bjoern/pypsa-eur
1
0
Fork 0
Code Issues Pull Requests Actions 1 Packages Projects Releases Wiki Activity

Merge branch 'master' into agriculture-energy-co2

Browse Source
This commit is contained in:
Fabian Neumann 2021-08-16 14:30:15 +02:00
commit 38352927fc
8 changed files with 133 additions and 29 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
.gitignore vendored
View File

@ -28,7 +28,7 @@ gurobi.log
/data/.nfs*
/data/Industrial_Database.csv
/data/retro/tabula-calculator-calcsetbuilding.csv
/data
*.org
*.nc

18
Snakefile
View File

@ -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",

40
config.default.yaml
View File

@ -30,6 +30,7 @@ scenario:
# B for biomass supply, I for industry, shipping and aviation
# solar+c0.5 reduces the capital cost of solar to 50\% of reference value
# solar+p3 multiplies the available installable potential by factor 3
# co2 stored+e2 multiplies the potential of CO2 sequestration by a factor 2
# dist{n} includes distribution grids with investment cost of n times cost in data/costs.csv
# for myopic/perfect foresight cb states the carbon budget in GtCO2 (cumulative
# emissions throughout the transition path in the timeframe determined by the
@ -177,6 +178,15 @@ sector:
agriculture_machinery_fuel_efficiency: 0.7 # for conversion of fuel oil to use
agriculture_machinery_electric_efficiency: 0.3 # for conversion of electricity to use
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
shipping_hydrogen_liquefaction: true # whether to consider liquefaction costs for shipping H2 demands
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
@ -231,10 +241,32 @@ 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)
@ -474,4 +506,8 @@ 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"

8
doc/release_notes.rst
View File

@ -60,8 +60,12 @@ 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.
* Added option for hydrogen liquefaction costs for hydrogen demand in shipping.
This introduces a new ``H2 liquid`` bus at each location.
It is activated via ``sector: shipping_hydrogen_liquefaction: true``.
* 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
View File

@ -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
View File

@ -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"
}

69
scripts/prepare_sector_network.py
View File

@ -911,7 +911,7 @@ def add_storage(n, costs):
)
# hydrogen stored overground (where not already underground)
h2_capital_cost = costs.at["hydrogen storage tank", "fixed"]
h2_capital_cost = costs.at["hydrogen storage tank incl. compressor", "fixed"]
nodes_overground = cavern_nodes.index.symmetric_difference(nodes)
n.madd("Store",
@ -946,9 +946,9 @@ def add_storage(n, costs):
p_min_pu=-1,
p_nom_extendable=True,
length=h2_links.length.values,
capital_cost=costs.at['H2 pipeline', 'fixed'] * h2_links.length.values,
capital_cost=costs.at['H2 (g) pipeline', 'fixed'] * h2_links.length.values,
carrier="H2 pipeline",
lifetime=costs.at['H2 pipeline', 'lifetime']
lifetime=costs.at['H2 (g) pipeline', 'lifetime']
)
n.add("Carrier", "battery")
@ -1002,7 +1002,7 @@ def add_storage(n, costs):
carrier="Sabatier",
efficiency=costs.at["methanation", "efficiency"],
efficiency2=-costs.at["methanation", "efficiency"] * costs.at['gas', 'CO2 intensity'],
capital_cost=costs.at["methanation", "fixed"],
capital_cost=costs.at["methanation", "fixed"] * costs.at["methanation", "efficiency"], # costs given per kW_gas
lifetime=costs.at['methanation', 'lifetime']
)
@ -1719,18 +1719,66 @@ def add_industry(n, costs):
p_set=industrial_demand.loc[nodes, "hydrogen"] / 8760
)
if options["shipping_hydrogen_liquefaction"]:
n.madd("Bus",
nodes,
suffix=" H2 liquid",
carrier="H2 liquid",
location=nodes
)
n.madd("Link",
nodes + " H2 liquefaction",
bus0=nodes + " H2",
bus1=nodes + " H2 liquid",
carrier="H2 liquefaction",
efficiency=costs.at["H2 liquefaction", 'efficiency'],
capital_cost=costs.at["H2 liquefaction", 'fixed'],
p_nom_extendable=True,
lifetime=costs.at['H2 liquefaction', 'lifetime']
)
shipping_bus = nodes + " H2 liquid"
else:
shipping_bus = nodes + " H2"
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,
suffix=" H2 for shipping",
bus=nodes + " H2",
bus=shipping_bus,
carrier="H2 for shipping",
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",
@ -1993,14 +2041,19 @@ def maybe_adjust_costs_and_potentials(n, opts):
suptechs = map(lambda c: c.split("-", 2)[0], carrier_list)
if oo[0].startswith(tuple(suptechs)):
carrier = oo[0]
attr_lookup = {"p": "p_nom_max", "c": "capital_cost"}
attr_lookup = {"p": "p_nom_max", "e": "e_nom_max", "c": "capital_cost"}
attr = attr_lookup[oo[1][0]]
factor = float(oo[1][1:])
#beware if factor is 0 and p_nom_max is np.inf, 0*np.inf is nan
if carrier == "AC": # lines do not have carrier
n.lines[attr] *= factor
else:
comps = {"Generator", "Link", "StorageUnit"} if attr == 'p_nom_max' else {"Generator", "Link", "StorageUnit", "Store"}
if attr == 'p_nom_max':
comps = {"Generator", "Link", "StorageUnit"}
elif attr == 'e_nom_max':
comps = {"Store"}
else:
comps = {"Generator", "Link", "StorageUnit", "Store"}
for c in n.iterate_components(comps):
if carrier=='solar':
sel = c.df.carrier.str.contains(carrier) & ~c.df.carrier.str.contains("solar rooftop")

1
scripts/solve_network.py
View File

@ -151,7 +151,6 @@ def add_chp_constraints(n):
def extra_functionality(n, snapshots):
add_chp_constraints(n)
add_battery_constraints(n)