Merge branch 'master' into transport
This commit is contained in:
Fabian Neumann
GitHub
commit
d4fd472762
109
.github/workflows/ci.yaml
vendored
Normal file
109
.github/workflows/ci.yaml
vendored
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@ -0,0 +1,109 @@
|
||||
# SPDX-FileCopyrightText: : 2021 The PyPSA-Eur Authors
|
||||
#
|
||||
# SPDX-License-Identifier: CC0-1.0
|
||||
|
||||
name: CI
|
||||
|
||||
# Caching method based on and described by:
|
||||
# epassaro (2021): https://dev.to/epassaro/caching-anaconda-environments-in-github-actions-5hde
|
||||
# and code in GitHub repo: https://github.com/epassaro/cache-conda-envs
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- master
|
||||
pull_request:
|
||||
branches:
|
||||
- master
|
||||
schedule:
|
||||
- cron: "0 5 * * TUE"
|
||||
|
||||
env:
|
||||
CONDA_CACHE_NUMBER: 1 # Change this value to manually reset the environment cache
|
||||
DATA_CACHE_NUMBER: 1
|
||||
|
||||
jobs:
|
||||
build:
|
||||
|
||||
strategy:
|
||||
matrix:
|
||||
include:
|
||||
# Matrix required to handle caching with Mambaforge
|
||||
- os: ubuntu-latest
|
||||
label: ubuntu-latest
|
||||
prefix: /usr/share/miniconda3/envs/pypsa-eur
|
||||
|
||||
# - os: macos-latest
|
||||
# label: macos-latest
|
||||
# prefix: /Users/runner/miniconda3/envs/pypsa-eur
|
||||
|
||||
# - os: windows-latest
|
||||
# label: windows-latest
|
||||
# prefix: C:\Miniconda3\envs\pypsa-eur
|
||||
|
||||
name: ${{ matrix.label }}
|
||||
|
||||
runs-on: ${{ matrix.os }}
|
||||
|
||||
defaults:
|
||||
run:
|
||||
shell: bash -l {0}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v2
|
||||
|
||||
- name: Clone pypsa-eur and technology-data repositories
|
||||
run: |
|
||||
git clone https://github.com/pypsa/pypsa-eur ../pypsa-eur
|
||||
git clone https://github.com/pypsa/technology-data ../technology-data
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||||
cp ../pypsa-eur/test/config.test1.yaml ../pypsa-eur/config.yaml
|
||||
|
||||
- name: Setup secrets
|
||||
run: |
|
||||
echo -ne "url: ${CDSAPI_URL}\nkey: ${CDSAPI_TOKEN}\n" > ~/.cdsapirc
|
||||
|
||||
- name: Add solver to environment
|
||||
run: |
|
||||
echo -e " - coincbc\n - ipopt<3.13.3" >> ../pypsa-eur/envs/environment.yaml
|
||||
|
||||
- name: Setup Mambaforge
|
||||
uses: conda-incubator/setup-miniconda@v2
|
||||
with:
|
||||
miniforge-variant: Mambaforge
|
||||
miniforge-version: latest
|
||||
activate-environment: pypsa-eur
|
||||
use-mamba: true
|
||||
|
||||
- name: Set cache dates
|
||||
run: |
|
||||
echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
|
||||
echo "WEEK=$(date +'%Y%U')" >> $GITHUB_ENV
|
||||
|
||||
- name: Cache data and cutouts folders
|
||||
uses: actions/cache@v3
|
||||
with:
|
||||
path: |
|
||||
data
|
||||
../pypsa-eur/cutouts
|
||||
../pypsa-eur/data
|
||||
key: data-cutouts-${{ env.WEEK }}-${{ env.DATA_CACHE_NUMBER }}
|
||||
|
||||
- name: Create environment cache
|
||||
uses: actions/cache@v2
|
||||
id: cache
|
||||
with:
|
||||
path: ${{ matrix.prefix }}
|
||||
key: ${{ matrix.label }}-conda-${{ env.DATE }}-${{ env.CONDA_CACHE_NUMBER }}
|
||||
|
||||
- name: Update environment due to outdated or unavailable cache
|
||||
run: mamba env update -n pypsa-eur -f ../pypsa-eur/envs/environment.yaml
|
||||
if: steps.cache.outputs.cache-hit != 'true'
|
||||
|
||||
- name: Test snakemake workflow
|
||||
run: |
|
||||
conda activate pypsa-eur
|
||||
conda list
|
||||
cp test/config.overnight.yaml config.yaml
|
||||
snakemake -call solve_all_networks
|
||||
cp test/config.myopic.yaml config.yaml
|
||||
snakemake -call solve_all_networks
|
||||
26
Snakefile
26
Snakefile
@ -45,18 +45,22 @@ rule prepare_sector_networks:
|
||||
**config['scenario'])
|
||||
|
||||
datafiles = [
|
||||
"eea/UNFCCC_v23.csv",
|
||||
"switzerland-sfoe/switzerland-new_format.csv",
|
||||
"nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
|
||||
"myb1-2017-nitro.xls",
|
||||
"Industrial_Database.csv",
|
||||
"emobility/KFZ__count",
|
||||
"emobility/Pkw__count",
|
||||
"data/eea/UNFCCC_v23.csv",
|
||||
"data/switzerland-sfoe/switzerland-new_format.csv",
|
||||
"data/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson",
|
||||
"data/myb1-2017-nitro.xls",
|
||||
"data/Industrial_Database.csv",
|
||||
"data/emobility/KFZ__count",
|
||||
"data/emobility/Pkw__count",
|
||||
"data/h2_salt_caverns_GWh_per_sqkm.geojson",
|
||||
directory("data/eurostat-energy_balances-june_2016_edition"),
|
||||
directory("data/eurostat-energy_balances-may_2018_edition"),
|
||||
directory("data/jrc-idees-2015"),
|
||||
]
|
||||
|
||||
if config.get('retrieve_sector_databundle', True):
|
||||
rule retrieve_sector_databundle:
|
||||
output: expand('data/{file}', file=datafiles)
|
||||
output: *datafiles
|
||||
log: "logs/retrieve_sector_databundle.log"
|
||||
script: 'scripts/retrieve_sector_databundle.py'
|
||||
|
||||
@ -252,9 +256,9 @@ rule build_biomass_potentials:
|
||||
enspreso_biomass=HTTP.remote("https://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/ENSPRESO/ENSPRESO_BIOMASS.xlsx", keep_local=True),
|
||||
nuts2="data/nuts/NUTS_RG_10M_2013_4326_LEVL_2.geojson", # https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/#nuts21
|
||||
regions_onshore=pypsaeur("resources/regions_onshore_elec_s{simpl}_{clusters}.geojson"),
|
||||
nuts3_population="../pypsa-eur/data/bundle/nama_10r_3popgdp.tsv.gz",
|
||||
swiss_cantons="../pypsa-eur/data/bundle/ch_cantons.csv",
|
||||
swiss_population="../pypsa-eur/data/bundle/je-e-21.03.02.xls",
|
||||
nuts3_population=pypsaeur("data/bundle/nama_10r_3popgdp.tsv.gz"),
|
||||
swiss_cantons=pypsaeur("data/bundle/ch_cantons.csv"),
|
||||
swiss_population=pypsaeur("data/bundle/je-e-21.03.02.xls"),
|
||||
country_shapes=pypsaeur('resources/country_shapes.geojson')
|
||||
output:
|
||||
biomass_potentials_all='resources/biomass_potentials_all_s{simpl}_{clusters}.csv',
|
||||
|
||||
@ -1,3 +1,4 @@
|
||||
attribute,type,unit,default,description,status
|
||||
build_year,integer,year,n/a,build year,Input (optional)
|
||||
lifetime,float,years,n/a,lifetime,Input (optional)
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
||||
|
@ -2,12 +2,12 @@ attribute,type,unit,default,description,status
|
||||
bus2,string,n/a,n/a,2nd bus,Input (optional)
|
||||
bus3,string,n/a,n/a,3rd bus,Input (optional)
|
||||
bus4,string,n/a,n/a,4th bus,Input (optional)
|
||||
efficiency2,static or series,per unit,1.,2nd bus efficiency,Input (optional)
|
||||
efficiency3,static or series,per unit,1.,3rd bus efficiency,Input (optional)
|
||||
efficiency4,static or series,per unit,1.,4th bus efficiency,Input (optional)
|
||||
p2,series,MW,0.,2nd bus output,Output
|
||||
p3,series,MW,0.,3rd bus output,Output
|
||||
p4,series,MW,0.,4th bus output,Output
|
||||
build_year,integer,year,n/a,build year,Input (optional)
|
||||
lifetime,float,years,n/a,lifetime,Input (optional)
|
||||
efficiency2,static or series,per unit,1,2nd bus efficiency,Input (optional)
|
||||
efficiency3,static or series,per unit,1,3rd bus efficiency,Input (optional)
|
||||
efficiency4,static or series,per unit,1,4th bus efficiency,Input (optional)
|
||||
p2,series,MW,0,2nd bus output,Output
|
||||
p3,series,MW,0,3rd bus output,Output
|
||||
p4,series,MW,0,4th bus output,Output
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
||||
|
@ -1,4 +1,4 @@
|
||||
attribute,type,unit,default,description,status
|
||||
build_year,integer,year,n/a,build year,Input (optional)
|
||||
lifetime,float,years,n/a,lifetime,Input (optional)
|
||||
carrier,string,n/a,n/a,carrier,Input (optional)
|
||||
lifetime,float,years,inf,lifetime,Input (optional)
|
||||
build_year,int,year ,0,build year,Input (optional)
|
||||
|
||||
|
@ -8,15 +8,22 @@ idx = pd.IndexSlice
|
||||
|
||||
import pypsa
|
||||
import yaml
|
||||
import numpy as np
|
||||
|
||||
from add_existing_baseyear import add_build_year_to_new_assets
|
||||
from helper import override_component_attrs
|
||||
from solve_network import basename
|
||||
|
||||
|
||||
def add_brownfield(n, n_p, year):
|
||||
|
||||
print("adding brownfield")
|
||||
|
||||
# electric transmission grid set optimised capacities of previous as minimum
|
||||
n.lines.s_nom_min = n_p.lines.s_nom_opt
|
||||
dc_i = n.links[n.links.carrier=="DC"].index
|
||||
n.links.loc[dc_i, "p_nom_min"] = n_p.links.loc[dc_i, "p_nom_opt"]
|
||||
|
||||
for c in n_p.iterate_components(["Link", "Generator", "Store"]):
|
||||
|
||||
attr = "e" if c.name == "Store" else "p"
|
||||
@ -25,7 +32,7 @@ def add_brownfield(n, n_p, year):
|
||||
# CO2 or global EU values since these are already in n
|
||||
n_p.mremove(
|
||||
c.name,
|
||||
c.df.index[c.df.lifetime.isna()]
|
||||
c.df.index[c.df.lifetime==np.inf]
|
||||
)
|
||||
|
||||
# remove assets whose build_year + lifetime < year
|
||||
@ -44,7 +51,7 @@ def add_brownfield(n, n_p, year):
|
||||
)]
|
||||
|
||||
threshold = snakemake.config['existing_capacities']['threshold_capacity']
|
||||
|
||||
|
||||
if not chp_heat.empty:
|
||||
threshold_chp_heat = (threshold
|
||||
* c.df.efficiency[chp_heat.str.replace("heat", "electric")].values
|
||||
@ -55,7 +62,7 @@ def add_brownfield(n, n_p, year):
|
||||
c.name,
|
||||
chp_heat[c.df.loc[chp_heat, attr + "_nom_opt"] < threshold_chp_heat]
|
||||
)
|
||||
|
||||
|
||||
n_p.mremove(
|
||||
c.name,
|
||||
c.df.index[c.df[attr + "_nom_extendable"] & ~c.df.index.isin(chp_heat) & (c.df[attr + "_nom_opt"] < threshold)]
|
||||
@ -75,16 +82,44 @@ def add_brownfield(n, n_p, year):
|
||||
for tattr in n.component_attrs[c.name].index[selection]:
|
||||
n.import_series_from_dataframe(c.pnl[tattr], c.name, tattr)
|
||||
|
||||
# deal with gas network
|
||||
pipe_carrier = ['gas pipeline']
|
||||
if snakemake.config["sector"]['H2_retrofit']:
|
||||
# drop capacities of previous year to avoid duplicating
|
||||
to_drop = n.links.carrier.isin(pipe_carrier) & (n.links.build_year!=year)
|
||||
n.mremove("Link", n.links.loc[to_drop].index)
|
||||
|
||||
# subtract the already retrofitted from today's gas grid capacity
|
||||
h2_retrofitted_fixed_i = n.links[(n.links.carrier=='H2 pipeline retrofitted') & (n.links.build_year!=year)].index
|
||||
gas_pipes_i = n.links[n.links.carrier.isin(pipe_carrier)].index
|
||||
CH4_per_H2 = 1 / snakemake.config["sector"]["H2_retrofit_capacity_per_CH4"]
|
||||
fr = "H2 pipeline retrofitted"
|
||||
to = "gas pipeline"
|
||||
# today's pipe capacity
|
||||
pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom']
|
||||
# already retrofitted capacity from gas -> H2
|
||||
already_retrofitted = (n.links.loc[h2_retrofitted_fixed_i, 'p_nom']
|
||||
.rename(lambda x: basename(x).replace(fr, to)).groupby(level=0).sum())
|
||||
remaining_capacity = pipe_capacity - CH4_per_H2 * already_retrofitted.reindex(index=pipe_capacity.index).fillna(0)
|
||||
n.links.loc[gas_pipes_i, "p_nom"] = remaining_capacity
|
||||
else:
|
||||
new_pipes = n.links.carrier.isin(pipe_carrier) & (n.links.build_year==year)
|
||||
n.links.loc[new_pipes, "p_nom"] = 0.
