initial ship raster implementation

Snakefile

@@ -185,6 +185,22 @@ if config['enable'].get('retrieve_natura_raster', True):
         run: move(input[0], output[0])
 
 
+if config['enable'].get('build_ship_raster', False):
+    rule build_ship_raster:
+        input:
+            ship_density="data/bundle/shipdensity/shipdensity_global.zip",
+            cutouts=expand("cutouts/{cutouts}.nc", **config['atlite'])
+        output: "resources/europe_shipdensity_raster.nc"
+        log: "logs/build_ship_raster.log"
+        script: "scripts/build_ship_raster.py"
+
+
+if config['enable'].get('retrieve_ship_raster', True):
+    rule retrieve_ship_raster:
+        input: HTTP.remote("https://tubcloud.tu-berlin.de/s/P9HArMwKbTH48Tf", keep_local=True, static=True)
+        output: "resources/europe_shipdensity_raster.nc"
+        run: move(input[0], output[0])
+
 rule build_renewable_profiles:
     input:
         base_network="networks/base.nc",
@@ -195,6 +211,9 @@ rule build_renewable_profiles:
         gebco=lambda w: ("data/bundle/GEBCO_2014_2D.nc"
                          if "max_depth" in config["renewable"][w.technology].keys()
                          else []),
+        ship_density= lambda w: ("resources/europe_shipdensity_raster.nc"
+                         if "ship_threshold" in config["renewable"][w.technology].keys()
+                         else []),
         country_shapes='resources/country_shapes.geojson',
         offshore_shapes='resources/offshore_shapes.geojson',
         regions=lambda w: ("resources/regions_onshore.geojson"

config.default.yaml

@@ -30,6 +30,8 @@ enable:
   retrieve_cutout: true
   build_natura_raster: false
   retrieve_natura_raster: true
+  build_ship_raster: false
+  retrieve_ship_raster: true
   custom_busmap: false
 
 electricity:
@@ -134,6 +136,7 @@ renewable:
     # until done more rigorously in #153
     corine: [44, 255]
     natura: true
+    ship_threshold: 400
     max_depth: 50
     max_shore_distance: 30000
     potential: simple # or conservative
@@ -151,6 +154,7 @@ renewable:
     # until done more rigorously in #153
     corine: [44, 255]
     natura: true
+    ship_threshold: 400
     max_depth: 50
     min_shore_distance: 30000
     potential: simple # or conservative

