WIP

Author: paulhoefer

examples/example_analyze_14a_ding0_grids.py

@@ -1368,243 +1368,4 @@ def plot_network(
 """
 if __name__ == "__main__":
     edisgo = main()
-"""
-
-
-# ============================================================================
-# TEMPORARY TEST FOR EV FUNCTIONS
-# ============================================================================
-GRID_BASE_PATH = "/home/paul/eDisGo/examples/30879"
-EXPORT_DIR = Path("/home/paul/eDisGo/examples/test_ev_exports")
-EXPORT_DIR.mkdir(parents=True, exist_ok=True)
-
-# Load grid
-print("\n1. Loading ding0 grid...")
-edisgo = EDisGo(ding0_grid=GRID_BASE_PATH, legacy_ding0_grids=False)
-
-# Set timeindex
-timeindex = pd.date_range("2035-01-15 00:00:00", periods=24*7, freq="h")
-edisgo.set_timeindex(timeindex)
-
-# Import generators
-print("2. Importing generators...")
-scenario = "eGon2035"
-edisgo.import_generators(generator_scenario=scenario)
-
-# ============================================================================
-# EV PART
-# ============================================================================
-# Import + distribute + integrate together
-edisgo.import_electromobility(scenario=scenario)
-
-# Apply charging strategy (writes timeseries for the integrated CP load IDs from eDisGo)
-edisgo.apply_charging_strategy(strategy="dumb")
-
-# ============================================================================
-# Checks
-# ============================================================================
-print("\n3. Checking imported EV data...")
-
-# Charging points
-cp_df = edisgo.topology.charging_points_df.copy()
-print("Charging points shape:", cp_df.shape)
-print(cp_df.head())
-
-# Charging processes
-cp_process_df = edisgo.electromobility.charging_processes_df.copy()
-print("Charging processes shape:", cp_process_df.shape)
-print(cp_process_df.head())
-
-# Charging point time series
-loads_df = edisgo.timeseries.loads_active_power.copy()
-print("Loads active power shape:", loads_df.shape)
-print(loads_df.head())
-
-# ============================================================================
-# Export charging point time series
-# ============================================================================
-print("\n5. Exporting charging point time series...")
-
-timeseries_csv = EXPORT_DIR / "charging_points_timeseries.csv"
-loads_df.to_csv(timeseries_csv, index=True)
-
-print(f"Charging point time series exported to: {timeseries_csv}")
-
-# Optional: export only 5 sample charging points
-sample_cols = loads_df.columns[:10]
-df_sample = loads_df[sample_cols]
-
-sample_csv = EXPORT_DIR / "charging_points_timeseries_sample_5.csv"
-df_sample.to_csv(sample_csv, index=True)
-
-print(f"Sample 5 charging point time series exported to: {sample_csv}")
-
-# ============================================================================
-# Show full output for 5 charging points and plot
-# ============================================================================
-print("\n6. Full output for 5 charging points...")
-# with pd.option_context(
-#     "display.max_rows", None,
-#     "display.max_columns", None,
-#     "display.width", None
-# ):
-#     print(df_sample)
-
-# Plot 5 charging point time series
-df_sample.plot(figsize=(12, 5))
-plt.title("Charging profiles (5 sample CPs)")
-plt.ylabel("Power")
-plt.xlabel("Time")
-plt.tight_layout()
-plt.show()
-
-# ============================================================================
-# Export shp files of whole grid including charging points
-# ============================================================================
-from pathlib import Path
-import pandas as pd
-from shapely.geometry import LineString
-
-EXPORT_DIR = Path("/home/paul/eDisGo/examples/test_ev_exports/network_shp")
-EXPORT_DIR.mkdir(parents=True, exist_ok=True)
-
-# Helper: detect coordinate columns in buses_df
-def find_xy_columns(df):
-    candidates_x = ["x", "X", "lon", "longitude"]
-    candidates_y = ["y", "Y", "lat", "latitude"]
-
-    x_col = next((c for c in candidates_x if c in df.columns), None)
-    y_col = next((c for c in candidates_y if c in df.columns), None)
-
-    if x_col is None or y_col is None:
-        raise ValueError(
-            f"Could not find coordinate columns in buses_df. Columns are: {list(df.columns)}"
-        )
-    return x_col, y_col
-
-# Base topology tables
-buses_df = edisgo.topology.buses_df.copy()
-lines_df = edisgo.topology.lines_df.copy()
-loads_df = edisgo.topology.loads_df.copy()
