|
1
|
|
|
"""Import MaStR dataset and write to DB tables |
|
2
|
|
|
|
|
3
|
|
|
Data dump from Marktstammdatenregister (2022-11-17) is imported into the |
|
4
|
|
|
database. Only some technologies are taken into account and written to the |
|
5
|
|
|
following tables: |
|
6
|
|
|
|
|
7
|
|
|
* PV: table `supply.egon_power_plants_pv` |
|
8
|
|
|
* wind turbines: table `supply.egon_power_plants_wind` |
|
9
|
|
|
* biomass/biogas plants: table `supply.egon_power_plants_biomass` |
|
10
|
|
|
* hydro plants: table `supply.egon_power_plants_hydro` |
|
11
|
|
|
|
|
12
|
|
|
Handling of empty source data in MaStr dump: |
|
13
|
|
|
|
|
14
|
|
|
* `voltage_level`: inferred based on nominal power (`capacity`) using the |
|
15
|
|
|
ranges from |
|
16
|
|
|
https://redmine.iks.cs.ovgu.de/oe/projects/ego-n/wiki/Definition_of_thresholds_for_voltage_level_assignment |
|
17
|
|
|
which results in True in column `voltage_level_inferred`. Remaining datasets |
|
18
|
|
|
are set to -1 (which only occurs if `capacity` is empty). |
|
19
|
|
|
* `supply.egon_power_plants_*.bus_id`: set to -1 (only if not within grid |
|
20
|
|
|
districts or no geom available, e.g. for units with nom. power <30 kW) |
|
21
|
|
|
* `supply.egon_power_plants_hydro.plant_type`: NaN |
|
22
|
|
|
|
|
23
|
|
|
The data is used especially for the generation of status quo grids by ding0. |
|
24
|
|
|
""" |
|
25
|
|
|
|
|
26
|
|
|
from __future__ import annotations |
|
27
|
|
|
|
|
28
|
|
|
from pathlib import Path |
|
29
|
|
|
|
|
30
|
|
|
from loguru import logger |
|
31
|
|
|
import geopandas as gpd |
|
32
|
|
|
import numpy as np |
|
33
|
|
|
import pandas as pd |
|
34
|
|
|
|
|
35
|
|
|
from egon.data import config, db |
|
36
|
|
|
from egon.data.datasets.mastr import WORKING_DIR_MASTR_NEW |
|
37
|
|
|
from egon.data.datasets.power_plants.mastr_db_classes import ( |
|
38
|
|
|
EgonMastrGeocoded, |
|
39
|
|
|
EgonPowerPlantsBiomass, |
|
40
|
|
|
EgonPowerPlantsCombustion, |
|
41
|
|
|
EgonPowerPlantsGsgk, |
|
42
|
|
|
EgonPowerPlantsHydro, |
|
43
|
|
|
EgonPowerPlantsNuclear, |
|
44
|
|
|
EgonPowerPlantsPv, |
|
45
|
|
|
EgonPowerPlantsStorage, |
|
46
|
|
|
EgonPowerPlantsWind, |
|
47
|
|
|
add_metadata, |
|
48
|
|
|
) |
|
49
|
|
|
from egon.data.datasets.power_plants.pv_rooftop_buildings import ( |
|
50
|
|
|
federal_state_data, |
|
51
|
|
|
) |
|
52
|
|
|
|
|
53
|
|
|
TESTMODE_OFF = ( |
|
54
|
|
|
config.settings()["egon-data"]["--dataset-boundary"] == "Everything" |
|
55
|
|
|
) |
|
56
|
|
|
|
|
57
|
|
|
|
|
58
|
|
|
def isfloat(num: str): |
|
59
|
|
|
""" |
|
60
|
|
|
Determine if string can be converted to float. |
|
61
|
|
|
|
|
62
|
|
|
Parameters |
|
63
|
|
|
----------- |
|
64
|
|
|
num : str |
|
65
|
|
|
String to parse. |
|
66
|
|
|
Returns |
|
67
|
|
|
------- |
|
68
|
|
|
bool |
|
69
|
|
|
Returns True in string can be parsed to float. |
|
70
|
|
|
""" |
|
71
|
|
|
try: |
|
72
|
|
|
float(num) |
|
73
|
|
|
return True |
|
