Total Complexity | 48 |
Total Lines | 1223 |
Duplicated Lines | 5.72 % |
Changes | 0 |
Duplicate code is one of the most pungent code smells. A rule that is often used is to re-structure code once it is duplicated in three or more places.
Common duplication problems, and corresponding solutions are:
Complex classes like data.datasets.sanity_checks often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
1 | """ |
||
2 | This module does sanity checks for both the eGon2035 and the eGon100RE scenario |
||
3 | separately where a percentage error is given to showcase difference in output |
||
4 | and input values. Please note that there are missing input technologies in the |
||
5 | supply tables. |
||
6 | Authors: @ALonso, @dana, @nailend, @nesnoj |
||
7 | """ |
||
8 | |||
9 | from sqlalchemy import Numeric |
||
10 | from sqlalchemy.sql import and_, cast, func, or_ |
||
11 | import numpy as np |
||
12 | import pandas as pd |
||
13 | |||
14 | from egon.data import config, db, logger |
||
15 | from egon.data.datasets import Dataset |
||
16 | from egon.data.datasets.electricity_demand_timeseries.cts_buildings import ( |
||
17 | EgonCtsElectricityDemandBuildingShare, |
||
18 | EgonCtsHeatDemandBuildingShare, |
||
19 | ) |
||
20 | from egon.data.datasets.emobility.motorized_individual_travel.db_classes import ( |
||
21 | EgonEvCountMunicipality, |
||
22 | EgonEvCountMvGridDistrict, |
||
23 | EgonEvCountRegistrationDistrict, |
||
24 | EgonEvMvGridDistrict, |
||
25 | EgonEvPool, |
||
26 | EgonEvTrip, |
||
27 | ) |
||
28 | from egon.data.datasets.emobility.motorized_individual_travel.helpers import ( |
||
29 | DATASET_CFG, |
||
30 | read_simbev_metadata_file, |
||
31 | ) |
||
32 | from egon.data.datasets.etrago_setup import ( |
||
33 | EgonPfHvLink, |
||
34 | EgonPfHvLinkTimeseries, |
||
35 | EgonPfHvLoad, |
||
36 | EgonPfHvLoadTimeseries, |
||
37 | EgonPfHvStore, |
||
38 | EgonPfHvStoreTimeseries, |
||
39 | ) |
||
40 | from egon.data.datasets.scenario_parameters import get_sector_parameters |
||
41 | |||
42 | TESTMODE_OFF = ( |
||
43 | config.settings()["egon-data"]["--dataset-boundary"] == "Everything" |
||
44 | ) |
||
45 | |||
46 | |||
47 | class SanityChecks(Dataset): |
||
48 | def __init__(self, dependencies): |
||
49 | super().__init__( |
||
50 | name="SanityChecks", |
||
51 | version="0.0.5", |
||
52 | dependencies=dependencies, |
||
53 | tasks={ |
||
54 | etrago_eGon2035_electricity, |
||
55 | etrago_eGon2035_heat, |
||
56 | residential_electricity_annual_sum, |
||
57 | residential_electricity_hh_refinement, |
||
58 | cts_electricity_demand_share, |
||
59 | cts_heat_demand_share, |
||
60 | sanitycheck_emobility_mit, |
||
61 | }, |
||
62 | ) |
||
63 | |||
64 | |||
65 | def etrago_eGon2035_electricity(): |
||
66 | """Execute basic sanity checks. |
||
67 | |||
68 | Returns print statements as sanity checks for the electricity sector in |
||
69 | the eGon2035 scenario. |
||
70 | |||
71 | Parameters |
||
72 | ---------- |
||
73 | None |
||
74 | |||
75 | Returns |
||
76 | ------- |
||
77 | None |
||
78 | """ |
||
79 | |||
80 | scn = "eGon2035" |
||
81 | |||
82 | # Section to check generator capacities |
||
83 | logger.info(f"Sanity checks for scenario {scn}") |
||
84 | logger.info( |
||
85 | "For German electricity generators the following deviations between " |
||
86 | "the inputs and outputs can be observed:" |
||
87 | ) |
||
88 | |||
89 | carriers_electricity = [ |
||
90 | "other_non_renewable", |
||
91 | "other_renewable", |
||
92 | "reservoir", |
||
93 | "run_of_river", |
||
94 | "oil", |
||
95 | "wind_onshore", |
||
96 | "wind_offshore", |
||
97 | "solar", |
||
98 | "solar_rooftop", |
||
99 | "biomass", |
||
100 | ] |
||
101 | |||
102 | for carrier in carriers_electricity: |
||
103 | |||
104 | if carrier == "biomass": |
||
105 | sum_output = db.select_dataframe( |
||
106 | """SELECT scn_name, SUM(p_nom::numeric) as output_capacity_mw |
||
107 | FROM grid.egon_etrago_generator |
||
108 | WHERE bus IN ( |
||
109 | SELECT bus_id FROM grid.egon_etrago_bus |
||
110 | WHERE scn_name = 'eGon2035' |
||
111 | AND country = 'DE') |
||
112 | AND carrier IN ('biomass', 'industrial_biomass_CHP', |
||
113 | 'central_biomass_CHP') |
||
114 | GROUP BY (scn_name); |
||
115 | """, |
||
116 | warning=False, |
||
117 | ) |
||
118 | |||
119 | else: |
||
120 | sum_output = db.select_dataframe( |
||
121 | f"""SELECT scn_name, |
||
122 | SUM(p_nom::numeric) as output_capacity_mw |
||
123 | FROM grid.egon_etrago_generator |
||
124 | WHERE scn_name = '{scn}' |
||
125 | AND carrier IN ('{carrier}') |
||
126 | AND bus IN |
||
127 | (SELECT bus_id |
||
128 | FROM grid.egon_etrago_bus |
||
129 | WHERE scn_name = 'eGon2035' |
||
130 | AND country = 'DE') |
||
131 | GROUP BY (scn_name); |
||
132 | """, |
