get_clustering_from_busmap(
        n,
        busmap,
        bus_strategies=bus_strategies,
        aggregate_generators_weighted=True,
        aggregate_generators_carriers=aggregate_carriers,
        aggregate_one_ports=["Load", "StorageUnit"],
        line_length_factor=line_length_factor,
        line_strategies=line_strategies,
        generator_strategies=generator_strategies,
        one_port_strategies=one_port_strategies,
        scale_link_capital_costs=False,
    )
@ -424,7 +425,10 @@ def clustering_for_n_clusters(
            n.links.eval("underwater_fraction * length").div(nc.links.length).dropna()
        )
        nc.links["capital_cost"] = nc.links["capital_cost"].add(
-            (nc.links.length - n.links.length).clip(lower=0).mul(extended_link_costs),
+            (nc.links.length - n.links.length)
            .clip(lower=0)
            .mul(extended_link_costs)
            .dropna(),
            fill_value=0,
        )
@ -462,28 +466,20 @@ if __name__ == "__main__":
        )
    configure_logging(snakemake)
    params = snakemake.params
    solver_name = snakemake.config["solving"]["solver"]["name"]
    n = pypsa.Network(snakemake.input.network)
-    focus_weights = snakemake.config.get("focus_weights", None)
+    exclude_carriers = params.cluster_network["exclude_carriers"]
    renewable_carriers = pd.Index(
        [
            tech
            for tech in n.generators.carrier.unique()
            if tech in snakemake.config["renewable"]
        ]
    )
    exclude_carriers = snakemake.config["clustering"]["cluster_network"].get(
        "exclude_carriers", []
    )
    aggregate_carriers = set(n.generators.carrier) - set(exclude_carriers)
    conventional_carriers = set(params.conventional_carriers)
    if snakemake.wildcards.clusters.endswith("m"):
        n_clusters = int(snakemake.wildcards.clusters[:-1])
-        conventional = set(
+        aggregate_carriers = params.conventional_carriers & aggregate_carriers
-            snakemake.config["electricity"].get("conventional_carriers", [])
+    elif snakemake.wildcards.clusters.endswith("c"):
-        )
+        n_clusters = int(snakemake.wildcards.clusters[:-1])
-        aggregate_carriers = conventional.intersection(aggregate_carriers)
+        aggregate_carriers = aggregate_carriers - conventional_carriers
    elif snakemake.wildcards.clusters == "all":
        n_clusters = len(n.buses)
    else:
@ -493,37 +489,20 @@ if __name__ == "__main__":
        # Fast-path if no clustering is necessary
        busmap = n.buses.index.to_series()
        linemap = n.lines.index.to_series()
-        clustering = pypsa.networkclustering.Clustering(
+        clustering = pypsa.clustering.spatial.Clustering(
            n, busmap, linemap, linemap, pd.Series(dtype="O")
        )
    else:
        line_length_factor = snakemake.config["lines"]["length_factor"]
        Nyears = n.snapshot_weightings.objective.sum() / 8760
        hvac_overhead_cost = load_costs(
            snakemake.input.tech_costs,
-            snakemake.config["costs"],
+            params.costs,
-            snakemake.config["electricity"],
+            params.max_hours,
            Nyears,
        ).at["HVAC overhead", "capital_cost"]
-        def consense(x):
+        custom_busmap = params.custom_busmap
            v = x.iat[0]
            assert (
                x == v
            ).all() or x.isnull().all(), "The `potential` configuration option must agree for all renewable carriers, for now!"
            return v
        aggregation_strategies = snakemake.config["clustering"].get(
            "aggregation_strategies", {}
        )
        # translate str entries of aggregation_strategies to pd.Series functions:
        aggregation_strategies = {
            p: {k: getattr(pd.Series, v) for k, v in aggregation_strategies[p].items()}
            for p in aggregation_strategies.keys()
        }
        custom_busmap = snakemake.config["enable"].get("custom_busmap", False)
        if custom_busmap:
            custom_busmap = pd.read_csv(
                snakemake.input.custom_busmap, index_col=0, squeeze=True
@ -531,21 +510,18 @@ if __name__ == "__main__":
            custom_busmap.index = custom_busmap.index.astype(str)
            logger.info(f"Imported custom busmap from {snakemake.input.custom_busmap}")
        cluster_config = snakemake.config.get("clustering", {}).get(
            "cluster_network", {}
        )
        clustering = clustering_for_n_clusters(
            n,
            n_clusters,
            custom_busmap,
            aggregate_carriers,
-            line_length_factor,
+            params.length_factor,
-            aggregation_strategies,
+            params.aggregation_strategies,
-            snakemake.config["solving"]["solver"]["name"],
+            solver_name,
-            cluster_config.get("algorithm", "hac"),
+            params.cluster_network["algorithm"],
-            cluster_config.get("feature", "solar+onwind-time"),
+            params.cluster_network["feature"],
            hvac_overhead_cost,
-            focus_weights,
+            params.focus_weights,
        )
    update_p_nom_max(clustering.network)
--- a/scripts/make_summary.py
+++ b/scripts/make_summary.py
@ -16,7 +16,6 @@ import sys
 import numpy as np
 import pandas as pd
 import pypsa
 from _helpers import override_component_attrs
 from prepare_sector_network import prepare_costs
 idx = pd.IndexSlice
@ -198,7 +197,7 @@ def calculate_costs(n, label, costs):
 def calculate_cumulative_cost():
-    planning_horizons = snakemake.config["scenario"]["planning_horizons"]
+    planning_horizons = snakemake.params.scenario["planning_horizons"]
    cumulative_cost = pd.DataFrame(
        index=df["costs"].sum().index,
@ -300,9 +299,9 @@ def calculate_energy(n, label, energy):
                )
                # remove values where bus is missing (bug in nomopyomo)
                no_bus = c.df.index[c.df["bus" + port] == ""]
-                totals.loc[no_bus] = n.component_attrs[c.name].loc[
+                totals.loc[no_bus] = float(
-                    "p" + port, "default"
+                    n.component_attrs[c.name].loc["p" + port, "default"]
-                ]
+                )
                c_energies -= totals.groupby(c.df.carrier).sum()
        c_energies = pd.concat([c_energies], keys=[c.list_name])
@ -660,8 +659,7 @@ def make_summaries(networks_dict):
    for label, filename in networks_dict.items():
        logger.info(f"Make summary for scenario {label}, using {filename}")
-        overrides = override_component_attrs(snakemake.input.overrides)
+        n = pypsa.Network(filename)
        n = pypsa.Network(filename, override_component_attrs=overrides)
        assign_carriers(n)
        assign_locations(n)
@ -689,20 +687,20 @@ if __name__ == "__main__":
        (weather_year, cluster, ll, opt + sector_opt, planning_horizon): "results/"
        + snakemake.params.RDIR