74
|
|
|
except ValueError: |
|
75
|
|
|
return False |
|
76
|
|
|
|
|
77
|
|
|
|
|
78
|
|
|
def zip_and_municipality_from_standort( |
|
79
|
|
|
standort: str, |
|
80
|
|
|
) -> tuple[str, bool]: |
|
81
|
|
|
""" |
|
82
|
|
|
Get zip code and municipality from Standort string split into a list. |
|
83
|
|
|
|
|
84
|
|
|
Parameters |
|
85
|
|
|
----------- |
|
86
|
|
|
standort : str |
|
87
|
|
|
Standort as given from MaStR data. |
|
88
|
|
|
Returns |
|
89
|
|
|
------- |
|
90
|
|
|
str |
|
91
|
|
|
Standort with only the zip code and municipality |
|
92
|
|
|
as well a ', Germany' added. |
|
93
|
|
|
""" |
|
94
|
|
|
standort_list = standort.split() |
|
95
|
|
|
|
|
96
|
|
|
found = False |
|
97
|
|
|
count = 0 |
|
98
|
|
|
|
|
99
|
|
|
for count, elem in enumerate(standort_list): |
|
100
|
|
|
if len(elem) != 5: |
|
101
|
|
|
continue |
|
102
|
|
|
if not elem.isnumeric(): |
|
103
|
|
|
continue |
|
104
|
|
|
|
|
105
|
|
|
found = True |
|
106
|
|
|
|
|
107
|
|
|
break |
|
108
|
|
|
|
|
109
|
|
|
if found: |
|
110
|
|
|
cleaned_str = " ".join(standort_list[count:]) |
|
111
|
|
|
|
|
112
|
|
|
return cleaned_str, found |
|
113
|
|
|
|
|
114
|
|
|
logger.warning( |
|
115
|
|
|
"Couldn't identify zip code. This entry will be dropped." |
|
116
|
|
|
f" Original standort: {standort}." |
|
117
|
|
|
) |
|
118
|
|
|
|
|
119
|
|
|
return standort, found |
|
120
|
|
|
|
|
121
|
|
|
|
|
122
|
|
View Code Duplication |
def infer_voltage_level( |
|
|
|
|
|
|
123
|
|
|
units_gdf: gpd.GeoDataFrame, |
|
124
|
|
|
) -> gpd.GeoDataFrame: |
|
125
|
|
|
""" |
|
126
|
|
|
Infer nan values in voltage level derived from generator capacity to |
|
127
|
|
|
the power plants. |
|
128
|
|
|
|
|
129
|
|
|
Parameters |
|
130
|
|
|
----------- |
|
131
|
|
|
units_gdf : geopandas.GeoDataFrame |
|
132
|
|
|
GeoDataFrame containing units with voltage levels from MaStR |
|
133
|
|
|
Returns |
|
134
|
|
|
------- |
|
135
|
|
|
geopandas.GeoDataFrame |
|
136
|
|
|
GeoDataFrame containing units all having assigned a voltage level. |
|
137
|
|
|
""" |
|
138
|
|
|
|
|
139
|
|
|
def voltage_levels(p: float) -> int: |
|
140
|
|
|
if p <= 100: |
|
141
|
|
|
return 7 |
|
142
|
|
|
elif p <= 200: |
|
143
|
|
|
return 6 |
|
144
|
|
|
elif p <= 5500: |
|
145
|
|
|
return 5 |
|
146
|
|
|
elif p <= 20000: |
|
147
|
|
|
return 4 |
|
148
|
|
|
elif p <= 120000: |
|
149
|
|
|
return 3 |
|
150
|
|
|
return 1 |
|
151
|
|
|
|
|
152
|
|
|
units_gdf["voltage_level_inferred"] = False |
|
153
|
|
|
mask = units_gdf.voltage_level.isna() |
|
154
|
|
|
units_gdf.loc[mask, "voltage_level_inferred"] = True |
|
155
|
|
|
units_gdf.loc[mask, "voltage_level"] = units_gdf.loc[ |
|
156
|
|
|
mask |
|
157
|
|
|
].Nettonennleistung.apply(voltage_levels) |
|
158
|
|
|
|
|
159
|
|
|
return units_gdf |
|
160
|
|
|
|
|
161
|
|
|
|
|
162
|
|
|
def import_mastr() -> None: |
|
163
|
|
|
"""Import MaStR data into database""" |
|
164
|
|
|
engine = db.engine() |
|