|
||||
n.links.loc[new_pipes, "p_nom_min"] = 0.
|
||||
|
||||
|
||||
|
||||
#%%
|
||||
if __name__ == "__main__":
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake(
|
||||
'add_brownfield',
|
||||
simpl='',
|
||||
clusters=48,
|
||||
clusters="37",
|
||||
opts="",
|
||||
lv=1.0,
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
|
||||
sector_opts='168H-T-H-B-I-solar+p3-dist1',
|
||||
planning_horizons=2030,
|
||||
)
|
||||
|
||||
|
||||
@ -12,9 +12,11 @@ import xarray as xr
|
||||
import pypsa
|
||||
import yaml
|
||||
|
||||
from prepare_sector_network import prepare_costs
|
||||
from prepare_sector_network import prepare_costs, define_spatial
|
||||
from helper import override_component_attrs
|
||||
|
||||
from types import SimpleNamespace
|
||||
spatial = SimpleNamespace()
|
||||
|
||||
def add_build_year_to_new_assets(n, baseyear):
|
||||
"""
|
||||
@ -28,7 +30,7 @@ def add_build_year_to_new_assets(n, baseyear):
|
||||
# Give assets with lifetimes and no build year the build year baseyear
|
||||
for c in n.iterate_components(["Link", "Generator", "Store"]):
|
||||
|
||||
assets = c.df.index[~c.df.lifetime.isna() & c.df.build_year==0]
|
||||
assets = c.df.index[(c.df.lifetime!=np.inf) & (c.df.build_year==0)]
|
||||
c.df.loc[assets, "build_year"] = baseyear
|
||||
|
||||
# add -baseyear to name
|
||||
@ -153,13 +155,13 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
|
||||
df_agg.Fueltype = df_agg.Fueltype.map(rename_fuel)
|
||||
|
||||
# assign clustered bus
|
||||
busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0, squeeze=True)
|
||||
busmap = pd.read_csv(snakemake.input.busmap, index_col=0, squeeze=True)
|
||||
busmap_s = pd.read_csv(snakemake.input.busmap_s, index_col=0).squeeze()
|
||||
busmap = pd.read_csv(snakemake.input.busmap, index_col=0).squeeze()
|
||||
|
||||
inv_busmap = {}
|
||||
for k, v in busmap.iteritems():
|
||||
inv_busmap[v] = inv_busmap.get(v, []) + [k]
|
||||
|
||||
|
||||
clustermaps = busmap_s.map(busmap)
|
||||
clustermaps.index = clustermaps.index.astype(int)
|
||||
|
||||
@ -197,10 +199,15 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
|
||||
capacity = capacity[capacity > snakemake.config['existing_capacities']['threshold_capacity']]
|
||||
|
||||
if generator in ['solar', 'onwind', 'offwind']:
|
||||
|
||||
|
||||
suffix = '-ac' if generator == 'offwind' else ''
|
||||
name_suffix = f' {generator}{suffix}-{baseyear}'
|
||||
|
||||
# to consider electricity grid connection costs or a split between
|
||||
# solar utility and rooftop as well, rather take cost assumptions
|
||||
# from existing network than from the cost database
|
||||
capital_cost = n.generators.loc[n.generators.carrier==generator+suffix, "capital_cost"].mean()
|
||||
|
||||
if 'm' in snakemake.wildcards.clusters:
|
||||
|
||||
for ind in capacity.index:
|
||||
@ -213,14 +220,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
|
||||
|
||||
p_max_pu = n.generators_t.p_max_pu[[i + name_suffix for i in inv_ind]]
|
||||
p_max_pu.columns=[i + name_suffix for i in inv_ind ]
|
||||
|
||||
|
||||
n.madd("Generator",
|
||||
[i + name_suffix for i in inv_ind],
|
||||
bus=ind,
|
||||
carrier=generator,
|
||||
p_nom=capacity[ind] / len(inv_ind), # split among regions in a country
|
||||
marginal_cost=costs.at[generator,'VOM'],
|
||||
capital_cost=costs.at[generator,'fixed'],
|
||||
capital_cost=capital_cost,
|
||||
efficiency=costs.at[generator, 'efficiency'],
|
||||
p_max_pu=p_max_pu,
|
||||
build_year=grouping_year,
|
||||
@ -238,7 +245,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
|
||||
carrier=generator,
|
||||
p_nom=capacity,
|
||||
marginal_cost=costs.at[generator, 'VOM'],
|
||||
capital_cost=costs.at[generator, 'fixed'],
|
||||
capital_cost=capital_cost,
|
||||
efficiency=costs.at[generator, 'efficiency'],
|
||||
p_max_pu=p_max_pu.rename(columns=n.generators.bus),
|
||||
build_year=grouping_year,
|
||||
@ -246,11 +253,14 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
|
||||
)
|
||||
|
||||
else:
|
||||
bus0 = vars(spatial)[carrier[generator]].nodes
|
||||
if "EU" not in vars(spatial)[carrier[generator]].locations:
|
||||
bus0 = bus0.intersection(capacity.index + " gas")
|
||||
|
||||
n.madd("Link",
|
||||
capacity.index,
|
||||
suffix= " " + generator +"-" + str(grouping_year),
|
||||
bus0="EU " + carrier[generator],
|
||||
bus0=bus0,
|
||||
bus1=capacity.index,
|
||||
bus2="co2 atmosphere",
|
||||
carrier=generator,
|
||||
@ -399,10 +409,11 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
|
||||
lifetime=costs.at[costs_name, 'lifetime']
|
||||
)
|
||||
|
||||
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix= f" {name} gas boiler-{grouping_year}",
|
||||
bus0="EU gas",
|
||||
bus0=spatial.gas.nodes,
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
bus2="co2 atmosphere",
|
||||
carrier=name + " gas boiler",
|
||||
@ -417,7 +428,7 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
|
||||
n.madd("Link",
|
||||
nodes[name],
|
||||
suffix=f" {name} oil boiler-{grouping_year}",
|
||||
bus0="EU oil",
|
||||
bus0=spatial.oil.nodes,
|
||||
bus1=nodes[name] + " " + name + " heat",
|
||||
bus2="co2 atmosphere",
|
||||
carrier=name + " oil boiler",
|
||||
@ -436,17 +447,17 @@ def add_heating_capacities_installed_before_baseyear(n, baseyear, grouping_years
|
||||
threshold = snakemake.config['existing_capacities']['threshold_capacity']
|
||||
n.mremove("Link", [index for index in n.links.index.to_list() if str(grouping_year) in index and n.links.p_nom[index] < threshold])
|
||||
|
||||
|
||||
#%%
|
||||
if __name__ == "__main__":
|
||||
if 'snakemake' not in globals():
|
||||
from helper import mock_snakemake
|
||||
snakemake = mock_snakemake(
|
||||
'add_existing_baseyear',
|
||||
simpl='',
|
||||
clusters=45,
|
||||
clusters="37",
|
||||
lv=1.0,
|
||||
opts='',
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
|
||||
sector_opts='168H-T-H-B-I-solar+p3-dist1',
|
||||
planning_horizons=2020,
|
||||
)
|
||||
|
||||
@ -459,7 +470,8 @@ if __name__ == "__main__":
|
||||
|
||||
overrides = override_component_attrs(snakemake.input.overrides)
|
||||
n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
|
||||
|
||||
# define spatial resolution of carriers
|
||||
spatial = define_spatial(n.buses[n.buses.carrier=="AC"].index, options)
|
||||
add_build_year_to_new_assets(n, baseyear)
|
||||
|
||||
Nyears = n.snapshot_weightings.generators.sum() / 8760.
|
||||
@ -471,7 +483,7 @@ if __name__ == "__main__":
|
||||
snakemake.config['costs']['lifetime']
|
||||
)
|
||||
|
||||
grouping_years=snakemake.config['existing_capacities']['grouping_years']
|
||||
grouping_years = snakemake.config['existing_capacities']['grouping_years']
|
||||
add_power_capacities_installed_before_baseyear(n, grouping_years, costs, baseyear)
|
||||
|
||||
if "H" in opts:
|
||||
|
||||
@ -144,10 +144,12 @@ def build_nuts2_shapes():
|
||||
nuts2 = gpd.GeoDataFrame(gpd.read_file(snakemake.input.nuts2).set_index('id').geometry)
|
||||
|
||||
countries = gpd.read_file(snakemake.input.country_shapes).set_index('name')
|
||||
missing = countries.loc[["AL", "RS", "BA"]]
|
||||
missing_iso2 = countries.index.intersection(["AL", "RS", "BA"])
|
||||
missing = countries.loc[missing_iso2]
|
||||
|
||||
nuts2.rename(index={"ME00": "ME", "MK00": "MK"}, inplace=True)
|
||||
|
||||
return nuts2.append(missing)
|
||||
return pd.concat([nuts2, missing])
|
||||
|
||||
|
||||
def area(gdf):
|
||||
|
||||
@ -26,7 +26,7 @@ def build_gas_input_locations(lng_fn, planned_lng_fn, entry_fn, prod_fn, countri
|
||||
planned_lng = pd.read_csv(planned_lng_fn)
|
||||
planned_lng.geometry = planned_lng.geometry.apply(wkt.loads)
|
||||
planned_lng = gpd.GeoDataFrame(planned_lng, crs=4326)
|
||||
lng = lng.append(planned_lng, ignore_index=True)
|
||||
lng = pd.concat([lng, planned_lng], ignore_index=True)
|
||||
|
||||
# Entry points from outside the model scope
|
||||
entry = read_scigrid_gas(entry_fn)
|
||||
|
||||
@ -115,14 +115,14 @@ def get_energy_ratio(country):
|
||||
# estimate physical output, energy consumption in the sector and country
|
||||
fn = f"{eurostat_dir}/{eb_names[country]}.XLSX"
|
||||
df = pd.read_excel(fn, sheet_name='2016', index_col=2,
|
||||
header=0, skiprows=1, squeeze=True)
|
||||
header=0, skiprows=1).squeeze('columns')
|
||||
e_country = df.loc[eb_sectors.keys(
|
||||
), 'Total all products'].rename(eb_sectors)
|
||||
|
||||
fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_EU28.xlsx'
|
||||
|
||||
df = pd.read_excel(fn, sheet_name='Ind_Summary',
|
||||
index_col=0, header=0, squeeze=True)
|
||||
index_col=0, header=0).squeeze('columns')
|
||||
|
||||
assert df.index[48] == "by sector"
|
||||
year_i = df.columns.get_loc(year)
|
||||
@ -142,7 +142,7 @@ def industry_production_per_country(country):
|
||||
fn = f'{jrc_dir}/JRC-IDEES-2015_Industry_{jrc_country}.xlsx'
|
||||
sheet = sub_sheet_name_dict[sector]
|
||||
df = pd.read_excel(fn, sheet_name=sheet,
|
||||
index_col=0, header=0, squeeze=True)
|
||||
index_col=0, header=0).squeeze('columns')
|
||||
|
||||
year_i = df.columns.get_loc(year)
|
||||
df = df.iloc[find_physical_output(df), year_i]
|
||||
|
||||
@ -78,9 +78,8 @@ def load_idees_data(sector, country="EU28"):
|
||||
sheet_name=list(sheets.values()),
|
||||
index_col=0,
|
||||
header=0,
|
||||
squeeze=True,
|
||||
usecols=usecols,
|
||||
)
|
||||
).squeeze('columns')
|
||||
|
||||
for k, v in sheets.items():
|
||||
idees[k] = idees.pop(v)
|
||||
|
||||
@ -33,7 +33,7 @@ if __name__ == '__main__':
|
||||
|
||||
urban_fraction = pd.read_csv(snakemake.input.urban_percent,
|
||||
header=None, index_col=0,
|
||||
names=['fraction'], squeeze=True) / 100.
|
||||
names=['fraction']).squeeze() / 100.
|
||||
|
||||
# fill missing Balkans values
|
||||
missing = ["AL", "ME", "MK"]
|
||||
|
||||
@ -223,6 +223,26 @@ def plot_map(network, components=["links", "stores", "storage_units", "generator
|
||||
bbox_inches="tight"
|
||||
)
|
||||
|
||||
def group_pipes(df, drop_direction=False):
|
||||
"""Group pipes which connect same buses and return overall capacity.
