minor fixes and address deprecation warnings

This commit is contained in:
Fabian Neumann 2023-02-16 20:13:26 +01:00
parent c2a249ec79
commit b14d657042
7 changed files with 21 additions and 13 deletions

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@ -1,4 +1,4 @@
version: 0.6.0 version: 0.7.0
logging_level: INFO logging_level: INFO
@ -510,6 +510,7 @@ plotting:
natural gas: '#e05b09' natural gas: '#e05b09'
CCGT: '#a85522' CCGT: '#a85522'
CCGT marginal: '#a85522' CCGT marginal: '#a85522'
allam: '#B98F76'
gas for industry co2 to atmosphere: '#692e0a' gas for industry co2 to atmosphere: '#692e0a'
gas for industry co2 to stored: '#8a3400' gas for industry co2 to stored: '#8a3400'
gas for industry: '#853403' gas for industry: '#853403'

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@ -71,9 +71,9 @@ author = u'2019-2021 Tom Brown (KIT, TUB), Marta Victoria (Aarhus University), L
# built documents. # built documents.
# #
# The short X.Y version. # The short X.Y version.
version = u'0.6' version = u'0.7'
# The full version, including alpha/beta/rc tags. # The full version, including alpha/beta/rc tags.
release = u'0.6.0' release = u'0.7.0'
# The language for content autogenerated by Sphinx. Refer to documentation # The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages. # for a list of supported languages.

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@ -8,6 +8,11 @@ Future release
.. note:: .. note::
This unreleased version currently may require the master branches of PyPSA, PyPSA-Eur, and the technology-data repository. This unreleased version currently may require the master branches of PyPSA, PyPSA-Eur, and the technology-data repository.
* new feature
PyPSA-Eur-Sec 0.7.0 (16th February 2023)
========================================
This release includes the addition of the European gas transmission network and This release includes the addition of the European gas transmission network and
incorporates retrofitting options to hydrogen. incorporates retrofitting options to hydrogen.

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@ -178,7 +178,7 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
busmap = pd.read_csv(snakemake.input.busmap, index_col=0).squeeze() busmap = pd.read_csv(snakemake.input.busmap, index_col=0).squeeze()
inv_busmap = {} inv_busmap = {}
for k, v in busmap.iteritems(): for k, v in busmap.items():
inv_busmap[v] = inv_busmap.get(v, []) + [k] inv_busmap[v] = inv_busmap.get(v, []) + [k]
clustermaps = busmap_s.map(busmap) clustermaps = busmap_s.map(busmap)

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@ -40,7 +40,7 @@ if __name__ == '__main__':
reference = ["RS", "BA"] reference = ["RS", "BA"]
average = urban_fraction[reference].mean() average = urban_fraction[reference].mean()
fill_values = pd.Series({ct: average for ct in missing}) fill_values = pd.Series({ct: average for ct in missing})
urban_fraction = urban_fraction.append(fill_values) urban_fraction = pd.concat([urban_fraction, fill_values])
# population in each grid cell # population in each grid cell
pop_cells = pd.Series(I.dot(nuts3['pop'])) pop_cells = pd.Series(I.dot(nuts3['pop']))

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@ -28,8 +28,8 @@ def build_transport_demand(traffic_fn, airtemp_fn, nodes, nodal_transport_data):
## Get overall demand curve for all vehicles ## Get overall demand curve for all vehicles
traffic = pd.read_csv( traffic = pd.read_csv(
traffic_fn, skiprows=2, usecols=["count"], squeeze=True traffic_fn, skiprows=2, usecols=["count"]
) ).squeeze("columns")
transport_shape = generate_periodic_profiles( transport_shape = generate_periodic_profiles(
dt_index=snapshots, dt_index=snapshots,
@ -118,7 +118,7 @@ def bev_availability_profile(fn, snapshots, nodes, options):
Derive plugged-in availability for passenger electric vehicles. Derive plugged-in availability for passenger electric vehicles.
""" """
traffic = pd.read_csv(fn, skiprows=2, usecols=["count"], squeeze=True) traffic = pd.read_csv(fn, skiprows=2, usecols=["count"]).squeeze("columns")
avail_max = options["bev_avail_max"] avail_max = options["bev_avail_max"]
avail_mean = options["bev_avail_mean"] avail_mean = options["bev_avail_mean"]

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@ -527,6 +527,8 @@ def add_co2_tracking(n, options):
e_nom_max = pd.read_csv(snakemake.input.sequestration_potential, index_col=0).squeeze() e_nom_max = pd.read_csv(snakemake.input.sequestration_potential, index_col=0).squeeze()
e_nom_max = e_nom_max.reindex(spatial.co2.locations).fillna(0.).clip(upper=upper_limit).mul(1e6) / annualiser # t e_nom_max = e_nom_max.reindex(spatial.co2.locations).fillna(0.).clip(upper=upper_limit).mul(1e6) / annualiser # t
e_nom_max = e_nom_max.rename(index=lambda x: x + " co2 stored") e_nom_max = e_nom_max.rename(index=lambda x: x + " co2 stored")
else:
e_nom_max = np.inf
n.madd("Store", n.madd("Store",
spatial.co2.nodes, spatial.co2.nodes,
@ -759,8 +761,8 @@ def add_ammonia(n, costs):
carrier="Haber-Bosch", carrier="Haber-Bosch",
efficiency=1 / (cf_industry["MWh_elec_per_tNH3_electrolysis"] / cf_industry["MWh_NH3_per_tNH3"]), # output: MW_NH3 per MW_elec efficiency=1 / (cf_industry["MWh_elec_per_tNH3_electrolysis"] / cf_industry["MWh_NH3_per_tNH3"]), # output: MW_NH3 per MW_elec
efficiency2=-cf_industry["MWh_H2_per_tNH3_electrolysis"] / cf_industry["MWh_elec_per_tNH3_electrolysis"], # input: MW_H2 per MW_elec efficiency2=-cf_industry["MWh_H2_per_tNH3_electrolysis"] / cf_industry["MWh_elec_per_tNH3_electrolysis"], # input: MW_H2 per MW_elec
capital_cost=costs.at["Haber-Bosch synthesis", "fixed"], capital_cost=costs.at["Haber-Bosch", "fixed"],
lifetime=costs.at["Haber-Bosch synthesis", 'lifetime'] lifetime=costs.at["Haber-Bosch", 'lifetime']
) )
n.madd("Link", n.madd("Link",
@ -2905,6 +2907,9 @@ if __name__ == "__main__":
if "B" in opts: if "B" in opts:
add_biomass(n, costs) add_biomass(n, costs)
if options['ammonia']:
add_ammonia(n, costs)
if "I" in opts: if "I" in opts:
add_industry(n, costs) add_industry(n, costs)
@ -2917,9 +2922,6 @@ if __name__ == "__main__":
if options['dac']: if options['dac']:
add_dac(n, costs) add_dac(n, costs)
if options['ammonia']:
add_ammonia(n, costs)
if "decentral" in opts: if "decentral" in opts:
decentral(n) decentral(n)