        + f"/postnetworks/elec_s{simpl}_{cluster}_l{ll}_{opt}_{sector_opt}_{planning_horizon}.nc"
-        for weather_year in snakemake.config["scenario"]["weather_year"]
+        for weather_year in snakemake.params.scenario["weather_year"]
-        for simpl in snakemake.config["scenario"]["simpl"]
+        for simpl in snakemake.params.scenario["simpl"]
-        for cluster in snakemake.config["scenario"]["clusters"]
+        for cluster in snakemake.params.scenario["clusters"]
-        for opt in snakemake.config["scenario"]["opts"]
+        for opt in snakemake.params.scenario["opts"]
-        for sector_opt in snakemake.config["scenario"]["sector_opts"]
+        for sector_opt in snakemake.params.scenario["sector_opts"]
-        for ll in snakemake.config["scenario"]["ll"]
+        for ll in snakemake.params.scenario["ll"]
-        for planning_horizon in snakemake.config["scenario"]["planning_horizons"]
+        for planning_horizon in snakemake.params.scenario["planning_horizons"]
    }
-    Nyears = len(pd.date_range(freq="h", **snakemake.config["snapshots"])) / 8760
+    Nyears = len(pd.date_range(freq="h", **snakemake.params.snapshots)) / 8760
    costs_db = prepare_costs(
        snakemake.input.costs,
-        snakemake.config["costs"],
+        snakemake.params.costs,
        Nyears,
    )
@ -712,7 +710,7 @@ if __name__ == "__main__":
    to_csv(df)
-    if snakemake.config["foresight"] == "myopic":
+    if snakemake.params.foresight == "myopic":
        cumulative_cost = calculate_cumulative_cost()
        cumulative_cost.to_csv(
            "results/" + snakemake.params.RDIR + "/csvs/cumulative_cost.csv"
--- a/scripts/plot_network.py
+++ b/scripts/plot_network.py
@ -20,7 +20,6 @@ import geopandas as gpd
 import matplotlib.pyplot as plt
 import pandas as pd
 import pypsa
 from _helpers import override_component_attrs
 from make_summary import assign_carriers
 from plot_summary import preferred_order, rename_techs
 from pypsa.plot import add_legend_circles, add_legend_lines, add_legend_patches
@ -70,7 +69,7 @@ def plot_map(
    transmission=False,
    with_legend=True,
 ):
-    tech_colors = snakemake.config["plotting"]["tech_colors"]
+    tech_colors = snakemake.params.plotting["tech_colors"]
    n = network.copy()
    assign_location(n)
@ -116,9 +115,7 @@ def plot_map(
    costs = costs.stack()  # .sort_index()
    # hack because impossible to drop buses...
-    eu_location = snakemake.config["plotting"].get(
+    eu_location = snakemake.params.plotting.get("eu_node_location", dict(x=-5.5, y=46))
        "eu_node_location", dict(x=-5.5, y=46)
    )
    n.buses.loc["EU gas", "x"] = eu_location["x"]
    n.buses.loc["EU gas", "y"] = eu_location["y"]
@ -315,7 +312,7 @@ def plot_h2_map(network, regions):
    h2_new = n.links[n.links.carrier == "H2 pipeline"]
    h2_retro = n.links[n.links.carrier == "H2 pipeline retrofitted"]
-    if snakemake.config["foresight"] == "myopic":
+    if snakemake.params.foresight == "myopic":
        # sum capacitiy for pipelines from different investment periods
        h2_new = group_pipes(h2_new)
@ -558,7 +555,7 @@ def plot_ch4_map(network):
    link_widths_used = max_usage / linewidth_factor
    link_widths_used[max_usage < line_lower_threshold] = 0.0
-    tech_colors = snakemake.config["plotting"]["tech_colors"]
+    tech_colors = snakemake.params.plotting["tech_colors"]
    pipe_colors = {
        "gas pipeline": "#f08080",
@ -700,7 +697,7 @@ def plot_map_without(network):
    # hack because impossible to drop buses...
    if "EU gas" in n.buses.index:
-        eu_location = snakemake.config["plotting"].get(
+        eu_location = snakemake.params.plotting.get(
            "eu_node_location", dict(x=-5.5, y=46)
        )
        n.buses.loc["EU gas", "x"] = eu_location["x"]
@ -876,7 +873,7 @@ def plot_series(network, carrier="AC", name="test"):
            stacked=True,
            linewidth=0.0,
            color=[
-                snakemake.config["plotting"]["tech_colors"][i.replace(suffix, "")]
+                snakemake.params.plotting["tech_colors"][i.replace(suffix, "")]
                for i in new_columns
            ],
        )
@ -933,12 +930,11 @@ if __name__ == "__main__":
    logging.basicConfig(level=snakemake.config["logging"]["level"])
-    overrides = override_component_attrs(snakemake.input.overrides)
+    n = pypsa.Network(snakemake.input.network)
    n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
    regions = gpd.read_file(snakemake.input.regions).set_index("name")
-    map_opts = snakemake.config["plotting"]["map"]
+    map_opts = snakemake.params.plotting["map"]
    if map_opts["boundaries"] is None:
        map_opts["boundaries"] = regions.total_bounds[[0, 2, 1, 3]] + [-1, 1, -1, 1]
--- a/scripts/plot_summary.py
+++ b/scripts/plot_summary.py
@ -142,10 +142,10 @@ def plot_costs():
    df = df.groupby(df.index.map(rename_techs)).sum()
-    to_drop = df.index[df.max(axis=1) < snakemake.config["plotting"]["costs_threshold"]]
+    to_drop = df.index[df.max(axis=1) < snakemake.params.plotting["costs_threshold"]]
    logger.info(
-        f"Dropping technology with costs below {snakemake.config['plotting']['costs_threshold']} EUR billion per year"
+        f"Dropping technology with costs below {snakemake.params['plotting']['costs_threshold']} EUR billion per year"
    )
    logger.debug(df.loc[to_drop])
@ -165,7 +165,7 @@ def plot_costs():
        kind="bar",
        ax=ax,
        stacked=True,
-        color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index],
+        color=[snakemake.params.plotting["tech_colors"][i] for i in new_index],
    )
    handles, labels = ax.get_legend_handles_labels()
@ -173,7 +173,7 @@ def plot_costs():
    handles.reverse()
    labels.reverse()
-    ax.set_ylim([0, snakemake.config["plotting"]["costs_max"]])
+    ax.set_ylim([0, snakemake.params.plotting["costs_max"]])
    ax.set_ylabel("System Cost [EUR billion per year]")
@ -201,11 +201,11 @@ def plot_energy():
    df = df.groupby(df.index.map(rename_techs)).sum()
    to_drop = df.index[
-        df.abs().max(axis=1) < snakemake.config["plotting"]["energy_threshold"]
+        df.abs().max(axis=1) < snakemake.params.plotting["energy_threshold"]
    ]
    logger.info(
-        f"Dropping all technology with energy consumption or production below {snakemake.config['plotting']['energy_threshold']} TWh/a"
+        f"Dropping all technology with energy consumption or production below {snakemake.params['plotting']['energy_threshold']} TWh/a"
    )
    logger.debug(df.loc[to_drop])
@ -227,7 +227,7 @@ def plot_energy():
        kind="bar",
        ax=ax,
        stacked=True,
-        color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index],
+        color=[snakemake.params.plotting["tech_colors"][i] for i in new_index],
    )
    handles, labels = ax.get_legend_handles_labels()
@ -237,8 +237,8 @@ def plot_energy():
    ax.set_ylim(
        [
-            snakemake.config["plotting"]["energy_min"],
+            snakemake.params.plotting["energy_min"],