|
||||
"""
|
||||
if drop_direction:
|
||||
positive_order = df.bus0 < df.bus1
|
||||
df_p = df[positive_order]
|
||||
swap_buses = {"bus0": "bus1", "bus1": "bus0"}
|
||||
df_n = df[~positive_order].rename(columns=swap_buses)
|
||||
df = pd.concat([df_p, df_n])
|
||||
|
||||
# there are pipes for each investment period rename to AC buses name for plotting
|
||||
df.index = df.apply(
|
||||
lambda x: f"H2 pipeline {x.bus0.replace(' H2', '')} -> {x.bus1.replace(' H2', '')}",
|
||||
axis=1
|
||||
)
|
||||
# group pipe lines connecting the same buses and rename them for plotting
|
||||
pipe_capacity = df["p_nom_opt"].groupby(level=0).sum()
|
||||
|
||||
return pipe_capacity
|
||||
|
||||
|
||||
def plot_h2_map(network):
|
||||
|
||||
@ -235,7 +255,7 @@ def plot_h2_map(network):
|
||||
bus_size_factor = 1e5
|
||||
linewidth_factor = 1e4
|
||||
# MW below which not drawn
|
||||
line_lower_threshold = 1e3
|
||||
line_lower_threshold = 1e2
|
||||
|
||||
# Drop non-electric buses so they don't clutter the plot
|
||||
n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
|
||||
@ -246,28 +266,20 @@ def plot_h2_map(network):
|
||||
|
||||
# make a fake MultiIndex so that area is correct for legend
|
||||
bus_sizes.rename(index=lambda x: x.replace(" H2", ""), level=0, inplace=True)
|
||||
|
||||
# drop all links which are not H2 pipelines
|
||||
n.links.drop(n.links.index[~n.links.carrier.str.contains("H2 pipeline")], inplace=True)
|
||||
|
||||
h2_new = n.links.loc[n.links.carrier=="H2 pipeline", "p_nom_opt"]
|
||||
|
||||
h2_new = n.links.loc[n.links.carrier=="H2 pipeline"]
|
||||
h2_retro = n.links.loc[n.links.carrier=='H2 pipeline retrofitted']
|
||||
# sum capacitiy for pipelines from different investment periods
|
||||
h2_new = group_pipes(h2_new)
|
||||
h2_retro = group_pipes(h2_retro, drop_direction=True).reindex(h2_new.index).fillna(0)
|
||||
|
||||
positive_order = h2_retro.bus0 < h2_retro.bus1
|
||||
h2_retro_p = h2_retro[positive_order]
|
||||
swap_buses = {"bus0": "bus1", "bus1": "bus0"}
|
||||
h2_retro_n = h2_retro[~positive_order].rename(columns=swap_buses)
|
||||
h2_retro = pd.concat([h2_retro_p, h2_retro_n])
|
||||
|
||||
h2_retro.index = h2_retro.apply(
|
||||
lambda x: f"H2 pipeline {x.bus0.replace(' H2', '')} -> {x.bus1.replace(' H2', '')}",
|
||||
axis=1
|
||||
)
|
||||
|
||||
h2_retro = h2_retro["p_nom_opt"]
|
||||
|
||||
n.links.rename(index=lambda x: x.split("-2")[0], inplace=True)
|
||||
n.links = n.links.groupby(level=0).first()
|
||||
link_widths_total = (h2_new + h2_retro) / linewidth_factor
|
||||
link_widths_total = link_widths_total.groupby(level=0).sum().reindex(n.links.index).fillna(0.)
|
||||
link_widths_total = link_widths_total.reindex(n.links.index).fillna(0.)
|
||||
link_widths_total[n.links.p_nom_opt < line_lower_threshold] = 0.
|
||||
|
||||
retro = n.links.p_nom_opt.where(n.links.carrier=='H2 pipeline retrofitted', other=0.)
|
||||
@ -281,7 +293,7 @@ def plot_h2_map(network):
|
||||
figsize=(7, 6),
|
||||
subplot_kw={"projection": ccrs.PlateCarree()}
|
||||
)
|
||||
|
||||
|
||||
n.plot(
|
||||
bus_sizes=bus_sizes,
|
||||
bus_colors=snakemake.config['plotting']['tech_colors'],
|
||||
@ -365,7 +377,7 @@ def plot_ch4_map(network):
|
||||
# Drop non-electric buses so they don't clutter the plot
|
||||
n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
|
||||
|
||||
fossil_gas_i = n.generators[n.generators.carrier=="gas"].index
|
||||
fossil_gas_i = n.generators[n.generators.carrier=="gas"].index
|
||||
fossil_gas = n.generators_t.p.loc[:,fossil_gas_i].mul(n.snapshot_weightings.generators, axis=0).sum().groupby(n.generators.loc[fossil_gas_i,"bus"]).sum() / bus_size_factor
|
||||
fossil_gas.rename(index=lambda x: x.replace(" gas", ""), inplace=True)
|
||||
fossil_gas = fossil_gas.reindex(n.buses.index).fillna(0)
|
||||
@ -390,10 +402,10 @@ def plot_ch4_map(network):
|
||||
to_remove = n.links.index[~n.links.carrier.str.contains("gas pipeline")]
|
||||
n.links.drop(to_remove, inplace=True)
|
||||
|
||||
link_widths_rem = n.links.p_nom_opt / linewidth_factor
|
||||
link_widths_rem = n.links.p_nom_opt / linewidth_factor
|
||||
link_widths_rem[n.links.p_nom_opt < line_lower_threshold] = 0.
|
||||
|
||||
link_widths_orig = n.links.p_nom / linewidth_factor
|
||||
link_widths_orig = n.links.p_nom / linewidth_factor
|
||||
link_widths_orig[n.links.p_nom < line_lower_threshold] = 0.
|
||||
|
||||
max_usage = n.links_t.p0.abs().max(axis=0)
|
||||
@ -422,7 +434,7 @@ def plot_ch4_map(network):
|
||||
link_colors='lightgrey',
|
||||
link_widths=link_widths_orig,
|
||||
branch_components=["Link"],
|
||||
ax=ax,
|
||||
ax=ax,
|
||||
**map_opts
|
||||
)
|
||||
|
||||
@ -452,7 +464,7 @@ def plot_ch4_map(network):
|
||||
facecolor='grey'
|
||||
)
|
||||
labels = ["{} TWh".format(s) for s in (10, 100)]
|
||||
|
||||
|
||||
l2 = ax.legend(
|
||||
handles, labels,
|
||||
loc="upper left",
|
||||
@ -462,7 +474,7 @@ def plot_ch4_map(network):
|
||||
title='gas generation',
|
||||
handler_map=make_handler_map_to_scale_circles_as_in(ax)
|
||||
)
|
||||
|
||||
|
||||
ax.add_artist(l2)
|
||||
|
||||
handles = []
|
||||
@ -471,7 +483,7 @@ def plot_ch4_map(network):
|
||||
for s in (50, 10):
|
||||
handles.append(plt.Line2D([0], [0], color="grey", linewidth=s * 1e3 / linewidth_factor))
|
||||
labels.append("{} GW".format(s))
|
||||
|
||||
|
||||
l1_1 = ax.legend(
|
||||
handles, labels,
|
||||
loc="upper left",
|
||||
@ -481,7 +493,7 @@ def plot_ch4_map(network):
|
||||
handletextpad=1.5,
|
||||
title='gas pipeline used capacity'
|
||||
)
|
||||
|
||||
|
||||
ax.add_artist(l1_1)
|
||||
|
||||
fig.savefig(
|
||||
@ -695,11 +707,11 @@ if __name__ == "__main__":
|
||||
snakemake = mock_snakemake(
|
||||
'plot_network',
|
||||
simpl='',
|
||||
clusters=45,
|
||||
lv=1.5,
|
||||
clusters="45",
|
||||
lv=1.0,
|
||||
opts='',
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar+p3-dist1',
|
||||
planning_horizons=2030,
|
||||
sector_opts='168H-T-H-B-I-A-solar+p3-dist1',
|
||||
planning_horizons="2050",
|
||||
)
|
||||
|
||||
overrides = override_component_attrs(snakemake.input.overrides)
|
||||
|
||||
@ -27,7 +27,7 @@ from types import SimpleNamespace
|
||||
spatial = SimpleNamespace()
|
||||
|
||||
|
||||
def define_spatial(nodes):
|
||||
def define_spatial(nodes, options):
|
||||
"""
|
||||
Namespace for spatial
|
||||
|
||||
@ -37,7 +37,6 @@ def define_spatial(nodes):
|
||||
"""
|
||||
|
||||
global spatial
|
||||
global options
|
||||
|
||||
spatial.nodes = nodes
|
||||
|
||||
@ -72,7 +71,7 @@ def define_spatial(nodes):
|
||||
spatial.co2.vents = ["co2 vent"]
|
||||
|
||||
spatial.co2.df = pd.DataFrame(vars(spatial.co2), index=nodes)
|
||||
|
||||
|
||||
# gas
|
||||
|
||||
spatial.gas = SimpleNamespace()
|
||||
@ -94,6 +93,28 @@ def define_spatial(nodes):
|
||||
|
||||
spatial.gas.df = pd.DataFrame(vars(spatial.gas), index=nodes)
|
||||
|
||||
# oil
|
||||
spatial.oil = SimpleNamespace()
|
||||
spatial.oil.nodes = ["EU oil"]
|
||||
spatial.oil.locations = ["EU"]
|
||||
|
||||
# uranium
|
||||
spatial.uranium = SimpleNamespace()
|
||||
spatial.uranium.nodes = ["EU uranium"]
|
||||
spatial.uranium.locations = ["EU"]
|
||||
|
||||
# coal
|
||||
spatial.coal = SimpleNamespace()
|
||||
spatial.coal.nodes = ["EU coal"]
|
||||
spatial.coal.locations = ["EU"]
|
||||
|
||||
# lignite
|
||||
spatial.lignite = SimpleNamespace()
|
||||
spatial.lignite.nodes = ["EU lignite"]
|
||||
spatial.lignite.locations = ["EU"]
|
||||
|
||||
return spatial
|
||||
|
||||
|
||||
from types import SimpleNamespace
|
||||
spatial = SimpleNamespace()
|
||||
@ -251,6 +272,7 @@ def create_network_topology(n, prefix, carriers=["DC"], connector=" -> ", bidire
|
||||
|
||||
ln_attrs = ["bus0", "bus1", "length"]
|
||||
lk_attrs = ["bus0", "bus1", "length", "underwater_fraction"]
|
||||
lk_attrs = n.links.columns.intersection(lk_attrs)
|
||||
|
||||
candidates = pd.concat([
|
||||
n.lines[ln_attrs],
|
||||
@ -277,7 +299,7 @@ def create_network_topology(n, prefix, carriers=["DC"], connector=" -> ", bidire
|
||||
topo_reverse = topo.copy()
|
||||
topo_reverse.rename(columns=swap_buses, inplace=True)
|
||||
topo_reverse.index = topo_reverse.apply(make_index, axis=1)
|
||||
topo = topo.append(topo_reverse)
|
||||
topo = pd.concat([topo, topo_reverse])
|
||||
|
||||
return topo
|
||||
|
||||
@ -351,7 +373,8 @@ def add_carrier_buses(n, carrier, nodes=None):
|
||||
"""
|
||||
|
||||
if nodes is None:
|
||||
nodes = ["EU " + carrier]
|
||||
nodes = vars(spatial)[carrier].nodes
|
||||
location = vars(spatial)[carrier].locations
|
||||
|
||||
# skip if carrier already exists
|
||||
if carrier in n.carriers.index:
|
||||
@ -364,7 +387,7 @@ def add_carrier_buses(n, carrier, nodes=None):
|
||||
|
||||
n.madd("Bus",
|
||||
nodes,
|
||||
location=nodes.str.replace(" " + carrier, ""),
|
||||
location=location,
|
||||
carrier=carrier
|
||||
)
|
||||
|
||||
@ -572,7 +595,6 @@ def cycling_shift(df, steps=1):
|
||||
return df
|
||||
|
||||
|
||||
|
||||
# TODO checkout PyPSA-Eur script
|
||||
def prepare_costs(cost_file, USD_to_EUR, discount_rate, Nyears, lifetime):
|
||||
|
||||
@ -612,10 +634,8 @@ def add_generation(n, costs):
|
||||
|
||||
for generator, carrier in conventionals.items():
|
||||
|
||||
if carrier == 'gas':
|
||||
carrier_nodes = spatial.gas.nodes
|
||||
else:
|
||||
carrier_nodes = ["EU " + carrier]
|
||||
|
||||
carrier_nodes = vars(spatial)[carrier].nodes
|
||||
|
||||
add_carrier_buses(n, carrier, carrier_nodes)
|
||||
|
||||
@ -851,18 +871,20 @@ def add_storage_and_grids(n, costs):
|
||||
)
|
||||
|
||||
cavern_types = snakemake.config["sector"]["hydrogen_underground_storage_locations"]
|
||||
h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0)[cavern_types].sum(axis=1)
|
||||
h2_caverns = pd.read_csv(snakemake.input.h2_cavern, index_col=0)
|
||||
|
||||
# only use sites with at least 2 TWh potential
|
||||
h2_caverns = h2_caverns[h2_caverns > 2]
|
||||
|
||||
# convert TWh to MWh
|
||||
h2_caverns = h2_caverns * 1e6
|
||||
if not h2_caverns.empty and options['hydrogen_underground_storage']:
|
||||
|
||||
# clip at 1000 TWh for one location
|
||||
h2_caverns.clip(upper=1e9, inplace=True)
|
||||
h2_caverns = h2_caverns[cavern_types].sum(axis=1)
|
||||
|
||||
if options['hydrogen_underground_storage']:
|
||||