config_float.yaml

@@ -0,0 +1,333 @@
+# SPDX-FileCopyrightText: : 2017-2020 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: CC0-1.0
+
+version: 0.4.0
+tutorial: false
+
+logging:
+  level: INFO
+  format: '%(levelname)s:%(name)s:%(message)s'
+
+summary_dir: results
+
+scenario:
+  simpl: ['']
+  ll: ['copt']
+  clusters: [100]
+  opts: [Co2L-24H]
+
+countries: ['BE','DE', 'DK', 'GB', 'NL', 'NO']
+
+clustering:
+  simplify:
+    to_substations: false # network is simplified to nodes with positive or negative power injection (i.e. substations or offwind connections)
+
+snapshots:
+  start: "2013-01-01"
+  end: "2014-01-01"
+  closed: 'left' # end is not inclusive
+
+enable:
+  prepare_links_p_nom: false
+  retrieve_databundle: true
+  build_cutout: false
+  retrieve_cutout: false
+  build_natura_raster: false
+  retrieve_natura_raster: true
+  custom_busmap: false
+  split_offshore_regions: true #splits big offshore regions into smaller regions
+  build_ship_raster: true
+  retrieve_ship_raster: true
+
+electricity:
+  voltages: [220., 300., 380.]
+  co2limit: 7.75e+7 # 0.05 * 3.1e9*0.5
+  co2base: 1.487e+9
+  agg_p_nom_limits: data/agg_p_nom_minmax.csv
+
+  extendable_carriers:
+    Generator: []
+    StorageUnit: [] # battery, H2
+    Store: [battery, H2]
+    Link: []
+
+  max_hours:
+    battery: 6
+    H2: 168
+
+  powerplants_filter: false # use pandas query strings here, e.g. Country not in ['Germany']
+  custom_powerplants: false # use pandas query strings here, e.g. Country in ['Germany']
+  conventional_carriers: [nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
+  renewable_capacities_from_OPSD: [] # onwind, offwind, solar
+
+  # estimate_renewable_capacities_from_capacity_stats:
+  #   # Wind is the Fueltype in ppm.data.Capacity_stats, onwind, offwind-{ac,dc} the carrier in PyPSA-Eur
+  #   Wind: [onwind, offwind-ac, offwind-dc]
+  #   Solar: [solar]
+
+atlite:
+  nprocesses: 1
+  show_progress: false
+  cutouts:
+    # use 'base' to determine geographical bounds and time span from config
+    # base: 
+      # module: era5  
+    europe-2013-era5:
+      module: era5 # in priority order 
+      dx: 0.3
+      dy: 0.3
+      time: ['2013', '2013']
+
+      
+renewable:
+  onwind:
+    cutout: europe-2013-era5
+    resource:
+      method: wind
+      turbine: Vestas_V112_3MW
+    capacity_per_sqkm: 3 # ScholzPhd Tab 4.3.1: 10MW/km^2
+    # correction_factor: 0.93
+    corine:
+      # Scholz, Y. (2012). Renewable energy based electricity supply at low costs:
+      #  development of the REMix model and application for Europe. ( p.42 / p.28)
+      grid_codes: [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
+                   24, 25, 26, 27, 28, 29, 31, 32]
+      distance: 1000
+      distance_grid_codes: [1, 2, 3, 4, 5, 6]
+    natura: true
+    potential: simple # or conservative
+    clip_p_max_pu: 1.e-2
+  offwind-ac:
+    cutout: europe-2013-era5
+    resource:
+      method: wind
+      turbine: NREL_ReferenceTurbine_2020ATB_12MW_offshore
+    capacity_per_sqkm: 2
+    correction_factor: 0.8855
+    # proxy for wake losses
+    # from 10.1016/j.energy.2018.08.153
+    # until done more rigorously in #153
+    #corine: [44, 255]
+    natura: true
+    max_depth: 60
+    max_shore_distance: 30000
+    potential: simple # or conservative
+    clip_p_max_pu: 1.e-2
+    calculate_topology_cost: true
+  offwind-dc:
+    cutout: europe-2013-era5
+    resource:
+      method: wind
+      turbine: NREL_ReferenceTurbine_2020ATB_12MW_offshore
+    capacity_per_sqkm: 2
+    correction_factor: 0.8855
+    # proxy for wake losses
+    # from 10.1016/j.energy.2018.08.153
+    # until done more rigorously in #153
+    #corine: [44, 255]
+    natura: true
+    max_depth: 60
+    min_shore_distance: 30000
+    potential: simple # or conservative
+    clip_p_max_pu: 1.e-2
+    calculate_topology_cost: true
+  offwind-float:
+    cutout: europe-2013-era5
+    resource:
+      method: wind
+      turbine: NREL_ReferenceTurbine_5MW_offshore
+    # ScholzPhd Tab 4.3.1: 10MW/km^2
+    capacity_per_sqkm: 2
+    correction_factor: 0.8855
+    # proxy for wake losses
+    # from 10.1016/j.energy.2018.08.153
+    # until done more rigorously in #153
+    #corine: [44, 255]
+    natura: true
+    min_depth: 60
+    potential: simple # or conservative
+    clip_p_max_pu: 1.e-2
+  solar:
+    cutout: europe-2013-era5
+    resource:
+      method: pv
+      panel: CSi
+      orientation:
+        slope: 35.
+        azimuth: 180.
+    capacity_per_sqkm: 1.7 # ScholzPhd Tab 4.3.1: 170 MW/km^2
+    # Correction factor determined by comparing uncorrected area-weighted full-load hours to those
+    # published in Supplementary Data to
+    # Pietzcker, Robert Carl, et al. "Using the sun to decarbonize the power
+    # sector: The economic potential of photovoltaics and concentrating solar
+    # power." Applied Energy 135 (2014): 704-720.
