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Exogenous transition path for shipping, Steel, and Aluminum production (#136)

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* Update .gitignore

* Add fictitious load to account for non-transformed shipping emissions

The share of shipping demand that is transformed is defined now for different years to be used with the myopic code.
The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions.

* Split colours for H2 in Industry and H2 in shipping when plotting balances.

When plotting the balance for H2, the rename dictionary merges all the demands containing H2.
This commit disables such merging and keeps different colours for H2 in shipping and H2 in industry. This is useful when one wants to look at the H2 balance and have an overview of where the H2 is consumed in the model.

* Make transformation of Steel and Aluminum production depends on year

Previously, the transformation of the Steel and Aluminum production was assumed to occur overnight.
This commit enables the definition of a transformation path via the config.yaml file.
This requires adding the {planning_horizon} to the input and output file name of the following rules:
build_industrial_production_per_country_tomorrow
build_industrial_production_per_node
build_industry_energy_demand_per_node
prepare_sector_network

* small follow-up to merge

* Add oil consumed in shipping as a load to EU oil bus

* Update scripts/prepare_sector_network.py

* add planning_horizons wildcard to benchmark paths

* fixup: double fraction_primary for steel

Co-authored-by: Fabian Neumann <fabian.neumann@outlook.de>
This commit is contained in:
martavp 2021-08-04 18:19:02 +02:00 committed by GitHub
parent 50dd4ce285
commit fab31e6524
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7 changed files with 91 additions and 22 deletions
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2
.gitignore vendored
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@ -28,7 +28,7 @@ gurobi.log
/data/.nfs*
/data/Industrial_Database.csv
/data/retro/tabula-calculator-calcsetbuilding.csv
/data
*.org
*.nc

18
Snakefile
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@ -220,10 +220,10 @@ rule build_industrial_production_per_country_tomorrow:
input:
industrial_production_per_country="resources/industrial_production_per_country.csv"
output:
industrial_production_per_country_tomorrow="resources/industrial_production_per_country_tomorrow.csv"
industrial_production_per_country_tomorrow="resources/industrial_production_per_country_tomorrow_{planning_horizons}.csv"
threads: 1
resources: mem_mb=1000
benchmark: "benchmarks/build_industrial_production_per_country_tomorrow"
benchmark: "benchmarks/build_industrial_production_per_country_tomorrow_{planning_horizons}"
script: 'scripts/build_industrial_production_per_country_tomorrow.py'
@ -243,25 +243,25 @@ rule build_industrial_distribution_key:
rule build_industrial_production_per_node:
input:
industrial_distribution_key="resources/industrial_distribution_key_elec_s{simpl}_{clusters}.csv",
industrial_production_per_country_tomorrow="resources/industrial_production_per_country_tomorrow.csv"
industrial_production_per_country_tomorrow="resources/industrial_production_per_country_tomorrow_{planning_horizons}.csv"
output:
industrial_production_per_node="resources/industrial_production_elec_s{simpl}_{clusters}.csv"
industrial_production_per_node="resources/industrial_production_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
threads: 1
resources: mem_mb=1000
benchmark: "benchmarks/build_industrial_production_per_node/s{simpl}_{clusters}"
benchmark: "benchmarks/build_industrial_production_per_node/s{simpl}_{clusters}_{planning_horizons}"
script: 'scripts/build_industrial_production_per_node.py'
rule build_industrial_energy_demand_per_node:
input:
industry_sector_ratios="resources/industry_sector_ratios.csv",
industrial_production_per_node="resources/industrial_production_elec_s{simpl}_{clusters}.csv",
industrial_production_per_node="resources/industrial_production_elec_s{simpl}_{clusters}_{planning_horizons}.csv",
industrial_energy_demand_per_node_today="resources/industrial_energy_demand_today_elec_s{simpl}_{clusters}.csv"
output:
industrial_energy_demand_per_node="resources/industrial_energy_demand_elec_s{simpl}_{clusters}.csv"
industrial_energy_demand_per_node="resources/industrial_energy_demand_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
threads: 1
resources: mem_mb=1000
benchmark: "benchmarks/build_industrial_energy_demand_per_node/s{simpl}_{clusters}"
benchmark: "benchmarks/build_industrial_energy_demand_per_node/s{simpl}_{clusters}_{planning_horizons}"
script: 'scripts/build_industrial_energy_demand_per_node.py'
@ -333,7 +333,7 @@ rule prepare_sector_network:
busmap=pypsaeur("resources/busmap_elec_s{simpl}_{clusters}.csv"),
clustered_pop_layout="resources/pop_layout_elec_s{simpl}_{clusters}.csv",
simplified_pop_layout="resources/pop_layout_elec_s{simpl}.csv",
industrial_demand="resources/industrial_energy_demand_elec_s{simpl}_{clusters}.csv",
industrial_demand="resources/industrial_energy_demand_elec_s{simpl}_{clusters}_{planning_horizons}.csv",
heat_demand_urban="resources/heat_demand_urban_elec_s{simpl}_{clusters}.nc",
heat_demand_rural="resources/heat_demand_rural_elec_s{simpl}_{clusters}.nc",
heat_demand_total="resources/heat_demand_total_elec_s{simpl}_{clusters}.nc",

