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

Merge pull request #623 from PyPSA/sec-subset-countries

Browse Source 
Run also sector-coupled build part for subset of countries
This commit is contained in:
Fabian Neumann 2023-03-09 11:53:29 +01:00 committed by GitHub
commit db83d5608f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
15 changed files with 92 additions and 184 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
.github/workflows/ci.yaml vendored
View File

@ -26,6 +26,7 @@ jobs:
build:
strategy:
fail-fast: false
matrix:
include:
# Matrix required to handle caching with Mambaforge

4
Snakefile
View File

@ -69,8 +69,8 @@ rule purge:
message:
"Purging generated resources and results. Downloads are kept."
run:
rmtree("resources/")
rmtree("results/")
rmtree("resources/", ignore_errors=True)
rmtree("results/", ignore_errors=True)
rule dag:

6
scripts/add_existing_baseyear.py
View File

@ -431,10 +431,10 @@ def add_heating_capacities_installed_before_baseyear(
ratio_residential = pd.Series(
[
(
n.loads_t.p_set.sum()["{} residential rural heat".format(node)]
n.loads_t.p_set.sum()[f"{node} residential rural heat"]
/ (
n.loads_t.p_set.sum()["{} residential rural heat".format(node)]
+ n.loads_t.p_set.sum()["{} services rural heat".format(node)]
n.loads_t.p_set.sum()[f"{node} residential rural heat"]
+ n.loads_t.p_set.sum()[f"{node} services rural heat"]
)
)
for node in nodal_df.index

31
scripts/build_ammonia_production.py
View File

@ -6,32 +6,11 @@
Build ammonia production.
"""
import country_converter as coco
import pandas as pd
country_to_alpha2 = {
"Austriae": "AT",
"Bulgaria": "BG",
"Belgiume": "BE",
"Croatia": "HR",
"Czechia": "CZ",
"Estonia": "EE",
"Finland": "FI",
"France": "FR",
"Germany": "DE",
"Greece": "GR",
"Hungarye": "HU",
"Italye": "IT",
"Lithuania": "LT",
"Netherlands": "NL",
"Norwaye": "NO",
"Poland": "PL",
"Romania": "RO",
"Serbia": "RS",
"Slovakia": "SK",
"Spain": "ES",
"Switzerland": "CH",
"United Kingdom": "GB",
}
cc = coco.CountryConverter()
if __name__ == "__main__":
if "snakemake" not in globals():
@ -48,10 +27,10 @@ if __name__ == "__main__":
skipfooter=19,
)
ammonia.rename(country_to_alpha2, inplace=True)
ammonia.index = cc.convert(ammonia.index, to="iso2")
years = [str(i) for i in range(2013, 2018)]
countries = country_to_alpha2.values()
countries = ammonia.index.intersection(snakemake.config["countries"])
ammonia = ammonia.loc[countries, years].astype(float)
# convert from ktonN to ktonNH3