-            snakemake.config["plotting"]["energy_max"],
+            snakemake.params.plotting["energy_max"],
        ]
    )
@ -287,7 +287,7 @@ def plot_balances():
        df = df.groupby(df.index.map(rename_techs)).sum()
        to_drop = df.index[
-            df.abs().max(axis=1) < snakemake.config["plotting"]["energy_threshold"] / 10
+            df.abs().max(axis=1) < snakemake.params.plotting["energy_threshold"] / 10
        ]
        if v[0] in co2_carriers:
@ -296,7 +296,7 @@ def plot_balances():
            units = "TWh/a"
        logger.debug(
-            f"Dropping technology energy balance smaller than {snakemake.config['plotting']['energy_threshold']/10} {units}"
+            f"Dropping technology energy balance smaller than {snakemake.params['plotting']['energy_threshold']/10} {units}"
        )
        logger.debug(df.loc[to_drop])
@ -317,7 +317,7 @@ def plot_balances():
            kind="bar",
            ax=ax,
            stacked=True,
-            color=[snakemake.config["plotting"]["tech_colors"][i] for i in new_index],
+            color=[snakemake.params.plotting["tech_colors"][i] for i in new_index],
        )
        handles, labels = ax.get_legend_handles_labels()
@ -455,10 +455,10 @@ def plot_carbon_budget_distribution(input_eurostat):
    ax1 = plt.subplot(gs1[0, 0])
    ax1.set_ylabel("CO$_2$ emissions (Gt per year)", fontsize=22)
    ax1.set_ylim([0, 5])
-    ax1.set_xlim([1990, snakemake.config["scenario"]["planning_horizons"][-1] + 1])
+    ax1.set_xlim([1990, snakemake.params.planning_horizons[-1] + 1])
    path_cb = "results/" + snakemake.params.RDIR + "/csvs/"
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    e_1990 = co2_emissions_year(countries, input_eurostat, opts, year=1990)
    CO2_CAP = pd.read_csv(path_cb + "carbon_budget_distribution.csv", index_col=0)
@ -555,7 +555,7 @@ if __name__ == "__main__":
    plot_balances()
-    for sector_opts in snakemake.config["scenario"]["sector_opts"]:
+    for sector_opts in snakemake.params.sector_opts:
        opts = sector_opts.split("-")
        for o in opts:
            if "cb" in o:
--- a/scripts/prepare_network.py
+++ b/scripts/prepare_network.py
@ -233,7 +233,22 @@ def enforce_autarky(n, only_crossborder=False):
    n.mremove("Link", links_rm)
-def set_line_nom_max(n, s_nom_max_set=np.inf, p_nom_max_set=np.inf):
+def set_line_nom_max(
    n,
    s_nom_max_set=np.inf,
    p_nom_max_set=np.inf,
    s_nom_max_ext=np.inf,
    p_nom_max_ext=np.inf,
 ):
    if np.isfinite(s_nom_max_ext) and s_nom_max_ext > 0:
        logger.info(f"Limiting line extensions to {s_nom_max_ext} MW")
        n.lines["s_nom_max"] = n.lines["s_nom"] + s_nom_max_ext
    if np.isfinite(p_nom_max_ext) and p_nom_max_ext > 0:
        logger.info(f"Limiting line extensions to {p_nom_max_ext} MW")
        hvdc = n.links.index[n.links.carrier == "DC"]
        n.links.loc[hvdc, "p_nom_max"] = n.links.loc[hvdc, "p_nom"] + p_nom_max_ext
    n.lines.s_nom_max.clip(upper=s_nom_max_set, inplace=True)
    n.links.p_nom_max.clip(upper=p_nom_max_set, inplace=True)
@ -258,12 +273,12 @@ if __name__ == "__main__":
    Nyears = n.snapshot_weightings.objective.sum() / 8760.0
    costs = load_costs(
        snakemake.input.tech_costs,
-        snakemake.config["costs"],
+        snakemake.params.costs,
-        snakemake.config["electricity"],
+        snakemake.params.max_hours,
        Nyears,
    )
-    set_line_s_max_pu(n, snakemake.config["lines"]["s_max_pu"])
+    set_line_s_max_pu(n, snakemake.params.lines["s_max_pu"])
    for o in opts:
        m = re.match(r"^\d+h$", o, re.IGNORECASE)
@ -282,11 +297,11 @@ if __name__ == "__main__":
        if "Co2L" in o:
            m = re.findall("[0-9]*\.?[0-9]+$", o)
            if len(m) > 0:
-                co2limit = float(m[0]) * snakemake.config["electricity"]["co2base"]
+                co2limit = float(m[0]) * snakemake.params.co2base
                add_co2limit(n, co2limit, Nyears)
                logger.info("Setting CO2 limit according to wildcard value.")
            else:
-                add_co2limit(n, snakemake.config["electricity"]["co2limit"], Nyears)
+                add_co2limit(n, snakemake.params.co2limit, Nyears)
                logger.info("Setting CO2 limit according to config value.")
            break
@ -298,11 +313,13 @@ if __name__ == "__main__":
                add_gaslimit(n, limit, Nyears)
                logger.info("Setting gas usage limit according to wildcard value.")
            else:
-                add_gaslimit(n, snakemake.config["electricity"].get("gaslimit"), Nyears)
+                add_gaslimit(n, snakemake.params.gaslimit, Nyears)
                logger.info("Setting gas usage limit according to config value.")
            break
    for o in opts:
        if "+" not in o:
            continue
        oo = o.split("+")
        suptechs = map(lambda c: c.split("-", 2)[0], n.carriers.index)
        if oo[0].startswith(tuple(suptechs)):
@ -327,7 +344,7 @@ if __name__ == "__main__":
                add_emission_prices(n, dict(co2=float(m[0])))
            else:
                logger.info("Setting emission prices according to config value.")
-                add_emission_prices(n, snakemake.config["costs"]["emission_prices"])
+                add_emission_prices(n, snakemake.params.costs["emission_prices"])
            break
    ll_type, factor = snakemake.wildcards.ll[0], snakemake.wildcards.ll[1:]
@ -335,8 +352,10 @@ if __name__ == "__main__":
    set_line_nom_max(
        n,
-        s_nom_max_set=snakemake.config["lines"].get("s_nom_max,", np.inf),
+        s_nom_max_set=snakemake.params.lines.get("s_nom_max", np.inf),
-        p_nom_max_set=snakemake.config["links"].get("p_nom_max,", np.inf),
+        p_nom_max_set=snakemake.params.links.get("p_nom_max", np.inf),
        s_nom_max_ext=snakemake.params.lines.get("max_extension", np.inf),
        p_nom_max_ext=snakemake.params.links.get("max_extension", np.inf),
    )
    if "ATK" in opts:
--- a/scripts/prepare_sector_network.py
+++ b/scripts/prepare_sector_network.py
@ -17,18 +17,14 @@ import numpy as np
 import pandas as pd
 import pypsa
 import xarray as xr
-from _helpers import (
+from _helpers import generate_periodic_profiles, update_config_with_sector_opts
-    generate_periodic_profiles,
+from add_electricity import calculate_annuity, sanitize_carriers
    override_component_attrs,
    update_config_with_sector_opts,
 )
 from build_energy_totals import build_co2_totals, build_eea_co2, build_eurostat_co2
 from networkx.algorithms import complement
 from networkx.algorithms.connectivity.edge_augmentation import k_edge_augmentation
 from pypsa.geo import haversine_pts
 from pypsa.io import import_components_from_dataframe
 from scipy.stats import beta
 from vresutils.costdata import annuity
 logger = logging.getLogger(__name__)
@ -200,12 +196,12 @@ def co2_emissions_year(
    """
    Calculate CO2 emissions in one specific year (e.g. 1990 or 2018).
