snakemake: Add skeletons and add prepare_links_p_nom rule
This commit is contained in:
Jonas Hoersch
parent
a19ff893e6
commit
6e1566ac32
157
Snakefile
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157
Snakefile
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configfile: "config.yaml"
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localrules: all, prepare_links_p_nom, base_network, add_electricity, add_sectors, extract_summaries, plot_network, scenario_comparions
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wildcard_constraints:
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resarea="[a-zA-Z0-9]+",
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cost="[-a-zA-Z0-9]+",
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sectors="[+a-zA-Z0-9]+",
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opts="[-+a-zA-Z0-9]+"
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rule all:
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input: "results/version-{version}/summaries/costs2-summary.csv".format(version=config['version'])
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rule prepare_links_p_nom:
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output: 'data/links_p_nom.csv'
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threads: 1
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resources: mem_mb=500
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script: 'scripts/prepare_links_p_nom.py'
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rule base_network:
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input:
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eg_buses='data/entsoegridkit/buses.csv',
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eg_lines='data/entsoegridkit/lines.csv',
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eg_links='data/entsoegridkit/links.csv',
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eg_converters='data/entsoegridkit/converters.csv',
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eg_transformers='data/entsoegridkit/transformers.csv',
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parameter_corrections='data/parameter_corrections.yaml',
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links_p_nom='data/links_p_nom.csv'
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output: "networks/base_{opts}.h5"
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benchmark: "benchmarks/base_network_{opts}"
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threads: 1
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resources: mem_mb=500
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script: "scripts/base_network.py"
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rule landuse_remove_protected_and_conservation_areas:
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input:
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landuse = "data/Original_UTM35north/sa_lcov_2013-14_gti_utm35n_vs22b.tif",
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protected_areas = "data/SAPAD_OR_2017_Q2/",
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conservation_areas = "data/SACAD_OR_2017_Q2/"
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output: "resources/landuse_without_protected_conservation.tiff"
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benchmark: "benchmarks/landuse_remove_protected_and_conservation_areas"
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threads: 1
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resources: mem_mb=10000
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script: "scripts/landuse_remove_protected_and_conservation_areas.py"
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rule landuse_map_to_tech_and_supply_region:
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input:
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landuse = "resources/landuse_without_protected_conservation.tiff",
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supply_regions = "data/supply_regions/supply_regions.shp",
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resarea = lambda w: config['data']['resarea'][w.resarea]
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output:
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raster = "resources/raster_{tech}_percent_{resarea}.tiff",
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area = "resources/area_{tech}_{resarea}.csv"
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benchmark: "benchmarks/landuse_map_to_tech_and_supply_region/{tech}_{resarea}"
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threads: 1
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resources: mem_mb=17000
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script: "scripts/landuse_map_to_tech_and_supply_region.py"
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rule inflow_per_country:
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input: EIA_hydro_gen="data/EIA_hydro_generation_2011_2014.csv"
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output: "resources/hydro_inflow.nc"
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benchmark: "benchmarks/inflow_per_country"
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threads: 1
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resources: mem_mb=1000
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script: "scripts/inflow_per_country.py"
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rule add_electricity:
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input:
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base_network='networks/base_{opts}.h5',
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supply_regions='data/supply_regions/supply_regions.shp',
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load='data/SystemEnergy2009_13.csv',
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wind_pv_profiles='data/Wind_PV_Normalised_Profiles.xlsx',
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wind_area='resources/area_wind_{resarea}.csv',
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solar_area='resources/area_solar_{resarea}.csv',
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existing_generators="data/Existing Power Stations SA.xlsx",
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hydro_inflow="resources/hydro_inflow.csv",
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tech_costs="data/technology_costs.xlsx"
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output: "networks/elec_{cost}_{resarea}_{opts}.h5"
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benchmark: "benchmarks/add_electricity/elec_{resarea}_{opts}"
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threads: 1
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resources: mem_mb=1000
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script: "scripts/add_electricity.py"
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rule add_sectors:
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input:
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network="networks/elec_{cost}_{resarea}_{opts}.h5",
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emobility="data/emobility"
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output: "networks/sector_{cost}_{resarea}_{sectors}_{opts}.h5"
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benchmark: "benchmarks/add_sectors/sector_{resarea}_{sectors}_{opts}"
