config.yaml: Remove unnecessary settings
Adjustments made to scripts to read correct settings. Documentation of scenario options improved.
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@ -7,16 +7,21 @@ run: 'your-run-name' # use this to keep track of runs with different settings
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scenario:
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scenario:
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sectors: [E] # ignore this legacy setting
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sectors: [E] # ignore this legacy setting
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simpl: [''] # only relevant for PyPSA-Eur
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simpl: [''] # only relevant for PyPSA-Eur
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lv: [1.0,1.5] # can be any float >= 1.0 or "opt"
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lv: [1.0,1.5] # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
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clusters: [45,50] # any integer between 37 and several hundred
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clusters: [45,50] # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
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opts: [''] # only relevant for PyPSA-Eur
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opts: [''] # only relevant for PyPSA-Eur
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sector_opts: [Co2L0-3H-T-H-B-I-solar3-dist1] # this is where the main scenario settings are
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sector_opts: [Co2L0-3H-T-H-B-I-solar3-dist1] # this is where the main scenario settings are
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# to really understand the options here, look in scripts/prepare_sector_network.py
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# to really understand the options here, look in scripts/prepare_sector_network.py
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# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
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# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
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# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
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# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
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# xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
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# single letters are sectors: T for land transport, H for building heating,
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# B for biomass supply, I for industry, shipping and aviation
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# solarx or onwindx changes the available installable potential by factor x
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# solarx or onwindx changes the available installable potential by factor x
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# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
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# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
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# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
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snapshots:
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snapshots:
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# arguments to pd.date_range
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# arguments to pd.date_range
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start: "2013-01-01"
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start: "2013-01-01"
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@ -24,25 +29,9 @@ snapshots:
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closed: 'left' # end is not inclusive
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closed: 'left' # end is not inclusive
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electricity:
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voltages: [220., 300., 380.]
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extendable_carriers:
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Generator: [] # [OCGT]
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StorageUnit: [] # [battery, H2, CAES]
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max_hours:
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battery: 6
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H2: 168
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conventional_carriers: [] # nuclear, oil, OCGT, CCGT, coal, lignite, geothermal, biomass]
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atlite:
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atlite:
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cutout_dir: '../pypsa-eur/cutouts'
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cutout_dir: '../pypsa-eur/cutouts'
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cutout_name: "europe-2013-era5"
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renewable:
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onwind:
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cutout: europe-2013-era5
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biomass:
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biomass:
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year: 2030
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year: 2030
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@ -6,7 +6,7 @@ import atlite
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout = atlite.Cutout(snakemake.config['atlite']['cutout_name'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'])
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cutout_dir=snakemake.config['atlite']['cutout_dir'])
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@ -18,7 +18,7 @@ if 'snakemake' not in globals():
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time = pd.date_range(freq='m', **snakemake.config['snapshots'])
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time = pd.date_range(freq='m', **snakemake.config['snapshots'])
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params = dict(years=slice(*time.year[[0, -1]]), months=slice(*time.month[[0, -1]]))
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params = dict(years=slice(*time.year[[0, -1]]), months=slice(*time.month[[0, -1]]))
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout = atlite.Cutout(snakemake.config['atlite']['cutout_name'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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**params)
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**params)
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@ -21,7 +21,7 @@ if 'snakemake' not in globals():
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snakemake.input["urban_percent"] = "data/urban_percent.csv"
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snakemake.input["urban_percent"] = "data/urban_percent.csv"
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout = atlite.Cutout(snakemake.config['atlite']['cutout_name'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'])
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cutout_dir=snakemake.config['atlite']['cutout_dir'])
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grid_cells = cutout.grid_cells()
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grid_cells = cutout.grid_cells()
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@ -101,4 +101,3 @@ for key in pop_cells.keys():
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[('y', cutout.coords['y']), ('x', cutout.coords['x'])])
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[('y', cutout.coords['y']), ('x', cutout.coords['x'])])
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layout.to_netcdf(snakemake.output["pop_layout_"+key])
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layout.to_netcdf(snakemake.output["pop_layout_"+key])
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@ -25,7 +25,7 @@ params = dict(years=slice(*time.year[[0, -1]]), months=slice(*time.month[[0, -1]
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout = atlite.Cutout(snakemake.config['atlite']['cutout_name'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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**params)
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**params)
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@ -19,7 +19,7 @@ time = pd.date_range(freq='m', **snakemake.config['snapshots'])
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params = dict(years=slice(*time.year[[0, -1]]), months=slice(*time.month[[0, -1]]))
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params = dict(years=slice(*time.year[[0, -1]]), months=slice(*time.month[[0, -1]]))
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cutout = atlite.Cutout(snakemake.config['renewable']['onwind']['cutout'],
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cutout = atlite.Cutout(snakemake.config['atlite']['cutout_name'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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cutout_dir=snakemake.config['atlite']['cutout_dir'],
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**params)
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**params)
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