# only use sites with at least 2 TWh potential
|
||||
h2_caverns = h2_caverns[h2_caverns > 2]
|
||||
|
||||
# convert TWh to MWh
|
||||
h2_caverns = h2_caverns * 1e6
|
||||
|
||||
# clip at 1000 TWh for one location
|
||||
h2_caverns.clip(upper=1e9, inplace=True)
|
||||
|
||||
logger.info("Add hydrogen underground storage")
|
||||
|
||||
@ -875,7 +897,8 @@ def add_storage_and_grids(n, costs):
|
||||
e_nom_max=h2_caverns.values,
|
||||
e_cyclic=True,
|
||||
carrier="H2 Store",
|
||||
capital_cost=h2_capital_cost
|
||||
capital_cost=h2_capital_cost,
|
||||
lifetime=costs.at["hydrogen storage underground", "lifetime"]
|
||||
)
|
||||
|
||||
# hydrogen stored overground (where not already underground)
|
||||
@ -925,7 +948,7 @@ def add_storage_and_grids(n, costs):
|
||||
carrier="gas pipeline",
|
||||
lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
|
||||
)
|
||||
|
||||
|
||||
# remove fossil generators where there is neither
|
||||
# production, LNG terminal, nor entry-point beyond system scope
|
||||
|
||||
@ -960,24 +983,27 @@ def add_storage_and_grids(n, costs):
|
||||
|
||||
# apply k_edge_augmentation weighted by length of complement edges
|
||||
k_edge = options.get("gas_network_connectivity_upgrade", 3)
|
||||
augmentation = k_edge_augmentation(G, k_edge, avail=complement_edges.values)
|
||||
new_gas_pipes = pd.DataFrame(augmentation, columns=["bus0", "bus1"])
|
||||
new_gas_pipes["length"] = new_gas_pipes.apply(haversine, axis=1)
|
||||
augmentation = list(k_edge_augmentation(G, k_edge, avail=complement_edges.values))
|
||||
|
||||
new_gas_pipes.index = new_gas_pipes.apply(
|
||||
lambda x: f"gas pipeline new {x.bus0} <-> {x.bus1}", axis=1)
|
||||
if augmentation:
|
||||
|
||||
n.madd("Link",
|
||||
new_gas_pipes.index,
|
||||
bus0=new_gas_pipes.bus0 + " gas",
|
||||
bus1=new_gas_pipes.bus1 + " gas",
|
||||
p_min_pu=-1, # new gas pipes are bidirectional
|
||||
p_nom_extendable=True,
|
||||
length=new_gas_pipes.length,
|
||||
capital_cost=new_gas_pipes.length * costs.at['CH4 (g) pipeline', 'fixed'],
|
||||
carrier="gas pipeline new",
|
||||
lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
|
||||
)
|
||||
new_gas_pipes = pd.DataFrame(augmentation, columns=["bus0", "bus1"])
|
||||
new_gas_pipes["length"] = new_gas_pipes.apply(haversine, axis=1)
|
||||
|
||||
new_gas_pipes.index = new_gas_pipes.apply(
|
||||
lambda x: f"gas pipeline new {x.bus0} <-> {x.bus1}", axis=1)
|
||||
|
||||
n.madd("Link",
|
||||
new_gas_pipes.index,
|
||||
bus0=new_gas_pipes.bus0 + " gas",
|
||||
bus1=new_gas_pipes.bus1 + " gas",
|
||||
p_min_pu=-1, # new gas pipes are bidirectional
|
||||
p_nom_extendable=True,
|
||||
length=new_gas_pipes.length,
|
||||
capital_cost=new_gas_pipes.length * costs.at['CH4 (g) pipeline', 'fixed'],
|
||||
carrier="gas pipeline new",
|
||||
lifetime=costs.at['CH4 (g) pipeline', 'lifetime']
|
||||
)
|
||||
|
||||
if options["H2_retrofit"]:
|
||||
|
||||
@ -1225,10 +1251,10 @@ def add_land_transport(n, costs):
|
||||
|
||||
if ice_share > 0:
|
||||
|
||||
if "EU oil" not in n.buses.index:
|
||||
n.add("Bus",
|
||||
"EU oil",
|
||||
location="EU",
|
||||
if "oil" not in n.buses.carrier.unique():
|
||||
n.madd("Bus",
|
||||
spatial.oil.nodes,
|
||||
location=spatial.oil.locations,
|
||||
carrier="oil"
|
||||
)
|
||||
|
||||
@ -1237,7 +1263,7 @@ def add_land_transport(n, costs):
|
||||
n.madd("Load",
|
||||
nodes,
|
||||
suffix=" land transport oil",
|
||||
bus="EU oil",
|
||||
bus=spatial.oil.nodes,
|
||||
carrier="land transport oil",
|
||||
p_set=ice_share / ice_efficiency * transport[nodes]
|
||||
)
|
||||
@ -1743,8 +1769,7 @@ def add_biomass(n, costs):
|
||||
transport_costs = pd.read_csv(
|
||||
snakemake.input.biomass_transport_costs,
|
||||
index_col=0,
|
||||
squeeze=True
|
||||
)
|
||||
).squeeze()
|
||||
|
||||
# add biomass transport
|
||||
biomass_transport = create_network_topology(n, "biomass transport ", bidirectional=False)
|
||||
@ -1955,7 +1980,7 @@ def add_industry(n, costs):
|
||||
n.madd("Load",
|
||||
nodes,
|
||||
suffix=" shipping oil",
|
||||
bus="EU oil",
|
||||
bus=spatial.oil.nodes,
|
||||
carrier="shipping oil",
|
||||
p_set=p_set
|
||||
)
|
||||
@ -1969,30 +1994,29 @@ def add_industry(n, costs):
|
||||
p_set=-co2
|
||||
)
|
||||
|
||||
if "EU oil" not in n.buses.index:
|
||||
|
||||
n.add("Bus",
|
||||
"EU oil",
|
||||
location="EU",
|
||||
if "oil" not in n.buses.carrier.unique():
|
||||
n.madd("Bus",
|
||||
spatial.oil.nodes,
|
||||
location=spatial.oil.locations,
|
||||
carrier="oil"
|
||||
)
|
||||
|
||||
if "EU oil Store" not in n.stores.index:
|
||||
if "oil" not in n.stores.carrier.unique():
|
||||
|
||||
#could correct to e.g. 0.001 EUR/kWh * annuity and O&M
|
||||
n.add("Store",
|
||||
"EU oil Store",
|
||||
bus="EU oil",
|
||||
n.madd("Store",
|
||||
[oil_bus + " Store" for oil_bus in spatial.oil.nodes],
|
||||
bus=spatial.oil.nodes,
|
||||
e_nom_extendable=True,
|
||||
e_cyclic=True,
|
||||
carrier="oil",
|
||||
)
|
||||
|
||||
if "EU oil" not in n.generators.index:
|
||||
if "oil" not in n.generators.carrier.unique():
|
||||
|
||||
n.add("Generator",
|
||||
"EU oil",
|
||||
bus="EU oil",
|
||||
n.madd("Generator",
|
||||
spatial.oil.nodes,
|
||||
bus=spatial.oil.nodes,
|
||||
p_nom_extendable=True,
|
||||
carrier="oil",
|
||||
marginal_cost=costs.at["oil", 'fuel']
|
||||
@ -2007,7 +2031,7 @@ def add_industry(n, costs):
|
||||
n.madd("Link",
|
||||
nodes_heat[name] + f" {name} oil boiler",
|
||||
p_nom_extendable=True,
|
||||
bus0="EU oil",
|
||||
bus0=spatial.oil.nodes,
|
||||
bus1=nodes_heat[name] + f" {name} heat",
|
||||
bus2="co2 atmosphere",
|
||||
carrier=f"{name} oil boiler",
|
||||
@ -2020,7 +2044,7 @@ def add_industry(n, costs):
|
||||
n.madd("Link",
|
||||
nodes + " Fischer-Tropsch",
|
||||
bus0=nodes + " H2",
|
||||
bus1="EU oil",
|
||||
bus1=spatial.oil.nodes,
|
||||
bus2=spatial.co2.nodes,
|
||||
carrier="Fischer-Tropsch",
|
||||
efficiency=costs.at["Fischer-Tropsch", 'efficiency'],
|
||||
@ -2030,9 +2054,9 @@ def add_industry(n, costs):
|
||||
lifetime=costs.at['Fischer-Tropsch', 'lifetime']
|
||||
)
|
||||
|
||||
n.add("Load",
|
||||
"naphtha for industry",
|
||||
bus="EU oil",
|
||||
n.madd("Load",
|
||||
["naphtha for industry"],
|
||||
bus=spatial.oil.nodes,
|
||||
carrier="naphtha for industry",
|
||||
p_set=industrial_demand.loc[nodes, "naphtha"].sum() / 8760
|
||||
)
|
||||
@ -2040,9 +2064,9 @@ def add_industry(n, costs):
|
||||
all_aviation = ["total international aviation", "total domestic aviation"]
|
||||
p_set = pop_weighted_energy_totals.loc[nodes, all_aviation].sum(axis=1).sum() * 1e6 / 8760
|
||||
|
||||
n.add("Load",
|
||||
"kerosene for aviation",
|
||||
bus="EU oil",
|
||||
n.madd("Load",
|
||||
["kerosene for aviation"],
|
||||
bus=spatial.oil.nodes,
|
||||
carrier="kerosene for aviation",
|
||||
p_set=p_set
|
||||
)
|
||||
@ -2195,7 +2219,7 @@ def add_agriculture(n, costs):
|
||||
|
||||
n.add("Load",
|
||||
"agriculture machinery oil",
|
||||
bus="EU oil",
|
||||
bus=spatial.oil.nodes,
|
||||
carrier="agriculture machinery oil",
|
||||
p_set=ice_share * machinery_nodal_energy.sum() * 1e6 / 8760
|
||||
)
|
||||
@ -2301,7 +2325,7 @@ if __name__ == "__main__":
|
||||
|
||||
patch_electricity_network(n)
|
||||
|
||||
define_spatial(pop_layout.index)
|
||||
spatial = define_spatial(pop_layout.index, options)
|
||||
|
||||
if snakemake.config["foresight"] == 'myopic':
|
||||
|
||||
@ -2376,7 +2400,7 @@ if __name__ == "__main__":
|
||||
fn = snakemake.config['results_dir'] + snakemake.config['run'] + '/csvs/carbon_budget_distribution.csv'
|
||||
if not os.path.exists(fn):
|
||||
build_carbon_budget(o, fn)
|
||||
co2_cap = pd.read_csv(fn, index_col=0, squeeze=True)
|
||||
co2_cap = pd.read_csv(fn, index_col=0).squeeze()
|
||||
limit = co2_cap[investment_year]
|
||||
break
|
||||
for o in opts:
|
||||
|
||||
@ -33,14 +33,14 @@ def _add_land_use_constraint(n):
|
||||
existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"].groupby(n.generators.bus.map(n.buses.location)).sum()
|
||||
existing.index += " " + carrier + "-" + snakemake.wildcards.planning_horizons
|
||||
n.generators.loc[existing.index,"p_nom_max"] -= existing
|
||||
|
||||
|
||||
n.generators.p_nom_max.clip(lower=0, inplace=True)
|
||||
|
||||
|
||||
def _add_land_use_constraint_m(n):
|
||||
# if generators clustering is lower than network clustering, land_use accounting is at generators clusters
|
||||
|
||||
planning_horizons = snakemake.config["scenario"]["planning_horizons"]
|
||||
planning_horizons = snakemake.config["scenario"]["planning_horizons"]
|
||||
grouping_years = snakemake.config["existing_capacities"]["grouping_years"]
|
||||
current_horizon = snakemake.wildcards.planning_horizons
|
||||
|
||||
@ -48,9 +48,9 @@ def _add_land_use_constraint_m(n):
|
||||
|
||||
existing = n.generators.loc[n.generators.carrier==carrier,"p_nom"]
|
||||
ind = list(set([i.split(sep=" ")[0] + ' ' + i.split(sep=" ")[1] for i in existing.index]))
|
||||
|
||||
|
||||
previous_years = [
|
||||
str(y) for y in
|
||||
str(y) for y in
|
||||
planning_horizons + grouping_years
|
||||
if y < int(snakemake.wildcards.planning_horizons)
|
||||
]
|
||||
@ -59,13 +59,13 @@ def _add_land_use_constraint_m(n):
|
||||
ind2 = [i for i in ind if i + " " + carrier + "-" + p_year in existing.index]
|
||||
sel_current = [i + " " + carrier + "-" + current_horizon for i in ind2]
|
||||
sel_p_year = [i + " " + carrier + "-" + p_year for i in ind2]
|
||||
n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon)
|
||||
|
||||
n.generators.loc[sel_current, "p_nom_max"] -= existing.loc[sel_p_year].rename(lambda x: x[:-4] + current_horizon)
|
||||
|
||||
n.generators.p_nom_max.clip(lower=0, inplace=True)
|
||||
|
||||
|
||||
def prepare_network(n, solve_opts=None):
|
||||
|
||||
|
||||
if 'clip_p_max_pu' in solve_opts:
|
||||
for df in (n.generators_t.p_max_pu, n.generators_t.p_min_pu, n.storage_units_t.inflow):
|
||||
df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)
|
||||
@ -185,40 +185,43 @@ def add_chp_constraints(n):
|
||||
|
||||
define_constraints(n, lhs, "<=", 0, 'chplink', 'backpressure')
|
||||
|
||||
def basename(x):
|
||||
return x.split("-2")[0]
|
||||
|
||||
def add_pipe_retrofit_constraint(n):
|
||||
"""Add constraint for retrofitting existing CH4 pipelines to H2 pipelines."""