||
133 | warning=False, |
||
134 | ) |
||
135 | |||
136 | sum_input = db.select_dataframe( |
||
137 | f"""SELECT carrier, SUM(capacity::numeric) as input_capacity_mw |
||
138 | FROM supply.egon_scenario_capacities |
||
139 | WHERE carrier= '{carrier}' |
||
140 | AND scenario_name ='{scn}' |
||
141 | GROUP BY (carrier); |
||
142 | """, |
||
143 | warning=False, |
||
144 | ) |
||
145 | |||
146 | View Code Duplication | if ( |
|
|
|||
147 | sum_output.output_capacity_mw.sum() == 0 |
||
148 | and sum_input.input_capacity_mw.sum() == 0 |
||
149 | ): |
||
150 | logger.info( |
||
151 | f"No capacity for carrier '{carrier}' needed to be" |
||
152 | f" distributed. Everything is fine" |
||
153 | ) |
||
154 | |||
155 | elif ( |
||
156 | sum_input.input_capacity_mw.sum() > 0 |
||
157 | and sum_output.output_capacity_mw.sum() == 0 |
||
158 | ): |
||
159 | logger.info( |
||
160 | f"Error: Capacity for carrier '{carrier}' was not distributed " |
||
161 | f"at all!" |
||
162 | ) |
||
163 | |||
164 | elif ( |
||
165 | sum_output.output_capacity_mw.sum() > 0 |
||
166 | and sum_input.input_capacity_mw.sum() == 0 |
||
167 | ): |
||
168 | logger.info( |
||
169 | f"Error: Eventhough no input capacity was provided for carrier" |
||
170 | f"'{carrier}' a capacity got distributed!" |
||
171 | ) |
||
172 | |||
173 | else: |
||
174 | sum_input["error"] = ( |
||
175 | (sum_output.output_capacity_mw - sum_input.input_capacity_mw) |
||
176 | / sum_input.input_capacity_mw |
||
177 | ) * 100 |
||
178 | g = sum_input["error"].values[0] |
||
179 | |||
180 | logger.info(f"{carrier}: " + str(round(g, 2)) + " %") |
||
181 | |||
182 | # Section to check storage units |
||
183 | |||
184 | logger.info(f"Sanity checks for scenario {scn}") |
||
185 | logger.info( |
||
186 | "For German electrical storage units the following deviations between" |
||
187 | "the inputs and outputs can be observed:" |
||
188 | ) |
||
189 | |||
190 | carriers_electricity = ["pumped_hydro"] |
||
191 | |||
192 | for carrier in carriers_electricity: |
||
193 | |||
194 | sum_output = db.select_dataframe( |
||
195 | f"""SELECT scn_name, SUM(p_nom::numeric) as output_capacity_mw |
||
196 | FROM grid.egon_etrago_storage |
||
197 | WHERE scn_name = '{scn}' |
||
198 | AND carrier IN ('{carrier}') |
||
199 | AND bus IN |
||
200 | (SELECT bus_id |
||
201 | FROM grid.egon_etrago_bus |
||
202 | WHERE scn_name = 'eGon2035' |
||
203 | AND country = 'DE') |
||
204 | GROUP BY (scn_name); |
||
205 | """, |
||
206 | warning=False, |
||
207 | ) |
||
208 | |||
209 | sum_input = db.select_dataframe( |
||
210 | f"""SELECT carrier, SUM(capacity::numeric) as input_capacity_mw |
||
211 | FROM supply.egon_scenario_capacities |
||
212 | WHERE carrier= '{carrier}' |
||
213 | AND scenario_name ='{scn}' |
||
214 | GROUP BY (carrier); |
||
215 | """, |
||
216 | warning=False, |
||
217 | ) |
||
218 | |||
219 | View Code Duplication | if ( |
|
220 | sum_output.output_capacity_mw.sum() == 0 |
||
221 | and sum_input.input_capacity_mw.sum() == 0 |
||
222 | ): |
||
223 | print( |
||
224 | f"No capacity for carrier '{carrier}' needed to be " |
||
225 | f"distributed. Everything is fine" |
||
226 | ) |
||
227 | |||
228 | elif ( |
||
229 | sum_input.input_capacity_mw.sum() > 0 |
||
230 | and sum_output.output_capacity_mw.sum() == 0 |
||
231 | ): |
||
232 | print( |
||
233 | f"Error: Capacity for carrier '{carrier}' was not distributed" |
||
234 | f" at all!" |
||
235 | ) |
||
236 | |||
237 | elif ( |
||
238 | sum_output.output_capacity_mw.sum() > 0 |
||
239 | and sum_input.input_capacity_mw.sum() == 0 |
||
240 | ): |
||
241 | print( |
||
242 | f"Error: Eventhough no input capacity was provided for carrier" |
||
243 | f" '{carrier}' a capacity got distributed!" |
||
244 | ) |
||
245 | |||
246 | else: |
||
247 | sum_input["error"] = ( |
||
248 | (sum_output.output_capacity_mw - sum_input.input_capacity_mw) |
||
249 | / sum_input.input_capacity_mw |
||
250 | ) * 100 |
||
251 | g = sum_input["error"].values[0] |
||
252 | |||
253 | print(f"{carrier}: " + str(round(g, 2)) + " %") |
||
254 | |||
255 | # Section to check loads |
||
256 | |||
257 | print( |
||
258 | "For German electricity loads the following deviations between the" |
||
259 | " input and output can be observed:" |
||
260 | ) |
||
261 | |||
262 | output_demand = db.select_dataframe( |
||
263 | """SELECT a.scn_name, a.carrier, SUM((SELECT SUM(p) |
||
264 | FROM UNNEST(b.p_set) p))/1000000::numeric as load_twh |
||
265 | FROM grid.egon_etrago_load a |
||
266 | JOIN grid.egon_etrago_load_timeseries b |
||
267 | ON (a.load_id = b.load_id) |
||
268 | JOIN grid.egon_etrago_bus c |
||
269 | ON (a.bus=c.bus_id) |
||
270 | AND b.scn_name = 'eGon2035' |
||
271 | AND a.scn_name = 'eGon2035' |
||
272 | AND a.carrier = 'AC' |
