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

Fix attaching of load

Browse Source
This commit is contained in:
Jonas Hörsch 2018-08-06 21:38:13 +02:00
parent 95f50ceaea
commit 92530f370a
1 changed files with 5 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

9
scripts/add_electricity.py
View File

@ -14,6 +14,7 @@ import geopandas as gpd
from vresutils.costdata import annuity from vresutils.costdata import annuity
from vresutils.load import timeseries_opsd from vresutils.load import timeseries_opsd
from vresutils import transfer as vtransfer
import pypsa import pypsa
import powerplantmatching as ppm import powerplantmatching as ppm
@ -109,7 +110,7 @@ def attach_load(n):
regions = gpd.read_file(snakemake.input.regions).set_index('name').reindex(substation_lv_i) regions = gpd.read_file(snakemake.input.regions).set_index('name').reindex(substation_lv_i)
opsd_load = timeseries_opsd(snakemake.input.opsd_load) opsd_load = timeseries_opsd(snakemake.input.opsd_load)
nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index('id') nuts3 = gpd.read_file(snakemake.input.nuts3_shapes).set_index('index')
def normed(x): return x.divide(x.sum()) def normed(x): return x.divide(x.sum())
@ -120,8 +121,8 @@ def attach_load(n):
else: else:
nuts3_cntry = nuts3.loc[nuts3.country == cntry] nuts3_cntry = nuts3.loc[nuts3.country == cntry]
transfer = vtransfer.Shapes2Shapes(group, nuts3_cntry.geometry, normed=False).T.tocsr() transfer = vtransfer.Shapes2Shapes(group, nuts3_cntry.geometry, normed=False).T.tocsr()
gdp_n = pd.Series(transfer.dot(nuts3.gdp.fillna(1.).values), index=group.index) gdp_n = pd.Series(transfer.dot(nuts3_cntry['gdp'].fillna(1.).values), index=group.index)
pop_n = pd.Series(transfer.dot(nuts3.pop.fillna(1.).values), index=group.index) pop_n = pd.Series(transfer.dot(nuts3_cntry['pop'].fillna(1.).values), index=group.index)
# relative factors 0.6 and 0.4 have been determined from a linear # relative factors 0.6 and 0.4 have been determined from a linear
# regression on the country to continent load data (refer to vresutils.load._upsampling_weights) # regression on the country to continent load data (refer to vresutils.load._upsampling_weights)
@ -255,7 +256,7 @@ def attach_hydro(n, costs, ppl):
hydro_max_hours = c.get('hydro_max_hours') hydro_max_hours = c.get('hydro_max_hours')
if hydro_max_hours is None: if hydro_max_hours is None:
hydro_e_country = pd.read_csv(snakemake.input.hydro_capacities, index_col=0).clip(lower=0.2)*1e6 hydro_e_country = pd.read_csv(snakemake.input.hydro_capacities, index_col=0)["E_store[TWh]"].clip(lower=0.2)*1e6
hydro_max_hours_country = hydro_e_country / hydro.p_nom.groupby(country).sum() hydro_max_hours_country = hydro_e_country / hydro.p_nom.groupby(country).sum()
hydro_max_hours = country.loc[hydro.index].map(hydro_max_hours_country) hydro_max_hours = country.loc[hydro.index].map(hydro_max_hours_country)