49
scripts/build_energy_totals.py
View File

@ -10,12 +10,15 @@ logger = logging.getLogger(__name__)
import multiprocessing as mp
from functools import partial
import country_converter as coco
import geopandas as gpd
import numpy as np
import pandas as pd
from _helpers import mute_print
from tqdm import tqdm
cc = coco.CountryConverter()
idx = pd.IndexSlice
@ -33,8 +36,7 @@ def reverse(dictionary):
return {v: k for k, v in dictionary.items()}
# translations for Eurostat
eurostat_country_to_alpha2 = {
eurostat_codes = {
"EU28": "EU",
"EA19": "EA",
"Belgium": "BE",
@ -81,38 +83,10 @@ eurostat_country_to_alpha2 = {
"Switzerland": "CH",
}
non_EU = ["NO", "CH", "ME", "MK", "RS", "BA", "AL"]
idees_rename = {"GR": "EL", "GB": "UK"}
eu28 = [
"FR",
"DE",
"GB",
"IT",
"ES",
"PL",
"SE",
"NL",
"BE",
"FI",
"CZ",
"DK",
"PT",
"RO",
"AT",
"BG",
"EE",
"GR",
"LV",
"HU",
"IE",
"SK",
"LT",
"HR",
"LU",
"SI",
] + ["CY", "MT"]
eu28 = cc.EU28as("ISO2").ISO2.tolist()
eu28_eea = eu28.copy()
eu28_eea.remove("GB")
@ -161,7 +135,7 @@ def build_eurostat(input_eurostat, countries, report_year, year):
)
# sorted_index necessary for slicing
lookup = eurostat_country_to_alpha2
lookup = eurostat_codes
labelled_dfs = {
lookup[df.columns[0]]: df
for df in dfs.values()
@ -505,6 +479,8 @@ def build_energy_totals(countries, eurostat, swiss, idees):
# http://www.ssb.no/en/energi-og-industri/statistikker/husenergi/hvert-3-aar/2014-07-14
# The main heating source for about 73 per cent of the households is based on electricity
# => 26% is non-electric
if "NO" in df:
elec_fraction = 0.73
no_norway = df.drop("NO")
@ -687,7 +663,7 @@ def build_eurostat_co2(input_eurostat, countries, report_year, year=1990):
def build_co2_totals(countries, eea_co2, eurostat_co2):
co2 = eea_co2.reindex(countries)
for ct in countries.intersection(["BA", "RS", "AL", "ME", "MK"]):
for ct in pd.Index(countries).intersection(["BA", "RS", "AL", "ME", "MK"]):
mappings = {
"electricity": (
ct,
@ -724,9 +700,11 @@ def build_transport_data(countries, population, idees):
transport_data["number cars"] = idees["passenger cars"]
# CH from http://ec.europa.eu/eurostat/statistics-explained/index.php/Passenger_cars_in_the_EU#Luxembourg_has_the_highest_number_of_passenger_cars_per_inhabitant
if "CH" in countries:
transport_data.at["CH", "number cars"] = 4.136e6
missing = transport_data.index[transport_data["number cars"].isna()]
if not missing.empty:
logger.info(
f"Missing data on cars from:\n{list(missing)}\nFilling gaps with averaged data."
)
@ -739,6 +717,7 @@ def build_transport_data(countries, population, idees):
transport_data["average fuel efficiency"] = idees["passenger car efficiency"]
missing = transport_data.index[transport_data["average fuel efficiency"].isna()]
if not missing.empty:
logger.info(
f"Missing data on fuel efficiency from:\n{list(missing)}\nFilling gapswith averaged data."
)
@ -762,8 +741,8 @@ if __name__ == "__main__":
nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index("index")
population = nuts3["pop"].groupby(nuts3.country).sum()
countries = population.index
idees_countries = countries.intersection(eu28)
countries = snakemake.config["countries"]
idees_countries = pd.Index(countries).intersection(eu28)
data_year = config["energy_totals_year"]
report_year = snakemake.config["energy"]["eurostat_report_year"]

7
scripts/build_industrial_distribution_key.py
View File

@ -99,13 +99,12 @@ def prepare_hotmaps_database(regions):
return gdf
def build_nodal_distribution_key(hotmaps, regions):
def build_nodal_distribution_key(hotmaps, regions, countries):
"""
Build nodal distribution keys for each sector.
"""
sectors = hotmaps.Subsector.unique()
countries = regions.index.str[:2].unique()
keys = pd.DataFrame(index=regions.index, columns=sectors, dtype=float)
@ -148,10 +147,12 @@ if __name__ == "__main__":
logging.basicConfig(level=snakemake.config["logging"]["level"])
countries = snakemake.config["countries"]
regions = gpd.read_file(snakemake.input.regions_onshore).set_index("name")
hotmaps = prepare_hotmaps_database(regions)
keys = build_nodal_distribution_key(hotmaps, regions)
keys = build_nodal_distribution_key(hotmaps, regions, countries)
keys.to_csv(snakemake.output.industrial_distribution_key)