    """
-    emissions_scope = snakemake.config["energy"]["emissions"]
+    emissions_scope = snakemake.params.energy["emissions"]
    eea_co2 = build_eea_co2(snakemake.input.co2, year, emissions_scope)
    # TODO: read Eurostat data from year > 2014
    # this only affects the estimation of CO2 emissions for BA, RS, AL, ME, MK
-    report_year = snakemake.config["energy"]["eurostat_report_year"]
+    report_year = snakemake.params.energy["eurostat_report_year"]
    if year > 2014:
        eurostat_co2 = build_eurostat_co2(
            input_eurostat, countries, report_year, year=2014
@ -241,7 +237,7 @@ def build_carbon_budget(o, input_eurostat, fn, emissions_scope, report_year):
        carbon_budget = float(o[o.find("cb") + 2 : o.find("ex")])
        r = float(o[o.find("ex") + 2 :])
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    e_1990 = co2_emissions_year(
        countries, input_eurostat, opts, emissions_scope, report_year, year=1990
@ -252,7 +248,7 @@ def build_carbon_budget(o, input_eurostat, fn, emissions_scope, report_year):
        countries, input_eurostat, opts, emissions_scope, report_year, year=2018
    )
-    planning_horizons = snakemake.config["scenario"]["planning_horizons"]
+    planning_horizons = snakemake.params.planning_horizons
    t_0 = planning_horizons[0]
    if "be" in o:
@ -391,7 +387,7 @@ def update_wind_solar_costs(n, costs):
        with xr.open_dataset(profile) as ds:
            underwater_fraction = ds["underwater_fraction"].to_pandas()
            connection_cost = (
-                snakemake.config["lines"]["length_factor"]
+                snakemake.params.length_factor
                * ds["average_distance"].to_pandas()
                * (
                    underwater_fraction
@ -483,8 +479,8 @@ def remove_elec_base_techs(n):
    batteries and H2) from base electricity-only network, since they're added
    here differently using links.
    """
-    for c in n.iterate_components(snakemake.config["pypsa_eur"]):
+    for c in n.iterate_components(snakemake.params.pypsa_eur):
-        to_keep = snakemake.config["pypsa_eur"][c.name]
+        to_keep = snakemake.params.pypsa_eur[c.name]
        to_remove = pd.Index(c.df.carrier.unique()).symmetric_difference(to_keep)
        if to_remove.empty:
            continue
@ -674,7 +670,7 @@ def add_dac(n, costs):
 def add_co2limit(n, nyears=1.0, limit=0.0):
    logger.info(f"Adding CO2 budget limit as per unit of 1990 levels of {limit}")
-    countries = snakemake.config["countries"]
+    countries = snakemake.params.countries
    sectors = emission_sectors_from_opts(opts)
@ -731,7 +727,7 @@ def cycling_shift(df, steps=1):
    return df
-def prepare_costs(cost_file, config, nyears):
+def prepare_costs(cost_file, params, nyears):
    # set all asset costs and other parameters
    costs = pd.read_csv(cost_file, index_col=[0, 1]).sort_index()
@ -743,10 +739,10 @@ def prepare_costs(cost_file, config, nyears):
        costs.loc[:, "value"].unstack(level=1).groupby("technology").sum(min_count=1)
    )
-    costs = costs.fillna(config["fill_values"])
+    costs = costs.fillna(params["fill_values"])
    def annuity_factor(v):
-        return annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100
+        return calculate_annuity(v["lifetime"], v["discount rate"]) + v["FOM"] / 100
    costs["fixed"] = [
        annuity_factor(v) * v["investment"] * nyears for i, v in costs.iterrows()
@ -791,7 +787,7 @@ def add_ammonia(n, costs):
    nodes = pop_layout.index
-    cf_industry = snakemake.config["industry"]
+    cf_industry = snakemake.params.industry
    n.add("Carrier", "NH3")
@ -855,7 +851,7 @@ def add_wave(n, wave_cost_factor):
    capacity = pd.Series({"Attenuator": 750, "F2HB": 1000, "MultiPA": 600})
    # in EUR/MW
-    annuity_factor = annuity(25, 0.07) + 0.03
+    annuity_factor = calculate_annuity(25, 0.07) + 0.03
    costs = (
        1e6
        * wave_cost_factor
@ -1106,10 +1102,14 @@ def add_storage_and_grids(n, costs):
            lifetime=costs.at["OCGT", "lifetime"],
        )
-    cavern_types = snakemake.config["sector"]["hydrogen_underground_storage_locations"]
+    cavern_types = snakemake.params.sector["hydrogen_underground_storage_locations"]
    h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0)
-    if not h2_caverns.empty and options["hydrogen_underground_storage"]:
+    if (
        not h2_caverns.empty
        and options["hydrogen_underground_storage"]
        and set(cavern_types).intersection(h2_caverns.columns)
    ):
        h2_caverns = h2_caverns[cavern_types].sum(axis=1)
        # only use sites with at least 2 TWh potential
@ -3056,7 +3056,6 @@ def maybe_adjust_costs_and_potentials(n, opts):
            logger.info(f"changing {attr} for {carrier} by factor {factor}")
 # TODO this should rather be a config no wildcard
 def limit_individual_line_extension(n, maxext):
    logger.info(f"Limiting new HVAC and HVDC extensions to {maxext} MW")
    n.lines["s_nom_max"] = n.lines["s_nom"] + maxext
@ -3275,14 +3274,13 @@ if __name__ == "__main__":
    update_config_with_sector_opts(snakemake.config, snakemake.wildcards.sector_opts)
-    options = snakemake.config["sector"]
+    options = snakemake.params.sector
    opts = snakemake.wildcards.sector_opts.split("-")
    investment_year = int(snakemake.wildcards.planning_horizons[-4:])
-    overrides = override_component_attrs(snakemake.input.overrides)
+    n = pypsa.Network(snakemake.input.network)
    n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
    pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout, index_col=0)
    nhours = n.snapshot_weightings.generators.sum()
@ -3290,7 +3288,7 @@ if __name__ == "__main__":
    costs = prepare_costs(
        snakemake.input.costs,
-        snakemake.config["costs"],
+        snakemake.params.costs,
        nyears,
    )
@ -3306,10 +3304,10 @@ if __name__ == "__main__":
    spatial = define_spatial(pop_layout.index, options)
-    if snakemake.config["foresight"] == "myopic":
+    if snakemake.params.foresight == "myopic":
        add_lifetime_wind_solar(n, costs)
-        conventional = snakemake.config["existing_capacities"]["conventional_carriers"]
+        conventional = snakemake.params.conventional_carriers
        for carrier in conventional:
            add_carrier_buses(n, carrier)
@ -3379,15 +3377,15 @@ if __name__ == "__main__":
    n = set_temporal_aggregation(n, opts, solver_name, drop_leap_day)
    limit_type = "config"
-    limit = get(snakemake.config["co2_budget"], investment_year)
+    limit = get(snakemake.params.co2_budget, investment_year)
    for o in opts:
        if "cb" not in o:
            continue
        limit_type = "carbon budget"
        fn = "results/" + snakemake.params.RDIR + "/csvs/carbon_budget_distribution.csv"
        if not os.path.exists(fn):
-            emissions_scope = snakemake.config["energy"]["emissions"]
+            emissions_scope = snakemake.params.emissions_scope
-            report_year = snakemake.config["energy"]["eurostat_report_year"]
+            report_year = snakemake.params.eurostat_report_year
            build_carbon_budget(
                o, snakemake.input.eurostat, fn, emissions_scope, report_year
            )
@ -3422,8 +3420,8 @@ if __name__ == "__main__":
    if options["electricity_grid_connection"]:
        add_electricity_grid_connection(n, costs)
-    first_year_myopic = (snakemake.config["foresight"] == "myopic") and (
+    first_year_myopic = (snakemake.params.foresight == "myopic") and (
-        snakemake.config["scenario"]["planning_horizons"][0] == investment_year
+        snakemake.params.planning_horizons[0] == investment_year
    )
    if options.get("cluster_heat_buses", False) and not first_year_myopic:
@ -3431,4 +3429,6 @@ if __name__ == "__main__":
    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
    sanitize_carriers(n, snakemake.config)
    n.export_to_netcdf(snakemake.output[0])
--- a/scripts/retrieve_databundle.py
+++ b/scripts/retrieve_databundle.py
@ -58,9 +58,8 @@ if __name__ == "__main__":
    else:
        url = "https://zenodo.org/record/3517935/files/pypsa-eur-data-bundle.tar.xz"
    # Save locations
    tarball_fn = Path(f"{rootpath}/bundle.tar.xz")
-    to_fn = Path(f"{rootpath}/data")
+    to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
    logger.info(f"Downloading databundle from '{url}'.")