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threads: 1
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resources: mem_mb=1000
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script: "scripts/add_sectors.py"
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rule solve_network:
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input: network="networks/sector_{cost}_{resarea}_{sectors}_{opts}.h5"
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output: "results/version-{version}/networks/{{cost}}_{{resarea}}_{{sectors}}_{{opts}}.h5".format(version=config['version'])
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shadow: "shallow"
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log:
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gurobi="logs/{cost}_{resarea}_{sectors}_{opts}_gurobi.log",
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python="logs/{cost}_{resarea}_{sectors}_{opts}_python.log"
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benchmark: "benchmarks/solve_network/{cost}_{resarea}_{sectors}_{opts}"
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threads: 4
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resources: mem_mb=19000 # for electricity only
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script: "scripts/solve_network.py"
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rule plot_network:
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input:
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network='results/version-{version}/networks/{{cost}}_{{resarea}}_{{sectors}}_{{opts}}.h5'.format(version=config['version']),
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supply_regions='data/supply_regions/supply_regions.shp',
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resarea=lambda w: config['data']['resarea'][w.resarea]
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output:
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only_map=touch('results/version-{version}/plots/network_{{cost}}_{{resarea}}_{{sectors}}_{{opts}}_{{attr}}'.format(version=config['version'])),
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ext=touch('results/version-{version}/plots/network_{{cost}}_{{resarea}}_{{sectors}}_{{opts}}_{{attr}}_ext'.format(version=config['version']))
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params: ext=['png', 'pdf']
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script: "scripts/plot_network.py"
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# rule plot_costs:
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# input: 'results/summaries/costs2-summary.csv'
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# output:
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# expand('results/plots/costs_{cost}_{resarea}_{sectors}_{opt}',
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# **dict(chain(config['scenario'].items(), (('{param}')))
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# touch('results/plots/scenario_plots')
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# params:
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# tmpl="results/plots/costs_[cost]_[resarea]_[sectors]_[opt]"
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# exts=["pdf", "png"]
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# scripts: "scripts/plot_costs.py"
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rule scenario_comparison:
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input:
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expand('results/version-{version}/plots/network_{cost}_{sectors}_{opts}_{attr}_ext',
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version=config['version'],
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attr=['p_nom'],
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**config['scenario'])
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output:
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html='results/version-{version}/plots/scenario_{{param}}.html'.format(version=config['version'])
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params:
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tmpl="network_[cost]_[resarea]_[sectors]_[opts]_[attr]_ext",
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plot_dir='results/version-{}/plots'.format(config['version'])
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script: "scripts/scenario_comparison.py"
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rule extract_summaries:
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input:
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expand("results/version-{version}/networks/{cost}_{sectors}_{opts}.h5",
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version=config['version'],
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**config['scenario'])
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output:
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**{n: "results/version-{version}/summaries/{}-summary.csv".format(n, version=config['version'])
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for n in ['costs', 'costs2', 'e_curtailed', 'e_nom_opt', 'e', 'p_nom_opt']}
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params:
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scenario_tmpl="[cost]_[resarea]_[sectors]_[opts]",
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scenarios=config['scenario']
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script: "scripts/extract_summaries.py"
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# Local Variables:
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# mode: python
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# End:
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5
cluster.yaml
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cluster.yaml
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__default__:
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partition: x-men
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name: "pypsa-za.{rule}.{wildcards}"
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output: "logs/cluster/{rule}.{wildcards}.out"
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error: "logs/cluster/{rule}.{wildcards}.err"
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191
config.yaml
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config.yaml
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version: 0.1
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logging_level: INFO
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scenario:
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sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
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cost: [diw2030]
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lv: [1., 1.125, 1.25, 1.5, 2.0, 3.0]
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opts: [Co2L, Co2L-T] #, LC-FL, LC-T, Ep-T, Co2L-T]
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countries: ['AL', 'AT', 'BA', 'BE', 'BG', 'CH', 'CZ', 'DE', 'DK', 'EE', 'ES', 'FI', 'FR', 'GB', 'GR', 'HR', 'HU', 'IE', 'IT', 'LT', 'LU', 'LV', 'ME', 'MK', 'NL', 'NO', 'PL', 'PT', 'RO', 'RS', 'SE', 'SI', 'SK']
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historical_year: "2012"
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electricity:
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voltages: [220., 300., 380.]
