revision gas infrastructure representation
This commit is contained in:
Fabian Neumann
parent
37e2e53486
commit
6a00d5bfca
42
Snakefile
42
Snakefile
@ -78,16 +78,46 @@ rule build_simplified_population_layouts:
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benchmark: "benchmarks/build_clustered_population_layouts/s{simpl}"
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script: "scripts/build_clustered_population_layouts.py"
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if config["sector"]["gas_network"]:
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rule retrieve_gas_infrastructure_data:
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output: "data/gas_network/scigrid-gas/data/IGGIELGN_LNGs.csv"
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script: 'scripts/retrieve_gas_infrastructure_data.py'
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rule build_gas_network:
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input:
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gas_network="data/gas_network/gas_network_dataset.csv",
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country_shapes=pypsaeur("resources/country_shapes.geojson"),
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gas_network="data/gas_network/gas_network_dataset.csv"
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output:
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cleaned_gas_network="resources/gas_network.csv"
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resources: mem_mb=4000
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script: "scripts/build_gas_network.py"
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rule build_gas_import_locations:
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input:
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lng="data/gas_network/scigrid-gas/data/IGGIELGN_LNGs.geojson"
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entry="data/gas_network/scigrid-gas/data/IGGIELGN_BorderPoints.geojson"
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production="data/gas_network/scigrid-gas/data/IGGIELGN_Productions.geojson"
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regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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output:
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gas_input_nodes="resources/gas_input_nodes_s{simpl}_{clusters}.csv"
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resources: mem_mb=2000,
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script: "scripts/build_gas_import_locations.py"
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rule cluster_gas_network:
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input:
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cleaned_gas_network="data/gas_network/gas_network_dataset.csv",
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regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson"),
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regions_offshore=pypsaeur("resources/regions_offshore_elec_s{simpl}_{clusters}.geojson")
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output:
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clustered_gas_network="resources/gas_network_elec_s{simpl}_{clusters}.csv"
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resources: mem_mb=10000
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script: "scripts/build_gas_network.py"
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resources: mem_mb=4000
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script: "scripts/cluster_gas_network.py"
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gas_infrastructure = {**rules.cluster_gas_network.output, **rules.build_gas_import_locations.output}
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else:
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gas_infrastructure = {}
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rule build_heat_demands:
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input:
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@ -354,7 +384,6 @@ rule prepare_sector_network:
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energy_totals_name='resources/energy_totals.csv',
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co2_totals_name='resources/co2_totals.csv',
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transport_name='resources/transport_data.csv',
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clustered_gas_network="resources/gas_network_elec_s{simpl}_{clusters}.csv",
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traffic_data_KFZ="data/emobility/KFZ__count",
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traffic_data_Pkw="data/emobility/Pkw__count",
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biomass_potentials='resources/biomass_potentials_s{simpl}_{clusters}.csv',
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@ -387,7 +416,8 @@ rule prepare_sector_network:
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solar_thermal_urban="resources/solar_thermal_urban_elec_s{simpl}_{clusters}.nc",
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solar_thermal_rural="resources/solar_thermal_rural_elec_s{simpl}_{clusters}.nc",
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**build_retro_cost_output,
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**build_biomass_transport_costs_output
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**build_biomass_transport_costs_output,
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**gas_infrastructure
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output: RDIR + '/prenetworks/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc'
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threads: 1
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resources: mem_mb=2000
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@ -457,7 +457,6 @@ plotting:
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gas for industry: '#853403'
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gas for industry CC: '#692e0a'
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gas pipeline: '#ebbca0'
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Gas pipeline: '#ebbca0'
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# oil
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oil: '#c9c9c9'
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oil boiler: '#adadad'
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76
scripts/build_gas_import_locations.py
Normal file
76
scripts/build_gas_import_locations.py
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@ -0,0 +1,76 @@
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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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289
scripts/build_gas_network.py
Executable file → Normal file
289
scripts/build_gas_network.py
Executable file → Normal file
@ -1,5 +1,5 @@
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"""
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Builds clustered natural gas network based on data from:
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Preprocess gas network based on data from:
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[1] the SciGRID Gas project
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(https://www.gas.scigrid.de/)
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@ -15,174 +15,25 @@ import re
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import json
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import pandas as pd
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import geopandas as gpd
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import numpy as np
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from shapely.geometry import Point
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from pypsa.geo import haversine_pts
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def concat_gdf(gdf_list, crs='EPSG:4326'):
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"""Convert to gepandas dataframe with given Coordinate Reference System (crs)."""
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return gpd.GeoDataFrame(pd.concat(gdf_list),crs=crs)
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def string2list(string, with_None=True):
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def string2list(string, with_none=True):
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"""Convert string format to a list."""