48
scripts/build_industrial_energy_demand_per_country_today.py
View File

@ -10,9 +10,12 @@ Build industrial energy demand per country.
import multiprocessing as mp
from functools import partial
import country_converter as coco
import pandas as pd
from tqdm import tqdm
cc = coco.CountryConverter()
ktoe_to_twh = 0.011630
# name in JRC-IDEES Energy Balances
@ -56,36 +59,7 @@ fuels = {
"Electricity": "electricity",
}
eu28 = [
"FR",
"DE",
"GB",
"IT",
"ES",
"PL",
"SE",
"NL",
"BE",
"FI",
"DK",
"PT",
"RO",
"AT",
"BG",
"EE",
"GR",
"LV",
"CZ",
"HU",
"IE",
"SK",
"LT",
"HR",
"LU",
"SI",
"CY",
"MT",
]
eu28 = cc.EU28as("ISO2").ISO2.tolist()
jrc_names = {"GR": "EL", "GB": "UK"}
@ -154,7 +128,10 @@ def add_ammonia_energy_demand(demand):
return demand
def add_non_eu28_industrial_energy_demand(demand):
def add_non_eu28_industrial_energy_demand(countries, demand):
non_eu28 = countries.difference(eu28)
if non_eu28.empty:
return demand
# output in MtMaterial/a
fn = snakemake.input.industrial_production_per_country
production = pd.read_csv(fn, index_col=0) / 1e3
@ -164,12 +141,10 @@ def add_non_eu28_industrial_energy_demand(demand):
production["Basic chemicals (without ammonia)"] = production[chemicals].sum(axis=1)
production.drop(columns=chemicals, inplace=True)
eu28_production = production.loc[eu28].sum()
eu28_production = production.loc[countries.intersection(eu28)].sum()
eu28_energy = demand.groupby(level=1).sum()
eu28_averages = eu28_energy / eu28_production
non_eu28 = production.index.symmetric_difference(eu28)
demand_non_eu28 = pd.concat(
{k: v * eu28_averages for k, v in production.loc[non_eu28].iterrows()}
)
@ -206,12 +181,13 @@ if __name__ == "__main__":
config = snakemake.config["industry"]
year = config.get("reference_year", 2015)
countries = pd.Index(snakemake.config["countries"])
demand = industrial_energy_demand(eu28, year)
demand = industrial_energy_demand(countries.intersection(eu28), year)
demand = add_ammonia_energy_demand(demand)
demand = add_non_eu28_industrial_energy_demand(demand)
demand = add_non_eu28_industrial_energy_demand(countries, demand)
# for format compatibility
demand = demand.stack(dropna=False).unstack(level=[0, 2])

44
scripts/build_industrial_production_per_country.py
View File

@ -14,11 +14,14 @@ logger = logging.getLogger(__name__)
import multiprocessing as mp
import country_converter as coco
import numpy as np
import pandas as pd
from _helpers import mute_print
from tqdm import tqdm
cc = coco.CountryConverter()
tj_to_ktoe = 0.0238845
ktoe_to_twh = 0.01163
@ -36,41 +39,10 @@ sub_sheet_name_dict = {
"Other Industrial Sectors": "OIS",
}
non_EU = ["NO", "CH", "ME", "MK", "RS", "BA", "AL"]
eu28 = cc.EU28as("ISO2").ISO2.values
jrc_names = {"GR": "EL", "GB": "UK"}
eu28 = [
"FR",
"DE",
"GB",
"IT",
"ES",
"PL",
"SE",
"NL",
"BE",
"FI",
"DK",
"PT",
"RO",
"AT",
"BG",
"EE",
"GR",
"LV",
"CZ",
"HU",
"IE",
"SK",
"LT",
"HR",
"LU",
"SI",
"CY",
"MT",
]
sect2sub = {
"Iron and steel": ["Electric arc", "Integrated steelworks"],
"Chemicals Industry": [
@ -233,10 +205,10 @@ def industry_production_per_country(country, year, eurostat_dir, jrc_dir):
return df
ct = "EU28" if country in non_EU else country
demand = pd.concat([get_sector_data(s, ct) for s in sect2sub.keys()])
ct = "EU28" if country not in eu28 else country
demand = pd.concat([get_sector_data(s, ct) for s in sect2sub])
if country in non_EU:
if country not in eu28:
demand *= get_energy_ratio(country, eurostat_dir, jrc_dir, year)
demand.name = country
@ -309,7 +281,7 @@ if __name__ == "__main__":
logging.basicConfig(level=snakemake.config["logging"]["level"])
countries = non_EU + eu28
countries = snakemake.config["countries"]
year = snakemake.config["industry"]["reference_year"]