165
|
|
|
|
|
166
|
|
|
# import geocoded data |
|
167
|
|
|
cfg = config.datasets()["mastr_new"] |
|
168
|
|
|
path_parts = cfg["geocoding_path"] |
|
169
|
|
|
path = Path(*["."] + path_parts).resolve() |
|
170
|
|
|
path = list(path.iterdir())[0] |
|
171
|
|
|
|
|
172
|
|
|
deposit_id_geocoding = int(path.parts[-1].split(".")[0].split("_")[-1]) |
|
173
|
|
|
deposit_id_mastr = cfg["deposit_id"] |
|
174
|
|
|
|
|
175
|
|
|
if deposit_id_geocoding != deposit_id_mastr: |
|
176
|
|
|
raise AssertionError( |
|
177
|
|
|
f"The zenodo (sandbox) deposit ID {deposit_id_mastr} for the MaStR" |
|
178
|
|
|
f" dataset is not matching with the geocoding version " |
|
179
|
|
|
f"{deposit_id_geocoding}. Make sure to hermonize the data. When " |
|
180
|
|
|
f"the MaStR dataset is updated also update the geocoding and " |
|
181
|
|
|
f"update the egon data bundle. The geocoding can be done using: " |
|
182
|
|
|
f"https://github.com/RLI-sandbox/mastr-geocoding" |
|
183
|
|
|
) |
|
184
|
|
|
|
|
185
|
|
|
geocoding_gdf = gpd.read_file(path) |
|
186
|
|
|
|
|
187
|
|
|
# remove failed requests |
|
188
|
|
|
geocoding_gdf = geocoding_gdf.loc[geocoding_gdf.geometry.is_valid] |
|
189
|
|
|
|
|
190
|
|
|
# remove unnecesary columns |
|
191
|
|
|
geocoding_gdf.drop(columns="geocode_source", inplace=True) |
|
192
|
|
|
|
|
193
|
|
|
EgonMastrGeocoded.__table__.drop(bind=engine, checkfirst=True) |
|
194
|
|
|
EgonMastrGeocoded.__table__.create(bind=engine, checkfirst=True) |
|
195
|
|
|
|
|
196
|
|
|
geocoding_gdf.to_postgis( |
|
197
|
|
|
name=EgonMastrGeocoded.__tablename__, |
|
198
|
|
|
con=engine, |
|
199
|
|
|
if_exists="append", |
|
200
|
|
|
schema=EgonMastrGeocoded.__table_args__["schema"], |
|
201
|
|
|
index=True, |
|
202
|
|
|
) |
|
203
|
|
|
|
|
204
|
|
|
cfg = config.datasets()["power_plants"] |
|
205
|
|
|
|
|
206
|
|
|
cols_mapping = { |
|
207
|
|
|
"all": { |
|
208
|
|
|
"EinheitMastrNummer": "gens_id", |
|
209
|
|
|
"EinheitBetriebsstatus": "status", |
|
210
|
|
|
"Inbetriebnahmedatum": "commissioning_date", |
|
211
|
|
|
"Postleitzahl": "postcode", |
|
212
|
|
|
"Ort": "city", |
|
213
|
|
|
"Gemeinde": "municipality", |
|
214
|
|
|
"Bundesland": "federal_state", |
|
215
|
|
|
"Nettonennleistung": "capacity", |
|
216
|
|
|
"Einspeisungsart": "feedin_type", |
|
217
|
|
|
"DatumEndgueltigeStilllegung": "decommissioning_date", |
|
218
|
|
|
}, |
|
219
|
|
|
"pv": { |
|
220
|
|
|
"Lage": "site_type", |
|
221
|
|
|
"Standort": "site", |
|
222
|
|
|
"Nutzungsbereich": "usage_sector", |
|
223
|
|
|
"Hauptausrichtung": "orientation_primary", |
|
224
|
|
|
"HauptausrichtungNeigungswinkel": "orientation_primary_angle", |
|
225
|
|
|
"Nebenausrichtung": "orientation_secondary", |
|
226
|
|
|
"NebenausrichtungNeigungswinkel": "orientation_secondary_angle", |
|
227
|
|
|
"EinheitlicheAusrichtungUndNeigungswinkel": "orientation_uniform", |
|
228
|
|
|
"AnzahlModule": "module_count", |
|
229
|
|
|
