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Fix EV efficiency handling #626

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Fix EV efficiency handling #626

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95 changes: 24 additions & 71 deletions examples/loma-14a.py
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Original file line number Diff line number Diff line change
Expand Up @@ -61,21 +61,6 @@ def run_optimization_14a(edisgo):

def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):
"""Import EV charging points, apply charging strategy, and adjust CP/HP counts."""
# Temporary Check: Amount of CPs before importing eDisGo CPs
names = edisgo.topology.loads_df.query("type == 'charging_point'").index.astype(str)
print(
{
"existing": names.str.contains("Existing", case=False).sum(),
"additional": names.str.contains("Additional", case=False).sum(),
"rest": (
~(
names.str.contains("Existing", case=False)
| names.str.contains("Additional", case=False)
)
).sum(),
"total": len(names),
}
)

"""
After this function there are no time series yet. Only charging points and
Expand All @@ -91,21 +76,6 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):
import_electromobility_data_kwds={"shapefile_path": shapefile_path},
)

# Temporary Check: Amount of CPs after importing eDisGo CPs
names = edisgo.topology.loads_df.query("type == 'charging_point'").index.astype(str)
print(
{
"existing": names.str.contains("Existing", case=False).sum(),
"additional": names.str.contains("Additional", case=False).sum(),
"rest": (
~(
names.str.contains("Existing", case=False)
| names.str.contains("Additional", case=False)
)
).sum(),
"total": len(names),
}
)

"""
This step created the time series for the new eDisGo charging points.
Expand All @@ -125,6 +95,21 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):

edisgo.apply_charging_strategy(strategy="dumb")

# Apply EV charging efficiency correction
ev_charging_efficiency = 0.9

lap = edisgo.timeseries.loads_active_power.copy()

cp_names_before_transfer = edisgo.topology.loads_df.query(
"type == 'charging_point'"
).index.intersection(lap.columns)

lap.loc[:, cp_names_before_transfer] = (
lap.loc[:, cp_names_before_transfer] * ev_charging_efficiency
)
edisgo.timeseries.loads_active_power = lap


"""
This step then finally transfers the time series from suitable eDisGo
charging_points to Existing_ und Additional_ charging points which are
Expand All @@ -143,22 +128,6 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):
tol_2=0.9,
)

# Temporary Check: Amount of CPs after transferring time series
names = edisgo.topology.loads_df.query("type == 'charging_point'").index.astype(str)
print(
{
"existing": names.str.contains("Existing", case=False).sum(),
"additional": names.str.contains("Additional", case=False).sum(),
"rest": (
~(
names.str.contains("Existing", case=False)
| names.str.contains("Additional", case=False)
)
).sum(),
"total": len(names),
}
)

# ============================================================
# Optional Utilities for sensitivity analysis/changing the amount of cp/hp
# - target by absolute value or relative percentage
Expand All @@ -179,7 +148,7 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):

set_charging_points_to_target(
edisgo,
target_total=100, # sets total amount of CP to 1000
target_total=1500, # sets total amount of CP to 1000
# percentage=0.10, # increases total amount of CP by 10%
# percentage=-0.10, # decreases total amount of CP by 10%
eligible_buses=cp_eligible_buses,
Expand All @@ -191,7 +160,7 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):

set_heat_pumps_to_target(
edisgo,
target_total=100, # sets total amount of HP to 50
target_total=1500, # sets total amount of HP to 50
# percentage=0.10, # increases total amount of HP by 10%
# percentage=-0.10, # decreases total amount of HP by 10%
eligible_buses=hp_eligible_buses,
Expand All @@ -200,22 +169,6 @@ def integrate_ev_and_hp_for_14a(edisgo, *, shapefile_path, output_dir):
export_dir=output_dir, # only applies when there are deleted HP
)

# Temporary Check: Amount of CPs after total amount changed
names = edisgo.topology.loads_df.query("type == 'charging_point'").index.astype(str)
print(
{
"existing": names.str.contains("Existing", case=False).sum(),
"additional": names.str.contains("Additional", case=False).sum(),
"rest": (
~(
names.str.contains("Existing", case=False)
| names.str.contains("Additional", case=False)
)
).sum(),
"total": len(names),
}
)


def prepare_edisgo_for_14a(edisgo, *, shapefile_path, output_dir):
"""Apply topology fixes, EV integration, and pre-optimization setup."""
Expand Down Expand Up @@ -256,14 +209,14 @@ def main():
# grid_path = "/home/carlos/LoMa/exec_folder/results/MGB_quo_model_pypsa"

# Whole husum paths
# grid_path = "/home/carlos/LoMa/exec_folder/results/Husum_SLP_CP_pypsa"
# path_husum_district_shp = (
# "/home/carlos/LoMa/exec_folder/data/Input_files/MV_grid_district/husum_district.shp"
# )
grid_path = "/home/paul/LoMa/loma-repo/results/Whole_Husum_model_pypsa"
path_husum_district_shp = (
"/home/paul/LoMa/loma-repo/data/Input_files/MV_grid_district/husum_district.shp"
)

# MGB paths
grid_path = "/home/carlos/LoMa/exec_folder/results/MGB_SLP_CP_pypsa"
path_husum_district_shp = "/home/carlos/LoMa/exec_folder/MGB_district"
# grid_path = "/home/paul/LoMa/MGB_2035_model_pypsa"
# path_husum_district_shp = "/home/paul/LoMa/loma-repo/data/Input_files/MGB_district"

edisgo = EDisGo(pypsa_csv_dir=grid_path, snapshot_range=(0, 23))

Expand All @@ -275,7 +228,7 @@ def main():
pypsa_n = edisgo.to_pypsa()
edisgo.analyze()

output_dir = "/home/carlos/LoMa/output_edisgo"
output_dir = "/home/paul/LoMa/test/edisgo_output"

prepare_edisgo_for_14a(
edisgo,
Expand Down
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