|
||||
|
||||
gas_pipes_i = n.links[n.links.carrier=="gas pipeline"].index
|
||||
h2_retrofitted_i = n.links[n.links.carrier=='H2 pipeline retrofitted'].index
|
||||
gas_pipes_i = n.links.query("carrier == 'gas pipeline' and p_nom_extendable").index
|
||||
h2_retrofitted_i = n.links.query("carrier == 'H2 pipeline retrofitted' and p_nom_extendable").index
|
||||
|
||||
if h2_retrofitted_i.empty or gas_pipes_i.empty: return
|
||||
|
||||
link_p_nom = get_var(n, "Link", "p_nom")
|
||||
|
||||
pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom']
|
||||
|
||||
CH4_per_H2 = 1 / n.config["sector"]["H2_retrofit_capacity_per_CH4"]
|
||||
|
||||
fr = "H2 pipeline retrofitted"
|
||||
to = "gas pipeline"
|
||||
|
||||
pipe_capacity = n.links.loc[gas_pipes_i, 'p_nom'].rename(basename)
|
||||
|
||||
lhs = linexpr(
|
||||
(CH4_per_H2, link_p_nom.loc[h2_retrofitted_i].rename(index=lambda x: x.replace(fr, to))),
|
||||
(1, link_p_nom.loc[gas_pipes_i])
|
||||
)
|
||||
|
||||
lhs.rename(basename, inplace=True)
|
||||
define_constraints(n, lhs, "=", pipe_capacity, 'Link', 'pipe_retrofit')
|
||||
|
||||
|
||||
def add_co2_sequestration_limit(n, sns):
|
||||
|
||||
|
||||
co2_stores = n.stores.loc[n.stores.carrier=='co2 stored'].index
|
||||
|
||||
if co2_stores.empty or ('Store', 'e') not in n.variables.index:
|
||||
return
|
||||
|
||||
|
||||
vars_final_co2_stored = get_var(n, 'Store', 'e').loc[sns[-1], co2_stores]
|
||||
|
||||
|
||||
lhs = linexpr((1, vars_final_co2_stored)).sum()
|
||||
|
||||
limit = n.config["sector"].get("co2_sequestration_potential", 200) * 1e6
|
||||
@ -226,7 +229,7 @@ def add_co2_sequestration_limit(n, sns):
|
||||
if not "seq" in o: continue
|
||||
limit = float(o[o.find("seq")+3:])
|
||||
break
|
||||
|
||||
|
||||
name = 'co2_sequestration_limit'
|
||||
sense = "<="
|
||||
|
||||
@ -258,7 +261,7 @@ def solve_network(n, config, opts='', **kwargs):
|
||||
|
||||
if cf_solving.get('skip_iterations', False):
|
||||
network_lopf(n, solver_name=solver_name, solver_options=solver_options,
|
||||
extra_functionality=extra_functionality,
|
||||
extra_functionality=extra_functionality,
|
||||
keep_shadowprices=keep_shadowprices, **kwargs)
|
||||
else:
|
||||
ilopf(n, solver_name=solver_name, solver_options=solver_options,
|
||||
@ -277,10 +280,11 @@ if __name__ == "__main__":
|
||||
snakemake = mock_snakemake(
|
||||
'solve_network',
|
||||
simpl='',
|
||||
clusters=48,
|
||||
opts="",
|
||||
clusters="37",
|
||||
lv=1.0,
|
||||
sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
|
||||
planning_horizons=2050,
|
||||
sector_opts='168H-T-H-B-I-A-solar+p3-dist1',
|
||||
planning_horizons="2030",
|
||||
)
|
||||
|
||||
logging.basicConfig(filename=snakemake.log.python,
|
||||
|
||||
607
test/config.myopic.yaml
Normal file
607
test/config.myopic.yaml
Normal file
@ -0,0 +1,607 @@
|
||||
version: 0.6.0
|
||||
|
||||
logging_level: INFO
|
||||
|
||||
retrieve_sector_databundle: true
|
||||
|
||||
results_dir: results/
|
||||
summary_dir: results
|
||||
costs_dir: ../technology-data/outputs/
|
||||
run: test-myopic # use this to keep track of runs with different settings
|
||||
foresight: myopic # options are overnight, myopic, perfect (perfect is not yet implemented)
|
||||
# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
|
||||
|
||||
scenario:
|
||||
simpl: # only relevant for PyPSA-Eur
|
||||
- ''
|
||||
lv: # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
|
||||
- 1.5
|
||||
clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
|
||||
- 5
|
||||
opts: # only relevant for PyPSA-Eur
|
||||
- ''
|
||||
sector_opts: # this is where the main scenario settings are
|
||||
- 191H-T-H-B-I-A-solar+p3-dist1
|
||||
# to really understand the options here, look in scripts/prepare_sector_network.py
|
||||
# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
|
||||
# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
|
||||
# xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
|
||||
# single letters are sectors: T for land transport, H for building heating,
|
||||
# B for biomass supply, I for industry, shipping and aviation,
|
||||
# A for agriculture, forestry and fishing
|
||||
# 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
|
||||
# planning_horizons), be:beta decay; ex:exponential decay
|
||||
# cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
|
||||
# decay with initial growth rate 0
|
||||
planning_horizons: # investment years for myopic and perfect; or costs year for overnight
|
||||
- 2030
|
||||
- 2040
|
||||
- 2050
|
||||
# for example, set to [2020, 2030, 2040, 2050] for myopic foresight
|
||||
|
||||
# CO2 budget as a fraction of 1990 emissions
|
||||
# this is over-ridden if CO2Lx is set in sector_opts
|
||||
# this is also over-ridden if cb is set in sector_opts
|
||||
co2_budget:
|
||||
2020: 0.7011648746
|
||||
2025: 0.5241935484
|
||||
2030: 0.2970430108
|
||||
2035: 0.1500896057
|
||||
2040: 0.0712365591
|
||||
2045: 0.0322580645
|
||||
2050: 0
|
||||
|
||||
# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
|
||||
snapshots:
|
||||
# arguments to pd.date_range
|
||||
start: "2013-03-01"
|
||||
end: "2013-04-01"
|
||||
closed: left # end is not inclusive
|
||||
|
||||
atlite:
|
||||
cutout: ../pypsa-eur/cutouts/be-03-2013-era5.nc
|
||||
|
||||
# this information is NOT used but needed as an argument for
|
||||
# pypsa-eur/scripts/add_electricity.py/load_costs in make_summary.py
|
||||
electricity:
|
||||
max_hours:
|
||||
battery: 6
|
||||
H2: 168
|
||||
|
||||
# regulate what components with which carriers are kept from PyPSA-Eur;
|
||||
# some technologies are removed because they are implemented differently
|
||||
# (e.g. battery or H2 storage) or have different year-dependent costs
|
||||
# in PyPSA-Eur-Sec
|
||||
pypsa_eur:
|
||||
Bus:
|
||||
- AC
|
||||
Link:
|
||||
- DC
|
||||
Generator:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
StorageUnit:
|
||||
- PHS
|
||||
- hydro
|
||||
Store: []
|
||||
|
||||
|
||||
energy:
|
||||
energy_totals_year: 2011
|
||||
base_emissions_year: 1990
|
||||
eurostat_report_year: 2016
|
||||
emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
|
||||
|
||||
biomass:
|
||||
year: 2030
|
||||
scenario: ENS_Med
|
||||
classes:
|
||||
solid biomass:
|
||||
- Agricultural waste
|
||||
- Fuelwood residues
|
||||
- Secondary Forestry residues - woodchips
|
||||
- Sawdust
|
||||
- Residues from landscape care
|
||||
- Municipal waste
|
||||
not included:
|
||||
- Sugar from sugar beet
|
||||
- Rape seed
|
||||
- "Sunflower, soya seed "
|
||||
- Bioethanol barley, wheat, grain maize, oats, other cereals and rye
|
||||
- Miscanthus, switchgrass, RCG
|
||||
- Willow
|
||||
- Poplar
|
||||
- FuelwoodRW
|
||||
- C&P_RW
|
||||
biogas:
|
||||
- Manure solid, liquid
|
||||
- Sludge
|
||||
|
||||
|
||||
solar_thermal:
|
||||
clearsky_model: simple # should be "simple" or "enhanced"?
|
||||
orientation:
|
||||
slope: 45.
|
||||
azimuth: 180.
|
||||
|
||||
# only relevant for foresight = myopic or perfect
|
||||
existing_capacities:
|
||||
grouping_years: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]
|
||||
threshold_capacity: 10
|
||||
conventional_carriers:
|
||||
- lignite
|
||||
- coal
|
||||
- oil
|
||||
- uranium
|
||||
|
||||
|
||||
sector:
|
||||
district_heating:
|
||||
potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating
|
||||
# increase of today's district heating demand to potential maximum district heating share
|
||||
# progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
|
||||
progress:
|
||||
2020: 0.0
|
||||
2030: 0.3
|
||||
2040: 0.6
|
||||
2050: 1.0
|
||||
district_heating_loss: 0.15
|
||||
bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM
|
||||
bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value
|
||||
transport_heating_deadband_upper: 20.
|
||||
transport_heating_deadband_lower: 15.