38
config.default.yaml
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@ -175,6 +175,14 @@ sector:
transport_fuel_cell_efficiency: 0.5
transport_internal_combustion_efficiency: 0.3
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
shipping_hydrogen_share: # 1 means all hydrogen FC
2020: 0
2025: 0
2030: 0.05
2035: 0.15
2040: 0.3
2045: 0.6
2050: 1
time_dep_hp_cop: true #time dependent heat pump coefficient of performance
heat_pump_sink_T: 55. # Celsius, based on DTU / large area radiators; used in build_cop_profiles.py
# conservatively high to cover hot water and space heating in poorly-insulated buildings
@ -229,10 +237,32 @@ sector:
industry:
St_primary_fraction: 0.3 # fraction of steel produced via primary route (DRI + EAF) versus secondary route (EAF); today fraction is 0.6
St_primary_fraction: # fraction of steel produced via primary route versus secondary route (scrap+EAF); today fraction is 0.6
2020: 0.6
2025: 0.55
2030: 0.5
2035: 0.45
2040: 0.4
2045: 0.35
2050: 0.3
DRI_fraction: # fraction of the primary route converted to DRI + EAF
2020: 0
2025: 0
2030: 0.05
2035: 0.2
2040: 0.4
2045: 0.7
2050: 1
H2_DRI: 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2,LHV/ton_Steel from 51kgH2/tSt in Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
elec_DRI: 0.322 #electricity consumption in Direct Reduced Iron (DRI) shaft, MWh/tSt HYBRIT brochure https://ssabwebsitecdn.azureedge.net/-/media/hybrit/files/hybrit_brochure.pdf
Al_primary_fraction: 0.2 # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
Al_primary_fraction: # fraction of aluminium produced via the primary route versus scrap; today fraction is 0.4
2020: 0.4
2025: 0.375
2030: 0.35
2035: 0.325
2040: 0.3
2045: 0.25
2050: 0.2
MWh_CH4_per_tNH3_SMR: 10.8 # 2012's demand from https://ec.europa.eu/docsroom/documents/4165/attachments/1/translations/en/renditions/pdf
MWh_elec_per_tNH3_SMR: 0.7 # same source, assuming 94-6% split methane-elec of total energy demand 11.5 MWh/tNH3
MWh_H2_per_tNH3_electrolysis: 6.5 # from https://doi.org/10.1016/j.joule.2018.04.017, around 0.197 tH2/tHN3 (>3/17 since some H2 lost and used for energy)
@ -472,4 +502,8 @@ plotting:
solid biomass: '#DAA520'
today: '#D2691E'
shipping: '#6495ED'
shipping oil: "#6495ED"
shipping oil emissions: "#6495ED"
electricity distribution grid: '#333333'
H2 for industry: "#222222"
H2 for shipping: "#6495ED"

5
doc/release_notes.rst
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@ -60,11 +60,10 @@ Future release
These are included in the environment specifications of PyPSA-Eur.
* Consistent use of ``__main__`` block and further unspecific code cleaning.
* Distinguish costs for home battery storage and inverter from utility-scale battery costs.
* The share of shipping transformed into hydrogen fuel cell can be now defined for different years in the ``config.yaml`` file. The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions.
* The transformation of the Steel and Aluminium production can be now defined for different years in the ``config.yaml`` file.
* Include the option to alter the maximum energy capacity of a store via the ``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for sensitivity analyses. Example: ``co2 stored+e2`` multiplies the ``e_nom_max`` by factor 2. In this example, ``e_nom_max`` represents the CO2 sequestration potential in Europe.
PyPSA-Eur-Sec 0.5.0 (21st May 2021)
===================================