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p = re.compile('(?<!\\\\)\'')
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string = p.sub('\"', string)
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if with_None:
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if with_none:
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p2 = re.compile('None')
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string = p2.sub('\"None\"', string)
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else:
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p = re.compile('(?<!\\\\)\'')
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string = p.sub('\"', string)
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return json.loads(string)
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def load_gas_network(df_path):
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"""Load and format gas network data."""
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df = pd.read_csv(df_path, sep=',')
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df.long = df.long.apply(string2list)
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df.lat = df.lat.apply(string2list)
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df.node_id = df.node_id.apply(string2list)
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# pipes which can be used in both directions
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both_direct_df = df[df.is_bothDirection == 1].reset_index(drop=True)
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both_direct_df.node_id = both_direct_df.node_id.apply(lambda x: [x[1], x[0]])
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both_direct_df.long = both_direct_df.long.apply(lambda x: [x[1], x[0]])
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both_direct_df.lat = both_direct_df.lat.apply(lambda x: [x[1], x[0]])
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df_singledirect = pd.concat([df, both_direct_df]).reset_index(drop=True)
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df_singledirect.drop('is_bothDirection', axis=1)
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# create shapely geometry points
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df['point1'] = df.apply(lambda x: Point((x['long'][0], x['lat'][0])), axis=1)
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df['point2'] = df.apply(lambda x: Point((x['long'][1], x['lat'][1])), axis=1)
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df['point1_name'] = df.node_id.str[0]
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df['point2_name'] = df.node_id.str[1]
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part1 = df[['point1', 'point1_name']]
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part2 = df[['point2', 'point2_name']]
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part1.columns = ['geometry', 'name']
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part2.columns = ['geometry', 'name']
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points = [part1, part2]
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points = concat_gdf(points)
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points = points.drop_duplicates()
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points.reset_index(drop=True, inplace=True)
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return df, points
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def load_bus_regions(onshore_path, offshore_path):
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"""Load pypsa-eur on- and offshore regions and concat."""
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bus_regions_offshore = gpd.read_file(offshore_path)
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bus_regions_onshore = gpd.read_file(onshore_path)
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bus_regions = concat_gdf([bus_regions_offshore, bus_regions_onshore])
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bus_regions = bus_regions.dissolve(by='name', aggfunc='sum')
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bus_regions = bus_regions.reset_index()
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return bus_regions
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def points2buses(input_points, bus_regions):
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"""Map gas network points to network buses depending on bus region."""
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points = input_points.copy()
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points['bus'] = None
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buses_list = set(bus_regions.name)
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for bus in buses_list:
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mask = bus_regions[bus_regions.name == bus]
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index = gpd.clip(points, mask).index
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points.loc[index, 'bus'] = bus
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return points
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def build_gas_network_topology(df, points2buses):
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"""Create gas network between pypsa buses.
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Parameters
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----------
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df : pd.DataFrame
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gas network data
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points2buses_map : pd.DataFrame
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mapping of gas network points to pypsa buses
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Returns
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-------
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gas_connections : pd.DataFrame
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gas network connecting pypsa buses
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"""
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tmp_df = points2buses[['bus', 'name']]
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tmp_df.columns = ['buses_start', 'name']
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gas_connections = df.merge(tmp_df, left_on='point1_name', right_on='name')
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tmp_df.columns = ['buses_destination', 'name']
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gas_connections = gas_connections.merge(tmp_df, left_on='point2_name', right_on='name')
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# drop all pipes connecting the same bus
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gas_connections = gas_connections[gas_connections.buses_start != gas_connections.buses_destination]
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gas_connections.reset_index(drop=True, inplace=True)
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gas_connections.drop(['point1', 'point2'], axis=1, inplace=True)
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return gas_connections
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def check_missing(nodes, gas_connections):
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"""Check which nodes are not connected to the gas network."""
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start_buses = gas_connections.buses_start.dropna().unique()
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end_buses = gas_connections.buses_destination.dropna().unique()
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missing_start = nodes[[bus not in start_buses for bus in nodes]]
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missing_end = nodes[[bus not in end_buses for bus in nodes]]
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logger.info(f"- The following buses are missing in gas network data as a start bus:"
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f"\n {', '.join(map(str, missing_start))} \n"
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f"- The following buses are missing in gas network data as an end bus:"
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f"\n {', '.join(map(str, missing_end))} \n"
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f"- The following buses are missing completely:"
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f"\n {', '.join(map(str, missing_start.intersection(missing_end)))}")
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def clean_dataset(nodes, gas_connections):
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"""Convert units and save only necessary data."""