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co2limit: xxx
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extendable_carriers:
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Generator: [OCGT]
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StorageUnit: [Battery, H2] # [CAES]
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SAFE_reservemargin: 0.1
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max_hours:
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Battery: 3
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H2: 10
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reanalysis:
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cutout: europe_2011_2016
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landusetype_percent:
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wind:
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- [[7, 8, 9, 41], 80]
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# - [[5, 6], 50]
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# - [[11, 12, 14, 15], 10]
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solar:
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- [[7, 8, 9, 41], 80]
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# - [[11, 12, 14, 15], 50]
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# - [[46, 47, 51, 56, 64, 68, 72], 10]
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capacity_per_sqm:
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wind: 5 # half of 10 (IWES)
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solar: 16.5 # half of 33 (IWES)
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lines:
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types:
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220.: "Al/St 240/40 2-bundle 220.0"
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300.: "Al/St 240/40 3-bundle 300.0"
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380.: "Al/St 240/40 4-bundle 380.0"
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s_max_pu: 0.7
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length_factor: 1.25
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links:
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s_max_pu: 0.7
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transformers:
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x: 0.1
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s_nom: 2000.
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type: ''
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costs:
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discountrate: 0.07
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# Marginal and capital costs can be overwritten
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# capital_cost:
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# Wind: Bla
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marginal_cost: #
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PV: 0.01
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Wind: 0.015
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EUR_to_ZAR: 15.63
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emission_prices: # only used with the option Ep (emission prices)
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# Externality costs from Integrated Energy Plan by the ZA DOE
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co2: 0.27e+3
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sox: 7.6e+3
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nox: 4.5e+3
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hg: 41484.e-6 # is also part of the excel sheet
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particulate: 11.3e+3
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solving:
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options:
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formulation: kirchhoff
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clip_p_max_pu: 1.e-2
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load_shedding: true
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noisy_costs: true
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min_iterations: 4
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max_iterations: 8
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# max_iterations: 1
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# nhours: 10
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solver:
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name: gurobi_persistent
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threads: 4
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method: 2
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crossover: 0 # -1 (Choose freely)
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BarConvTol: 1.e-5
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FeasibilityTol: 1.e-6
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LogToConsole: 0
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OutputFlag: 1
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plotting:
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map:
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figsize: [7, 7]
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boundaries: [16, -35, 33, -22]
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p_nom:
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bus_size_factor: 5.e+4
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linewidth_factor: 3.e+3 # 1.e+3 #3.e+3
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costs_max: 800
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vre_techs: ["Wind", "PV"]
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conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
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storage_techs: ["Hydro", "CAES", "Battery", "Pumped storage", "Hydro+PS"]
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store_techs: ["Li ion", "water tanks"]
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load_carriers: ["AC load", "heat load", "Li ion load"]
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AC_carriers: ["AC line", "AC transformer"]
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link_carriers: ["DC line", "Converter AC-DC"]
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heat_links: ["heat pump", "resistive heater", "CHP heat", "CHP electric",
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"gas boiler", "central heat pump", "central resistive heater", "central CHP heat",
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"central CHP electric", "central gas boiler"]
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heat_generators: ["gas boiler", "central gas boiler", "solar thermal collector", "central solar thermal collector"]
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tech_colors:
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Wind: "xkcd:azure"
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Hydro: "g"
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ror: "g"
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Hydro+PS: "g"
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PV: "y"
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OCGT: "brown"