||
273 | AND c.scn_name= 'eGon2035' |
||
274 | AND c.country='DE' |
||
275 | GROUP BY (a.scn_name, a.carrier); |
||
276 | |||
277 | """, |
||
278 | warning=False, |
||
279 | )["load_twh"].values[0] |
||
280 | |||
281 | input_cts_ind = db.select_dataframe( |
||
282 | """SELECT scenario, |
||
283 | SUM(demand::numeric/1000000) as demand_mw_regio_cts_ind |
||
284 | FROM demand.egon_demandregio_cts_ind |
||
285 | WHERE scenario= 'eGon2035' |
||
286 | AND year IN ('2035') |
||
287 | GROUP BY (scenario); |
||
288 | |||
289 | """, |
||
290 | warning=False, |
||
291 | )["demand_mw_regio_cts_ind"].values[0] |
||
292 | |||
293 | input_hh = db.select_dataframe( |
||
294 | """SELECT scenario, SUM(demand::numeric/1000000) as demand_mw_regio_hh |
||
295 | FROM demand.egon_demandregio_hh |
||
296 | WHERE scenario= 'eGon2035' |
||
297 | AND year IN ('2035') |
||
298 | GROUP BY (scenario); |
||
299 | """, |
||
300 | warning=False, |
||
301 | )["demand_mw_regio_hh"].values[0] |
||
302 | |||
303 | input_demand = input_hh + input_cts_ind |
||
304 | |||
305 | e = round((output_demand - input_demand) / input_demand, 2) * 100 |
||
306 | |||
307 | print(f"electricity demand: {e} %") |
||
308 | |||
309 | |||
310 | def etrago_eGon2035_heat(): |
||
311 | """Execute basic sanity checks. |
||
312 | |||
313 | Returns print statements as sanity checks for the heat sector in |
||
314 | the eGon2035 scenario. |
||
315 | |||
316 | Parameters |
||
317 | ---------- |
||
318 | None |
||
319 | |||
320 | Returns |
||
321 | ------- |
||
322 | None |
||
323 | """ |
||
324 | |||
325 | # Check input and output values for the carriers "other_non_renewable", |
||
326 | # "other_renewable", "reservoir", "run_of_river" and "oil" |
||
327 | |||
328 | scn = "eGon2035" |
||
329 | |||
330 | # Section to check generator capacities |
||
331 | print(f"Sanity checks for scenario {scn}") |
||
332 | print( |
||
333 | "For German heat demands the following deviations between the inputs" |
||
334 | " and outputs can be observed:" |
||
335 | ) |
||
336 | |||
337 | # Sanity checks for heat demand |
||
338 | |||
339 | output_heat_demand = db.select_dataframe( |
||
340 | """SELECT a.scn_name, |
||
341 | (SUM( |
||
342 | (SELECT SUM(p) FROM UNNEST(b.p_set) p))/1000000)::numeric as load_twh |
||
343 | FROM grid.egon_etrago_load a |
||
344 | JOIN grid.egon_etrago_load_timeseries b |
||
345 | ON (a.load_id = b.load_id) |
||
346 | JOIN grid.egon_etrago_bus c |
||
347 | ON (a.bus=c.bus_id) |
||
348 | AND b.scn_name = 'eGon2035' |
||
349 | AND a.scn_name = 'eGon2035' |
||
350 | AND c.scn_name= 'eGon2035' |
||
351 | AND c.country='DE' |
||
352 | AND a.carrier IN ('rural_heat', 'central_heat') |
||
353 | GROUP BY (a.scn_name); |
||
354 | """, |
||
355 | warning=False, |
||
356 | )["load_twh"].values[0] |
||
357 | |||
358 | input_heat_demand = db.select_dataframe( |
||
359 | """SELECT scenario, SUM(demand::numeric/1000000) as demand_mw_peta_heat |
||
360 | FROM demand.egon_peta_heat |
||
361 | WHERE scenario= 'eGon2035' |
||
362 | GROUP BY (scenario); |
||
363 | """, |
||
364 | warning=False, |
||
365 | )["demand_mw_peta_heat"].values[0] |
||
366 | |||
367 | e_demand = ( |
||
368 | round((output_heat_demand - input_heat_demand) / input_heat_demand, 2) |
||
369 | * 100 |
||
370 | ) |
||
371 | |||
372 | logger.info(f"heat demand: {e_demand} %") |
||
373 | |||
374 | # Sanity checks for heat supply |
||
375 | |||
376 | logger.info( |
||
377 | "For German heat supplies the following deviations between the inputs " |
||
378 | "and outputs can be observed:" |
||
379 | ) |
||
380 | |||
381 | # Comparison for central heat pumps |
||
382 | heat_pump_input = db.select_dataframe( |
||
383 | """SELECT carrier, SUM(capacity::numeric) as Urban_central_heat_pump_mw |
||
384 | FROM supply.egon_scenario_capacities |
||
385 | WHERE carrier= 'urban_central_heat_pump' |
||
386 | AND scenario_name IN ('eGon2035') |
||
387 | GROUP BY (carrier); |
||
388 | """, |
||
389 | warning=False, |
||
390 | )["urban_central_heat_pump_mw"].values[0] |
||
391 | |||
392 | heat_pump_output = db.select_dataframe( |
||
393 | """SELECT carrier, SUM(p_nom::numeric) as Central_heat_pump_mw |
||
394 | FROM grid.egon_etrago_link |
||
395 | WHERE carrier= 'central_heat_pump' |
||
396 | AND scn_name IN ('eGon2035') |
||
397 | GROUP BY (carrier); |
||
398 | """, |
||
399 | warning=False, |
||
400 | )["central_heat_pump_mw"].values[0] |
||
401 | |||
402 | e_heat_pump = ( |
||
403 | round((heat_pump_output - heat_pump_input) / heat_pump_output, 2) * 100 |
||
404 | ) |
||
405 | |||
406 | logger.info(f"'central_heat_pump': {e_heat_pump} % ") |
||
407 | |||
408 | # Comparison for residential heat pumps |
||
409 | |||
410 | input_residential_heat_pump = db.select_dataframe( |
||