"zugeordneteWirkleistungWechselrichter": "capacity_inverter", |
|
230
|
|
|
}, |
|
231
|
|
|
"wind": { |
|
232
|
|
|
"Lage": "site_type", |
|
233
|
|
|
"Hersteller": "manufacturer_name", |
|
234
|
|
|
"Typenbezeichnung": "type_name", |
|
235
|
|
|
"Nabenhoehe": "hub_height", |
|
236
|
|
|
"Rotordurchmesser": "rotor_diameter", |
|
237
|
|
|
}, |
|
238
|
|
|
"biomass": { |
|
239
|
|
|
"Technologie": "technology", |
|
240
|
|
|
"Hauptbrennstoff": "main_fuel", |
|
241
|
|
|
"Biomasseart": "fuel_type", |
|
242
|
|
|
"ThermischeNutzleistung": "th_capacity", |
|
243
|
|
|
}, |
|
244
|
|
|
"hydro": { |
|
245
|
|
|
"ArtDerWasserkraftanlage": "plant_type", |
|
246
|
|
|
"ArtDesZuflusses": "water_origin", |
|
247
|
|
|
}, |
|
248
|
|
|
"combustion": { |
|
249
|
|
|
"Energietraeger": "carrier", |
|
250
|
|
|
"Hauptbrennstoff": "main_fuel", |
|
251
|
|
|
"WeitererHauptbrennstoff": "other_main_fuel", |
|
252
|
|
|
"Technologie": "technology", |
|
253
|
|
|
"ThermischeNutzleistung": "th_capacity", |
|
254
|
|
|
}, |
|
255
|
|
|
"gsgk": { |
|
256
|
|
|
"Energietraeger": "carrier", |
|
257
|
|
|
"Technologie": "technology", |
|
258
|
|
|
}, |
|
259
|
|
|
"nuclear": { |
|
260
|
|
|
"Energietraeger": "carrier", |
|
261
|
|
|
"Technologie": "technology", |
|
262
|
|
|
}, |
|
263
|
|
|
"storage": { |
|
264
|
|
|
"Energietraeger": "carrier", |
|
265
|
|
|
"Technologie": "technology", |
|
266
|
|
|
"Batterietechnologie": "battery_type", |
|
267
|
|
|
"Pumpspeichertechnologie": "pump_storage_type", |
|
268
|
|
|
}, |
|
269
|
|
|
} |
|
270
|
|
|
|
|
271
|
|
|
source_files = { |
|
272
|
|
|
"pv": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_pv"], |
|
273
|
|
|
"wind": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_wind"], |
|
274
|
|
|
"biomass": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_biomass"], |
|
275
|
|
|
"hydro": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_hydro"], |
|
276
|
|
|
"combustion": WORKING_DIR_MASTR_NEW |
|
277
|
|
|
/ cfg["sources"]["mastr_combustion"], |
|
278
|
|
|
"gsgk": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_gsgk"], |
|
279
|
|
|
"nuclear": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_nuclear"], |
|
280
|
|
|
"storage": WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_storage"], |
|
281
|
|
|
} |
|
282
|
|
|
|
|
283
|
|
|
target_tables = { |
|
284
|
|
|
"pv": EgonPowerPlantsPv, |
|
285
|
|
|
"wind": EgonPowerPlantsWind, |
|
286
|
|
|
"biomass": EgonPowerPlantsBiomass, |
|
287
|
|
|
"hydro": EgonPowerPlantsHydro, |
|
288
|
|
|
"combustion": EgonPowerPlantsCombustion, |
|
289
|
|
|
"gsgk": EgonPowerPlantsGsgk, |
|
290
|
|
|
"nuclear": EgonPowerPlantsNuclear, |
|
291
|
|
|
"storage": EgonPowerPlantsStorage, |
|
292
|
|
|
} |
|
293
|
|
|
|
|
294
|
|
|
vlevel_mapping = { |
|
295
|
|
|
"Höchstspannung": 1, |
|
296
|
|
|
"UmspannungZurHochspannung": 2, |
|
297
|
|
|
"Hochspannung": 3, |
|
298
|
|
|
"UmspannungZurMittelspannung": 4, |
|
299
|
|
|