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check_missing(nodes, gas_connections)
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determine_pipe_capacity(gas_connections)
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cols = [
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'is_bothDirection',
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'capacity_recalculated',
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'buses_start',
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'buses_destination',
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'id',
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'length_km'
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]
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clean_pipes = gas_connections[cols].dropna()
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# convert GW -> MW
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clean_pipes.loc[:, 'capacity_recalculated'] *= 1e3
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# rename columns
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to_rename = {
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'capacity_recalculated': 'pipe_capacity_MW',
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'buses_start': 'bus0',
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'buses_destination': 'bus1'
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}
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clean_pipes.rename(columns=to_rename, inplace=True)
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return clean_pipes
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def diameter2capacity(pipe_diameter_mm):
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"""Calculate pipe capacity based on diameter.
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"""Calculate pipe capacity in MW based on diameter in mm.
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20 inch (500 mm) 50 bar -> 1.5 GW CH4 pipe capacity (LHV)
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24 inch (600 mm) 50 bar -> 5 GW CH4 pipe capacity (LHV)
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@ -193,69 +44,107 @@ def diameter2capacity(pipe_diameter_mm):
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"""
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# slopes definitions
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m0 = (5 - 1.5) / (600 - 500)
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m1 = (11.25 - 5) / (900 - 600)
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m2 = (21.7 - 11.25) / (1200 - 900)
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m0 = (1500 - 0) / (500 - 0)
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m1 = (5000 - 1500) / (600 - 500)
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m2 = (11250 - 5000) / (900 - 600)
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m3 = (21700 - 11250) / (1200 - 900)
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# intercept
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a0 = -16
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a1 = -7.5
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a2 = -20.1
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a0 = 0
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a1 = -16000
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a2 = -7500
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a3 = -20100
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if pipe_diameter_mm < 500:
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return np.nan
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elif pipe_diameter_mm < 600:
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return a0 + m0 * pipe_diameter_mm
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elif pipe_diameter_mm < 900:
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elif pipe_diameter_mm < 600:
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return a1 + m1 * pipe_diameter_mm
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else:
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elif pipe_diameter_mm < 900:
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return a2 + m2 * pipe_diameter_mm
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else:
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return a3 + m3 * pipe_diameter_mm
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def determine_pipe_capacity(gas_network):
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"""Check pipe capacity depending on diameter and pressure."""
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def find_terminal_points(df):
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gas_network["capacity_recalculated"] = gas_network.diameter_mm.apply(diameter2capacity)
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latlon = []
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# if pipe capacity smaller than 1.5 GW take original pipe capacity
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low_cap = gas_network.Capacity_GWh_h < 1.5
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gas_network.loc[low_cap, "capacity_recalculated"] = gas_network.loc[low_cap, "capacity_recalculated"].fillna(gas_network.loc[low_cap, "Capacity_GWh_h"])
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for attr in ["lat", "long"]:
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# for pipes without diameter assume 500 mm diameter
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gas_network["capacity_recalculated"].fillna(1.5, inplace=True)
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s = df[attr].apply(string2list)
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# for nord stream take orginal data
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nord_stream = gas_network[gas_network.max_pressure_bar==220].index
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gas_network.loc[nord_stream, "capacity_recalculated"] = gas_network.loc[nord_stream, "Capacity_GWh_h"]
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s = s.apply(lambda x: [x[0], x[-1]])
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latlon.append(pd.DataFrame(s.to_list(),
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columns=[f"{attr}0", f"{attr}1"]
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))
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latlon = pd.concat(latlon, axis=1)
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points = latlon.apply(
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lambda x: {
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"point0": Point(x.long0, x.lat0),
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"point1": Point(x.long1, x.lat1)
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},
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axis=1,
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result_type='expand'
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)
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return pd.concat([df, points], axis=1)
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def process_gas_network_data(fn):
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df = pd.read_csv(fn, sep=',')
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df = find_terminal_points(df)
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to_drop = ["name", "source_id", "country_code", "node_id",
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"long", "lat", "lat_mean", "long_mean", "num_compressor"]
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df.drop(to_drop, axis=1, inplace=True)
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to_rename = {
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"is_bothDirection": "bidirectional",
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"start_year": "build_year",
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"length_km": "length",
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"Capacity_GWh_h": "p_nom_data",
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"id": "tags",
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}
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df.rename(columns=to_rename, inplace=True)
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df.bidirectional = df.bidirectional.astype(bool)
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# convert from GWh/h to MW
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df.p_nom_data *= 1e3
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||||
# for pipes with missing diameter, assume 500 mm
|
||||
df.loc[df.diameter_mm.isna(), "diameter_mm"] = 500.
