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Merge branch 'master' of github.com:nworbmot/pypsa-eur-sec

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This commit is contained in:
Tom Brown 2020-01-31 19:25:19 +01:00
commit ab401907b2
3 changed files with 12 additions and 2 deletions
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2
Snakefile
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@ -172,7 +172,7 @@ rule build_industrial_demand:
rule prepare_sector_network: rule prepare_sector_network:
input: input:
network=pypsaeur('networks/{network}_s{simpl}_{clusters}_lv{lv}_{opts}.nc'), network=pypsaeur('networks/{network}_s{simpl}_{clusters}_ec_lv{lv}_{opts}.nc'),
energy_totals_name='data/energy_totals.csv', energy_totals_name='data/energy_totals.csv',
co2_totals_name='data/co2_totals.csv', co2_totals_name='data/co2_totals.csv',
transport_name='data/transport_data.csv', transport_name='data/transport_data.csv',

10
scripts/build_biomass_potentials.py
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@ -21,6 +21,16 @@ def build_biomass_potentials():
df_new = pd.concat(df_dict) df_new = pd.concat(df_dict)
# solid biomass includes: Primary agricultural residues (MINBIOAGRW1),
# Forestry energy residue (MINBIOFRSF1),
# Secondary forestry residues (MINBIOWOOW1),
# Secondary Forestry residues – sawdust (MINBIOWOO1a)',
# Forestry residues from landscape care biomass (MINBIOFRSF1a),
# Municipal waste (MINBIOMUN1)',
# biogas includes : Manure biomass potential (MINBIOGAS1),
# Sludge biomass (MINBIOSLU1)
us_type = pd.Series(index=df_new.columns) us_type = pd.Series(index=df_new.columns)
us_type.iloc[0:7] = "not included" us_type.iloc[0:7] = "not included"
us_type.iloc[7:8] = "biogas" us_type.iloc[7:8] = "biogas"

2
scripts/solve_network.py
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@ -59,7 +59,7 @@ def prepare_network(n, solve_opts=None):
solve_opts = snakemake.config['solving']['options'] solve_opts = snakemake.config['solving']['options']
if 'clip_p_max_pu' in solve_opts: if 'clip_p_max_pu' in solve_opts:
for df in (n.generators_t.p_max_pu, n.storage_units_t.inflow): 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) df.where(df>solve_opts['clip_p_max_pu'], other=0., inplace=True)
if solve_opts.get('load_shedding'): if solve_opts.get('load_shedding'):