"Mittelspannung": 5, |
|
300
|
|
|
"UmspannungZurNiederspannung": 6, |
|
301
|
|
|
"Niederspannung": 7, |
|
302
|
|
|
} |
|
303
|
|
|
|
|
304
|
|
|
# import locations |
|
305
|
|
|
locations = pd.read_csv( |
|
306
|
|
|
WORKING_DIR_MASTR_NEW / cfg["sources"]["mastr_location"], |
|
307
|
|
|
index_col=None, |
|
308
|
|
|
) |
|
309
|
|
|
|
|
310
|
|
|
# import grid districts |
|
311
|
|
|
mv_grid_districts = db.select_geodataframe( |
|
312
|
|
|
f""" |
|
313
|
|
|
SELECT * FROM {cfg['sources']['egon_mv_grid_district']} |
|
314
|
|
|
""", |
|
315
|
|
|
epsg=4326, |
|
316
|
|
|
) |
|
317
|
|
|
|
|
318
|
|
|
# import units |
|
319
|
|
|
technologies = [ |
|
320
|
|
|
"pv", |
|
321
|
|
|
"wind", |
|
322
|
|
|
"biomass", |
|
323
|
|
|
"hydro", |
|
324
|
|
|
"combustion", |
|
325
|
|
|
"gsgk", |
|
326
|
|
|
"nuclear", |
|
327
|
|
|
"storage", |
|
328
|
|
|
] |
|
329
|
|
|
|
|
330
|
|
|
for tech in technologies: |
|
331
|
|
|
# read units |
|
332
|
|
|
logger.info(f"===== Importing MaStR dataset: {tech} =====") |
|
333
|
|
|
logger.debug("Reading CSV and filtering data...") |
|
334
|
|
|
units = pd.read_csv( |
|
335
|
|
|
source_files[tech], |
|
336
|
|
|
usecols=( |
|
337
|
|
|
["LokationMastrNummer", "Laengengrad", "Breitengrad", "Land"] |
|
338
|
|
|
+ list(cols_mapping["all"].keys()) |
|
339
|
|
|
+ list(cols_mapping[tech].keys()) |
|
340
|
|
|
), |
|
341
|
|
|
index_col=None, |
|
342
|
|
|
dtype={"Postleitzahl": str}, |
|
343
|
|
|
low_memory=False, |
|
344
|
|
|
).rename(columns=cols_mapping) |
|
345
|
|
|
|
|
346
|
|
|
|
|
347
|
|
|
# drop units outside of Germany |
|
348
|
|
|
len_old = len(units) |
|
349
|
|
|
units = units.loc[units.Land == "Deutschland"] |
|
350
|
|
|
logger.debug( |
|
351
|
|
|
f"{len_old - len(units)} units outside of Germany dropped..." |
|
352
|
|
|
) |
|
353
|
|
|
|
|
354
|
|
|
# get boundary |
|
355
|
|
|
boundary = ( |
|
356
|
|
|
federal_state_data(geocoding_gdf.crs).dissolve().at[0, "geom"] |
|
357
|
|
|
) |
|
358
|
|
|
|
|
359
|
|
|
# drop not operating units |
|
360
|
|
|
len_old = len(units) |
|
361
|
|
|
units = units.loc[ |
|
362
|
|
|
units.EinheitBetriebsstatus.isin( |
|
363
|
|
|
["InBetrieb", "VoruebergehendStillgelegt"] |
|
364
|
|
|
) |
|
365
|
|
|
] |
|
366
|
|
|
logger.debug(f"{len_old - len(units)} not operating units dropped...") |
|
367
|
|
|
|
|
368
|
|
|
# filter for SH units if in testmode |
|
369
|
|
|
if not TESTMODE_OFF: |
|
370
|
|
|
logger.info( |
|
371
|
|
|
"TESTMODE: Dropping all units outside of Schleswig-Holstein..." |
|
372
|
|
|
) |
|
373
|
|
|
units = units.loc[units.Bundesland == "SchleswigHolstein"] |
|
374
|
|
|
|
|
375
|
|
|
# merge and rename voltage level |
|
376
|
|
|
logger.debug("Merging with locations and allocate voltage level...") |
|
377
|
|
|
units = units.merge( |
|
378
|
|
|
locations[["MaStRNummer", "Spannungsebene"]], |
|
379
|
|
|
left_on="LokationMastrNummer", |
|
380
|
|
|
right_on="MaStRNummer", |
|
381
|
|
|
how="left", |