411 | """SELECT carrier, SUM(capacity::numeric) as residential_heat_pump_mw |
||
412 | FROM supply.egon_scenario_capacities |
||
413 | WHERE carrier= 'residential_rural_heat_pump' |
||
414 | AND scenario_name IN ('eGon2035') |
||
415 | GROUP BY (carrier); |
||
416 | """, |
||
417 | warning=False, |
||
418 | )["residential_heat_pump_mw"].values[0] |
||
419 | |||
420 | output_residential_heat_pump = db.select_dataframe( |
||
421 | """SELECT carrier, SUM(p_nom::numeric) as rural_heat_pump_mw |
||
422 | FROM grid.egon_etrago_link |
||
423 | WHERE carrier= 'rural_heat_pump' |
||
424 | AND scn_name IN ('eGon2035') |
||
425 | GROUP BY (carrier); |
||
426 | """, |
||
427 | warning=False, |
||
428 | )["rural_heat_pump_mw"].values[0] |
||
429 | |||
430 | e_residential_heat_pump = ( |
||
431 | round( |
||
432 | (output_residential_heat_pump - input_residential_heat_pump) |
||
433 | / input_residential_heat_pump, |
||
434 | 2, |
||
435 | ) |
||
436 | * 100 |
||
437 | ) |
||
438 | logger.info(f"'residential heat pumps': {e_residential_heat_pump} %") |
||
439 | |||
440 | # Comparison for resistive heater |
||
441 | resistive_heater_input = db.select_dataframe( |
||
442 | """SELECT carrier, |
||
443 | SUM(capacity::numeric) as Urban_central_resistive_heater_MW |
||
444 | FROM supply.egon_scenario_capacities |
||
445 | WHERE carrier= 'urban_central_resistive_heater' |
||
446 | AND scenario_name IN ('eGon2035') |
||
447 | GROUP BY (carrier); |
||
448 | """, |
||
449 | warning=False, |
||
450 | )["urban_central_resistive_heater_mw"].values[0] |
||
451 | |||
452 | resistive_heater_output = db.select_dataframe( |
||
453 | """SELECT carrier, SUM(p_nom::numeric) as central_resistive_heater_MW |
||
454 | FROM grid.egon_etrago_link |
||
455 | WHERE carrier= 'central_resistive_heater' |
||
456 | AND scn_name IN ('eGon2035') |
||
457 | GROUP BY (carrier); |
||
458 | """, |
||
459 | warning=False, |
||
460 | )["central_resistive_heater_mw"].values[0] |
||
461 | |||
462 | e_resistive_heater = ( |
||
463 | round( |
||
464 | (resistive_heater_output - resistive_heater_input) |
||
465 | / resistive_heater_input, |
||
466 | 2, |
||
467 | ) |
||
468 | * 100 |
||
469 | ) |
||
470 | |||
471 | logger.info(f"'resistive heater': {e_resistive_heater} %") |
||
472 | |||
473 | # Comparison for solar thermal collectors |
||
474 | |||
475 | input_solar_thermal = db.select_dataframe( |
||
476 | """SELECT carrier, SUM(capacity::numeric) as solar_thermal_collector_mw |
||
477 | FROM supply.egon_scenario_capacities |
||
478 | WHERE carrier= 'urban_central_solar_thermal_collector' |
||
479 | AND scenario_name IN ('eGon2035') |
||
480 | GROUP BY (carrier); |
||
481 | """, |
||
482 | warning=False, |
||
483 | )["solar_thermal_collector_mw"].values[0] |
||
484 | |||
485 | output_solar_thermal = db.select_dataframe( |
||
486 | """SELECT carrier, SUM(p_nom::numeric) as solar_thermal_collector_mw |
||
487 | FROM grid.egon_etrago_generator |
||
488 | WHERE carrier= 'solar_thermal_collector' |
||
489 | AND scn_name IN ('eGon2035') |
||
490 | GROUP BY (carrier); |
||
491 | """, |
||
492 | warning=False, |
||
493 | )["solar_thermal_collector_mw"].values[0] |
||
494 | |||
495 | e_solar_thermal = ( |
||
496 | round( |
||
497 | (output_solar_thermal - input_solar_thermal) / input_solar_thermal, |
||
498 | 2, |
||
499 | ) |
||
500 | * 100 |
||
501 | ) |
||
502 | logger.info(f"'solar thermal collector': {e_solar_thermal} %") |
||
503 | |||
504 | # Comparison for geothermal |
||
505 | |||
506 | input_geo_thermal = db.select_dataframe( |
||
507 | """SELECT carrier, |
||
508 | SUM(capacity::numeric) as Urban_central_geo_thermal_MW |
||
509 | FROM supply.egon_scenario_capacities |
||
510 | WHERE carrier= 'urban_central_geo_thermal' |
||
511 | AND scenario_name IN ('eGon2035') |
||
512 | GROUP BY (carrier); |
||
513 | """, |
||
514 | warning=False, |
||
515 | )["urban_central_geo_thermal_mw"].values[0] |
||
516 | |||
517 | output_geo_thermal = db.select_dataframe( |
||
518 | """SELECT carrier, SUM(p_nom::numeric) as geo_thermal_MW |
||
519 | FROM grid.egon_etrago_generator |
||
520 | WHERE carrier= 'geo_thermal' |
||
521 | AND scn_name IN ('eGon2035') |
||
522 | GROUP BY (carrier); |
||
523 | """, |
||
524 | warning=False, |
||
525 | )["geo_thermal_mw"].values[0] |
||
526 | |||
527 | e_geo_thermal = ( |
||
528 | round((output_geo_thermal - input_geo_thermal) / input_geo_thermal, 2) |
||
529 | * 100 |
||
530 | ) |
||
531 | logger.info(f"'geothermal': {e_geo_thermal} %") |
||
532 | |||
533 | |||
534 | def residential_electricity_annual_sum(rtol=1e-5): |
||
535 | """Sanity check for dataset electricity_demand_timeseries : |
||
536 | Demand_Building_Assignment |
||
537 | |||
538 | Aggregate the annual demand of all census cells at NUTS3 to compare |
||