    disable_progress = snakemake.config["run"].get("disable_progressbar", False)
--- a/scripts/retrieve_gas_infrastructure_data.py
+++ b/scripts/retrieve_gas_infrastructure_data.py
@ -29,7 +29,7 @@ if __name__ == "__main__":
    # Save locations
    zip_fn = Path(f"{rootpath}/IGGIELGN.zip")
-    to_fn = Path(f"{rootpath}/data/gas_network/scigrid-gas")
+    to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
    logger.info(f"Downloading databundle from '{url}'.")
    disable_progress = snakemake.config["run"].get("disable_progressbar", False)
--- a/scripts/retrieve_sector_databundle.py
+++ b/scripts/retrieve_sector_databundle.py
@ -10,23 +10,25 @@ import logging
 logger = logging.getLogger(__name__)
 import os
 import sys
 import tarfile
 from pathlib import Path
 # Add pypsa-eur scripts to path for import of _helpers
 sys.path.insert(0, os.getcwd() + "/../pypsa-eur/scripts")
 from _helpers import configure_logging, progress_retrieve
 if __name__ == "__main__":
    if "snakemake" not in globals():
        from _helpers import mock_snakemake
        snakemake = mock_snakemake("retrieve_databundle")
        rootpath = ".."
    else:
        rootpath = "."
    configure_logging(snakemake)
    url = "https://zenodo.org/record/5824485/files/pypsa-eur-sec-data-bundle.tar.gz"
-    tarball_fn = Path("sector-bundle.tar.gz")
+    tarball_fn = Path(f"{rootpath}/sector-bundle.tar.gz")
-    to_fn = Path("data")
+    to_fn = Path(rootpath) / Path(snakemake.output[0]).parent.parent
    logger.info(f"Downloading databundle from '{url}'.")
    disable_progress = snakemake.config["run"].get("disable_progressbar", False)
--- a/scripts/simplify_network.py
+++ b/scripts/simplify_network.py
@ -86,22 +86,21 @@ The rule :mod:`simplify_network` does up to four things:
 """
 import logging
-from functools import reduce
+from functools import partial, reduce
 import numpy as np
 import pandas as pd
 import pypsa
 import scipy as sp
-from _helpers import configure_logging, get_aggregation_strategies, update_p_nom_max
+from _helpers import configure_logging, update_p_nom_max
 from add_electricity import load_costs
 from cluster_network import cluster_regions, clustering_for_n_clusters
-from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
+from pypsa.clustering.spatial import (
 from pypsa.networkclustering import (
    aggregategenerators,
    aggregateoneport,
    busmap_by_stubs,
    get_clustering_from_busmap,
 )
 from pypsa.io import import_components_from_dataframe, import_series_from_dataframe
 from scipy.sparse.csgraph import connected_components, dijkstra
 logger = logging.getLogger(__name__)
@ -149,17 +148,17 @@ def simplify_network_to_380(n):
    return n, trafo_map
-def _prepare_connection_costs_per_link(n, costs, config):
+def _prepare_connection_costs_per_link(n, costs, renewable_carriers, length_factor):
    if n.links.empty:
        return {}
    connection_costs_per_link = {}
-    for tech in config["renewable"]:
+    for tech in renewable_carriers:
        if tech.startswith("offwind"):
            connection_costs_per_link[tech] = (
                n.links.length
-                * config["lines"]["length_factor"]
+                * length_factor
                * (
                    n.links.underwater_fraction
                    * costs.at[tech + "-connection-submarine", "capital_cost"]
@ -172,10 +171,18 @@ def _prepare_connection_costs_per_link(n, costs, config):
 def _compute_connection_costs_to_bus(
-    n, busmap, costs, config, connection_costs_per_link=None, buses=None
+    n,
    busmap,
    costs,
    renewable_carriers,
    length_factor,
    connection_costs_per_link=None,
    buses=None,
 ):
    if connection_costs_per_link is None:
-        connection_costs_per_link = _prepare_connection_costs_per_link(n, costs, config)
+        connection_costs_per_link = _prepare_connection_costs_per_link(
            n, costs, renewable_carriers, length_factor
        )
    if buses is None:
        buses = busmap.index[busmap.index != busmap.values]
@ -245,11 +252,15 @@ def _aggregate_and_move_components(
    _adjust_capital_costs_using_connection_costs(n, connection_costs_to_bus, output)
-    _, generator_strategies = get_aggregation_strategies(aggregation_strategies)
+    generator_strategies = aggregation_strategies["generators"]
    carriers = set(n.generators.carrier) - set(exclude_carriers)
-    generators, generators_pnl = aggregategenerators(
+    generators, generators_pnl = aggregateoneport(
-        n, busmap, carriers=carriers, custom_strategies=generator_strategies
+        n,
        busmap,
        "Generator",
        carriers=carriers,
        custom_strategies=generator_strategies,
    )
    replace_components(n, "Generator", generators, generators_pnl)
@ -265,7 +276,16 @@ def _aggregate_and_move_components(
        n.mremove(c, df.index[df.bus0.isin(buses_to_del) | df.bus1.isin(buses_to_del)])
-def simplify_links(n, costs, config, output, aggregation_strategies=dict()):
+def simplify_links(
    n,
    costs,
    renewables,
    length_factor,
    p_max_pu,
    exclude_carriers,
    output,
    aggregation_strategies=dict(),
 ):
    ## Complex multi-node links are folded into end-points
    logger.info("Simplifying connected link components")
@ -315,7 +335,9 @@ def simplify_links(n, costs, config, output, aggregation_strategies=dict()):
    busmap = n.buses.index.to_series()
-    connection_costs_per_link = _prepare_connection_costs_per_link(n, costs, config)
+    connection_costs_per_link = _prepare_connection_costs_per_link(
        n, costs, renewables, length_factor
    )
    connection_costs_to_bus = pd.DataFrame(
        0.0, index=n.buses.index, columns=list(connection_costs_per_link)
    )
@ -333,12 +355,17 @@ def simplify_links(n, costs, config, output, aggregation_strategies=dict()):
            )
            busmap.loc[buses] = b[np.r_[0, m.argmin(axis=0), 1]]
            connection_costs_to_bus.loc[buses] += _compute_connection_costs_to_bus(
-                n, busmap, costs, config, connection_costs_per_link, buses
+                n,
                busmap,
                costs,
                renewables,
                length_factor,
                connection_costs_per_link,
                buses,
            )
            all_links = [i for _, i in sum(links, [])]
            p_max_pu = config["links"].get("p_max_pu", 1.0)
            lengths = n.links.loc[all_links, "length"]
            name = lengths.idxmax() + "+{}".format(len(links) - 1)
            params = dict(
@ -377,10 +404,6 @@ def simplify_links(n, costs, config, output, aggregation_strategies=dict()):
    logger.debug("Collecting all components using the busmap")
    exclude_carriers = config["clustering"]["simplify_network"].get(