|
382
|
|
|
) |
|
383
|
|
|
# convert voltage levels to numbers |
|
384
|
|
|
units["voltage_level"] = units.Spannungsebene.replace(vlevel_mapping) |
|
385
|
|
|
# set voltage level for nan values |
|
386
|
|
|
units = infer_voltage_level(units) |
|
387
|
|
|
|
|
388
|
|
|
# add geometry |
|
389
|
|
|
logger.debug("Adding geometries...") |
|
390
|
|
|
units = gpd.GeoDataFrame( |
|
391
|
|
|
units, |
|
392
|
|
|
geometry=gpd.points_from_xy( |
|
393
|
|
|
units["Laengengrad"], units["Breitengrad"], crs=4326 |
|
394
|
|
|
), |
|
395
|
|
|
crs=4326, |
|
396
|
|
|
) |
|
397
|
|
|
|
|
398
|
|
|
units["geometry_geocoded"] = ( |
|
399
|
|
|
units.Laengengrad.isna() | units.Laengengrad.isna() |
|
400
|
|
|
) |
|
401
|
|
|
|
|
402
|
|
|
units.loc[~units.geometry_geocoded, "geometry_geocoded"] = ~units.loc[ |
|
403
|
|
|
~units.geometry_geocoded, "geometry" |
|
404
|
|
|
].is_valid |
|
405
|
|
|
|
|
406
|
|
|
units_wo_geom = units["geometry_geocoded"].sum() |
|
407
|
|
|
|
|
408
|
|
|
logger.debug( |
|
409
|
|
|
f"{units_wo_geom}/{len(units)} units do not have a geometry!" |
|
410
|
|
|
" Adding geocoding results." |
|
411
|
|
|
) |
|
412
|
|
|
|
|
413
|
|
|
# determine zip and municipality string |
|
414
|
|
|
mask = ( |
|
415
|
|
|
units.Postleitzahl.apply(isfloat) |
|
416
|
|
|
& ~units.Postleitzahl.isna() |
|
417
|
|
|
& ~units.Gemeinde.isna() |
|
418
|
|
|
) |
|
419
|
|
|
units["zip_and_municipality"] = np.nan |
|
420
|
|
|
ok_units = units.loc[mask] |
|
421
|
|
|
|
|
422
|
|
|
units.loc[mask, "zip_and_municipality"] = ( |
|
423
|
|
|
ok_units.Postleitzahl.astype(float) |
|
424
|
|
|
.astype(int) |
|
425
|
|
|
.astype(str) |
|
426
|
|
|
.str.zfill(5) |
|
427
|
|
|
+ " " |
|
428
|
|
|
+ ok_units.Gemeinde.astype(str).str.rstrip().str.lstrip() |
|
429
|
|
|
+ ", Deutschland" |
|
430
|
|
|
) |
|
431
|
|
|
|
|
432
|
|
|
# get zip and municipality from Standort |
|
433
|
|
|
parse_df = units.loc[~mask] |
|
434
|
|
|
|
|
435
|
|
|
if not parse_df.empty and "Standort" in parse_df.columns: |
|
436
|
|
|
init_len = len(parse_df) |
|
437
|
|
|
|
|
438
|
|
|
logger.info( |
|
439
|
|
|
f"Parsing ZIP code and municipality from Standort for " |
|
440
|
|
|
f"{init_len} values for {tech}." |
|
441
|
|
|
) |
|
442
|
|
|
|
|
443
|
|
|
parse_df[["zip_and_municipality", "drop_this"]] = ( |
|
444
|
|
|
parse_df.Standort.astype(str) |
|
445
|
|
|
.apply(zip_and_municipality_from_standort) |
|
446
|
|
|
.tolist() |
|
447
|
|
|
) |
|
448
|
|
|
|
|
449
|
|
|
parse_df = parse_df.loc[parse_df.drop_this] |
|
450
|
|
|
|
|
451
|
|
|
if not parse_df.empty: |
|
452
|
|
|
units.loc[parse_df.index, "zip_and_municipality"] = ( |
|
453
|
|
|
parse_df.zip_and_municipality |
|
454
|
|
|
) |
|
455
|
|
|
|
|
456
|
|
|
# add geocoding to missing |
|
457
|
|
|
units = units.merge( |
|
458
|
|
|
right=geocoding_gdf[["zip_and_municipality", "geometry"]].rename( |
|
459
|
|
|
columns={"geometry": "temp"} |
|
460
|
|
|
), |
|
461
|
|
|
