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

[pre-commit.ci] auto fixes from pre-commit.com hooks

Browse Source 
for more information, see https://pre-commit.ci
This commit is contained in:
pre-commit-ci[bot] 2024-03-04 08:44:51 +00:00
parent 04d3164d7f
commit 4242a0841c
3 changed files with 129 additions and 96 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
scripts/build_transport_demand.py
View File

@ -21,7 +21,7 @@ logger = logging.getLogger(__name__)
def build_nodal_transport_data(fn, pop_layout):
# get numbers of car and fuel efficieny per country
transport_data = pd.read_csv(fn, index_col=0)
# break number of cars down to nodal level based on population density
nodal_transport_data = transport_data.loc[pop_layout.ct].fillna(0.0)
nodal_transport_data.index = pop_layout.index
@ -39,12 +39,11 @@ def build_nodal_transport_data(fn, pop_layout):
def build_transport_demand(traffic_fn, airtemp_fn, nodes, nodal_transport_data):
"""
returns transport demand per bus in unit kinetic energy.
Returns transport demand per bus in unit kinetic energy.
"""
# averaged weekly counts from the year 2010-2015
traffic = pd.read_csv(traffic_fn, skiprows=2,
usecols=["count"]).squeeze("columns")
traffic = pd.read_csv(traffic_fn, skiprows=2, usecols=["count"]).squeeze("columns")
# create annual profile take account time zone + summer time
transport_shape = generate_periodic_profiles(
dt_index=snapshots,
@ -65,7 +64,6 @@ def build_transport_demand(traffic_fn, airtemp_fn, nodes, nodal_transport_data):
options["ICE_upper_degree_factor"],
)
# divide out the heating/cooling demand from ICE totals
ice_correction = (transport_shape * (1 + dd_ICE)).sum() / transport_shape.sum()
@ -75,9 +73,8 @@ def build_transport_demand(traffic_fn, airtemp_fn, nodes, nodal_transport_data):
- pop_weighted_energy_totals["electricity rail"]
)
return (
(transport_shape.multiply(energy_totals_transport) * 1e6 * nyears)
.divide(nodal_transport_data["average fuel efficiency"] * ice_correction)
return (transport_shape.multiply(energy_totals_transport) * 1e6 * nyears).divide(
nodal_transport_data["average fuel efficiency"] * ice_correction
)
@ -141,7 +138,7 @@ def bev_availability_profile(fn, snapshots, nodes, options):
def bev_dsm_profile(snapshots, nodes, options):
dsm_week = np.zeros((24 * 7,))
# assuming that at a certain time ("bev_dsm_restriction_time") EVs have to
# be charged to a minimum value (defined in bev_dsm_restriction_value)
dsm_week[(np.arange(0, 7, 1) * 24 + options["bev_dsm_restriction_time"])] = options[
@ -154,7 +151,8 @@ def bev_dsm_profile(snapshots, nodes, options):
weekly_profile=dsm_week,
)
#%%
# %%
if __name__ == "__main__":
if "snakemake" not in globals():
from _helpers import mock_snakemake

