pypsa-eur/rules/retrieve.smk

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# SPDX-FileCopyrightText: : 2023-2024 The PyPSA-Eur Authors
#
# SPDX-License-Identifier: MIT
import requests
from datetime import datetime, timedelta
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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 = [
"je-e-21.03.02.xls",
"eez/World_EEZ_v8_2014.shp",
"naturalearth/ne_10m_admin_0_countries.shp",
"NUTS_2013_60M_SH/data/NUTS_RG_60M_2013.shp",
"nama_10r_3popgdp.tsv.gz",
"nama_10r_3gdp.tsv.gz",
"corine/g250_clc06_V18_5.tif",
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"eea/UNFCCC_v23.csv",
"nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
"myb1-2017-nitro.xls",
"emobility/KFZ__count",
"emobility/Pkw__count",
"h2_salt_caverns_GWh_per_sqkm.geojson",
"natura/natura.tiff",
"gebco/GEBCO_2014_2D.nc",
"GDP_per_capita_PPP_1990_2015_v2.nc",
"ppp_2013_1km_Aggregated.tif",
]
rule retrieve_databundle:
output:
expand("data/bundle/{file}", file=datafiles),
directory("data/bundle/jrc-idees-2015"),
log:
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"logs/retrieve_databundle.log",
resources:
mem_mb=1000,
retries: 2
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conda:
"../envs/retrieve.yaml"
script:
"../scripts/retrieve_databundle.py"
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rule retrieve_eurostat_data:
output:
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directory("data/eurostat/Balances-April2023"),
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log:
"logs/retrieve_eurostat_data.log",
retries: 2
script:
"../scripts/retrieve_eurostat_data.py"
rule retrieve_eurostat_household_data:
output:
"data/eurostat/eurostat-household_energy_balances-february_2024.csv",
log:
"logs/retrieve_eurostat_household_data.log",
retries: 2
script:
"../scripts/retrieve_eurostat_household_data.py"
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if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True):
rule retrieve_cutout:
input:
storage(
"https://zenodo.org/records/12791128/files/{cutout}.nc",
),
output:
protected("cutouts/" + CDIR + "{cutout}.nc"),
log:
"logs/" + CDIR + "retrieve_cutout_{cutout}.log",
resources:
mem_mb=5000,
retries: 2
run:
move(input[0], output[0])
validate_checksum(output[0], input[0])
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if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", True):
rule retrieve_cost_data:
params:
version=config_provider("costs", "version"),
output:
resources("costs_{year}.csv"),
log:
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logs("retrieve_cost_data_{year}.log"),
resources:
mem_mb=1000,
retries: 2
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conda:
"../envs/retrieve.yaml"
script:
"../scripts/retrieve_cost_data.py"
if config["enable"]["retrieve"]:
datafiles = [
"IGGIELGN_LNGs.geojson",
"IGGIELGN_BorderPoints.geojson",
"IGGIELGN_Productions.geojson",
"IGGIELGN_Storages.geojson",
"IGGIELGN_PipeSegments.geojson",
]
rule retrieve_gas_infrastructure_data:
output:
expand("data/gas_network/scigrid-gas/data/{files}", files=datafiles),
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log:
"logs/retrieve_gas_infrastructure_data.log",
retries: 2
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conda:
"../envs/retrieve.yaml"
script:
"../scripts/retrieve_gas_infrastructure_data.py"
if config["enable"]["retrieve"]:
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rule retrieve_electricity_demand:
params:
versions=["2019-06-05", "2020-10-06"],
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output:
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"data/electricity_demand_raw.csv",
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log:
"logs/retrieve_electricity_demand.log",
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resources:
mem_mb=5000,
retries: 2
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conda:
"../envs/retrieve.yaml"
script:
"../scripts/retrieve_electricity_demand.py"
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if config["enable"]["retrieve"]:
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rule retrieve_synthetic_electricity_demand:
input:
storage(
"https://zenodo.org/records/10820928/files/demand_hourly.csv",
),
output:
"data/load_synthetic_raw.csv",
log:
"logs/retrieve_synthetic_electricity_demand.log",
resources:
mem_mb=5000,
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retries: 2
run:
move(input[0], output[0])
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if config["enable"]["retrieve"]:
rule retrieve_ship_raster:
input:
storage(
"https://zenodo.org/records/12760663/files/shipdensity_global.zip",
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keep_local=True,
),
output:
"data/shipdensity_global.zip",
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log:
"logs/retrieve_ship_raster.log",
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resources:
mem_mb=5000,
retries: 2
run:
move(input[0], output[0])
validate_checksum(output[0], input[0])