|
||||
ICE_lower_degree_factor: 0.375 #in per cent increase in fuel consumption per degree above deadband
|
||||
ICE_upper_degree_factor: 1.6
|
||||
EV_lower_degree_factor: 0.98
|
||||
EV_upper_degree_factor: 0.63
|
||||
bev_dsm: true #turns on EV battery
|
||||
bev_availability: 0.5 #How many cars do smart charging
|
||||
bev_energy: 0.05 #average battery size in MWh
|
||||
bev_charge_efficiency: 0.9 #BEV (dis-)charging efficiency
|
||||
bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
|
||||
bev_charge_rate: 0.011 #3-phase charger with 11 kW
|
||||
bev_avail_max: 0.95
|
||||
bev_avail_mean: 0.8
|
||||
v2g: true #allows feed-in to grid from EV battery
|
||||
#what is not EV or FCEV is oil-fuelled ICE
|
||||
land_transport_fuel_cell_share:
|
||||
2020: 0
|
||||
2030: 0.05
|
||||
2040: 0.1
|
||||
2050: 0.15
|
||||
land_transport_electric_share:
|
||||
2020: 0
|
||||
2030: 0.25
|
||||
2040: 0.6
|
||||
2050: 0.85
|
||||
transport_fuel_cell_efficiency: 0.5
|
||||
transport_internal_combustion_efficiency: 0.3
|
||||
agriculture_machinery_electric_share: 0
|
||||
agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use
|
||||
agriculture_machinery_electric_efficiency: 0.3 # electricity per use
|
||||
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
|
||||
shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
|
||||
shipping_hydrogen_share:
|
||||
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
|
||||
reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH)
|
||||
# this can represent e.g. building renovation, building demolition, or if
|
||||
# the factor is negative: increasing floor area, increased thermal comfort, population growth
|
||||
reduce_space_heat_exogenously_factor: # 0.29 # per unit reduction in space heat demand
|
||||
# the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
|
||||
2020: 0.10 # this results in a space heat demand reduction of 10%
|
||||
2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita
|
||||
2030: 0.09
|
||||
2035: 0.11
|
||||
2040: 0.16
|
||||
2045: 0.21
|
||||
2050: 0.29
|
||||
retrofitting : # co-optimises building renovation to reduce space heat demand
|
||||
retro_endogen: false # co-optimise space heat savings
|
||||
cost_factor: 1.0 # weight costs for building renovation
|
||||
interest_rate: 0.04 # for investment in building components
|
||||
annualise_cost: true # annualise the investment costs
|
||||
tax_weighting: false # weight costs depending on taxes in countries
|
||||
construction_index: true # weight costs depending on labour/material costs per country
|
||||
tes: true
|
||||
tes_tau: # 180 day time constant for centralised, 3 day for decentralised
|
||||
decentral: 3
|
||||
central: 180
|
||||
boilers: true
|
||||
oil_boilers: false
|
||||
chp: true
|
||||
micro_chp: false
|
||||
solar_thermal: true
|
||||
solar_cf_correction: 0.788457 # = >>> 1/1.2683
|
||||
marginal_cost_storage: 0. #1e-4
|
||||
methanation: true
|
||||
helmeth: true
|
||||
dac: true
|
||||
co2_vent: true
|
||||
SMR: true
|
||||
co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe
|
||||
co2_sequestration_cost: 10 #EUR/tCO2 for sequestration of CO2
|
||||
co2_network: false
|
||||
cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture
|
||||
hydrogen_underground_storage: true
|
||||
hydrogen_underground_storage_locations:
|
||||
# - onshore # more than 50 km from sea
|
||||
- nearshore # within 50 km of sea
|
||||
# - offshore
|
||||
use_fischer_tropsch_waste_heat: true
|
||||
use_fuel_cell_waste_heat: true
|
||||
electricity_distribution_grid: true
|
||||
electricity_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
electricity_grid_connection: true # only applies to onshore wind and utility PV
|
||||
H2_network: true
|
||||
gas_network: false
|
||||
H2_retrofit: false # if set to True existing gas pipes can be retrofitted to H2 pipes
|
||||
# according to hydrogen backbone strategy (April, 2020) p.15
|
||||
# https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
|
||||
# 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
|
||||
H2_retrofit_capacity_per_CH4: 0.6 # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
|
||||
gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
|
||||
gas_distribution_grid: true
|
||||
gas_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
biomass_transport: false # biomass transport between nodes
|
||||
conventional_generation: # generator : carrier
|
||||
OCGT: gas
|
||||
|
||||
|
||||
industry:
|
||||
St_primary_fraction: # 0.3 # 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: # 1 # 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
|
||||
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)
|
||||
MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
|
||||
NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
|
||||
petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
|
||||
HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
|
||||
HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
|
||||
HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
|
||||
HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
|
||||
MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
|
||||
MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
|
||||
chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
|
||||
MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
|
||||
MWh_H2_per_tCl: -0.9372 # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
|
||||
methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
|
||||
MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
|
||||
MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
|
||||
hotmaps_locate_missing: false
|
||||
reference_year: 2015
|
||||
# references:
|
||||
# DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
|
||||
# Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
|
||||
|
||||
costs:
|
||||
lifetime: 25 #default lifetime
|
||||
# From a Lion Hirth paper, also reflects average of Noothout et al 2016
|
||||
discountrate: 0.07
|
||||
# [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html # noqa: E501
|
||||
USD2013_to_EUR2013: 0.7532
|
||||
|
||||
# Marginal and capital costs can be overwritten
|
||||
# capital_cost:
|
||||
# onwind: 500
|
||||
marginal_cost:
|
||||
solar: 0.01
|
||||
onwind: 0.015
|
||||
offwind: 0.015
|
||||
hydro: 0.
|
||||
H2: 0.
|
||||
battery: 0.
|
||||
|
||||
emission_prices: # only used with the option Ep (emission prices)
|
||||
co2: 0.
|
||||
|
||||
lines:
|
||||
length_factor: 1.25 #to estimate offwind connection costs
|
||||
|
||||
|
||||
solving:
|
||||
#tmpdir: "path/to/tmp"
|
||||
options:
|
||||
formulation: kirchhoff
|
||||
clip_p_max_pu: 1.e-2
|
||||
load_shedding: false
|
||||
noisy_costs: true
|
||||
skip_iterations: true
|
||||
track_iterations: false
|
||||
min_iterations: 4
|
||||
max_iterations: 6
|
||||
keep_shadowprices:
|
||||
- Bus
|
||||
- Line
|
||||
- Link
|
||||
- Transformer
|
||||
- GlobalConstraint
|
||||
- Generator
|
||||
- Store
|
||||
- StorageUnit
|
||||
|
||||
solver:
|
||||
name: cbc
|
||||
# threads: 4
|
||||
# method: 2 # barrier
|
||||
# crossover: 0
|
||||
# BarConvTol: 1.e-6
|
||||
# Seed: 123
|
||||
# AggFill: 0
|
||||
# PreDual: 0
|
||||
# GURO_PAR_BARDENSETHRESH: 200
|
||||
#FeasibilityTol: 1.e-6
|
||||
|
||||
#name: cplex
|
||||
#threads: 4
|
||||
#lpmethod: 4 # barrier
|
||||
#solutiontype: 2 # non basic solution, ie no crossover
|
||||
#barrier_convergetol: 1.e-5
|
||||
#feasopt_tolerance: 1.e-6
|
||||
mem: 4000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
|
||||
|
||||
|
||||
plotting:
|
||||
map:
|
||||
boundaries: [-11, 30, 34, 71]
|
||||
color_geomap:
|
||||
ocean: white
|
||||
land: whitesmoke
|
||||
costs_max: 1000
|
||||
costs_threshold: 1
|
||||
energy_max: 20000
|
||||
energy_min: -20000
|
||||
energy_threshold: 50
|
||||
vre_techs:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
renewable_storage_techs:
|
||||
- PHS
|
||||
- hydro
|
||||
conv_techs:
|
||||
- OCGT
|
||||
- CCGT
|
||||
- Nuclear
|
||||
- Coal
|
||||
storage_techs:
|
||||
- hydro+PHS
|
||||
- battery
|
||||
- H2
|
||||
load_carriers:
|
||||
- AC load
|
||||
AC_carriers:
|
||||
- AC line
|
||||
- AC transformer
|
||||
link_carriers:
|
||||
- DC line
|
||||
- Converter AC-DC
|
||||
heat_links:
|
||||
- heat pump
|
||||
- resistive heater
|
||||
- CHP heat
|
||||
- CHP electric
|
||||
- gas boiler
|
||||
- central heat pump
|
||||
- central resistive heater
|
||||
- central CHP heat
|
||||
- central CHP electric
|
||||
- central gas boiler
|
||||
heat_generators:
|
||||
- gas boiler
|
||||
- central gas boiler
|
||||
- solar thermal collector
|
||||
- central solar thermal collector
|
||||
tech_colors:
|
||||
# wind
|
||||
onwind: "#235ebc"
|
||||
onshore wind: "#235ebc"
|
||||
offwind: "#6895dd"
|
||||
offshore wind: "#6895dd"
|
||||
offwind-ac: "#6895dd"
|
||||
offshore wind (AC): "#6895dd"
|
||||
offwind-dc: "#74c6f2"
|
||||
offshore wind (DC): "#74c6f2"
|
||||
# water
|
||||
hydro: '#298c81'
|
||||
hydro reservoir: '#298c81'
|
||||
ror: '#3dbfb0'
|
||||
run of river: '#3dbfb0'
|
||||
hydroelectricity: '#298c81'
|
||||
PHS: '#51dbcc'
|
||||
wave: '#a7d4cf'
|
||||
# solar
|
||||
solar: "#f9d002"
|
||||
solar PV: "#f9d002"
|
||||
solar thermal: '#ffbf2b'
|
||||
solar rooftop: '#ffea80'
|
||||
# gas
|
||||
OCGT: '#e0986c'
|
||||
OCGT marginal: '#e0986c'
|
||||
OCGT-heat: '#e0986c'
|
||||
gas boiler: '#db6a25'
|
||||
gas boilers: '#db6a25'
|
||||
gas boiler marginal: '#db6a25'
|
||||
gas: '#e05b09'
|
||||
fossil gas: '#e05b09'
|
||||
natural gas: '#e05b09'
|
||||
CCGT: '#a85522'
|
||||
CCGT marginal: '#a85522'
|
||||
gas for industry co2 to atmosphere: '#692e0a'
|
||||
gas for industry co2 to stored: '#8a3400'
|
||||
gas for industry: '#853403'
|
||||
gas for industry CC: '#692e0a'
|
||||
gas pipeline: '#ebbca0'
|
||||
gas pipeline new: '#a87c62'
|
||||
# oil
|
||||
oil: '#c9c9c9'
|
||||
oil boiler: '#adadad'
|
||||
agriculture machinery oil: '#949494'
|
||||
shipping oil: "#808080"
|
||||
land transport oil: '#afafaf'
|
||||
# nuclear
|
||||
Nuclear: '#ff8c00'
|
||||
Nuclear marginal: '#ff8c00'
|
||||
nuclear: '#ff8c00'
|
||||
uranium: '#ff8c00'
|
||||
# coal
|
||||
Coal: '#545454'
|
||||
coal: '#545454'
|
||||
Coal marginal: '#545454'
|
||||
solid: '#545454'
|
||||
Lignite: '#826837'
|
||||
lignite: '#826837'
|
||||
Lignite marginal: '#826837'
|
||||
# biomass
|
||||
biogas: '#e3d37d'
|
||||
biomass: '#baa741'
|
||||
solid biomass: '#baa741'
|
||||
solid biomass transport: '#baa741'
|
||||
solid biomass for industry: '#7a6d26'
|
||||
solid biomass for industry CC: '#47411c'
|
||||
solid biomass for industry co2 from atmosphere: '#736412'
|
||||
solid biomass for industry co2 to stored: '#47411c'
|
||||
# power transmission
|
||||
lines: '#6c9459'
|
||||
transmission lines: '#6c9459'
|
||||
electricity distribution grid: '#97ad8c'
|
||||
# electricity demand
|
||||
Electric load: '#110d63'
|
||||
electric demand: '#110d63'
|
||||
electricity: '#110d63'
|
||||
industry electricity: '#2d2a66'
|
||||
industry new electricity: '#2d2a66'
|
||||
agriculture electricity: '#494778'
|
||||
# battery + EVs
|
||||
battery: '#ace37f'
|
||||
battery storage: '#ace37f'
|
||||
home battery: '#80c944'
|
||||
home battery storage: '#80c944'
|
||||
BEV charger: '#baf238'
|
||||
V2G: '#e5ffa8'
|
||||
land transport EV: '#baf238'
|
||||
Li ion: '#baf238'
|
||||
# hot water storage
|
||||
water tanks: '#e69487'
|
||||
hot water storage: '#e69487'
|
||||
hot water charging: '#e69487'
|
||||
hot water discharging: '#e69487'
|
||||
# heat demand
|
||||
Heat load: '#cc1f1f'
|
||||
heat: '#cc1f1f'
|
||||
heat demand: '#cc1f1f'
|
||||
rural heat: '#ff5c5c'
|
||||
central heat: '#cc1f1f'
|
||||
decentral heat: '#750606'
|
||||
low-temperature heat for industry: '#8f2727'
|
||||
process heat: '#ff0000'
|
||||
agriculture heat: '#d9a5a5'
|
||||
# heat supply
|
||||
heat pumps: '#2fb537'
|
||||
heat pump: '#2fb537'
|
||||
air heat pump: '#36eb41'
|
||||
ground heat pump: '#2fb537'
|
||||
Ambient: '#98eb9d'
|
||||
CHP: '#8a5751'
|
||||
CHP CC: '#634643'
|
||||
CHP heat: '#8a5751'
|
||||
CHP electric: '#8a5751'
|
||||
district heating: '#e8beac'
|
||||
resistive heater: '#d8f9b8'
|
||||
retrofitting: '#8487e8'
|
||||
building retrofitting: '#8487e8'
|
||||
# hydrogen
|
||||
H2 for industry: "#f073da"
|
||||
H2 for shipping: "#ebaee0"
|
||||
H2: '#bf13a0'
|
||||
hydrogen: '#bf13a0'
|
||||
SMR: '#870c71'
|
||||
SMR CC: '#4f1745'
|
||||
H2 liquefaction: '#d647bd'
|
||||
hydrogen storage: '#bf13a0'
|
||||
H2 storage: '#bf13a0'
|
||||
land transport fuel cell: '#6b3161'
|
||||
H2 pipeline: '#f081dc'
|