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OCGT marginal: "sandybrown"
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OCGT-heat: "orange"
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central gas boiler: "orange"
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gas boiler: "orange"
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gas boilers: "orange"
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gas boiler marginal: "orange"
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gas: "brown"
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lines: "k"
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AC line: "k"
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AC-AC: "k"
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transmission lines: "k"
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H2: "m"
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hydrogen storage: "m"
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Battery: "slategray"
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battery storage: "slategray"
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CAES: "lightgray"
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Nuclear: "r"
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Nuclear marginal: "r"
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Coal: "k"
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Coal marginal: "k"
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Lignite: "grey"
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Lignite marginal: "grey"
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CCGT: "orange"
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CCGT marginal: "orange"
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Diesel: "darkred"
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Diesel marginal: "darkred"
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heat pumps: "green"
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heat pump: "green"
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central heat pump: "green"
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resistive heater: "pink"
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central resistive heater: "pink"
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Sabatier: "turquoise"
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water tanks: "w"
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CHP: "r"
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CHP heat: "r"
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CHP electric: "r"
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central CHP heat: "r"
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central CHP electric: "r"
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Pumped storage: "g"
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Ambient: "k"
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AC load: "b"
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Heat load: "r"
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Li ion load: "grey"
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heat: "r"
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Li ion: "grey"
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district heating: "#CC4E5C"
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nice_names:
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# OCGT: "Gas"
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# OCGT marginal: "Gas (marginal)"
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#Battery: "Battery storage"
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lines: "Transmission lines"
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AC line: "AC lines"
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AC-AC: "DC lines"
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ror: "Run of river"
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nice_names_n:
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offwind: "offshore\nwind"
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onwind: "onshore\nwind"
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# OCGT: "Gas"
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H2: "Hydrogen\nstorage"
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# OCGT marginal: "Gas (marginal)"
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lines: "transmission\nlines"
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ror: "run of river"
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25
scripts/prepare_links_p_nom.py
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25
scripts/prepare_links_p_nom.py
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#!/usr/bin/env python
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import pandas as pd
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import numpy as np
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links_p_nom = pd.read_html('https://en.wikipedia.org/wiki/List_of_HVDC_projects', header=0, match="SwePol")[0]
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def extract_coordinates(s):
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regex = (r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(N|S) "
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r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(E|W)")
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e = s.str.extract(regex, expand=True)
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lat = (e[0].astype(float) + (e[1].astype(float) + e[2].astype(float)/60.)/60.)*e[3].map({'N': +1., 'S': -1.})
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lon = (e[4].astype(float) + (e[5].astype(float) + e[6].astype(float)/60.)/60.)*e[7].map({'E': +1., 'W': -1.})
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return lon, lat
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m_b = links_p_nom["Power (MW)"].str.contains('x').fillna(False)
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def multiply(s): return s.str[0].astype(float) * s.str[1].astype(float)
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links_p_nom.loc[m_b, "Power (MW)"] = links_p_nom.loc[m_b, "Power (MW)"].str.split('x').pipe(multiply)
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links_p_nom["Power (MW)"] = links_p_nom["Power (MW)"].str.extract("[-/]?([\d.]+)", expand=False).astype(float)
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links_p_nom['x1'], links_p_nom['y1'] = extract_coordinates(links_p_nom['Converter station 1'])
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links_p_nom['x2'], links_p_nom['y2'] = extract_coordinates(links_p_nom['Converter station 2'])
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links_p_nom.dropna(subset=['x1', 'y1', 'x2', 'y2']).to_csv(snakemake.output[0], index=False)
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4
snakemake_cluster
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4
snakemake_cluster
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#!/bin/bash
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snakemake --cluster-config cluster.yaml --cluster "sbatch --parsable -J '{cluster.name}' -p {cluster.partition} -n 1 --cpus-per-task {threads} -o '{cluster.output}' --mem {resources.mem_mb}" "$@"
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