+    # This correction factor of 0.854337 may be in order if using reanalysis data.
+    # for discussion refer to https://github.com/PyPSA/pypsa-eur/pull/304
+    # correction_factor: 0.854337
+    corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,
+             14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
+    natura: true
+    potential: simple # or conservative
+    clip_p_max_pu: 1.e-2
+  hydro:
+    cutout: europe-2013-era5
+    carriers: [ror, PHS, hydro]
+    PHS_max_hours: 6
+    hydro_max_hours: "energy_capacity_totals_by_country" # one of energy_capacity_totals_by_country, estimate_by_large_installations or a float
+    clip_min_inflow: 1.0
+
+lines:
+  types:
+    220.: "Al/St 240/40 2-bundle 220.0"
+    300.: "Al/St 240/40 3-bundle 300.0"
+    380.: "Al/St 240/40 4-bundle 380.0"
+  s_max_pu: 0.7
+  s_nom_max: .inf
+  length_factor: 1.25
+  under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
+
+links:
+  p_max_pu: 1.0
+  p_nom_max: .inf
+  include_tyndp: true
+  under_construction: 'zero' # 'zero': set capacity to zero, 'remove': remove, 'keep': with full capacity
+
+transformers:
+  x: 0.1
+  s_nom: 2000.
+  type: ''
+
+load:
+  power_statistics: True # only for files from <2019; set false in order to get ENTSOE transparency data 
+  interpolate_limit: 3 # data gaps up until this size are interpolated linearly
+  time_shift_for_large_gaps: 1w # data gaps up until this size are copied by copying from 
+  manual_adjustments: true # false
+  scaling_factor: 1.0
+
+costs:
+  year: 2030
+  discountrate: 0.07 # From a Lion Hirth paper, also reflects average of Noothout et al 2016
+  USD2013_to_EUR2013: 0.7532 # [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html
+  marginal_cost: # EUR/MWh
+    solar: 0.01
+    onwind: 0.015
+    offwind-ac: 0.015
+    offwind-dc: 0.015
+    hydro: 0.
+    H2: 0.
+    electrolysis: 0.
+    fuel cell: 0.
+    battery: 0.
+    battery inverter: 0.
+  emission_prices: # in currency per tonne emission, only used with the option Ep
+    co2: 0.
+
+solving:
+  options:
+    formulation: kirchhoff
+    load_shedding: false
+    noisy_costs: true
+    min_iterations: 4
+    max_iterations: 6
+    clip_p_max_pu: 0.01
+    skip_iterations: false
+    track_iterations: false
+    #nhours: 10
+  solver:
+    name: gurobi
+    threads: 4
+    method: 2 # barrier
+    crossover: 0
+    BarConvTol: 1.e-5
+    FeasibilityTol: 1.e-6
+    AggFill: 0
+    PreDual: 0
+    GURO_PAR_BARDENSETHRESH: 200
+  # solver:
+  #   name: cplex
+  #   threads: 4
+  #   lpmethod: 4 # barrier
+  #   solutiontype: 2 # non basic solution, ie no crossover
+  #   barrier.convergetol: 1.e-5
+  #   feasopt.tolerance: 1.e-6
+
+plotting:
+  map:
+    figsize: [7, 7]
+    boundaries: [-10.2, 29, 35,  72]
+    p_nom:
+      bus_size_factor: 5.e+4
+      linewidth_factor: 3.e+3
+
+  costs_max: 800
+  costs_threshold: 1
+
+  energy_max: 15000.
+  energy_min: -10000.
+  energy_threshold: 50.
+
+  vre_techs: ["onwind", "offwind-ac", "offwind-dc", "solar", "ror"]
+  conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
+  storage_techs: ["hydro+PHS", "battery", "H2"]
+  load_carriers: ["AC load"]
+  AC_carriers: ["AC line", "AC transformer"]
+  link_carriers: ["DC line", "Converter AC-DC"]
+  tech_colors:
+    "onwind" : "#235ebc"
+    "onshore wind" : "#235ebc"
+    'offwind' : "#6895dd"
+    'offwind-ac' : "#6895dd"
+    'offshore wind' : "#6895dd"
+    'offshore wind ac' : "#6895dd"
+    'offwind-dc' : "#74c6f2"
+    'offshore wind dc' : "#74c6f2"
+    "hydro" : "#08ad97"
+    "hydro+PHS" : "#08ad97"
+    "PHS" : "#08ad97"
+    "hydro reservoir" : "#08ad97"
+    'hydroelectricity' : '#08ad97'
+    "ror" : "#4adbc8"
+    "run of river" : "#4adbc8"
+    'solar' : "#f9d002"
+    'solar PV' : "#f9d002"
+    'solar thermal' : '#ffef60'
+    'biomass' : '#0c6013'
+    'solid biomass' : '#06540d'
+    'biogas' : '#23932d'
+    'waste' : '#68896b'
+    'geothermal' : '#ba91b1'
+    "OCGT" : "#d35050"
+    "gas" : "#d35050"
+    "natural gas" : "#d35050"
+    "CCGT" : "#b20101"
+    "nuclear" : "#ff9000"
+    "coal" : "#707070"
+    "lignite" : "#9e5a01"
+    "oil" : "#262626"
+    "H2" : "#ea048a"
+    "hydrogen storage" : "#ea048a"
+    "battery" : "#b8ea04"
+    "Electric load" : "#f9d002"
+    "electricity" : "#f9d002"
+    "lines" : "#70af1d"
+    "transmission lines" : "#70af1d"
+    "AC-AC" : "#70af1d"
+    "AC line" : "#70af1d"
+    "links" : "#8a1caf"
+    "HVDC links" : "#8a1caf"
+    "DC-DC" : "#8a1caf"
+    "DC link" : "#8a1caf"
+  nice_names:
+    OCGT: "Open-Cycle Gas"
+    CCGT: "Combined-Cycle Gas"
+    offwind-ac: "Offshore Wind (AC)"
+    offwind-dc: "Offshore Wind (DC)"
+    onwind: "Onshore Wind"
+    solar: "Solar"
+    PHS: "Pumped Hydro Storage"
+    hydro: "Reservoir & Dam"
+    battery: "Battery Storage"
+    H2: "Hydrogen Storage"
+    lines: "Transmission Lines"
+    ror: "Run of River"

