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remove adjust_transport_temporal_agg

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Fabian Neumann 2024-05-15 16:49:26 +02:00
parent 5b5be71341
commit 1aa4f12c5e
2 changed files with 0 additions and 30 deletions
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2
scripts/prepare_perfect_foresight.py
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@ -18,7 +18,6 @@ from _helpers import (
update_config_from_wildcards, update_config_from_wildcards,
) )
from add_existing_baseyear import add_build_year_to_new_assets from add_existing_baseyear import add_build_year_to_new_assets
from prepare_sector_network import adjust_transport_temporal_agg
from pypsa.descriptors import expand_series from pypsa.descriptors import expand_series
from pypsa.io import import_components_from_dataframe from pypsa.io import import_components_from_dataframe
from six import iterkeys from six import iterkeys
@ -521,7 +520,6 @@ if __name__ == "__main__":
segments = snakemake.params.time_resolution segments = snakemake.params.time_resolution
if isinstance(segments, (int, float)): if isinstance(segments, (int, float)):
n = apply_time_segmentation_perfect(n, segments, solver_name=solver_name) n = apply_time_segmentation_perfect(n, segments, solver_name=solver_name)
adjust_transport_temporal_agg(n)
# adjust global constraints lv limit if the same for all years # adjust global constraints lv limit if the same for all years
n = adjust_lvlimit(n) n = adjust_lvlimit(n)

28
scripts/prepare_sector_network.py
View File

@ -3751,32 +3751,6 @@ def lossy_bidirectional_links(n, carrier, efficiencies={}):
) )
def adjust_transport_temporal_agg(n):
engine_types = {
"fuel_cell": "land transport fuel cell",
"electric": "land transport EV",
"ice": "land transport oil",
}
p_set = n.loads_t.p_set.loc[:, n.loads.carrier == "land transport demand"]
for engine, carrier in engine_types.items():
share = get(options[f"land_transport_{engine}_share"], investment_year)
if share == 0:
continue
links_i = n.links[n.links.carrier == carrier].index
efficiency = n.links_t.efficiency.loc[:, links_i]
p_set.columns = efficiency.columns
p_nom = share * p_set.div(efficiency).max()
profile = p_set.div(efficiency) / p_set.div(efficiency).max()
n.links.loc[links_i, "p_nom"] = p_nom
n.links_t.p_max_pu[links_i] = profile
n.links_t.p_min_pu[links_i] = profile
# %% # %%
if __name__ == "__main__": if __name__ == "__main__":
if "snakemake" not in globals(): if "snakemake" not in globals():
@ -3881,8 +3855,6 @@ if __name__ == "__main__":
resolution = snakemake.params.time_resolution resolution = snakemake.params.time_resolution
n = set_temporal_aggregation(n, resolution, solver_name) n = set_temporal_aggregation(n, resolution, solver_name)
adjust_transport_temporal_agg(n)
co2_budget = snakemake.params.co2_budget co2_budget = snakemake.params.co2_budget
if isinstance(co2_budget, str) and co2_budget.startswith("cb"): if isinstance(co2_budget, str) and co2_budget.startswith("cb"):
fn = "results/" + snakemake.params.RDIR + "/csvs/carbon_budget_distribution.csv" fn = "results/" + snakemake.params.RDIR + "/csvs/carbon_budget_distribution.csv"