2
scripts/build_powerplants.py
View File

@ -115,7 +115,7 @@ if __name__ == "__main__":
configure_logging(snakemake)
n = pypsa.Network(snakemake.input.base_network)
countries = n.buses.country.unique()
countries = snakemake.config["countries"]
ppl = (
pm.powerplants(from_url=True)

2
scripts/build_retro_cost.py
View File

@ -308,7 +308,7 @@ def prepare_building_stock_data():
u_values.set_index(["country_code", "subsector", "bage", "type"], inplace=True)
# only take in config.yaml specified countries into account
countries = ct_total.index
countries = snakemake.config["countries"]
area_tot = area_tot.loc[countries]
return u_values, country_iso_dic, countries, area_tot, area

2
scripts/plot_summary.py
View File

@ -456,7 +456,7 @@ def plot_carbon_budget_distribution(input_eurostat):
ax1.set_xlim([1990, snakemake.config["scenario"]["planning_horizons"][-1] + 1])
path_cb = "results/" + snakemake.params.RDIR + "/csvs/"
countries = snakemake.confing["countries"]
countries = snakemake.config["countries"]
e_1990 = co2_emissions_year(countries, input_eurostat, opts, year=1990)
CO2_CAP = pd.read_csv(path_cb + "carbon_budget_distribution.csv", index_col=0)

4
scripts/prepare_sector_network.py
View File

@ -238,7 +238,7 @@ def build_carbon_budget(o, input_eurostat, fn, emissions_scope, report_year):
carbon_budget = float(o[o.find("cb") + 2 : o.find("ex")])
r = float(o[o.find("ex") + 2 :])
countries = n.buses.country.dropna().unique()
countries = snakemake.config["countries"]
e_1990 = co2_emissions_year(
countries, input_eurostat, opts, emissions_scope, report_year, year=1990
@ -674,7 +674,7 @@ def add_dac(n, costs):
def add_co2limit(n, Nyears=1.0, limit=0.0):
logger.info(f"Adding CO2 budget limit as per unit of 1990 levels of {limit}")
countries = n.buses.country.dropna().unique()
countries = snakemake.config["countries"]
sectors = emission_sectors_from_opts(opts)

6
test/config.myopic.yaml
View File

@ -15,9 +15,9 @@ scenario:
ll:
- v1.5
clusters:
- 5
- 4
sector_opts:
- 191H-T-H-B-I-A-solar+p3-dist1
- 40H-T-H-B-I-A-solar+p3-dist1
planning_horizons:
- 2030
- 2040
@ -27,7 +27,7 @@ countries: ['BE']
snapshots:
start: "2013-03-01"
end: "2013-04-01"
end: "2013-03-08"
electricity:
renewable_carriers: [solar, onwind, offwind-ac, offwind-dc]

6
test/config.overnight.yaml
View File

@ -14,9 +14,9 @@ scenario:
ll:
- v1.5
clusters:
- 5
- 4
sector_opts:
- CO2L0-191H-T-H-B-I-A-solar+p3-dist1
- CO2L0-40H-T-H-B-I-A-solar+p3-dist1
planning_horizons:
- 2030
@ -24,7 +24,7 @@ countries: ['BE']
snapshots:
start: "2013-03-01"
end: "2013-04-01"
end: "2013-03-08"
electricity:
renewable_carriers: [solar, onwind, offwind-ac, offwind-dc]

4
test/config.test1.yaml
View File

@ -13,9 +13,9 @@ run:
scenario:
clusters:
- 5
- 4
opts:
- Co2L-24H
- Co2L-40H
countries: ['BE']