539 | with initial scaling parameters from DemandRegio. |
||
540 | """ |
||
541 | |||
542 | df_nuts3_annual_sum = db.select_dataframe( |
||
543 | sql=""" |
||
544 | SELECT dr.nuts3, dr.scenario, dr.demand_regio_sum, profiles.profile_sum |
||
545 | FROM ( |
||
546 | SELECT scenario, SUM(demand) AS profile_sum, vg250_nuts3 |
||
547 | FROM demand.egon_demandregio_zensus_electricity AS egon, |
||
548 | boundaries.egon_map_zensus_vg250 AS boundaries |
||
549 | Where egon.zensus_population_id = boundaries.zensus_population_id |
||
550 | AND sector = 'residential' |
||
551 | GROUP BY vg250_nuts3, scenario |
||
552 | ) AS profiles |
||
553 | JOIN ( |
||
554 | SELECT nuts3, scenario, sum(demand) AS demand_regio_sum |
||
555 | FROM demand.egon_demandregio_hh |
||
556 | GROUP BY year, scenario, nuts3 |
||
557 | ) AS dr |
||
558 | ON profiles.vg250_nuts3 = dr.nuts3 and profiles.scenario = dr.scenario |
||
559 | """ |
||
560 | ) |
||
561 | |||
562 | np.testing.assert_allclose( |
||
563 | actual=df_nuts3_annual_sum["profile_sum"], |
||
564 | desired=df_nuts3_annual_sum["demand_regio_sum"], |
||
565 | rtol=rtol, |
||
566 | verbose=False, |
||
567 | ) |
||
568 | |||
569 | logger.info( |
||
570 | "Aggregated annual residential electricity demand" |
||
571 | " matches with DemandRegio at NUTS-3." |
||
572 | ) |
||
573 | |||
574 | |||
575 | def residential_electricity_hh_refinement(rtol=1e-5): |
||
576 | """Sanity check for dataset electricity_demand_timeseries : |
||
577 | Household Demands |
||
578 | |||
579 | Check sum of aggregated household types after refinement method |
||
580 | was applied and compare it to the original census values.""" |
||
581 | |||
582 | df_refinement = db.select_dataframe( |
||
583 | sql=""" |
||
584 | SELECT refined.nuts3, refined.characteristics_code, |
||
585 | refined.sum_refined::int, census.sum_census::int |
||
586 | FROM( |
||
587 | SELECT nuts3, characteristics_code, SUM(hh_10types) as sum_refined |
||
588 | FROM society.egon_destatis_zensus_household_per_ha_refined |
||
589 | GROUP BY nuts3, characteristics_code) |
||
590 | AS refined |
||
591 | JOIN( |
||
592 | SELECT t.nuts3, t.characteristics_code, sum(orig) as sum_census |
||
593 | FROM( |
||
594 | SELECT nuts3, cell_id, characteristics_code, |
||
595 | sum(DISTINCT(hh_5types))as orig |
||
596 | FROM society.egon_destatis_zensus_household_per_ha_refined |
||
597 | GROUP BY cell_id, characteristics_code, nuts3) AS t |
||
598 | GROUP BY t.nuts3, t.characteristics_code ) AS census |
||
599 | ON refined.nuts3 = census.nuts3 |
||
600 | AND refined.characteristics_code = census.characteristics_code |
||
601 | """ |
||
602 | ) |
||
603 | |||
604 | np.testing.assert_allclose( |
||
605 | actual=df_refinement["sum_refined"], |
||
606 | desired=df_refinement["sum_census"], |
||
607 | rtol=rtol, |
||
608 | verbose=False, |
||
609 | ) |
||
610 | |||
611 | logger.info("All Aggregated household types match at NUTS-3.") |
||
612 | |||
613 | |||
614 | def cts_electricity_demand_share(rtol=1e-5): |
||
615 | """Sanity check for dataset electricity_demand_timeseries : |
||
616 | CtsBuildings |
||
617 | |||
618 | Check sum of aggregated cts electricity demand share which equals to one |
||
619 | for every substation as the substation profile is linearly disaggregated |
||
620 | to all buildings.""" |
||
621 | |||
622 | with db.session_scope() as session: |
||
623 | cells_query = session.query(EgonCtsElectricityDemandBuildingShare) |
||
624 | |||
625 | df_demand_share = pd.read_sql( |
||
626 | cells_query.statement, cells_query.session.bind, index_col=None |
||
627 | ) |
||
628 | |||
629 | np.testing.assert_allclose( |
||
630 | actual=df_demand_share.groupby(["bus_id", "scenario"])[ |
||
631 | "profile_share" |
||
632 | ].sum(), |
||
633 | desired=1, |
||
634 | rtol=rtol, |
||
635 | verbose=False, |
||
636 | ) |
||
637 | |||
638 | logger.info("The aggregated demand shares equal to one!.") |
||
639 | |||
640 | |||
641 | def cts_heat_demand_share(rtol=1e-5): |
||
642 | """Sanity check for dataset electricity_demand_timeseries |
||
643 | : CtsBuildings |
||
644 | |||
645 | Check sum of aggregated cts heat demand share which equals to one |
||
646 | for every substation as the substation profile is linearly disaggregated |
||
647 | to all buildings.""" |
||
648 | |||
649 | with db.session_scope() as session: |
||
650 | cells_query = session.query(EgonCtsHeatDemandBuildingShare) |
||
651 | |||
652 | df_demand_share = pd.read_sql( |
||
653 | cells_query.statement, cells_query.session.bind, index_col=None |
||
654 | ) |
||
655 | |||
656 | np.testing.assert_allclose( |
||
657 | actual=df_demand_share.groupby(["bus_id", "scenario"])[ |
||
658 | "profile_share" |
||
659 | ].sum(), |
||
660 | desired=1, |
||
661 | rtol=rtol, |
||