|
||||
|
||||
# for nord stream and small pipelines take original capacity data
|
||||
# otherwise inferred values from pipe diameter
|
||||
df["p_nom"] = df.diameter_mm.map(diameter2capacity)
|
||||
df.p_nom.update(
|
||||
df.p_nom_data.where((df.diameter_mm < 500) | (df.max_pressure_bar == 220))
|
||||
)
|
||||
|
||||
df["length_haversine"] = df.apply(
|
||||
lambda p: 1.5 * haversine_pts([p.point0.x, p.point1.y], [p.point1.x, p.point1.y]),
|
||||
axis=1
|
||||
)
|
||||
|
||||
df.length.update(df.length_haversine.where(df.length.isna()))
|
||||
|
||||
return df
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake('build_gas_network',
|
||||
network='elec', simpl='', clusters='37',
|
||||
lv='1.0', opts='', planning_horizons='2020',
|
||||
sector_opts='168H-T-H-B-I')
|
||||
snakemake = mock_snakemake('build_gas_network')
|
||||
|
||||
logging.basicConfig(level=snakemake.config['logging_level'])
|
||||
|
||||
# import gas network data
|
||||
gas_network, points = load_gas_network(snakemake.input.gas_network)
|
||||
gas_network = process_gas_network_data(snakemake.input.gas_network)
|
||||
|
||||
# get clustered bus regions
|
||||
bus_regions = load_bus_regions(
|
||||
snakemake.input.regions_onshore,
|
||||
snakemake.input.regions_offshore
|
||||
)
|
||||
nodes = pd.Index(bus_regions.name.unique())
|
||||
|
||||
# map gas network points to network buses
|
||||
points2buses_map = points2buses(points, bus_regions)
|
||||
|
||||
# create gas network between pypsa nodes
|
||||
gas_connections = build_gas_network_topology(gas_network, points2buses_map)
|
||||
|
||||
gas_connections = clean_dataset(nodes, gas_connections)
|
||||
|
||||
gas_connections.to_csv(snakemake.output.clustered_gas_network)
|
||||
gas_network.to_csv(snakemake.output.cleaned_gas_network)
|
||||
110
scripts/cluster_gas_network.py
Executable file
110
scripts/cluster_gas_network.py
Executable file
@ -0,0 +1,110 @@
|
||||
"""Cluster gas network."""
|
||||
|
||||
import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
import pandas as pd
|
||||
import geopandas as gpd
|
||||
|
||||
from shapely import wkt
|
||||
|
||||
|
||||
def concat_gdf(gdf_list, crs='EPSG:4326'):
|
||||
"""Concatenate multiple geopandas dataframes with common coordinate reference system (crs)."""
|
||||
return gpd.GeoDataFrame(pd.concat(gdf_list), crs=crs)
|
||||
|
||||
|
||||
def load_bus_regions(onshore_path, offshore_path):
|
||||
"""Load pypsa-eur on- and offshore regions and concat."""
|
||||
|
||||
bus_regions_offshore = gpd.read_file(offshore_path)
|
||||
bus_regions_onshore = gpd.read_file(onshore_path)
|
||||
bus_regions = concat_gdf([bus_regions_offshore, bus_regions_onshore])
|
||||
bus_regions = bus_regions.dissolve(by='name', aggfunc='sum')
|
||||
|
||||
return bus_regions
|
||||
|
||||
|
||||
def build_clustered_gas_network(df, bus_regions):
|
||||
|
||||
for i in [0,1]:
|
||||
|
||||
gdf = gpd.GeoDataFrame(geometry=df[f"point{i}"], crs="EPSG:4326")
|
||||
|
||||
bus_mapping = gpd.sjoin(gdf, bus_regions, how="left", op="within").index_right
|
||||
bus_mapping = bus_mapping.groupby(bus_mapping.index).first()
|
||||
|
||||
df[f"bus{i}"] = bus_mapping
|
||||
|
||||
df.drop(["point0", "point1"], axis=1, inplace=True)
|
||||
|
||||
# drop pipes where not both buses are inside regions
|
||||
df = df.loc[~df.bus0.isna() & ~df.bus1.isna()]
|
||||
|
||||
# drop pipes within one region
|
||||
df = df.loc[df.bus1 != df.bus0]
|
||||
|
||||
# create new numbered index
|
||||
df.reset_index(drop=True, inplace=True)
|
||||
|
||||
return df
|
||||
|
||||
|
||||
def reindex_pipes(df):
|
||||
|
||||
def make_index(x):
|
||||
connector = " <-> " if x.bidirectional else " -> "
|
||||
return "gas pipeline " + x.bus0 + connector + x.bus1
|
||||
|
||||
df.index = df.apply(make_index, axis=1)
|
||||
|
||||
df["p_min_pu"] = df.bidirectional.apply(lambda bi: -1 if bi else 0)
|
||||
df.drop("bidirectional", axis=1, inplace=True)
|
||||
