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for today's industry energy demand, separate MeOH, Cl and HVC

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I.e. split basic chemicals (without ammonia) into MeOH, Cl and HVC.

This now agrees with scheme for industrial sectors tomorrow.
This commit is contained in:
Tom Brown 2024-02-14 10:09:13 +01:00 committed by Fabian Neumann
parent 9c592d9f73
commit cbf7ed0d38
2 changed files with 26 additions and 25 deletions
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1
config/config.default.yaml
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@ -636,6 +636,7 @@ industry:
2040: 0.12
2045: 0.16
2050: 0.20
basic_chemicals_without_NH3_energy_demand_today: 1138. #TWh/a
HVC_production_today: 52.
MWh_elec_per_tHVC_mechanical_recycling: 0.547
MWh_elec_per_tHVC_chemical_recycling: 6.9

50
scripts/build_industrial_energy_demand_per_country_today.py
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@ -73,7 +73,7 @@ def industrial_energy_demand_per_country(country, year, jrc_dir):
def get_subsector_data(sheet):
df = df_dict[sheet][year].groupby(fuels).sum()
df["ammonia"] = 0.0
df["hydrogen"] = 0.0
df["other"] = df["all"] - df.loc[df.index != "all"].sum()
@ -94,36 +94,41 @@ def industrial_energy_demand_per_country(country, year, jrc_dir):
return df
def add_ammonia_energy_demand(demand):
def separate_basic_chemicals(demand):
# MtNH3/a
fn = snakemake.input.ammonia_production
ammonia = pd.read_csv(fn, index_col=0)[str(year)] / 1e3
def get_ammonia_by_fuel(x):
fuels = {
"gas": params["MWh_CH4_per_tNH3_SMR"],
"electricity": params["MWh_elec_per_tNH3_SMR"],
}
return pd.Series({k: x * v for k, v in fuels.items()})
ammonia_by_fuel = ammonia.apply(get_ammonia_by_fuel).T
ammonia_by_fuel = ammonia_by_fuel.unstack().reindex(
index=demand.index, fill_value=0.0
)
ammonia = pd.DataFrame({"ammonia": ammonia * params["MWh_NH3_per_tNH3"]}).T
ammonia = pd.DataFrame({"gas": ammonia * params["MWh_CH4_per_tNH3_SMR"],
"electricity" : ammonia * params["MWh_elec_per_tNH3_SMR"]}).T
demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0)
demand["Basic chemicals (without ammonia)"] = (
demand["Basic chemicals"] - ammonia_by_fuel
demand["Basic chemicals"] - demand["Ammonia"]
)
demand["Basic chemicals (without ammonia)"].clip(lower=0, inplace=True)
demand.drop(columns="Basic chemicals", inplace=True)
distribution = demand["Basic chemicals (without ammonia)"].groupby(level=0).sum()/params["basic_chemicals_without_NH3_energy_demand_today"]
chlorine = pd.DataFrame({"hydrogen": distribution * params["chlorine_production_today"] * params["MWh_H2_per_tCl"],
"electricity" : distribution * params["chlorine_production_today"] * params["MWh_elec_per_tCl"]}).T
methanol = pd.DataFrame({"gas": distribution * params["methanol_production_today"] * params["MWh_CH4_per_tMeOH"],
"electricity" : distribution * params["methanol_production_today"] * params["MWh_elec_per_tMeOH"]}).T
demand["Chlorine"] = chlorine.unstack().reindex(index=demand.index, fill_value=0.0)
demand["Methanol"] = methanol.unstack().reindex(index=demand.index, fill_value=0.0)
demand["HVC"] = (
demand["Basic chemicals (without ammonia)"] -demand["Methanol"] - demand["Chlorine"]
)
demand.drop(columns="Basic chemicals (without ammonia)", inplace=True)
demand["HVC"].clip(lower=0, inplace=True)
return demand
@ -135,11 +140,6 @@ def add_non_eu28_industrial_energy_demand(countries, demand):
fn = snakemake.input.industrial_production_per_country
production = pd.read_csv(fn, index_col=0) / 1e3
# recombine HVC, Chlorine and Methanol to Basic chemicals (without ammonia)
chemicals = ["HVC", "Chlorine", "Methanol"]
production["Basic chemicals (without ammonia)"] = production[chemicals].sum(axis=1)
production.drop(columns=chemicals, inplace=True)
eu28_production = production.loc[countries.intersection(eu28)].sum()
eu28_energy = demand.groupby(level=1).sum()
eu28_averages = eu28_energy / eu28_production
@ -182,7 +182,7 @@ if __name__ == "__main__":
demand = industrial_energy_demand(countries.intersection(eu28), year)
demand = add_ammonia_energy_demand(demand)
demand = separate_basic_chemicals(demand)
demand = add_non_eu28_industrial_energy_demand(countries, demand)