openego /
eGon-data
| @@ 261-284 (lines=24) @@ | ||
| 258 | ignore_index=True, |
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| 259 | ) |
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| 260 | next_bus_id += 1 |
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| 261 | if 220.0 in vnom_per_country[cntr]: |
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| 262 | central_buses = pd.concat( |
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| 263 | [ |
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| 264 | central_buses, |
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| 265 | pd.DataFrame( |
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| 266 | index=[central_buses.index.max() + 1], |
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| 267 | data={ |
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| 268 | "scn_name": scenario, |
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| 269 | "bus_id": next_bus_id, |
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| 270 | "x": central_buses[ |
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| 271 | central_buses.country == cntr |
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| 272 | ].x.unique()[0], |
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| 273 | "y": central_buses[ |
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| 274 | central_buses.country == cntr |
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| 275 | ].y.unique()[0], |
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| 276 | "country": cntr, |
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| 277 | "carrier": "AC", |
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| 278 | "v_nom": 220.0, |
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| 279 | }, |
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| 280 | ), |
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| 281 | ], |
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| 282 | ignore_index=True, |
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| 283 | ) |
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| 284 | next_bus_id += 1 |
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| 285 | ||
| 286 | # Add geometry column |
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| 287 | central_buses = gpd.GeoDataFrame( |
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| @@ 237-260 (lines=24) @@ | ||
| 234 | vnom_per_country = foreign_buses.groupby("country").v_nom.unique().copy() |
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| 235 | for cntr in vnom_per_country.index: |
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| 236 | print(cntr) |
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| 237 | if 110.0 in vnom_per_country[cntr]: |
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| 238 | central_buses = pd.concat( |
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| 239 | [ |
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| 240 | central_buses, |
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| 241 | pd.DataFrame( |
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| 242 | index=[central_buses.index.max() + 1], |
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| 243 | data={ |
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| 244 | "scn_name": scenario, |
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| 245 | "bus_id": next_bus_id, |
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| 246 | "x": central_buses[ |
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| 247 | central_buses.country == cntr |
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| 248 | ].x.unique()[0], |
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| 249 | "y": central_buses[ |
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| 250 | central_buses.country == cntr |
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| 251 | ].y.unique()[0], |
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| 252 | "country": cntr, |
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| 253 | "carrier": "AC", |
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| 254 | "v_nom": 110.0, |
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| 255 | }, |
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| 256 | ), |
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| 257 | ], |
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| 258 | ignore_index=True, |
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| 259 | ) |
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| 260 | next_bus_id += 1 |
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| 261 | if 220.0 in vnom_per_country[cntr]: |
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| 262 | central_buses = pd.concat( |
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| 263 | [ |
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