662 | verbose=False, |
||
663 | ) |
||
664 | |||
665 | logger.info("The aggregated demand shares equal to one!.") |
||
666 | |||
667 | |||
668 | def sanitycheck_emobility_mit(): |
||
669 | """Execute sanity checks for eMobility: motorized individual travel |
||
670 | |||
671 | Checks data integrity for eGon2035, eGon2035_lowflex and eGon100RE scenario |
||
672 | using assertions: |
||
673 | 1. Allocated EV numbers and EVs allocated to grid districts |
||
674 | 2. Trip data (original inout data from simBEV) |
||
675 | 3. Model data in eTraGo PF tables (grid.egon_etrago_*) |
||
676 | |||
677 | Parameters |
||
678 | ---------- |
||
679 | None |
||
680 | |||
681 | Returns |
||
682 | ------- |
||
683 | None |
||
684 | """ |
||
685 | |||
686 | def check_ev_allocation(): |
||
687 | # Get target number for scenario |
||
688 | ev_count_target = scenario_variation_parameters["ev_count"] |
||
689 | print(f" Target count: {str(ev_count_target)}") |
||
690 | |||
691 | # Get allocated numbers |
||
692 | ev_counts_dict = {} |
||
693 | with db.session_scope() as session: |
||
694 | for table, level in zip( |
||
695 | [ |
||
696 | EgonEvCountMvGridDistrict, |
||
697 | EgonEvCountMunicipality, |
||
698 | EgonEvCountRegistrationDistrict, |
||
699 | ], |
||
700 | ["Grid District", "Municipality", "Registration District"], |
||
701 | ): |
||
702 | query = session.query( |
||
703 | func.sum( |
||
704 | table.bev_mini |
||
705 | + table.bev_medium |
||
706 | + table.bev_luxury |
||
707 | + table.phev_mini |
||
708 | + table.phev_medium |
||
709 | + table.phev_luxury |
||
710 | ).label("ev_count") |
||
711 | ).filter( |
||
712 | table.scenario == scenario_name, |
||
713 | table.scenario_variation == scenario_var_name, |
||
714 | ) |
||
715 | |||
716 | ev_counts = pd.read_sql( |
||
717 | query.statement, query.session.bind, index_col=None |
||
718 | ) |
||
719 | ev_counts_dict[level] = ev_counts.iloc[0].ev_count |
||
720 | print( |
||
721 | f" Count table: Total count for level {level} " |
||
722 | f"(table: {table.__table__}): " |
||
723 | f"{str(ev_counts_dict[level])}" |
||
724 | ) |
||
725 | |||
726 | # Compare with scenario target (only if not in testmode) |
||
727 | if TESTMODE_OFF: |
||
728 | for level, count in ev_counts_dict.items(): |
||
729 | np.testing.assert_allclose( |
||
730 | count, |
||
731 | ev_count_target, |
||
732 | rtol=0.0001, |
||
733 | err_msg=f"EV numbers in {level} seems to be flawed.", |
||
734 | ) |
||
735 | else: |
||
736 | print(" Testmode is on, skipping sanity check...") |
||
737 | |||
738 | # Get allocated EVs in grid districts |
||
739 | with db.session_scope() as session: |
||
740 | query = session.query( |
||
741 | func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
||
742 | "ev_count" |
||
743 | ), |
||
744 | ).filter( |
||
745 | EgonEvMvGridDistrict.scenario == scenario_name, |
||
746 | EgonEvMvGridDistrict.scenario_variation == scenario_var_name, |
||
747 | ) |
||
748 | ev_count_alloc = ( |
||
749 | pd.read_sql(query.statement, query.session.bind, index_col=None) |
||
750 | .iloc[0] |
||
751 | .ev_count |
||
752 | ) |
||
753 | print( |
||
754 | f" EVs allocated to Grid Districts " |
||
755 | f"(table: {EgonEvMvGridDistrict.__table__}) total count: " |
||
756 | f"{str(ev_count_alloc)}" |
||
757 | ) |
||
758 | |||
759 | # Compare with scenario target (only if not in testmode) |
||
760 | if TESTMODE_OFF: |
||
761 | np.testing.assert_allclose( |
||
762 | ev_count_alloc, |
||
763 | ev_count_target, |
||
764 | rtol=0.0001, |
||
765 | err_msg=( |
||
766 | "EV numbers allocated to Grid Districts seems to be " |
||
767 | "flawed." |
||
768 | ), |
||
769 | ) |
||
770 | else: |
||
771 | print(" Testmode is on, skipping sanity check...") |
||
772 | |||
773 | return ev_count_alloc |
||
774 | |||
775 | def check_trip_data(): |
||
776 | # Check if trips start at timestep 0 and have a max. of 35040 steps |
||
777 | # (8760h in 15min steps) |
||
778 | print(" Checking timeranges...") |
||
779 | with db.session_scope() as session: |
||
780 | query = session.query( |
||
781 | func.count(EgonEvTrip.event_id).label("cnt") |
||
782 | ).filter( |
||
783 | or_( |
||
784 | and_( |
||
785 | EgonEvTrip.park_start > 0, |
||
786 | EgonEvTrip.simbev_event_id == 0, |
||
787 | ), |
||
788 | EgonEvTrip.park_end |
||
789 | > (60 / int(meta_run_config.stepsize)) * 8760, |
||
790 | ), |
||
791 | EgonEvTrip.scenario == scenario_name, |
||
792 | ) |
||
793 | invalid_trips = pd.read_sql( |
||
794 | query.statement, query.session.bind, index_col=None |
||
795 | ) |
||
796 | np.testing.assert_equal( |
||
797 | invalid_trips.iloc[0].cnt, |
||
798 | 0, |
||
799 | err_msg=( |
||
800 | f"{str(invalid_trips.iloc[0].cnt)} trips in table " |
||
801 | f"{EgonEvTrip.__table__} have invalid timesteps." |
