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Split industrial demand across nodes by population

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This commit is contained in:
Tom Brown 2019-07-18 15:55:58 +02:00
parent b132193f7f
commit 7509d61348
3 changed files with 14 additions and 9 deletions
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3
Snakefile
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@ -159,7 +159,8 @@ rule build_industrial_demand_per_country:
rule build_industrial_demand:
input:
clustered_pop_layout="resources/pop_layout_{network}_s{simpl}_{clusters}.csv"
clustered_pop_layout="resources/pop_layout_{network}_s{simpl}_{clusters}.csv",
industrial_demand_per_country="resources/industrial_demand_per_country.csv"
output:
industrial_demand="resources/industrial_demand_{network}_s{simpl}_{clusters}.csv"
threads: 1

4
config.yaml
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@ -7,10 +7,10 @@ run: '190712-test_district'
scenario:
sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
simpl: ['']
lv: [1.0,1.25,2.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
lv: [1.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
clusters: [128] #[90, 128, 181] #[45, 64, 90, 128, 181, 256] #, 362] # (2**np.r_[5.5:9:.5]).astype(int) minimum is 37
opts: [''] #for pypsa-eur
sector_opts: [Co2L0-3H-T-H-B-I,Co2L0-3H-T-H-B-I-nodistrict]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H] #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
sector_opts: [Co2L0-3H-T-H-B-I]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H] #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
# Co2L will give default (5%); Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions

16
scripts/build_industrial_demand.py
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@ -4,15 +4,18 @@ import pandas as pd
idx = pd.IndexSlice
def build_industrial_demand():
pop_layout = pd.read_csv(snakemake.input.clustered_pop_layout,index_col=0)
pop_layout["ct"] = pop_layout.index.str[:2]
ct_total = pop_layout.total.groupby(pop_layout["ct"]).sum()
pop_layout["ct_total"] = pop_layout["ct"].map(ct_total.get)
pop_layout["fraction"] = pop_layout["total"]/pop_layout["ct_total"]
population = pd.read_csv(snakemake.input.clustered_pop_layout,
index_col=0)
industrial_demand_per_country = pd.read_csv(snakemake.input.industrial_demand_per_country,index_col=0)
totals = pd.Series(data=[1100.,1814.,586.,400.,580.,186.],
index=["industry new electricity","industry process heat",
"naphtha feedstock","shipping H2","aviation kerosene","process emissions"])
industrial_demand = industrial_demand_per_country.loc[pop_layout.ct].fillna(0.)
industrial_demand.index = pop_layout.index
industrial_demand = industrial_demand.multiply(pop_layout.fraction,axis=0)
industrial_demand = pd.DataFrame({i : population["total"]*totals[i]*1e6/population["total"].sum() for i in totals.index })
industrial_demand.to_csv(snakemake.output.industrial_demand)
@ -27,6 +30,7 @@ if __name__ == "__main__":
snakemake = Dict()
snakemake.input = Dict()
snakemake.input['clustered_pop_layout'] = "resources/pop_layout_elec_s_128.csv"
snakemake.input['industrial_demand_per_country']="resources/industrial_demand_per_country.csv"
snakemake.output = Dict()
snakemake.output['industrial_demand'] = "resources/industrial_demand_elec_s_128.csv"
with open('config.yaml') as f: