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use production to determine today's energy demand for basic chemicals

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This uniformises how demand for basic chemicals is calculated.

We also avoid unnecessary use of ammonia production separately.
This commit is contained in:
Tom Brown 2024-02-14 12:24:58 +01:00 committed by Fabian Neumann
parent cc57952402
commit 7f3ad792a9
3 changed files with 17 additions and 32 deletions
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3
config/config.default.yaml
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@ -636,8 +636,7 @@ industry:
2040: 0.12 2040: 0.12
2045: 0.16 2045: 0.16
2050: 0.20 2050: 0.20
basic_chemicals_without_NH3_energy_demand_today: 1138. #TWh/a basic_chemicals_without_NH3_production_today: 69. #Mt/a, = 86 Mtethylene-equiv - 17 MtNH3
basic_chemicals_without_NH3_production_today: 69. #Mt/a
HVC_production_today: 52. HVC_production_today: 52.
MWh_elec_per_tHVC_mechanical_recycling: 0.547 MWh_elec_per_tHVC_mechanical_recycling: 0.547
MWh_elec_per_tHVC_chemical_recycling: 6.9 MWh_elec_per_tHVC_chemical_recycling: 6.9

1
rules/build_sector.smk
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@ -566,7 +566,6 @@ rule build_industrial_energy_demand_per_country_today:
industry=config["industry"], industry=config["industry"],
input: input:
jrc="data/bundle-sector/jrc-idees-2015", jrc="data/bundle-sector/jrc-idees-2015",
ammonia_production=RESOURCES + "ammonia_production.csv",
industrial_production_per_country=RESOURCES industrial_production_per_country=RESOURCES
+ "industrial_production_per_country.csv", + "industrial_production_per_country.csv",
output: output:

45
scripts/build_industrial_energy_demand_per_country_today.py
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@ -94,51 +94,34 @@ def industrial_energy_demand_per_country(country, year, jrc_dir):
return df return df
def separate_basic_chemicals(demand): def separate_basic_chemicals(demand, production):
# MtNH3/a
fn = snakemake.input.ammonia_production
ammonia = pd.read_csv(fn, index_col=0)[str(year)] / 1e3
ammonia = pd.DataFrame({"gas": ammonia * params["MWh_CH4_per_tNH3_SMR"], ammonia = pd.DataFrame({"hydrogen": production["Ammonia"] * params["MWh_H2_per_tNH3_electrolysis"],
"electricity" : ammonia * params["MWh_elec_per_tNH3_SMR"]}).T "electricity" : production["Ammonia"] * params["MWh_elec_per_tNH3_electrolysis"]}).T
chlorine = pd.DataFrame({"hydrogen": production["Chlorine"] * params["MWh_H2_per_tCl"],
"electricity" : production["Chlorine"] * params["MWh_elec_per_tCl"]}).T
methanol = pd.DataFrame({"gas": production["Methanol"] * params["MWh_CH4_per_tMeOH"],
"electricity" : production["Methanol"] * params["MWh_elec_per_tMeOH"]}).T
demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0) demand["Ammonia"] = ammonia.unstack().reindex(index=demand.index, fill_value=0.0)
demand["Basic chemicals (without ammonia)"] = (
demand["Basic chemicals"] - demand["Ammonia"]
)
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["Chlorine"] = chlorine.unstack().reindex(index=demand.index, fill_value=0.0)
demand["Methanol"] = methanol.unstack().reindex(index=demand.index, fill_value=0.0) demand["Methanol"] = methanol.unstack().reindex(index=demand.index, fill_value=0.0)
demand["HVC"] = ( demand["HVC"] = (
demand["Basic chemicals (without ammonia)"] -demand["Methanol"] - demand["Chlorine"] demand["Basic chemicals"] - demand["Ammonia"] - demand["Methanol"] - demand["Chlorine"]
) )
demand.drop(columns="Basic chemicals (without ammonia)", inplace=True) demand.drop(columns="Basic chemicals", inplace=True)
demand["HVC"].clip(lower=0, inplace=True) demand["HVC"].clip(lower=0, inplace=True)
return demand return demand
def add_non_eu28_industrial_energy_demand(countries, demand): def add_non_eu28_industrial_energy_demand(countries, demand, production):
non_eu28 = countries.difference(eu28) non_eu28 = countries.difference(eu28)
if non_eu28.empty: if non_eu28.empty:
return demand return demand
# output in MtMaterial/a
fn = snakemake.input.industrial_production_per_country
production = pd.read_csv(fn, index_col=0) / 1e3
eu28_production = production.loc[countries.intersection(eu28)].sum() eu28_production = production.loc[countries.intersection(eu28)].sum()
eu28_energy = demand.groupby(level=1).sum() eu28_energy = demand.groupby(level=1).sum()
@ -182,9 +165,13 @@ if __name__ == "__main__":
demand = industrial_energy_demand(countries.intersection(eu28), year) demand = industrial_energy_demand(countries.intersection(eu28), year)
demand = separate_basic_chemicals(demand) # output in MtMaterial/a
production = pd.read_csv(snakemake.input.industrial_production_per_country,
index_col=0) / 1e3
demand = add_non_eu28_industrial_energy_demand(countries, demand) demand = separate_basic_chemicals(demand, production)
demand = add_non_eu28_industrial_energy_demand(countries, demand, production)
# for format compatibility # for format compatibility
demand = demand.stack(dropna=False).unstack(level=[0, 2]) demand = demand.stack(dropna=False).unstack(level=[0, 2])