||
802 | ), |
||
803 | ) |
||
804 | |||
805 | # Check if charging demand can be covered by available charging energy |
||
806 | # while parking |
||
807 | print(" Compare charging demand with available power...") |
||
808 | with db.session_scope() as session: |
||
809 | query = session.query( |
||
810 | func.count(EgonEvTrip.event_id).label("cnt") |
||
811 | ).filter( |
||
812 | func.round( |
||
813 | cast( |
||
814 | (EgonEvTrip.park_end - EgonEvTrip.park_start + 1) |
||
815 | * EgonEvTrip.charging_capacity_nominal |
||
816 | * (int(meta_run_config.stepsize) / 60), |
||
817 | Numeric, |
||
818 | ), |
||
819 | 3, |
||
820 | ) |
||
821 | < cast(EgonEvTrip.charging_demand, Numeric), |
||
822 | EgonEvTrip.scenario == scenario_name, |
||
823 | ) |
||
824 | invalid_trips = pd.read_sql( |
||
825 | query.statement, query.session.bind, index_col=None |
||
826 | ) |
||
827 | np.testing.assert_equal( |
||
828 | invalid_trips.iloc[0].cnt, |
||
829 | 0, |
||
830 | err_msg=( |
||
831 | f"In {str(invalid_trips.iloc[0].cnt)} trips (table: " |
||
832 | f"{EgonEvTrip.__table__}) the charging demand cannot be " |
||
833 | f"covered by available charging power." |
||
834 | ), |
||
835 | ) |
||
836 | |||
837 | def check_model_data(): |
||
838 | # Check if model components were fully created |
||
839 | print(" Check if all model components were created...") |
||
840 | # Get MVGDs which got EV allocated |
||
841 | with db.session_scope() as session: |
||
842 | query = ( |
||
843 | session.query( |
||
844 | EgonEvMvGridDistrict.bus_id, |
||
845 | ) |
||
846 | .filter( |
||
847 | EgonEvMvGridDistrict.scenario == scenario_name, |
||
848 | EgonEvMvGridDistrict.scenario_variation |
||
849 | == scenario_var_name, |
||
850 | ) |
||
851 | .group_by(EgonEvMvGridDistrict.bus_id) |
||
852 | ) |
||
853 | mvgds_with_ev = ( |
||
854 | pd.read_sql(query.statement, query.session.bind, index_col=None) |
||
855 | .bus_id.sort_values() |
||
856 | .to_list() |
||
857 | ) |
||
858 | |||
859 | # Load model components |
||
860 | with db.session_scope() as session: |
||
861 | query = ( |
||
862 | session.query( |
||
863 | EgonPfHvLink.bus0.label("mvgd_bus_id"), |
||
864 | EgonPfHvLoad.bus.label("emob_bus_id"), |
||
865 | EgonPfHvLoad.load_id.label("load_id"), |
||
866 | EgonPfHvStore.store_id.label("store_id"), |
||
867 | ) |
||
868 | .select_from(EgonPfHvLoad, EgonPfHvStore) |
||
869 | .join( |
||
870 | EgonPfHvLoadTimeseries, |
||
871 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
||
872 | ) |
||
873 | .join( |
||
874 | EgonPfHvStoreTimeseries, |
||
875 | EgonPfHvStoreTimeseries.store_id == EgonPfHvStore.store_id, |
||
876 | ) |
||
877 | .filter( |
||
878 | EgonPfHvLoad.carrier == "land transport EV", |
||
879 | EgonPfHvLoad.scn_name == scenario_name, |
||
880 | EgonPfHvLoadTimeseries.scn_name == scenario_name, |
||
881 | EgonPfHvStore.carrier == "battery storage", |
||
882 | EgonPfHvStore.scn_name == scenario_name, |
||
883 | EgonPfHvStoreTimeseries.scn_name == scenario_name, |
||
884 | EgonPfHvLink.scn_name == scenario_name, |
||
885 | EgonPfHvLink.bus1 == EgonPfHvLoad.bus, |
||
886 | EgonPfHvLink.bus1 == EgonPfHvStore.bus, |
||
887 | ) |
||
888 | ) |
||
889 | model_components = pd.read_sql( |
||
890 | query.statement, query.session.bind, index_col=None |
||
891 | ) |
||
892 | |||
893 | # Check number of buses with model components connected |
||
894 | mvgd_buses_with_ev = model_components.loc[ |
||
895 | model_components.mvgd_bus_id.isin(mvgds_with_ev) |
||
896 | ] |
||
897 | np.testing.assert_equal( |
||
898 | len(mvgds_with_ev), |
||
899 | len(mvgd_buses_with_ev), |
||
900 | err_msg=( |
||
901 | f"Number of Grid Districts with connected model components " |
||
902 | f"({str(len(mvgd_buses_with_ev))} in tables egon_etrago_*) " |
||
903 | f"differ from number of Grid Districts that got EVs " |
||
904 | f"allocated ({len(mvgds_with_ev)} in table " |
||
905 | f"{EgonEvMvGridDistrict.__table__})." |
||
906 | ), |
||
907 | ) |
||
908 | |||
909 | # Check if all required components exist (if no id is NaN) |
||
910 | np.testing.assert_equal( |
||
911 | model_components.drop_duplicates().isna().any().any(), |
||
912 | False, |
||
913 | err_msg=( |
||
914 | f"Some components are missing (see True values): " |
||
915 | f"{model_components.drop_duplicates().isna().any()}" |
||
916 | ), |
||
917 | ) |
||
918 | |||
919 | # Get all model timeseries |
||
920 | print(" Loading model timeseries...") |
||
921 | # Get all model timeseries |
||
922 | model_ts_dict = { |
||
923 | "Load": { |
||
924 | "carrier": "land transport EV", |
||
925 | "table": EgonPfHvLoad, |
||
926 | "table_ts": EgonPfHvLoadTimeseries, |
||
927 | "column_id": "load_id", |
||
928 | "columns_ts": ["p_set"], |
||
929 | "ts": None, |
||
930 | }, |
||