||||
H2 pipeline retrofitted: '#ba99b5'
|
||||
H2 Fuel Cell: '#c251ae'
|
||||
H2 Electrolysis: '#ff29d9'
|
||||
# syngas
|
||||
Sabatier: '#9850ad'
|
||||
methanation: '#c44ce6'
|
||||
methane: '#c44ce6'
|
||||
helmeth: '#e899ff'
|
||||
# synfuels
|
||||
Fischer-Tropsch: '#25c49a'
|
||||
liquid: '#25c49a'
|
||||
kerosene for aviation: '#a1ffe6'
|
||||
naphtha for industry: '#57ebc4'
|
||||
# co2
|
||||
CC: '#f29dae'
|
||||
CCS: '#f29dae'
|
||||
CO2 sequestration: '#f29dae'
|
||||
DAC: '#ff5270'
|
||||
co2 stored: '#f2385a'
|
||||
co2: '#f29dae'
|
||||
co2 vent: '#ffd4dc'
|
||||
CO2 pipeline: '#f5627f'
|
||||
# emissions
|
||||
process emissions CC: '#000000'
|
||||
process emissions: '#222222'
|
||||
process emissions to stored: '#444444'
|
||||
process emissions to atmosphere: '#888888'
|
||||
oil emissions: '#aaaaaa'
|
||||
shipping oil emissions: "#555555"
|
||||
land transport oil emissions: '#777777'
|
||||
agriculture machinery oil emissions: '#333333'
|
||||
# other
|
||||
shipping: '#03a2ff'
|
||||
power-to-heat: '#2fb537'
|
||||
power-to-gas: '#c44ce6'
|
||||
power-to-H2: '#ff29d9'
|
||||
power-to-liquid: '#25c49a'
|
||||
gas-to-power/heat: '#ee8340'
|
||||
waste: '#e3d37d'
|
||||
other: '#000000'
|
||||
605
test/config.overnight.yaml
Normal file
605
test/config.overnight.yaml
Normal file
@ -0,0 +1,605 @@
|
||||
version: 0.6.0
|
||||
|
||||
logging_level: INFO
|
||||
|
||||
retrieve_sector_databundle: true
|
||||
|
||||
results_dir: results/
|
||||
summary_dir: results
|
||||
costs_dir: ../technology-data/outputs/
|
||||
run: test-overnight # use this to keep track of runs with different settings
|
||||
foresight: overnight # options are overnight, myopic, perfect (perfect is not yet implemented)
|
||||
# if you use myopic or perfect foresight, set the investment years in "planning_horizons" below
|
||||
|
||||
scenario:
|
||||
simpl: # only relevant for PyPSA-Eur
|
||||
- ''
|
||||
lv: # allowed transmission line volume expansion, can be any float >= 1.0 (today) or "opt"
|
||||
- 1.5
|
||||
clusters: # number of nodes in Europe, any integer between 37 (1 node per country-zone) and several hundred
|
||||
- 5
|
||||
opts: # only relevant for PyPSA-Eur
|
||||
- ''
|
||||
sector_opts: # this is where the main scenario settings are
|
||||
- CO2L0-191H-T-H-B-I-A-solar+p3-dist1
|
||||
# to really understand the options here, look in scripts/prepare_sector_network.py
|
||||
# Co2Lx specifies the CO2 target in x% of the 1990 values; default will give default (5%);
|
||||
# Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
|
||||
# xH is the temporal resolution; 3H is 3-hourly, i.e. one snapshot every 3 hours
|
||||
# single letters are sectors: T for land transport, H for building heating,
|
||||
# B for biomass supply, I for industry, shipping and aviation,
|
||||
# A for agriculture, forestry and fishing
|
||||
# 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
|
||||
# planning_horizons), be:beta decay; ex:exponential decay
|
||||
# cb40ex0 distributes a carbon budget of 40 GtCO2 following an exponential
|
||||
# decay with initial growth rate 0
|
||||
planning_horizons: # investment years for myopic and perfect; or costs year for overnight
|
||||
- 2030
|
||||
# for example, set to [2020, 2030, 2040, 2050] for myopic foresight
|
||||
|
||||
# CO2 budget as a fraction of 1990 emissions
|
||||
# this is over-ridden if CO2Lx is set in sector_opts
|
||||
# this is also over-ridden if cb is set in sector_opts
|
||||
co2_budget:
|
||||
2020: 0.7011648746
|
||||
2025: 0.5241935484
|
||||
2030: 0.2970430108
|
||||
2035: 0.1500896057
|
||||
2040: 0.0712365591
|
||||
2045: 0.0322580645
|
||||
2050: 0
|
||||
|
||||
# snapshots are originally set in PyPSA-Eur/config.yaml but used again by PyPSA-Eur-Sec
|
||||
snapshots:
|
||||
# arguments to pd.date_range
|
||||
start: "2013-03-01"
|
||||
end: "2013-04-01"
|
||||
closed: left # end is not inclusive
|
||||
|
||||
atlite:
|
||||
cutout: ../pypsa-eur/cutouts/be-03-2013-era5.nc
|
||||
|
||||
# this information is NOT used but needed as an argument for
|
||||
# pypsa-eur/scripts/add_electricity.py/load_costs in make_summary.py
|
||||
electricity:
|
||||
max_hours:
|
||||
battery: 6
|
||||
H2: 168
|
||||
|
||||
# regulate what components with which carriers are kept from PyPSA-Eur;
|
||||
# some technologies are removed because they are implemented differently
|
||||
# (e.g. battery or H2 storage) or have different year-dependent costs
|
||||
# in PyPSA-Eur-Sec
|
||||
pypsa_eur:
|
||||
Bus:
|
||||
- AC
|
||||
Link:
|
||||
- DC
|
||||
Generator:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
StorageUnit:
|
||||
- PHS
|
||||
- hydro
|
||||
Store: []
|
||||
|
||||
|
||||
energy:
|
||||
energy_totals_year: 2011
|
||||
base_emissions_year: 1990
|
||||
eurostat_report_year: 2016
|
||||
emissions: CO2 # "CO2" or "All greenhouse gases - (CO2 equivalent)"
|
||||
|
||||
biomass:
|
||||
year: 2030
|
||||
scenario: ENS_Med
|
||||
classes:
|
||||
solid biomass:
|
||||
- Agricultural waste
|
||||
- Fuelwood residues
|
||||
- Secondary Forestry residues - woodchips
|
||||
- Sawdust
|
||||
- Residues from landscape care
|
||||
- Municipal waste
|
||||
not included:
|
||||
- Sugar from sugar beet
|
||||
- Rape seed
|
||||
- "Sunflower, soya seed "
|
||||
- Bioethanol barley, wheat, grain maize, oats, other cereals and rye
|
||||
- Miscanthus, switchgrass, RCG
|
||||
- Willow
|
||||
- Poplar
|
||||
- FuelwoodRW
|
||||
- C&P_RW
|
||||
biogas:
|
||||
- Manure solid, liquid
|
||||
- Sludge
|
||||
|
||||
|
||||
solar_thermal:
|
||||
clearsky_model: simple # should be "simple" or "enhanced"?
|
||||
orientation:
|
||||
slope: 45.
|
||||
azimuth: 180.
|
||||
|
||||
# only relevant for foresight = myopic or perfect
|
||||
existing_capacities:
|
||||
grouping_years: [1980, 1985, 1990, 1995, 2000, 2005, 2010, 2015, 2019]
|
||||
threshold_capacity: 10
|
||||
conventional_carriers:
|
||||
- lignite
|
||||
- coal
|
||||
- oil
|
||||
- uranium
|
||||
|
||||
|
||||
sector:
|
||||
district_heating:
|
||||
potential: 0.6 # maximum fraction of urban demand which can be supplied by district heating
|
||||
# increase of today's district heating demand to potential maximum district heating share
|
||||
# progress = 0 means today's district heating share, progress = 1 means maximum fraction of urban demand is supplied by district heating
|
||||
progress: 1
|
||||
# 2020: 0.0
|
||||
# 2030: 0.3
|
||||
# 2040: 0.6
|
||||
# 2050: 1.0
|
||||
district_heating_loss: 0.15
|
||||
bev_dsm_restriction_value: 0.75 #Set to 0 for no restriction on BEV DSM
|
||||
bev_dsm_restriction_time: 7 #Time at which SOC of BEV has to be dsm_restriction_value
|
||||
transport_heating_deadband_upper: 20.
|
||||
transport_heating_deadband_lower: 15.
|
||||
ICE_lower_degree_factor: 0.375 #in per cent increase in fuel consumption per degree above deadband
|
||||
ICE_upper_degree_factor: 1.6
|
||||
EV_lower_degree_factor: 0.98
|
||||
EV_upper_degree_factor: 0.63
|
||||
bev_dsm: true #turns on EV battery
|
||||
bev_availability: 0.5 #How many cars do smart charging
|
||||
bev_energy: 0.05 #average battery size in MWh
|
||||
bev_charge_efficiency: 0.9 #BEV (dis-)charging efficiency
|
||||
bev_plug_to_wheel_efficiency: 0.2 #kWh/km from EPA https://www.fueleconomy.gov/feg/ for Tesla Model S
|
||||
bev_charge_rate: 0.011 #3-phase charger with 11 kW
|
||||
bev_avail_max: 0.95
|
||||
bev_avail_mean: 0.8
|
||||
v2g: true #allows feed-in to grid from EV battery
|
||||
#what is not EV or FCEV is oil-fuelled ICE
|
||||
land_transport_fuel_cell_share: 0.15 # 1 means all FCEVs
|
||||
# 2020: 0
|
||||
# 2030: 0.05
|
||||
# 2040: 0.1
|
||||
# 2050: 0.15
|
||||
land_transport_electric_share: 0.85 # 1 means all EVs
|
||||
# 2020: 0
|
||||
# 2030: 0.25
|
||||
# 2040: 0.6
|
||||
# 2050: 0.85
|
||||
transport_fuel_cell_efficiency: 0.5
|
||||
transport_internal_combustion_efficiency: 0.3
|
||||
agriculture_machinery_electric_share: 0
|
||||
agriculture_machinery_fuel_efficiency: 0.7 # fuel oil per use
|
||||
agriculture_machinery_electric_efficiency: 0.3 # electricity per use
|
||||
shipping_average_efficiency: 0.4 #For conversion of fuel oil to propulsion in 2011
|
||||
shipping_hydrogen_liquefaction: false # whether to consider liquefaction costs for shipping H2 demands
|
||||
shipping_hydrogen_share: 1 # 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
|
||||
reduce_space_heat_exogenously: true # reduces space heat demand by a given factor (applied before losses in DH)
|
||||
# this can represent e.g. building renovation, building demolition, or if
|
||||
# the factor is negative: increasing floor area, increased thermal comfort, population growth
|
||||
reduce_space_heat_exogenously_factor: 0.29 # per unit reduction in space heat demand
|
||||
# the default factors are determined by the LTS scenario from http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221
|
||||
# 2020: 0.10 # this results in a space heat demand reduction of 10%
|
||||
# 2025: 0.09 # first heat demand increases compared to 2020 because of larger floor area per capita
|
||||
# 2030: 0.09
|
||||
# 2035: 0.11
|
||||
# 2040: 0.16
|
||||
# 2045: 0.21
|
||||
# 2050: 0.29
|
||||
retrofitting : # co-optimises building renovation to reduce space heat demand
|
||||
retro_endogen: false # co-optimise space heat savings
|
||||
cost_factor: 1.0 # weight costs for building renovation
|
||||
interest_rate: 0.04 # for investment in building components
|
||||
annualise_cost: true # annualise the investment costs
|
||||
tax_weighting: false # weight costs depending on taxes in countries
|
||||
construction_index: true # weight costs depending on labour/material costs per country
|
||||
tes: true
|
||||
tes_tau: # 180 day time constant for centralised, 3 day for decentralised
|
||||
decentral: 3
|
||||
central: 180
|
||||
boilers: true
|
||||
oil_boilers: false
|
||||
chp: true
|
||||
micro_chp: false
|
||||
solar_thermal: true
|
||||
solar_cf_correction: 0.788457 # = >>> 1/1.2683
|
||||
marginal_cost_storage: 0. #1e-4
|
||||
methanation: true
|
||||
helmeth: true
|
||||
dac: true
|
||||
co2_vent: true
|
||||
SMR: true
|
||||
co2_sequestration_potential: 200 #MtCO2/a sequestration potential for Europe
|
||||
co2_sequestration_cost: 10 #EUR/tCO2 for sequestration of CO2
|
||||
co2_network: false
|
||||
cc_fraction: 0.9 # default fraction of CO2 captured with post-combustion capture
|
||||
hydrogen_underground_storage: true
|
||||
hydrogen_underground_storage_locations:
|
||||
# - onshore # more than 50 km from sea
|
||||
- nearshore # within 50 km of sea
|
||||
# - offshore
|
||||
use_fischer_tropsch_waste_heat: true
|
||||
use_fuel_cell_waste_heat: true
|
||||
electricity_distribution_grid: true
|
||||
electricity_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
electricity_grid_connection: true # only applies to onshore wind and utility PV
|
||||
H2_network: true
|
||||
gas_network: true
|
||||
H2_retrofit: true # if set to True existing gas pipes can be retrofitted to H2 pipes
|
||||
# according to hydrogen backbone strategy (April, 2020) p.15
|
||||
# https://gasforclimate2050.eu/wp-content/uploads/2020/07/2020_European-Hydrogen-Backbone_Report.pdf
|
||||
# 60% of original natural gas capacity could be used in cost-optimal case as H2 capacity
|
||||
H2_retrofit_capacity_per_CH4: 0.6 # ratio for H2 capacity per original CH4 capacity of retrofitted pipelines
|
||||
gas_network_connectivity_upgrade: 1 # https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation
|
||||
gas_distribution_grid: true
|
||||
gas_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv
|
||||
biomass_transport: false # biomass transport between nodes
|
||||
conventional_generation: # generator : carrier
|
||||
OCGT: gas
|
||||
|
||||
|
||||
industry:
|
||||
St_primary_fraction: 0.3 # 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: 1 # 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
|
||||
# 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)
|
||||
MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
|
||||
NH3_process_emissions: 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
|
||||
petrochemical_process_emissions: 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
|
||||
HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
|
||||
HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
|
||||
HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
|
||||
HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
|
||||
MWh_elec_per_tHVC_mechanical_recycling: 0.547 # from SI of https://doi.org/10.1016/j.resconrec.2020.105010, Table S5, for HDPE, PP, PS, PET. LDPE would be 0.756.