20
scripts/build_industrial_production_per_country_tomorrow.py
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@ -2,6 +2,8 @@
import pandas as pd
from prepare_sector_network import get
if __name__ == '__main__':
if 'snakemake' not in globals():
from helper import mock_snakemake
@ -9,27 +11,35 @@ if __name__ == '__main__':
config = snakemake.config["industry"]
investment_year = int(snakemake.wildcards.planning_horizons)
fn = snakemake.input.industrial_production_per_country
production = pd.read_csv(fn, index_col=0)
keys = ["Integrated steelworks", "Electric arc"]
total_steel = production[keys].sum(axis=1)
st_primary_fraction = get(config["St_primary_fraction"], investment_year)
dri_fraction = get(config["DRI_fraction"], investment_year)
int_steel = production["Integrated steelworks"].sum()
fraction_persistent_primary = config["St_primary_fraction"] * total_steel.sum() / int_steel
fraction_persistent_primary = st_primary_fraction * total_steel.sum() / int_steel
dri = fraction_persistent_primary * production["Integrated steelworks"]
dri = dri_fraction * fraction_persistent_primary * production["Integrated steelworks"]
production.insert(2, "DRI + Electric arc", dri)
production["Electric arc"] = total_steel - production["DRI + Electric arc"]
production["Integrated steelworks"] = 0.
not_dri = (1 - dri_fraction)
production["Integrated steelworks"] = not_dri * fraction_persistent_primary * production["Integrated steelworks"]
production["Electric arc"] = total_steel - production["DRI + Electric arc"] - production["Integrated steelworks"]
keys = ["Aluminium - primary production", "Aluminium - secondary production"]
total_aluminium = production[keys].sum(axis=1)
key_pri = "Aluminium - primary production"
key_sec = "Aluminium - secondary production"
fraction_persistent_primary = config["Al_primary_fraction"] * total_aluminium.sum() / production[key_pri].sum()
al_primary_fraction = get(config["Al_primary_fraction"], investment_year)
fraction_persistent_primary = al_primary_fraction * total_aluminium.sum() / production[key_pri].sum()
production[key_pri] = fraction_persistent_primary * production[key_pri]
production[key_sec] = total_aluminium - production[key_pri]

4
scripts/plot_summary.py
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@ -34,7 +34,9 @@ def rename_techs(label):
rename_if_contains_dict = {
"water tanks": "hot water storage",
"retrofitting": "building retrofitting",
"H2": "hydrogen storage",
"H2 Electrolysis": "hydrogen storage",
"H2 Fuel Cell": "hydrogen storage",
"H2 pipeline": "hydrogen storage",
"battery": "battery storage",
"CC": "CC"
}

26
scripts/prepare_sector_network.py
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@ -1716,7 +1716,8 @@ def add_industry(n, costs):
all_navigation = ["total international navigation", "total domestic navigation"]
efficiency = options['shipping_average_efficiency'] / costs.at["fuel cell", "efficiency"]
p_set = nodal_energy_totals.loc[nodes, all_navigation].sum(axis=1) * 1e6 * efficiency / 8760
shipping_hydrogen_share = get(options['shipping_hydrogen_share'], investment_year)
p_set = shipping_hydrogen_share * nodal_energy_totals.loc[nodes, all_navigation].sum(axis=1) * 1e6 * efficiency / 8760
n.madd("Load",
nodes,
@ -1726,6 +1727,29 @@ def add_industry(n, costs):
p_set=p_set
)
if shipping_hydrogen_share < 1:
shipping_oil_share = 1 - shipping_hydrogen_share
p_set = shipping_oil_share * nodal_energy_totals.loc[nodes, all_navigation].sum(axis=1) * 1e6 / 8760.
n.madd("Load",
nodes,
suffix=" shipping oil",
bus="EU oil",
carrier="shipping oil",
p_set=p_set
)
co2 = shipping_oil_share * nodal_energy_totals.loc[nodes, all_navigation].sum().sum() * 1e6 / 8760 * costs.at["oil", "CO2 intensity"]
n.add("Load",
"shipping oil emissions",
bus="co2 atmosphere",
carrier="shipping oil emissions",
p_set=-co2
)
if "EU oil" not in n.buses.index:
n.add("Bus",