202
scripts/prepare_sector_network.py
View File

@ -1505,15 +1505,22 @@ def add_storage_and_grids(n, costs):
def check_land_transport_shares(shares):
# Sums up the shares, ignoring None values
total_share = sum(filter(None, shares))
total_share = sum(filter(None, shares))
if total_share != 1:
logger.warning(
f"Total land transport shares sum up to {total_share:.2%},"
"corresponding to increased or decreased demand assumptions."
)
def get_temp_efficency(car_efficiency, temperature, deadband_lw, deadband_up,
degree_factor_lw, degree_factor_up):
def get_temp_efficency(
car_efficiency,
temperature,
deadband_lw,
deadband_up,
degree_factor_lw,
degree_factor_up,
):
"""
Correct temperature depending on heating and cooling for respective car
type.
@ -1526,14 +1533,23 @@ def get_temp_efficency(car_efficiency, temperature, deadband_lw, deadband_up,
degree_factor_lw,
degree_factor_up,
)
temp_eff = 1 / (1+dd)
temp_eff = 1 / (1 + dd)
return car_efficiency * temp_eff
def add_EVs(n, nodes, avail_profile, dsm_profile, p_set, electric_share,
number_cars, temperature):
def add_EVs(
n,
nodes,
avail_profile,
dsm_profile,
p_set,
electric_share,
number_cars,
temperature,
):
n.add("Carrier", "Li ion")
n.madd(
@ -1544,35 +1560,37 @@ def add_EVs(n, nodes, avail_profile, dsm_profile, p_set, electric_share,
carrier="Li ion",
unit="MWh_el",
)
car_efficiency = costs.at['Battery electric (passenger cars)', 'efficiency']
# temperature corrected efficiency
efficiency = get_temp_efficency(car_efficiency, temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["EV_lower_degree_factor"],
options["EV_upper_degree_factor"])
car_efficiency = costs.at["Battery electric (passenger cars)", "efficiency"]
# temperature corrected efficiency
efficiency = get_temp_efficency(
car_efficiency,
temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["EV_lower_degree_factor"],
options["EV_upper_degree_factor"],
)
suffix = " land transport EV"
p_nom = electric_share * p_set.div(efficiency).max()
profile = p_set.div(efficiency)/p_set.div(efficiency).max()
profile = p_set.div(efficiency) / p_set.div(efficiency).max()
n.madd(
"Link",
nodes,
suffix=suffix,
bus0=nodes + " EV battery",
bus0=nodes + " EV battery",
bus1=nodes + " land transport",
carrier="land transport EV",
efficiency=efficiency,
efficiency=efficiency,
p_min_pu=profile,
p_max_pu=profile,
p_nom=p_nom,
p_nom_extendable=False,
)
p_nom = number_cars * options.get("bev_charge_rate", 0.011) * electric_share
@ -1600,7 +1618,7 @@ def add_EVs(n, nodes, avail_profile, dsm_profile, p_set, electric_share,
p_max_pu=avail_profile[nodes],
efficiency=options.get("bev_charge_efficiency", 0.9),
)
if options["bev_dsm"]:
e_nom = (
number_cars
@ -1608,7 +1626,7 @@ def add_EVs(n, nodes, avail_profile, dsm_profile, p_set, electric_share,
* options["bev_availability"]
* electric_share
)
n.madd(
"Store",
nodes,
@ -1620,56 +1638,62 @@ def add_EVs(n, nodes, avail_profile, dsm_profile, p_set, electric_share,
e_max_pu=1,
e_min_pu=dsm_profile[nodes],
)
def add_fuel_cell_cars(n, nodes, p_set, fuel_cell_share, temperature):
car_efficiency = options["transport_fuel_cell_efficiency"]
# temperature corrected efficiency
efficiency = get_temp_efficency(car_efficiency, temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["ICE_lower_degree_factor"],
options["ICE_upper_degree_factor"])
# temperature corrected efficiency
efficiency = get_temp_efficency(
car_efficiency,
temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["ICE_lower_degree_factor"],
options["ICE_upper_degree_factor"],
)
suffix = " land transport fuel cell"
p_nom = fuel_cell_share * p_set.div(efficiency).max()
profile = p_set.div(efficiency)/p_set.div(efficiency).max()
profile = p_set.div(efficiency) / p_set.div(efficiency).max()
n.madd(
"Link",
nodes,
suffix=suffix,
bus0=spatial.h2.nodes,
bus1=nodes + " land transport",
carrier="land transport fuel cell",
efficiency=efficiency,
carrier="land transport fuel cell",
efficiency=efficiency,
p_nom_extendable=False,
p_nom=p_nom,
p_min_pu=profile,
p_max_pu=profile,
)
def add_ice_cars(n, nodes, p_set, ice_share, temperature):
add_carrier_buses(n, "oil")
car_efficiency = options["transport_internal_combustion_efficiency"]
# temperature corrected efficiency
efficiency = get_temp_efficency(car_efficiency, temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["ICE_lower_degree_factor"],
options["ICE_upper_degree_factor"])
# temperature corrected efficiency
efficiency = get_temp_efficency(
car_efficiency,
temperature,
options["transport_heating_deadband_lower"],
options["transport_heating_deadband_upper"],
options["ICE_lower_degree_factor"],
options["ICE_upper_degree_factor"],
)
suffix = " land transport ICE"
p_nom = ice_share * p_set.div(efficiency).max()
p_nom = ice_share * p_set.div(efficiency).max()
n.madd(
"Link",
nodes,
@ -1683,12 +1707,13 @@ def add_ice_cars(n, nodes, p_set, ice_share, temperature):
p_nom_extendable=False,
p_nom=p_nom,
)
def add_land_transport(n, costs):
# TODO options?
logger.info("Add land transport")
# read in transport demand in units kinetic energy
transport = pd.read_csv(
snakemake.input.transport_demand, index_col=0, parse_dates=True
@ -1702,54 +1727,62 @@ def add_land_transport(n, costs):
dsm_profile = pd.read_csv(
snakemake.input.dsm_profile, index_col=0, parse_dates=True
)
# exogenous share of passenger car type
engine_types = ["fuel_cell", "electric", "ice"]
shares = pd.Series()
for engine in engine_types:
shares[engine] = get(options[f"land_transport_{engine}_share"],
investment_year)
shares[engine] = get(options[f"land_transport_{engine}_share"], investment_year)
logger.info(f"{engine} share: {shares[engine]*100}%")
check_land_transport_shares(shares)
check_land_transport_shares(shares)
nodes = spatial.nodes
# Add load for transport demand
n.add("Carrier", "land transport demand")
n.madd("Bus",
nodes,
location=nodes,
suffix=" land transport",
carrier="land transport demand",
unit="MWh_kinetic")
n.madd(
"Bus",
nodes,
location=nodes,
suffix=" land transport",
carrier="land transport demand",
unit="MWh_kinetic",
)
p_set = transport[nodes]
# add demand
# add demand
n.madd(
"Load",
nodes,
suffix=" land transport",
bus=nodes + " land transport",
carrier="land transport demand",
p_set=p_set,
p_set=p_set,
)
# temperature for correction factor for heating/cooling
temperature = xr.open_dataarray(snakemake.input.temp_air_total).to_pandas()
if shares["electric"] > 0:
add_EVs(n, nodes, avail_profile, dsm_profile, p_set, shares["electric"],
number_cars, temperature)
add_EVs(
n,
nodes,
avail_profile,
dsm_profile,
p_set,
shares["electric"],
number_cars,
temperature,
)
if shares["fuel_cell"] > 0:
add_fuel_cell_cars(n, nodes, p_set, shares["fuel_cell"], temperature)
if shares["ice"] > 0:
add_ice_cars(n, nodes, p_set, shares["ice"], temperature)
def build_heat_demand(n):
@ -3643,7 +3676,8 @@ def lossy_bidirectional_links(n, carrier, efficiencies={}):
-compression_per_1000km * n.links.loc[carrier_i, "length_original"] / 1e3
)
#%%
# %%
if __name__ == "__main__":
if "snakemake" not in globals():
from _helpers import mock_snakemake

3
scripts/solve_network.py
View File

@ -921,7 +921,8 @@ def solve_network(n, config, solving, **kwargs):
return n
#%%
# %%
if __name__ == "__main__":
if "snakemake" not in globals():
from _helpers import mock_snakemake