scripts/build_renewable_profiles.py

@@ -241,6 +241,11 @@ if __name__ == '__main__':
         codes = corine["distance_grid_codes"]
         buffer = corine["distance"]
         excluder.add_raster(snakemake.input.corine, codes=codes, buffer=buffer, crs=3035)
+    
+    if "ship_threshold" in config:
+        shipping_threshold=config["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 "max_depth" in config:
         # lambda not supported for atlite + multiprocessing

scripts/build_ship_raster.py

@@ -0,0 +1,63 @@
+# SPDX-FileCopyrightText: : 2017-2022 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+
+"""
+Transforms the global ship density data from https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density to the size of the considered cutout. The global ship density raster is later used for the exclusion when calculating the offshore potentials.
+
+Relevant Settings
+-----------------
+
+.. code:: yaml
+
+    renewable:
+        {technology}:
+            cutout:
+
+.. seealso::
+    Documentation of the configuration file ``config.yaml`` at
+    :ref:`renewable_cf`
+
+Inputs
+------
+
+- ``data/bundle/shipdensity/shipdensity_global.zip``: `Global ship density from <https://datacatalog.worldbank.org/search/dataset/0037580/Global-Shipping-Traffic-Density>`.
+
+Outputs
+-------
+
+- ``resources/natura.tiff``: Reduced version of `Global ship density from <https://datacatalog.worldbank.org/search/dataset/0037580/` to reduce computation times.
+
+Description
+-----------
+
+"""
+
+import logging
+from _helpers import configure_logging
+from build_natura_raster import determine_cutout_xXyY
+
+import zipfile
+import xarray
+import os
+
+logger = logging.getLogger(__name__)
+
+if __name__ == "__main__":
+    if 'snakemake' not in globals():
+        from _helpers import mock_snakemake
+        snakemake = mock_snakemake('build_ship_raster')
+    configure_logging(snakemake)
+
+    cutouts = snakemake.input.cutouts
+    xs, Xs, ys, Ys = zip(*(determine_cutout_xXyY(cutout) for cutout in cutouts))
+    
+    with zipfile.ZipFile(snakemake.input.ship_density) as zip_f:
+        zip_f.extract("shipdensity_global.tif")
+        ship_density=xarray.open_dataarray("shipdensity_global.tif", engine="rasterio")
+        os.remove("shipdensity_global.tif") 
+
+    ship_density=ship_density.drop("band").sel(x=slice(min(xs),max(Xs)), y=slice(max(Ys),min(ys)))
+    
+    ship_density.to_netcdf(snakemake.output[0])
+