        "exclude_carriers", []
    )
    _aggregate_and_move_components(
        n,
        busmap,
@ -392,19 +415,23 @@ def simplify_links(n, costs, config, output, aggregation_strategies=dict()):
    return n, busmap
-def remove_stubs(n, costs, config, output, aggregation_strategies=dict()):
+def remove_stubs(
    n,
    costs,
    renewable_carriers,
    length_factor,
    simplify_network,
    output,
    aggregation_strategies=dict(),
 ):
    logger.info("Removing stubs")
-    across_borders = config["clustering"]["simplify_network"].get(
+    across_borders = simplify_network["remove_stubs_across_borders"]
        "remove_stubs_across_borders", True
    )
    matching_attrs = [] if across_borders else ["country"]
    busmap = busmap_by_stubs(n, matching_attrs)
-    connection_costs_to_bus = _compute_connection_costs_to_bus(n, busmap, costs, config)
+    connection_costs_to_bus = _compute_connection_costs_to_bus(
-
+        n, busmap, costs, renewable_carriers, length_factor
    exclude_carriers = config["clustering"]["simplify_network"].get(
        "exclude_carriers", []
    )
    _aggregate_and_move_components(
@ -413,7 +440,7 @@ def remove_stubs(n, costs, config, output, aggregation_strategies=dict()):
        connection_costs_to_bus,
        output,
        aggregation_strategies=aggregation_strategies,
-        exclude_carriers=exclude_carriers,
+        exclude_carriers=simplify_network["exclude_carriers"],
    )
    return n, busmap
@ -454,45 +481,42 @@ def aggregate_to_substations(n, aggregation_strategies=dict(), buses_i=None):
    busmap = n.buses.index.to_series()
    busmap.loc[buses_i] = dist.idxmin(1)
-    bus_strategies, generator_strategies = get_aggregation_strategies(
+    line_strategies = aggregation_strategies.get("lines", dict())
-        aggregation_strategies
+    generator_strategies = aggregation_strategies.get("generators", dict())
-    )
+    one_port_strategies = aggregation_strategies.get("one_ports", dict())
    clustering = get_clustering_from_busmap(
        n,
        busmap,
        bus_strategies=bus_strategies,
        aggregate_generators_weighted=True,
        aggregate_generators_carriers=None,
        aggregate_one_ports=["Load", "StorageUnit"],
        line_length_factor=1.0,
        line_strategies=line_strategies,
        generator_strategies=generator_strategies,
        one_port_strategies=one_port_strategies,
        scale_link_capital_costs=False,
    )
    return clustering.network, busmap
 def cluster(
-    n, n_clusters, config, algorithm="hac", feature=None, aggregation_strategies=dict()
+    n,
    n_clusters,
    focus_weights,
    solver_name,
    algorithm="hac",
    feature=None,
    aggregation_strategies=dict(),
 ):
    logger.info(f"Clustering to {n_clusters} buses")
    focus_weights = config.get("focus_weights", None)
    renewable_carriers = pd.Index(
        [
            tech
            for tech in n.generators.carrier.unique()
            if tech.split("-", 2)[0] in config["renewable"]
        ]
    )
    clustering = clustering_for_n_clusters(
        n,
        n_clusters,
        custom_busmap=False,
        aggregation_strategies=aggregation_strategies,
-        solver_name=config["solving"]["solver"]["name"],
+        solver_name=solver_name,
        algorithm=algorithm,
        feature=feature,
        focus_weights=focus_weights,
@ -508,92 +532,90 @@ if __name__ == "__main__":
        snakemake = mock_snakemake("simplify_network", weather_year="", simpl="")
    configure_logging(snakemake)
-    n = pypsa.Network(snakemake.input.network)
+    params = snakemake.params
    solver_name = snakemake.config["solving"]["solver"]["name"]
-    aggregation_strategies = snakemake.config["clustering"].get(
+    n = pypsa.Network(snakemake.input.network)
-        "aggregation_strategies", {}
+    Nyears = n.snapshot_weightings.objective.sum() / 8760
    )
    # translate str entries of aggregation_strategies to pd.Series functions:
    aggregation_strategies = {
        p: {k: getattr(pd.Series, v) for k, v in aggregation_strategies[p].items()}
        for p in aggregation_strategies.keys()
    }
    n, trafo_map = simplify_network_to_380(n)
    Nyears = n.snapshot_weightings.objective.sum() / 8760
    technology_costs = load_costs(
        snakemake.input.tech_costs,
-        snakemake.config["costs"],
+        params.costs,
-        snakemake.config["electricity"],
+        params.max_hours,
        Nyears,
    )
    n, simplify_links_map = simplify_links(
-        n, technology_costs, snakemake.config, snakemake.output, aggregation_strategies
+        n,
        technology_costs,
        params.renewable_carriers,
        params.length_factor,
        params.p_max_pu,
        params.simplify_network["exclude_carriers"],
        snakemake.output,
        params.aggregation_strategies,
    )
    busmaps = [trafo_map, simplify_links_map]
-    cluster_config = snakemake.config["clustering"]["simplify_network"]
+    if params.simplify_network["remove_stubs"]:
    if cluster_config.get("remove_stubs", True):
        n, stub_map = remove_stubs(
            n,
            technology_costs,
-            snakemake.config,
+            params.renewable_carriers,
            params.length_factor,
            params.simplify_network,
            snakemake.output,
-            aggregation_strategies=aggregation_strategies,
+            aggregation_strategies=params.aggregation_strategies,
        )
        busmaps.append(stub_map)
-    if cluster_config.get("to_substations", False):
+    if params.simplify_network["to_substations"]:
-        n, substation_map = aggregate_to_substations(n, aggregation_strategies)
+        n, substation_map = aggregate_to_substations(n, params.aggregation_strategies)
        busmaps.append(substation_map)
    # treatment of outliers (nodes without a profile for considered carrier):
    # all nodes that have no profile of the given carrier are being aggregated to closest neighbor
-    if (
+    if params.simplify_network["algorithm"] == "hac":
-        snakemake.config.get("clustering", {})
+        carriers = params.simplify_network["feature"].split("-")[0].split("+")
        .get("cluster_network", {})
        .get("algorithm", "hac")
        == "hac"
        or cluster_config.get("algorithm", "hac") == "hac"
    ):
        carriers = (
            cluster_config.get("feature", "solar+onwind-time").split("-")[0].split("+")
        )
        for carrier in carriers:
            buses_i = list(
                set(n.buses.index) - set(n.generators.query("carrier == @carrier").bus)
            )
            logger.info(
-                f"clustering preparaton (hac): aggregating {len(buses_i)} buses of type {carrier}."
