135 lines
4.9 KiB
Python
135 lines
4.9 KiB
Python
# coding: utf-8
|
|
|
|
import logging
|
|
logger = logging.getLogger(__name__)
|
|
|
|
import pandas as pd
|
|
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")
|
|
|
|
for c in n_p.iterate_components(["Link", "Generator", "Store"]):
|
|
|
|
attr = "e" if c.name == "Store" else "p"
|
|
|
|
# first, remove generators, links and stores that track
|
|
# CO2 or global EU values since these are already in n
|
|
n_p.mremove(
|
|
c.name,
|
|
c.df.index[c.df.lifetime==np.inf]
|
|
)
|
|
|
|
# remove assets whose build_year + lifetime < year
|
|
n_p.mremove(
|
|
c.name,
|
|
c.df.index[c.df.build_year + c.df.lifetime < year]
|
|
)
|
|
|
|
# remove assets if their optimized nominal capacity is lower than a threshold
|
|
# since CHP heat Link is proportional to CHP electric Link, make sure threshold is compatible
|
|
chp_heat = c.df.index[(
|
|
c.df[attr + "_nom_extendable"]
|
|
& c.df.index.str.contains("urban central")
|
|
& c.df.index.str.contains("CHP")
|
|
& c.df.index.str.contains("heat")
|
|
)]
|
|
|
|
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
|
|
* c.df.p_nom_ratio[chp_heat.str.replace("heat", "electric")].values
|
|
/ c.df.efficiency[chp_heat].values
|
|
)
|
|
n_p.mremove(
|
|
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)]
|
|
)
|
|
|
|
# copy over assets but fix their capacity
|
|
c.df[attr + "_nom"] = c.df[attr + "_nom_opt"]
|
|
c.df[attr + "_nom_extendable"] = False
|
|
|
|
n.import_components_from_dataframe(c.df, c.name)
|
|
|
|
# copy time-dependent
|
|
selection = (
|
|
n.component_attrs[c.name].type.str.contains("series")
|
|
& n.component_attrs[c.name].status.str.contains("Input")
|
|
)
|
|
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="37",
|
|
opts="",
|
|
lv=1.0,
|
|
sector_opts='168H-T-H-B-I-solar+p3-dist1',
|
|
planning_horizons=2030,
|
|
)
|
|
|
|
print(snakemake.input.network_p)
|
|
logging.basicConfig(level=snakemake.config['logging_level'])
|
|
|
|
year = int(snakemake.wildcards.planning_horizons)
|
|
|
|
overrides = override_component_attrs(snakemake.input.overrides)
|
|
n = pypsa.Network(snakemake.input.network, override_component_attrs=overrides)
|
|
|
|
add_build_year_to_new_assets(n, year)
|
|
|
|
n_p = pypsa.Network(snakemake.input.network_p, override_component_attrs=overrides)
|
|
|
|
add_brownfield(n, n_p, year)
|
|
|
|
n.export_to_netcdf(snakemake.output[0])
|