|
||||
df.sort_index(axis=1, inplace=True)
|
||||
|
||||
|
||||
def aggregate_parallel_pipes(df):
|
||||
|
||||
strategies = {
|
||||
'bus0': 'first',
|
||||
'bus1': 'first',
|
||||
"p_nom": 'sum',
|
||||
"p_nom_data": 'sum',
|
||||
"max_pressure_bar": "mean",
|
||||
"build_year": "mean",
|
||||
"diameter_mm": "mean",
|
||||
"length": 'mean',
|
||||
'tags': ' '.join,
|
||||
}
|
||||
df = df.groupby(df.index).agg(strategies)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake(
|
||||
'cluster_gas_network',
|
||||
simpl='',
|
||||
clusters='37'
|
||||
)
|
||||
|
||||
logging.basicConfig(level=snakemake.config['logging_level'])
|
||||
|
||||
fn = snakemake.input.cleaned_gas_network
|
||||
df = pd.read_csv(fn, index_col=0)
|
||||
for col in ["point0", "point1"]:
|
||||
df[col] = df[col].apply(wkt.loads)
|
||||
|
||||
bus_regions = load_bus_regions(
|
||||
snakemake.input.regions_onshore,
|
||||
snakemake.input.regions_offshore
|
||||
)
|
||||
|
||||
gas_network = build_clustered_gas_network(df, bus_regions)
|
||||
|
||||
reindex_pipes(gas_network)
|
||||
aggregate_parallel_pipes(gas_network)
|
||||
|
||||
gas_network.to_csv(snakemake.output.clustered_gas_network)
|
||||
@ -89,3 +89,15 @@ def mock_snakemake(rulename, **wildcards):
|
||||
|
||||
os.chdir(script_dir)
|
||||
return snakemake
|
||||
|
||||
# from pypsa-eur/_helpers.py
|
||||
def progress_retrieve(url, file):
|
||||
import urllib
|
||||
from progressbar import ProgressBar
|
||||
|
||||
pbar = ProgressBar(0, 100)
|
||||
|
||||
def dlProgress(count, blockSize, totalSize):
|
||||
pbar.update( int(count * blockSize * 100 / totalSize) )
|
||||
|
||||
urllib.request.urlretrieve(url, file, reporthook=dlProgress)
|
||||
@ -332,7 +332,7 @@ def plot_ch4_map(network):
|
||||
|
||||
supply_energy = get_nodal_balance().droplevel([0,1]).sort_index()
|
||||
|
||||
if "Gas pipeline" not in n.links.carrier.unique():
|
||||
if "gas pipeline" not in n.links.carrier.unique():
|
||||
return
|
||||
|
||||
assign_location(n)
|
||||
@ -372,7 +372,7 @@ def plot_ch4_map(network):
|
||||
bus_sizes = pd.concat([bus_sizes, methanation, biogas])
|
||||
bus_sizes.sort_index(inplace=True)
|
||||
|
||||
n.links.drop(n.links.index[n.links.carrier != "Gas pipeline"], inplace=True)
|
||||
n.links.drop(n.links.index[n.links.carrier != "gas pipeline"], inplace=True)
|
||||
|
||||
link_widths = n.links.p_nom_opt / linewidth_factor
|
||||
link_widths[n.links.p_nom_opt < line_lower_threshold] = 0.
|
||||
@ -426,7 +426,7 @@ def plot_ch4_map(network):
|
||||
bbox_inches="tight")
|
||||
|
||||
##################################################
|
||||
supply_energy.drop("Gas pipeline", level=1, inplace=True)
|
||||
supply_energy.drop("gas pipeline", level=1, inplace=True)
|
||||
supply_energy = supply_energy[abs(supply_energy)>5]
|
||||
supply_energy.rename(index=lambda x: x.replace(" gas",""), level=0, inplace=True)
|
||||
|
||||
|
||||
@ -1033,8 +1033,8 @@ def add_electricity_grid_connection(n, costs):
|
||||
n.generators.loc[gens, "capital_cost"] += costs.at['electricity grid connection', 'fixed']
|
||||
|
||||
|
||||
def add_storage(n, costs):
|
||||
print("adding electricity and hydrogen storage")
|
||||
def add_storage_and_grids(n, costs):
|
||||
print("adding electricity and hydrogen storage as well as hydrogen and gas grids")
|
||||
|
||||
nodes = pop_layout.index
|
||||
|
||||
@ -1106,11 +1106,93 @@ def add_storage(n, costs):
|
||||
capital_cost=h2_capital_cost
|
||||
)
|
||||
|
||||
if options["gas_network"]:
|
||||
|
||||
logger.info("Add gas network")
|
||||
|
||||
cols = [
|
||||
"bus0",
|
||||
"bus1",
|
||||
"p_min_pu",
|
||||
"p_nom",
|
||||
"tags",
|
||||
"length"
|
||||
"build_year"
|
||||
]
|
||||
fn = snakemake.input.clustered_gas_network
|
||||
gas_pipes = pd.read_csv(fn, usecols=cols, index_col=0)
|
||||
|
||||
if options["H2_retrofit"]:
|
||||
gas_pipes["p_nom_max"] = gas_pipes.gas_pipes.p_nom
|
||||
gas_pipes["p_nom_min"] = 0.