+                f"clustering preparation (hac): aggregating {len(buses_i)} buses of type {carrier}."
            )
            n, busmap_hac = aggregate_to_substations(
                n, params.aggregation_strategies, buses_i
            )
            n, busmap_hac = aggregate_to_substations(n, aggregation_strategies, buses_i)
            busmaps.append(busmap_hac)
    if snakemake.wildcards.simpl:
        n, cluster_map = cluster(
            n,
            int(snakemake.wildcards.simpl),
-            snakemake.config,
+            params.focus_weights,
-            cluster_config.get("algorithm", "hac"),
+            solver_name,
-            cluster_config.get("feature", None),
+            params.simplify_network["algorithm"],
-            aggregation_strategies,
+            params.simplify_network["feature"],
            params.aggregation_strategies,
        )
        busmaps.append(cluster_map)
    # some entries in n.buses are not updated in previous functions, therefore can be wrong. as they are not needed
    # and are lost when clustering (for example with the simpl wildcard), we remove them for consistency:
-    buses_c = {
+    remove = [
        "symbol",
        "tags",
        "under_construction",
        "substation_lv",
        "substation_off",
-    }.intersection(n.buses.columns)
+        "geometry",
-    n.buses = n.buses.drop(buses_c, axis=1)
+    ]
    n.buses.drop(remove, axis=1, inplace=True, errors="ignore")
    n.lines.drop(remove, axis=1, errors="ignore", inplace=True)
    update_p_nom_max(n)
--- a/scripts/solve_network.py
+++ b/scripts/solve_network.py
@ -33,26 +33,21 @@ import numpy as np
 import pandas as pd
 import pypsa
 import xarray as xr
-from _helpers import (
+from _helpers import configure_logging, update_config_with_sector_opts
    configure_logging,
    override_component_attrs,
    update_config_with_sector_opts,
 )
 from vresutils.benchmark import memory_logger
 logger = logging.getLogger(__name__)
 pypsa.pf.logger.setLevel(logging.WARNING)
 from pypsa.descriptors import get_switchable_as_dense as get_as_dense
-def add_land_use_constraint(n, config):
+def add_land_use_constraint(n, planning_horizons, config):
    if "m" in snakemake.wildcards.clusters:
-        _add_land_use_constraint_m(n, config)
+        _add_land_use_constraint_m(n, planning_horizons, config)
    else:
-        _add_land_use_constraint(n, config)
+        _add_land_use_constraint(n)
-def _add_land_use_constraint(n, config):
+def _add_land_use_constraint(n):
    # warning: this will miss existing offwind which is not classed AC-DC and has carrier 'offwind'
    for carrier in ["solar", "onwind", "offwind-ac", "offwind-dc"]:
@ -81,10 +76,10 @@ def _add_land_use_constraint(n, config):
    n.generators.p_nom_max.clip(lower=0, inplace=True)
-def _add_land_use_constraint_m(n, config):
+def _add_land_use_constraint_m(n, planning_horizons, config):
    # if generators clustering is lower than network clustering, land_use accounting is at generators clusters
-    planning_horizons = config["scenario"]["planning_horizons"]
+    planning_horizons = param["planning_horizons"]
    grouping_years = config["existing_capacities"]["grouping_years"]
    current_horizon = snakemake.wildcards.planning_horizons
@ -142,11 +137,18 @@ def add_co2_sequestration_limit(n, limit=200):
    )
-def prepare_network(n, solve_opts=None, config=None):
+def prepare_network(
    n,
    solve_opts=None,
    config=None,
    foresight=None,
    planning_horizons=None,
    co2_sequestration_potential=None,
 ):
    if "clip_p_max_pu" in solve_opts:
        for df in (
            n.generators_t.p_max_pu,
-            n.generators_t.p_min_pu,  # TODO: check if this can be removed
+            n.generators_t.p_min_pu,
            n.storage_units_t.inflow,
        ):
            df.where(df > solve_opts["clip_p_max_pu"], other=0.0, inplace=True)
@ -192,11 +194,11 @@ def prepare_network(n, solve_opts=None, config=None):
        n.set_snapshots(n.snapshots[:nhours])
        n.snapshot_weightings[:] = 8760.0 / nhours
-    if config["foresight"] == "myopic":
+    if foresight == "myopic":
-        add_land_use_constraint(n, config)
+        add_land_use_constraint(n, planning_horizons, config)
    if n.stores.carrier.eq("co2 stored").any():
-        limit = config["sector"].get("co2_sequestration_potential", 200)
+        limit = co2_sequestration_potential
        add_co2_sequestration_limit(n, limit=limit)
    return n
@ -229,8 +231,7 @@ def add_CCL_constraints(n, config):
    p_nom = n.model["Generator-p_nom"]
    gens = n.generators.query("p_nom_extendable").rename_axis(index="Generator-ext")
-    grouper = [gens.bus.map(n.buses.country), gens.carrier]
+    grouper = pd.concat([gens.bus.map(n.buses.country), gens.carrier])
    grouper = xr.DataArray(pd.MultiIndex.from_arrays(grouper), dims=["Generator-ext"])
    lhs = p_nom.groupby(grouper).sum().rename(bus="country")
    minimum = xr.DataArray(agg_p_nom_minmax["min"].dropna()).rename(dim_0="group")
@ -275,13 +276,13 @@ def add_EQ_constraints(n, o, scaling=1e-1):
    float_regex = "[0-9]*\.?[0-9]+"
    level = float(re.findall(float_regex, o)[0])
    if o[-1] == "c":
-        ggrouper = n.generators.bus.map(n.buses.country).to_xarray()
+        ggrouper = n.generators.bus.map(n.buses.country)
-        lgrouper = n.loads.bus.map(n.buses.country).to_xarray()
+        lgrouper = n.loads.bus.map(n.buses.country)
-        sgrouper = n.storage_units.bus.map(n.buses.country).to_xarray()
+        sgrouper = n.storage_units.bus.map(n.buses.country)
    else:
-        ggrouper = n.generators.bus.to_xarray()
+        ggrouper = n.generators.bus
-        lgrouper = n.loads.bus.to_xarray()
+        lgrouper = n.loads.bus
-        sgrouper = n.storage_units.bus.to_xarray()
+        sgrouper = n.storage_units.bus
    load = (
        n.snapshot_weightings.generators
        @ n.loads_t.p_set.groupby(lgrouper, axis=1).sum()
@ -295,7 +296,7 @@ def add_EQ_constraints(n, o, scaling=1e-1):
    p = n.model["Generator-p"]
    lhs_gen = (
        (p * (n.snapshot_weightings.generators * scaling))
-        .groupby(ggrouper)
+        .groupby(ggrouper.to_xarray())
        .sum()
        .sum("snapshot")
    )
@ -304,7 +305,7 @@ def add_EQ_constraints(n, o, scaling=1e-1):
        spillage = n.model["StorageUnit-spill"]
        lhs_spill = (
            (spillage * (-n.snapshot_weightings.stores * scaling))
-            .groupby(sgrouper)
+            .groupby(sgrouper.to_xarray())
            .sum()
            .sum("snapshot")
        )
@ -373,13 +374,14 @@ def add_SAFE_constraints(n, config):
    peakdemand = n.loads_t.p_set.sum(axis=1).max()
    margin = 1.0 + config["electricity"]["SAFE_reservemargin"]
    reserve_margin = peakdemand * margin
-    # TODO: do not take this from the plotting config!