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if config["enable"]["retrieve"]:
# Downloading Copernicus Global Land Cover for land cover and land use:
# Website: https://land.copernicus.eu/global/products/lc
rule download_copernicus_land_cover:
input:
storage(
"https://zenodo.org/records/3939050/files/PROBAV_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
),
output:
"data/Copernicus_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
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run:
move(input[0], output[0])
validate_checksum(output[0], input[0])
if config["enable"]["retrieve"]:
# Downloading LUISA Base Map for land cover and land use:
# Website: https://ec.europa.eu/jrc/en/luisa
rule retrieve_luisa_land_cover:
input:
storage(
"https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/LUISA/EUROPE/Basemaps/LandUse/2018/LATEST/LUISA_basemap_020321_50m.tif",
),
output:
"data/LUISA_basemap_020321_50m.tif",
run:
move(input[0], output[0])
if config["enable"]["retrieve"]:
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# Some logic to find the correct file URL
# Sometimes files are released delayed or ahead of schedule, check which file is currently available
def check_file_exists(url):
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response = requests.head(url)
return response.status_code == 200
# Basic pattern where WDPA files can be found
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url_pattern = (
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"https://d1gam3xoknrgr2.cloudfront.net/current/WDPA_{bYYYY}_Public_shp.zip"
)
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# 3-letter month + 4 digit year for current/previous/next month to test
current_monthyear = datetime.now().strftime("%b%Y")
prev_monthyear = (datetime.now() - timedelta(30)).strftime("%b%Y")
next_monthyear = (datetime.now() + timedelta(30)).strftime("%b%Y")
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# Test prioritised: current month -> previous -> next
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for bYYYY in [current_monthyear, prev_monthyear, next_monthyear]:
if check_file_exists(url := url_pattern.format(bYYYY=bYYYY)):
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break
else:
# If None of the three URLs are working
url = False
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assert (
url
), f"No WDPA files found at {url_pattern} for bY='{current_monthyear}, {prev_monthyear}, or {next_monthyear}'"
# Downloading protected area database from WDPA
# extract the main zip and then merge the contained 3 zipped shapefiles
# Website: https://www.protectedplanet.net/en/thematic-areas/wdpa
rule download_wdpa:
input:
storage(url, keep_local=True),
params:
zip="data/WDPA_shp.zip",
folder=directory("data/WDPA"),
output:
gpkg="data/WDPA.gpkg",
run:
shell("cp {input} {params.zip}")
shell("unzip -o {params.zip} -d {params.folder}")
for i in range(3):
# vsizip is special driver for directly working with zipped shapefiles in ogr2ogr
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layer_path = (
f"/vsizip/{params.folder}/WDPA_{bYYYY}_Public_shp_{i}.zip"
)
print(f"Adding layer {i+1} of 3 to combined output file.")
shell("ogr2ogr -f gpkg -update -append {output.gpkg} {layer_path}")
rule download_wdpa_marine:
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# Downloading Marine protected area database from WDPA
# extract the main zip and then merge the contained 3 zipped shapefiles
# Website: https://www.protectedplanet.net/en/thematic-areas/marine-protected-areas
input:
storage(
f"https://d1gam3xoknrgr2.cloudfront.net/current/WDPA_WDOECM_{bYYYY}_Public_marine_shp.zip",
keep_local=True,
),
params:
zip="data/WDPA_WDOECM_marine.zip",
folder=directory("data/WDPA_WDOECM_marine"),
output:
gpkg="data/WDPA_WDOECM_marine.gpkg",
run:
shell("cp {input} {params.zip}")
shell("unzip -o {params.zip} -d {params.folder}")
for i in range(3):
# vsizip is special driver for directly working with zipped shapefiles in ogr2ogr
layer_path = f"/vsizip/{params.folder}/WDPA_WDOECM_{bYYYY}_Public_marine_shp_{i}.zip"
print(f"Adding layer {i+1} of 3 to combined output file.")
shell("ogr2ogr -f gpkg -update -append {output.gpkg} {layer_path}")
if config["enable"]["retrieve"]:
rule retrieve_monthly_co2_prices:
input:
storage(
"https://www.eex.com/fileadmin/EEX/Downloads/EUA_Emission_Spot_Primary_Market_Auction_Report/Archive_Reports/emission-spot-primary-market-auction-report-2019-data.xls",
keep_local=True,
),
output:
"data/validation/emission-spot-primary-market-auction-report-2019-data.xls",
log:
"logs/retrieve_monthly_co2_prices.log",
resources:
mem_mb=5000,
retries: 2
run:
move(input[0], output[0])
if config["enable"]["retrieve"]:
rule retrieve_monthly_fuel_prices:
output:
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"data/validation/energy-price-trends-xlsx-5619002.xlsx",
log:
"logs/retrieve_monthly_fuel_prices.log",
resources:
mem_mb=5000,
retries: 2
conda:
"../envs/retrieve.yaml"
script:
"../scripts/retrieve_monthly_fuel_prices.py"