how="left", |
|
462
|
|
|
on="zip_and_municipality", |
|
463
|
|
|
) |
|
464
|
|
|
|
|
465
|
|
|
units.loc[units.geometry_geocoded, "geometry"] = units.loc[ |
|
466
|
|
|
units.geometry_geocoded, "temp" |
|
467
|
|
|
] |
|
468
|
|
|
|
|
469
|
|
|
init_len = len(units) |
|
470
|
|
|
|
|
471
|
|
|
logger.info( |
|
472
|
|
|
"Dropping units outside boundary by geometry or without geometry" |
|
473
|
|
|
"..." |
|
474
|
|
|
) |
|
475
|
|
|
|
|
476
|
|
|
units.dropna(subset=["geometry"], inplace=True) |
|
477
|
|
|
|
|
478
|
|
|
units = units.loc[units.geometry.within(boundary)] |
|
479
|
|
|
|
|
480
|
|
|
if init_len > 0: |
|
481
|
|
|
logger.debug( |
|
482
|
|
|
f"{init_len - len(units)}/{init_len} " |
|
483
|
|
|
f"({((init_len - len(units)) / init_len) * 100: g} %) dropped." |
|
484
|
|
|
) |
|
485
|
|
|
|
|
486
|
|
|
# drop unnecessary and rename columns |
|
487
|
|
|
logger.debug("Reformatting...") |
|
488
|
|
|
units.drop( |
|
489
|
|
|
columns=[ |
|
490
|
|
|
"LokationMastrNummer", |
|
491
|
|
|
"MaStRNummer", |
|
492
|
|
|
"Laengengrad", |
|
493
|
|
|
"Breitengrad", |
|
494
|
|
|
"Spannungsebene", |
|
495
|
|
|
"Land", |
|
496
|
|
|
"temp", |
|
497
|
|
|
], |
|
498
|
|
|
inplace=True, |
|
499
|
|
|
) |
|
500
|
|
|
|
|
501
|
|
|
mapping = cols_mapping["all"].copy() |
|
502
|
|
|
mapping.update(cols_mapping[tech]) |
|
503
|
|
|
mapping.update({"geometry": "geom"}) |
|
504
|
|
|
units.rename(columns=mapping, inplace=True) |
|
505
|
|
|
units["voltage_level"] = units.voltage_level.fillna(-1).astype(int) |
|
506
|
|
|
units["postcode"] = units["postcode"].apply( |
|
507
|
|
|
lambda x: int(float(x)) if not pd.isna(x) else pd.NA |
|
508
|
|
|
) |
|
509
|
|
|
units.set_geometry("geom", inplace=True) |
|
510
|
|
|
units["id"] = range(len(units)) |
|
511
|
|
|
|
|
512
|
|
|
# change capacity unit: kW to MW |
|
513
|
|
|
units["capacity"] = units["capacity"] / 1e3 |
|
514
|
|
|
if "capacity_inverter" in units.columns: |
|
515
|
|
|
units["capacity_inverter"] = units["capacity_inverter"] / 1e3 |
|
516
|
|
|
if "th_capacity" in units.columns: |
|
517
|
|
|
units["th_capacity"] = units["th_capacity"] / 1e3 |
|
518
|
|
|
|
|
519
|
|
|
# assign bus ids |
|
520
|
|
|
logger.debug("Assigning bus ids...") |
|
521
|
|
|
units = units.assign( |
|
522
|
|
|
bus_id=units.loc[~units.geom.x.isna()] |
|
523
|
|
|
.sjoin(mv_grid_districts[["bus_id", "geom"]], how="left") |
|
524
|
|
|
.drop(columns=["index_right"]) |
|
525
|
|
|
.bus_id |
|
526
|
|
|
) |
|
527
|
|
|
units["bus_id"] = units.bus_id.fillna(-1).astype(int) |
|
528
|
|
|
|
|
529
|
|
|
# write to DB |
|
530
|
|
|
logger.info(f"Writing {len(units)} units to DB...") |
|
531
|
|
|
|
|
532
|
|
|
units.to_postgis( |
|
533
|
|
|
name=target_tables[tech].__tablename__, |
|
534
|
|
|
con=engine, |
|
535
|
|
|
if_exists="append", |
|
536
|
|
|
schema=target_tables[tech].__table_args__["schema"], |
|
537
|
|
|
) |
|
538
|
|
|
|
|
539
|
|
|
add_metadata() |
|
540
|
|
|
|