|
||||
MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and electric steam cracking
|
||||
chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
|
||||
MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
|
||||
MWh_H2_per_tCl: -0.9372 # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
|
||||
methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
|
||||
MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
|
||||
MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
|
||||
hotmaps_locate_missing: false
|
||||
reference_year: 2015
|
||||
# references:
|
||||
# DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
|
||||
# Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
|
||||
|
||||
costs:
|
||||
lifetime: 25 #default lifetime
|
||||
# From a Lion Hirth paper, also reflects average of Noothout et al 2016
|
||||
discountrate: 0.07
|
||||
# [EUR/USD] ECB: https://www.ecb.europa.eu/stats/exchange/eurofxref/html/eurofxref-graph-usd.en.html # noqa: E501
|
||||
USD2013_to_EUR2013: 0.7532
|
||||
|
||||
# Marginal and capital costs can be overwritten
|
||||
# capital_cost:
|
||||
# onwind: 500
|
||||
marginal_cost:
|
||||
solar: 0.01
|
||||
onwind: 0.015
|
||||
offwind: 0.015
|
||||
hydro: 0.
|
||||
H2: 0.
|
||||
battery: 0.
|
||||
|
||||
emission_prices: # only used with the option Ep (emission prices)
|
||||
co2: 0.
|
||||
|
||||
lines:
|
||||
length_factor: 1.25 #to estimate offwind connection costs
|
||||
|
||||
|
||||
solving:
|
||||
#tmpdir: "path/to/tmp"
|
||||
options:
|
||||
formulation: kirchhoff
|
||||
clip_p_max_pu: 1.e-2
|
||||
load_shedding: false
|
||||
noisy_costs: true
|
||||
skip_iterations: true
|
||||
track_iterations: false
|
||||
min_iterations: 4
|
||||
max_iterations: 6
|
||||
keep_shadowprices:
|
||||
- Bus
|
||||
- Line
|
||||
- Link
|
||||
- Transformer
|
||||
- GlobalConstraint
|
||||
- Generator
|
||||
- Store
|
||||
- StorageUnit
|
||||
|
||||
solver:
|
||||
name: cbc
|
||||
# threads: 4
|
||||
# method: 2 # barrier
|
||||
# crossover: 0
|
||||
# BarConvTol: 1.e-6
|
||||
# Seed: 123
|
||||
# AggFill: 0
|
||||
# PreDual: 0
|
||||
# GURO_PAR_BARDENSETHRESH: 200
|
||||
#FeasibilityTol: 1.e-6
|
||||
|
||||
#name: cplex
|
||||
#threads: 4
|
||||
#lpmethod: 4 # barrier
|
||||
#solutiontype: 2 # non basic solution, ie no crossover
|
||||
#barrier_convergetol: 1.e-5
|
||||
#feasopt_tolerance: 1.e-6
|
||||
mem: 4000 #memory in MB; 20 GB enough for 50+B+I+H2; 100 GB for 181+B+I+H2
|
||||
|
||||
|
||||
plotting:
|
||||
map:
|
||||
boundaries: [-11, 30, 34, 71]
|
||||
color_geomap:
|
||||
ocean: white
|
||||
land: whitesmoke
|
||||
costs_max: 1000
|
||||
costs_threshold: 1
|
||||
energy_max: 20000
|
||||
energy_min: -20000
|
||||
energy_threshold: 50
|
||||
vre_techs:
|
||||
- onwind
|
||||
- offwind-ac
|
||||
- offwind-dc
|
||||
- solar
|
||||
- ror
|
||||
renewable_storage_techs:
|
||||
- PHS
|
||||
- hydro
|
||||
conv_techs:
|
||||
- OCGT
|
||||
- CCGT
|
||||
- Nuclear
|
||||
- Coal
|
||||
storage_techs:
|
||||
- hydro+PHS
|
||||
- battery
|
||||
- H2
|
||||
load_carriers:
|
||||
- AC load
|
||||
AC_carriers:
|
||||
- AC line
|
||||
- AC transformer
|
||||
link_carriers:
|
||||
- DC line
|
||||
- Converter AC-DC
|
||||
heat_links:
|
||||
- heat pump
|
||||
- resistive heater
|
||||
- CHP heat
|
||||
- CHP electric
|
||||
- gas boiler
|
||||
- central heat pump
|
||||
- central resistive heater
|
||||
- central CHP heat
|
||||
- central CHP electric
|
||||
- central gas boiler
|
||||
heat_generators:
|
||||
- gas boiler
|
||||
- central gas boiler
|
||||
- solar thermal collector
|
||||
- central solar thermal collector
|
||||
tech_colors:
|
||||
# wind
|
||||
onwind: "#235ebc"
|
||||
onshore wind: "#235ebc"
|
||||
offwind: "#6895dd"
|
||||
offshore wind: "#6895dd"
|
||||
offwind-ac: "#6895dd"
|
||||
offshore wind (AC): "#6895dd"
|
||||
offwind-dc: "#74c6f2"
|
||||
offshore wind (DC): "#74c6f2"
|
||||
# water
|
||||
hydro: '#298c81'
|
||||
hydro reservoir: '#298c81'
|
||||
ror: '#3dbfb0'
|
||||
run of river: '#3dbfb0'
|
||||
hydroelectricity: '#298c81'
|
||||
PHS: '#51dbcc'
|
||||
wave: '#a7d4cf'
|
||||
# solar
|
||||
solar: "#f9d002"
|
||||
solar PV: "#f9d002"
|
||||
solar thermal: '#ffbf2b'
|
||||
solar rooftop: '#ffea80'
|
||||
# gas
|
||||
OCGT: '#e0986c'
|
||||
OCGT marginal: '#e0986c'
|
||||
OCGT-heat: '#e0986c'
|
||||
gas boiler: '#db6a25'
|
||||
gas boilers: '#db6a25'
|
||||
gas boiler marginal: '#db6a25'
|
||||
gas: '#e05b09'
|
||||
fossil gas: '#e05b09'
|
||||
natural gas: '#e05b09'
|
||||
CCGT: '#a85522'
|
||||
CCGT marginal: '#a85522'
|
||||
gas for industry co2 to atmosphere: '#692e0a'
|
||||
gas for industry co2 to stored: '#8a3400'
|
||||
gas for industry: '#853403'
|
||||
gas for industry CC: '#692e0a'
|
||||
gas pipeline: '#ebbca0'
|
||||
gas pipeline new: '#a87c62'
|
||||
# oil
|
||||
oil: '#c9c9c9'
|
||||
oil boiler: '#adadad'
|
||||
agriculture machinery oil: '#949494'
|
||||
shipping oil: "#808080"
|
||||
land transport oil: '#afafaf'
|
||||
# nuclear
|
||||
Nuclear: '#ff8c00'
|
||||
Nuclear marginal: '#ff8c00'
|
||||
nuclear: '#ff8c00'
|
||||
uranium: '#ff8c00'
|
||||
# coal
|
||||
Coal: '#545454'
|
||||
coal: '#545454'
|
||||
Coal marginal: '#545454'
|
||||
solid: '#545454'
|
||||
Lignite: '#826837'
|
||||
lignite: '#826837'
|
||||
Lignite marginal: '#826837'
|
||||
# biomass
|
||||
biogas: '#e3d37d'
|
||||
biomass: '#baa741'
|
||||
solid biomass: '#baa741'
|
||||
solid biomass transport: '#baa741'
|
||||
solid biomass for industry: '#7a6d26'
|
||||
solid biomass for industry CC: '#47411c'
|
||||
solid biomass for industry co2 from atmosphere: '#736412'
|
||||
solid biomass for industry co2 to stored: '#47411c'
|
||||
# power transmission
|
||||
lines: '#6c9459'
|
||||
transmission lines: '#6c9459'
|
||||
electricity distribution grid: '#97ad8c'
|
||||
# electricity demand
|
||||
Electric load: '#110d63'
|
||||
electric demand: '#110d63'
|
||||
electricity: '#110d63'
|
||||
industry electricity: '#2d2a66'
|
||||
industry new electricity: '#2d2a66'
|
||||
agriculture electricity: '#494778'
|
||||
# battery + EVs
|
||||
battery: '#ace37f'
|
||||
battery storage: '#ace37f'
|
||||
home battery: '#80c944'
|
||||
home battery storage: '#80c944'
|
||||
BEV charger: '#baf238'
|
||||
V2G: '#e5ffa8'
|
||||
land transport EV: '#baf238'
|
||||
Li ion: '#baf238'
|
||||
# hot water storage
|
||||
water tanks: '#e69487'
|
||||
hot water storage: '#e69487'
|
||||
hot water charging: '#e69487'
|
||||
hot water discharging: '#e69487'
|
||||
# heat demand
|
||||
Heat load: '#cc1f1f'
|
||||
heat: '#cc1f1f'
|
||||
heat demand: '#cc1f1f'
|
||||
rural heat: '#ff5c5c'
|
||||
central heat: '#cc1f1f'
|
||||
decentral heat: '#750606'
|
||||
low-temperature heat for industry: '#8f2727'
|
||||
process heat: '#ff0000'
|
||||
agriculture heat: '#d9a5a5'
|
||||
# heat supply
|
||||
heat pumps: '#2fb537'
|
||||
heat pump: '#2fb537'
|
||||
air heat pump: '#36eb41'
|
||||
ground heat pump: '#2fb537'
|
||||
Ambient: '#98eb9d'
|
||||
CHP: '#8a5751'
|
||||
CHP CC: '#634643'
|
||||
CHP heat: '#8a5751'
|
||||
CHP electric: '#8a5751'
|
||||
district heating: '#e8beac'
|
||||
resistive heater: '#d8f9b8'
|
||||
retrofitting: '#8487e8'
|
||||
building retrofitting: '#8487e8'
|
||||
# hydrogen
|
||||
H2 for industry: "#f073da"
|
||||
H2 for shipping: "#ebaee0"
|
||||
H2: '#bf13a0'
|
||||
hydrogen: '#bf13a0'
|
||||
SMR: '#870c71'
|
||||
SMR CC: '#4f1745'
|
||||
H2 liquefaction: '#d647bd'
|
||||
hydrogen storage: '#bf13a0'
|
||||
H2 storage: '#bf13a0'
|
||||
land transport fuel cell: '#6b3161'
|
||||
H2 pipeline: '#f081dc'
|
||||
H2 pipeline retrofitted: '#ba99b5'
|
||||
H2 Fuel Cell: '#c251ae'
|
||||
H2 Electrolysis: '#ff29d9'
|
||||
# syngas
|
||||
Sabatier: '#9850ad'
|
||||
methanation: '#c44ce6'
|
||||
methane: '#c44ce6'
|
||||
helmeth: '#e899ff'
|
||||
# synfuels
|
||||
Fischer-Tropsch: '#25c49a'
|
||||
liquid: '#25c49a'
|
||||
kerosene for aviation: '#a1ffe6'
|
||||
naphtha for industry: '#57ebc4'
|
||||
# co2
|
||||
CC: '#f29dae'
|
||||
CCS: '#f29dae'
|
||||
CO2 sequestration: '#f29dae'
|
||||
DAC: '#ff5270'
|
||||
co2 stored: '#f2385a'
|
||||
co2: '#f29dae'
|
||||
co2 vent: '#ffd4dc'
|
||||
CO2 pipeline: '#f5627f'
|
||||
# emissions
|
||||
process emissions CC: '#000000'
|
||||
process emissions: '#222222'
|
||||
process emissions to stored: '#444444'
|
||||
process emissions to atmosphere: '#888888'
|
||||
oil emissions: '#aaaaaa'
|
||||
shipping oil emissions: "#555555"
|
||||
land transport oil emissions: '#777777'
|
||||
agriculture machinery oil emissions: '#333333'
|
||||
# other
|
||||
shipping: '#03a2ff'
|
||||
power-to-heat: '#2fb537'
|
||||
power-to-gas: '#c44ce6'
|
||||
power-to-H2: '#ff29d9'
|
||||
power-to-liquid: '#25c49a'
|
||||
gas-to-power/heat: '#ee8340'
|
||||
waste: '#e3d37d'
|
||||
other: '#000000'
|
||||
Loading…
Reference in New Issue
Block a user