+    conventional_carriers = config["electricity"]["conventional_carriers"]
-    conv_techs = config["plotting"]["conv_techs"]
+    ext_gens_i = n.generators.query(
-    ext_gens_i = n.generators.query("carrier in @conv_techs & p_nom_extendable").index
+        "carrier in @conventional_carriers & p_nom_extendable"
    ).index
    p_nom = n.model["Generator-p_nom"].loc[ext_gens_i]
    lhs = p_nom.sum()
    exist_conv_caps = n.generators.query(
-        "~p_nom_extendable & carrier in @conv_techs"
+        "~p_nom_extendable & carrier in @conventional_carriers"
    ).p_nom.sum()
    rhs = reserve_margin - exist_conv_caps
    n.model.add_constraints(lhs >= rhs, name="safe_mintotalcap")
@ -591,16 +593,15 @@ def extra_functionality(n, snapshots):
    add_pipe_retrofit_constraint(n)
-def solve_network(n, config, opts="", **kwargs):
+def solve_network(n, config, solving, opts="", **kwargs):
-    set_of_options = config["solving"]["solver"]["options"]
+    set_of_options = solving["solver"]["options"]
-    solver_options = (
+    solver_options = solving["solver_options"][set_of_options] if set_of_options else {}
-        config["solving"]["solver_options"][set_of_options] if set_of_options else {}
+    solver_name = solving["solver"]["name"]
-    )
+    cf_solving = solving["options"]
    solver_name = config["solving"]["solver"]["name"]
    cf_solving = config["solving"]["options"]
    track_iterations = cf_solving.get("track_iterations", False)
    min_iterations = cf_solving.get("min_iterations", 4)
    max_iterations = cf_solving.get("max_iterations", 6)
    transmission_losses = cf_solving.get("transmission_losses", 0)
    # add to network for extra_functionality
    n.config = config
@ -614,6 +615,7 @@ def solve_network(n, config, opts="", **kwargs):
    if skip_iterations:
        status, condition = n.optimize(
            solver_name=solver_name,
            transmission_losses=transmission_losses,
            extra_functionality=extra_functionality,
            **solver_options,
            **kwargs,
@ -624,6 +626,7 @@ def solve_network(n, config, opts="", **kwargs):
            track_iterations=track_iterations,
            min_iterations=min_iterations,
            max_iterations=max_iterations,
            transmission_losses=transmission_losses,
            extra_functionality=extra_functionality,
            **solver_options,
            **kwargs,
@ -664,27 +667,28 @@ if __name__ == "__main__":
    if "sector_opts" in snakemake.wildcards.keys():
        opts += "-" + snakemake.wildcards.sector_opts
    opts = [o for o in opts.split("-") if o != ""]
-    solve_opts = snakemake.config["solving"]["options"]
+    solve_opts = snakemake.params.solving["options"]
    np.random.seed(solve_opts.get("seed", 123))
    fn = getattr(snakemake.log, "memory", None)
    with memory_logger(filename=fn, interval=30.0) as mem:
        if "overrides" in snakemake.input.keys():
            overrides = override_component_attrs(snakemake.input.overrides)
            n = pypsa.Network(
                snakemake.input.network, override_component_attrs=overrides
            )
        else:
    n = pypsa.Network(snakemake.input.network)
-        n = prepare_network(n, solve_opts, config=snakemake.config)
+    n = prepare_network(
        n,
        solve_opts,
        config=snakemake.config,
        foresight=snakemake.params.foresight,
        planning_horizons=snakemake.params.planning_horizons,
        co2_sequestration_potential=snakemake.params["co2_sequestration_potential"],
    )
    n = solve_network(
-            n, config=snakemake.config, opts=opts, log_fn=snakemake.log.solver
+        n,
        config=snakemake.config,
        solving=snakemake.params.solving,
        opts=opts,
        log_fn=snakemake.log.solver,
    )
    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
    n.export_to_netcdf(snakemake.output[0])
    logger.info("Maximum memory usage: {}".format(mem.mem_usage))
--- a/scripts/solve_operations_network.py
+++ b/scripts/solve_operations_network.py
@ -11,13 +11,8 @@ import logging
 import numpy as np
 import pypsa
-from _helpers import (
+from _helpers import configure_logging, update_config_with_sector_opts
    configure_logging,
    override_component_attrs,
    update_config_with_sector_opts,
 )
 from solve_network import prepare_network, solve_network
 from vresutils.benchmark import memory_logger
 logger = logging.getLogger(__name__)
@ -43,18 +38,10 @@ if __name__ == "__main__":
    opts = (snakemake.wildcards.opts + "-" + snakemake.wildcards.sector_opts).split("-")
    opts = [o for o in opts if o != ""]
-    solve_opts = snakemake.config["solving"]["options"]
+    solve_opts = snakemake.params.options
    np.random.seed(solve_opts.get("seed", 123))
    fn = getattr(snakemake.log, "memory", None)
    with memory_logger(filename=fn, interval=30.0) as mem:
        if "overrides" in snakemake.input:
            overrides = override_component_attrs(snakemake.input.overrides)
            n = pypsa.Network(
                snakemake.input.network, override_component_attrs=overrides
            )
        else:
    n = pypsa.Network(snakemake.input.network)
    n.optimize.fix_optimal_capacities()
@ -65,5 +52,3 @@ if __name__ == "__main__":
    n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
    n.export_to_netcdf(snakemake.output[0])
    logger.info("Maximum memory usage: {}".format(mem.mem_usage))
		`@ -1,2 +0,0 @@`
			`attribute,type,unit,default,description,status`
			`carrier,string,n/a,n/a,carrier,Input (optional)`
		`@ -0,0 +1,2 @@`
							`,Unit,Values,Description`
							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"doc/configtables/othertoplevel.csv
		`@ -0,0 +1,2 @@`
							`,Unit,Values,Description`
							countries,--,"Subset of {'AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK'}","European countries defined by their `Two-letter country codes (ISO 3166-1) <https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2>`_ which should be included in the energy system model."
		`@ -0,0 +1,2 @@`
							`,Unit,Values,Description`
							foresight,string,"{overnight, myopic, perfect}","See :ref:`Foresight Options` for detail explanations."