|
||||
gas_pipes["capital_cost"] = 0.
|
||||
else:
|
||||
gas_pipes["p_nom_max"] = np.inf
|
||||
gas_pipes["p_nom_min"] = gas_pipes.gas_pipes.p_nom
|
||||
gas_pipes["capital_cost"] = gas_pipes.length * costs.at['CH4 (g) pipeline', 'fixed']
|
||||
|
||||
n.madd("Link",
|
||||
gas_pipes.index,
|
||||
bus0=gas_pipes.bus0 + " gas",
|
||||
bus1=gas_pipes.bus1 + " gas",
|
||||
p_min_pu=gas_pipes.p_min_pu,
|
||||
p_nom=gas_pipes.p_nom,
|
||||
p_nom_extendable=True,
|
||||
p_nom_max=gas_pipes.p_nom_max,
|
||||
p_nom_min=gas_pipes.p_nom_min,
|
||||
length=gas_pipes.length,
|
||||
capital_cost=gas_pipes.capital_cost,
|
||||
tags=gas_pipes.tags,
|
||||
carrier="gas pipeline",
|
||||
lifetime=50
|
||||
)
|
||||
|
||||
# remove fossil generators where there is neither
|
||||
# production, LNG terminal, nor entry-point beyond system scope
|
||||
fn = snakemake.input.gas_input_nodes
|
||||
gas_input_nodes = pd.read_csv(fn, index_col=0, squeeze=True).values
|
||||
remove_i = n.generators[
|
||||
(n.generators.carrier=="gas") &
|
||||
~n.generators.bus.map(n.buses.location).isin(gas_input_nodes)
|
||||
].index
|
||||
n.generators.drop(remove_i, inplace=True)
|
||||
|
||||
# TODO candidate gas network topology
|
||||
|
||||
|
||||
# retroftting existing CH4 pipes to H2 pipes
|
||||
if options["gas_network"] and options["H2_retrofit"]:
|
||||
|
||||
gas_pipe_i = n.links[n.links.carrier == "gas pipeline"].index
|
||||
n.links.loc[gas_pipe_i, "p_nom_extendable"] = True
|
||||
h2_pipes = gas_pipes.rename(index=lambda x:
|
||||
x.replace("gas pipeline", "H2 pipeline retrofitted"))
|
||||
|
||||
n.madd("Link",
|
||||
h2_pipes.index,
|
||||
bus0=h2_pipes.bus0 + " H2",
|
||||
bus1=h2_pipes.bus1 + " H2",
|
||||
p_min_pu=-1., # allow that all H2 pipelines can be used in other direction
|
||||
p_nom_max=h2_pipes.pipe_capacity_MW * options["H2_retrofit_capacity_per_CH4"],
|
||||
p_nom_extendable=True,
|
||||
length=h2_pipes.length_km,
|
||||
capital_cost=costs.at['H2 (g) pipeline repurposed', 'fixed'] * h2_pipes.length_km,
|
||||
type=gas_pipes.num_parallel,
|
||||
tags=h2_pipes.id,
|
||||
carrier="H2 pipeline retrofitted",
|
||||
lifetime=50
|
||||
)
|
||||
|
||||
attrs = ["bus0", "bus1", "length"]
|
||||
h2_links = pd.DataFrame(columns=attrs)
|
||||
|
||||
candidates = pd.concat({"lines": n.lines[attrs],
|
||||
"links": n.links.loc[n.links.carrier == "DC", attrs]})
|
||||
lines_sel = n.lines[attrs]
|
||||
links_sel = n.links.loc[n.links.carrier.isin(["DC", "gas pipeline"]), attrs]
|
||||
|
||||
candidates = pd.concat({
|
||||
"lines": lines_sel,
|
||||
"links": links_sel,
|
||||
})
|
||||
|
||||
for candidate in candidates.index:
|
||||
buses = [candidates.at[candidate, "bus0"], candidates.at[candidate, "bus1"]]
|
||||
@ -1134,96 +1216,6 @@ def add_storage(n, costs):
|
||||
lifetime=costs.at['H2 (g) pipeline', 'lifetime']
|
||||
)
|
||||
|
||||
if options["gas_network"]:
|
||||
|
||||
logger.info("Add gas network")
|
||||
|
||||
cols = [
|
||||
"bus0",
|
||||
"bus1",
|
||||
"is_bothDirection",
|
||||
"pipe_capacity_MW",
|
||||
"id",
|
||||
"length_km"
|
||||
]
|
||||
gas_pipes = pd.read_csv(snakemake.input.clustered_gas_network, usecols=cols)
|
||||
|
||||
def make_index(x):
|
||||
connector = " <-> " if x.is_bothDirection else " -> "
|
||||
return "Gas pipeline " + x.bus0 + connector + x.bus1
|
||||
|
||||
gas_pipes.index = gas_pipes.apply(make_index, axis=1)
|
||||
|
||||
# group parallel pipes together
|
||||
strategies = {
|
||||
'bus0': 'first',
|
||||
'bus1': 'first',
|
||||
'is_bothDirection': 'first',
|
