76 lines
2.2 KiB
Python
76 lines
2.2 KiB
Python
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"""
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Build import locations for fossil gas from entry-points and LNG terminals.
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"""
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import logging
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logger = logging.getLogger(__name__)
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import pandas as pd
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import geopandas as gpd
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def read_scigrid_gas(fn):
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df = gpd.read_file(fn)
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df = pd.concat([df, df.param.apply(pd.Series)], axis=1)
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df.drop(["param", "uncertainty", "method"], axis=1, inplace=True)
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return df
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def build_gas_input_locations(lng_fn, entry_fn, prod_fn):
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countries = snakemake.config["countries"]
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countries[countries.index('GB')] = 'UK'
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# LNG terminals
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lng = read_scigrid_gas(lng_fn)
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# Entry points from outside the model scope
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entry = read_scigrid_gas(entry_fn)
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entry["from_country"] = entry.from_country.str.rstrip()
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entry = entry.loc[
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~(entry.from_country.isin(countries) & entry.to_country.isin(countries)) & # only take non-EU entries
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~entry.name.str.contains("Tegelen") | # malformed datapoint
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(entry.from_country == "NO") # entries from NO to GB
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]
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# production sites inside the model scope
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prod = read_scigrid_gas(prod_fn)
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prod = prod.loc[
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(prod.geometry.y > 35) &
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(prod.geometry.x < 30)
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]
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return gpd.GeoDataFrame(
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geometry=pd.concat([prod.geometry, entry.geometry, lng.geometry]).reset_index(drop=True),
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crs=4326
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)
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if __name__ == "__main__":
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if 'snakemake' not in globals():
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from helper import mock_snakemake
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snakemake = mock_snakemake(
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'build_gas_import_locations',
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simpl='',
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clusters='37',
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)
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logging.basicConfig(level=snakemake.config['logging_level'])
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onshore_regions = gpd.read_file(snakemake.input.regions_onshore).set_index('name')
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gas_input_locations = build_gas_input_locations(
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snakemake.input.lng,
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snakemake.input.entry,
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snakemake.input.production
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)
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# recommended to use projected CRS rather than geographic CRS
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gas_input_nodes = gpd.sjoin_nearest(
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gas_input_locations.to_crs(3035),
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onshore_regions.to_crs(3035),
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how='left'
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).index_right.unique()
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pd.Series(gas_input_nodes, name='gas_input_nodes').to_csv(snakemake.output.gas_input_nodes)
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