-generators_df = edisgo.topology.generators_df.copy()
-transformers_df = edisgo.topology.transformers_df.copy()
-
-x_col, y_col = find_xy_columns(buses_df)
-
-# Optional: set CRS
-# Replace with the correct CRS of your ding0 grid if you know it
-CRS = "EPSG:4326"
-
-# 1) Buses -> Point shapefile
-buses_export = buses_df.reset_index().rename(columns={"index": "bus_id"})
-buses_gdf = gpd.GeoDataFrame(
-    buses_export,
-    geometry=gpd.points_from_xy(buses_export[x_col], buses_export[y_col]),
-    crs=CRS,
-)
-buses_gdf.to_file(EXPORT_DIR / "buses.shp", driver="ESRI Shapefile")
-
-# 2) Loads -> Point shapefile (including EV charging points)
-if "bus" in loads_df.columns:
-    loads_export = loads_df.reset_index().rename(columns={"index": "load_id"})
-    loads_export = loads_export.merge(
-        buses_df[[x_col, y_col]],
-        left_on="bus",
-        right_index=True,
-        how="left"
-    )
-    loads_gdf = gpd.GeoDataFrame(
-        loads_export,
-        geometry=gpd.points_from_xy(loads_export[x_col], loads_export[y_col]),
-        crs=CRS,
-    )
-    loads_gdf.to_file(EXPORT_DIR / "loads.shp", driver="ESRI Shapefile")
-
-# 3) Charging points only -> Point shapefile
-cp_df = edisgo.topology.charging_points_df.copy()
-if "bus" in cp_df.columns:
-    cp_export = cp_df.reset_index().rename(columns={"index": "charging_point_id"})
-    cp_export = cp_export.merge(
-        buses_df[[x_col, y_col]],
-        left_on="bus",
-        right_index=True,
-        how="left"
-    )
-    cp_gdf = gpd.GeoDataFrame(
-        cp_export,
-        geometry=gpd.points_from_xy(cp_export[x_col], cp_export[y_col]),
-        crs=CRS,
-    )
-    cp_gdf.to_file(EXPORT_DIR / "charging_points.shp", driver="ESRI Shapefile")
-else:
-    # fallback: if charging_points_df already has geometry
-    if "geometry" in cp_df.columns:
-        cp_gdf = gpd.GeoDataFrame(cp_df.reset_index(), geometry="geometry", crs=CRS)
-        cp_gdf.to_file(EXPORT_DIR / "charging_points.shp", driver="ESRI Shapefile")
-
-# 4) Generators -> Point shapefile
-if "bus" in generators_df.columns:
-    gen_export = generators_df.reset_index().rename(columns={"index": "generator_id"})
-    gen_export = gen_export.merge(
-        buses_df[[x_col, y_col]],
-        left_on="bus",
-        right_index=True,
-        how="left"
-    )
-    gen_gdf = gpd.GeoDataFrame(
-        gen_export,
-        geometry=gpd.points_from_xy(gen_export[x_col], gen_export[y_col]),
-        crs=CRS,
-    )
-    gen_gdf.to_file(EXPORT_DIR / "generators.shp", driver="ESRI Shapefile")
-
-# 5) Lines -> LineString shapefile
-required_line_cols = {"bus0", "bus1"}
-if required_line_cols.issubset(lines_df.columns):
-    line_records = []
-    for line_id, row in lines_df.iterrows():
-        bus0 = row["bus0"]
-        bus1 = row["bus1"]
-
-        if bus0 in buses_df.index and bus1 in buses_df.index:
-            x0, y0 = buses_df.loc[bus0, [x_col, y_col]]
-            x1, y1 = buses_df.loc[bus1, [x_col, y_col]]
-
-            geom = LineString([(x0, y0), (x1, y1)])
-            rec = row.to_dict()
-            rec["line_id"] = line_id
-            rec["geometry"] = geom
-            line_records.append(rec)
-
-    lines_gdf = gpd.GeoDataFrame(line_records, geometry="geometry", crs=CRS)
-    lines_gdf.to_file(EXPORT_DIR / "lines.shp", driver="ESRI Shapefile")
-
-# 6) Transformers -> simple connection lines between buses
-# Adjust column names if your dataframe uses different ones
-possible_hv_cols = ["bus0", "hv_bus", "bus_hv"]
-possible_lv_cols = ["bus1", "lv_bus", "bus_lv"]
-
-hv_col = next((c for c in possible_hv_cols if c in transformers_df.columns), None)
-lv_col = next((c for c in possible_lv_cols if c in transformers_df.columns), None)
-
-if hv_col and lv_col:
-    trafo_records = []
-    for trafo_id, row in transformers_df.iterrows():
-        bus_hv = row[hv_col]
-        bus_lv = row[lv_col]
-
-        if bus_hv in buses_df.index and bus_lv in buses_df.index:
-            x0, y0 = buses_df.loc[bus_hv, [x_col, y_col]]
-            x1, y1 = buses_df.loc[bus_lv, [x_col, y_col]]
-
-            geom = LineString([(x0, y0), (x1, y1)])
-            rec = row.to_dict()
-            rec["transformer_id"] = trafo_id
-            rec["geometry"] = geom
-            trafo_records.append(rec)
-
-    if trafo_records:
-        trafos_gdf = gpd.GeoDataFrame(trafo_records, geometry="geometry", crs=CRS)
-        trafos_gdf.to_file(EXPORT_DIR / "transformers.shp", driver="ESRI Shapefile")
-
-print(f"Shapefiles exported to: {EXPORT_DIR}")
+"""