||||
"pipe_capacity_MW": 'sum',
|
||||
"length_km": 'sum',
|
||||
'id': ' '.join,
|
||||
}
|
||||
gas_pipes = gas_pipes.groupby(gas_pipes.index).agg(strategies)
|
||||
|
||||
gas_pipes["num_parallel"] = gas_pipes.index.value_counts()
|
||||
gas_pipes["p_min_pu"] = gas_pipes.apply(lambda x: -1 if x.is_bothDirection else 0, axis=1)
|
||||
|
||||
if options["H2_retrofit"]:
|
||||
gas_pipes["p_nom_max"] = gas_pipes.gas_pipes.pipe_capacity_MW
|
||||
gas_pipes["p_nom_min"] = 0.
|
||||
gas_pipes["capital_cost"] = 0.
|
||||
else:
|
||||
gas_pipes["p_nom_max"] = np.inf
|
||||
gas_pipes["p_nom_min"] = gas_pipes.gas_pipes.pipe_capacity_MW
|
||||
gas_pipes["capital_cost"] = gas_pipes.length_km * costs.at['CH4 (g) pipeline', 'fixed']
|
||||
|
||||
n.madd("Link",
|
||||
gas_pipes.index,
|
||||
bus0=gas_pipes.bus0 + " gas",
|
||||
bus1=gas_pipes.bus1 + " gas",
|
||||
p_min_pu=gas_pipes.p_min_pu,
|
||||
p_nom=gas_pipes.pipe_capacity_MW,
|
||||
p_nom_extendable=True,
|
||||
p_nom_max=gas_pipes.p_nom_max,
|
||||
p_nom_min=gas_pipes.p_nom_min,
|
||||
length=gas_pipes.length_km,
|
||||
capital_cost=gas_pipes.capital_cost,
|
||||
type=gas_pipes.num_parallel,
|
||||
tags=gas_pipes.id,
|
||||
carrier="Gas pipeline",
|
||||
lifetime=50
|
||||
)
|
||||
|
||||
# remove fossil generators at all connected nodes
|
||||
# TODO what should be assumed here? rather located at LNG terminals?
|
||||
missing = nodes.difference(pd.concat([gas_pipes.bus0, gas_pipes.bus1]).unique())
|
||||
remove_i = n.generators[(n.generators.carrier=="gas")
|
||||
& (~n.generators.bus.str.replace(" gas","").isin(missing))].index
|
||||
n.generators.drop(remove_i, inplace=True)
|
||||
|
||||
# retroftting existing CH4 pipes to H2 pipes
|
||||
if options["gas_network"] and options["H2_retrofit"]:
|
||||
|
||||
gas_pipe_i = n.links[n.links.carrier == "Gas pipeline"].index
|
||||
n.links.loc[gas_pipe_i, "p_nom_extendable"] = True
|
||||
h2_pipes = gas_pipes.rename(index=lambda x:
|
||||
x.replace("Gas pipeline", "H2 pipeline retrofitted"))
|
||||
|
||||
n.madd("Link",
|
||||
h2_pipes.index,
|
||||
bus0=h2_pipes.bus0 + " H2",
|
||||
bus1=h2_pipes.bus1 + " H2",
|
||||
p_min_pu=-1., # allow that all H2 pipelines can be used in other direction
|
||||
p_nom_max=h2_pipes.pipe_capacity_MW * options["H2_retrofit_capacity_per_CH4"],
|
||||
p_nom_extendable=True,
|
||||
length=h2_pipes.length_km,
|
||||
capital_cost=costs.at['H2 (g) pipeline repurposed', 'fixed'] * h2_pipes.length_km,
|
||||
type=gas_pipes.num_parallel,
|
||||
tags=h2_pipes.id,
|
||||
carrier="H2 pipeline retrofitted",
|
||||
lifetime=50
|
||||
)
|
||||
|
||||
n.add("Carrier", "battery")
|
||||
|
||||
n.madd("Bus",
|
||||
@ -1963,14 +1955,6 @@ def add_industry(n, costs):
|
||||
# 1e6 to convert TWh to MWh
|
||||
industrial_demand = pd.read_csv(snakemake.input.industrial_demand, index_col=0) * 1e6
|
||||
|
||||
methane_demand = industrial_demand.loc[nodes, "methane"].div(8760).rename(index=lambda x: x + " gas for industry")
|
||||
|
||||
# need to aggregate methane demand if gas not nodally resolved
|
||||
if not options["gas_network"]:
|
||||
methane_demand = methane_demand.sum()
|
||||
|
||||
solid_biomass_by_country = industrial_demand["solid biomass"].groupby(pop_layout.ct).sum()
|
||||
|
||||
n.madd("Bus",
|
||||
spatial.biomass.industry,
|
||||
location=spatial.biomass.locations,
|
||||
@ -2018,11 +2002,18 @@ def add_industry(n, costs):
|
||||
location=spatial.gas.locations,
|
||||
carrier="gas for industry")
|
||||
|
||||
gas_demand = industrial_demand.loc[nodes, "methane"] / 8760.
|
||||
|
||||
if options["gas_network"]:
|
||||
spatial_gas_demand = gas_demand.rename(index=lambda x: x + " gas for industry")
|
||||
else:
|
||||
spatial_gas_demand = gas_demand.sum()
|
||||
|
||||
n.madd("Load",
|
||||
spatial.gas.industry,
|
||||
bus=spatial.gas.industry,
|
||||
carrier="gas for industry",
|
||||
p_set=methane_demand
|
||||
p_set=spatial_gas_demand
|
||||
)
|
||||
|
||||
n.madd("Link",
|
||||
@ -2463,7 +2454,7 @@ if __name__ == "__main__":
|
||||
|
||||
add_generation(n, costs)
|
||||
|
||||
add_storage(n, costs)
|
||||
add_storage_and_grids(n, costs)
|
||||
|
||||
# TODO merge with opts cost adjustment below
|
||||
for o in opts:
|
||||
|
||||
36
scripts/retrieve_gas_infrastructure_data.py
Normal file
36
scripts/retrieve_gas_infrastructure_data.py
Normal file
@ -0,0 +1,36 @@
|
||||
"""
|
||||
Retrieve gas infrastructure data from https://zenodo.org/record/4767098/files/IGGIELGN.zip
|
||||
"""
|
||||
|
||||
import logging
|
||||
from helper import progress_retrieve
|
||||
|
||||
import zipfile
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake('retrieve_gas_network_data')
|
||||
rootpath = '..'
|
||||
else:
|
||||
rootpath = '.'
|
||||
|
||||
url = "https://zenodo.org/record/4767098/files/IGGIELGN.zip"
|
||||
|
||||
# Save locations
|
||||
zip_fn = Path(f"{rootpath}/IGGIELGN.zip")
|
||||
to_fn = Path(f"{rootpath}/data/gas_network/scigrid-gas")
|
||||
|
||||
logger.info(f"Downloading databundle from '{url}'.")
|
||||
progress_retrieve(url, zip_fn)
|
||||
|
||||
logger.info(f"Extracting databundle.")
|
||||
zipfile.ZipFile(zip_fn).extractall(to_fn)
|
||||
|
||||
zip_fn.unlink()
|
||||
|
||||
logger.info(f"Gas infrastructure data available in '{to_fn}'.")
|
||||
@ -189,7 +189,7 @@ def add_chp_constraints(n):
|
||||
def add_pipe_retrofit_constraint(n):
|
||||
"""Add constraint for retrofitting existing CH4 pipelines to H2 pipelines."""
|
||||
|
||||
gas_pipes_i = n.links[n.links.carrier=="Gas pipeline"].index
|
||||
gas_pipes_i = n.links[n.links.carrier=="gas pipeline"].index
|
||||
h2_retrofitted_i = n.links[n.links.carrier=='H2 pipeline retrofitted'].index
|
||||
|
||||
if h2_retrofitted_i.empty or gas_pipes_i.empty: return
|
||||
@ -201,7 +201,7 @@ def add_pipe_retrofit_constraint(n):
|
||||
CH4_per_H2 = 1 / n.config["sector"]["H2_retrofit_capacity_per_CH4"]
|
||||
|
||||
lhs = linexpr(
|
||||
(CH4_per_H2, link_p_nom.loc[h2_retrofitted_i].rename(index=lambda x: x.replace("H2 pipeline retrofitted", "Gas pipeline"))),
|
||||
(CH4_per_H2, link_p_nom.loc[h2_retrofitted_i].rename(index=lambda x: x.replace("H2 pipeline retrofitted", "gas pipeline"))),
|
||||
(1, link_p_nom.loc[gas_pipes_i])
|
||||
)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user