931 | "Link": { |
||
932 | "carrier": "BEV charger", |
||
933 | "table": EgonPfHvLink, |
||
934 | "table_ts": EgonPfHvLinkTimeseries, |
||
935 | "column_id": "link_id", |
||
936 | "columns_ts": ["p_max_pu"], |
||
937 | "ts": None, |
||
938 | }, |
||
939 | "Store": { |
||
940 | "carrier": "battery storage", |
||
941 | "table": EgonPfHvStore, |
||
942 | "table_ts": EgonPfHvStoreTimeseries, |
||
943 | "column_id": "store_id", |
||
944 | "columns_ts": ["e_min_pu", "e_max_pu"], |
||
945 | "ts": None, |
||
946 | }, |
||
947 | } |
||
948 | |||
949 | with db.session_scope() as session: |
||
950 | for node, attrs in model_ts_dict.items(): |
||
951 | print(f" Loading {node} timeseries...") |
||
952 | subquery = ( |
||
953 | session.query(getattr(attrs["table"], attrs["column_id"])) |
||
954 | .filter(attrs["table"].carrier == attrs["carrier"]) |
||
955 | .filter(attrs["table"].scn_name == scenario_name) |
||
956 | .subquery() |
||
957 | ) |
||
958 | |||
959 | cols = [ |
||
960 | getattr(attrs["table_ts"], c) for c in attrs["columns_ts"] |
||
961 | ] |
||
962 | query = session.query( |
||
963 | getattr(attrs["table_ts"], attrs["column_id"]), *cols |
||
964 | ).filter( |
||
965 | getattr(attrs["table_ts"], attrs["column_id"]).in_( |
||
966 | subquery |
||
967 | ), |
||
968 | attrs["table_ts"].scn_name == scenario_name, |
||
969 | ) |
||
970 | attrs["ts"] = pd.read_sql( |
||
971 | query.statement, |
||
972 | query.session.bind, |
||
973 | index_col=attrs["column_id"], |
||
974 | ) |
||
975 | |||
976 | # Check if all timeseries have 8760 steps |
||
977 | print(" Checking timeranges...") |
||
978 | for node, attrs in model_ts_dict.items(): |
||
979 | for col in attrs["columns_ts"]: |
||
980 | ts = attrs["ts"] |
||
981 | invalid_ts = ts.loc[ts[col].apply(lambda _: len(_)) != 8760][ |
||
982 | col |
||
983 | ].apply(len) |
||
984 | np.testing.assert_equal( |
||
985 | len(invalid_ts), |
||
986 | 0, |
||
987 | err_msg=( |
||
988 | f"{str(len(invalid_ts))} rows in timeseries do not " |
||
989 | f"have 8760 timesteps. Table: " |
||
990 | f"{attrs['table_ts'].__table__}, Column: {col}, IDs: " |
||
991 | f"{str(list(invalid_ts.index))}" |
||
992 | ), |
||
993 | ) |
||
994 | |||
995 | # Compare total energy demand in model with some approximate values |
||
996 | # (per EV: 14,000 km/a, 0.17 kWh/km) |
||
997 | print(" Checking energy demand in model...") |
||
998 | total_energy_model = ( |
||
999 | model_ts_dict["Load"]["ts"].p_set.apply(lambda _: sum(_)).sum() |
||
1000 | / 1e6 |
||
1001 | ) |
||
1002 | print(f" Total energy amount in model: {total_energy_model} TWh") |
||
1003 | total_energy_scenario_approx = ev_count_alloc * 14000 * 0.17 / 1e9 |
||
1004 | print( |
||
1005 | f" Total approximated energy amount in scenario: " |
||
1006 | f"{total_energy_scenario_approx} TWh" |
||
1007 | ) |
||
1008 | np.testing.assert_allclose( |
||
1009 | total_energy_model, |
||
1010 | total_energy_scenario_approx, |
||
1011 | rtol=0.1, |
||
1012 | err_msg=( |
||
1013 | "The total energy amount in the model deviates heavily " |
||
1014 | "from the approximated value for current scenario." |
||
1015 | ), |
||
1016 | ) |
||
1017 | |||
1018 | # Compare total storage capacity |
||
1019 | print(" Checking storage capacity...") |
||
1020 | # Load storage capacities from model |
||
1021 | with db.session_scope() as session: |
||
1022 | query = session.query( |
||
1023 | func.sum(EgonPfHvStore.e_nom).label("e_nom") |
||
1024 | ).filter( |
||
1025 | EgonPfHvStore.scn_name == scenario_name, |
||
1026 | EgonPfHvStore.carrier == "battery storage", |
||
1027 | ) |
||
1028 | storage_capacity_model = ( |
||
1029 | pd.read_sql( |
||
1030 | query.statement, query.session.bind, index_col=None |
||
1031 | ).e_nom.sum() |
||
1032 | / 1e3 |
||
1033 | ) |
||
1034 | print( |
||
1035 | f" Total storage capacity ({EgonPfHvStore.__table__}): " |
||
1036 | f"{round(storage_capacity_model, 1)} GWh" |
||
1037 | ) |
||
1038 | |||
1039 | # Load occurences of each EV |
||
1040 | with db.session_scope() as session: |
||
1041 | query = ( |
||
1042 | session.query( |
||
1043 | EgonEvMvGridDistrict.bus_id, |
||
1044 | EgonEvPool.type, |
||
1045 | func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
||
1046 | "count" |
||
1047 | ), |
||
1048 | ) |
||
1049 | .join( |
||
1050 | EgonEvPool, |
||
1051 | EgonEvPool.ev_id |
||
1052 | == EgonEvMvGridDistrict.egon_ev_pool_ev_id, |
||
1053 | ) |
||
1054 | .filter( |
||
1055 | EgonEvMvGridDistrict.scenario == scenario_name, |
||
1056 | EgonEvMvGridDistrict.scenario_variation |
||
1057 | == scenario_var_name, |
||
1058 | EgonEvPool.scenario == scenario_name, |
||
1059 | ) |
||
1060 | .group_by(EgonEvMvGridDistrict.bus_id, EgonEvPool.type) |
||
1061 | ) |
||
1062 | count_per_ev_all = pd.read_sql( |
||
1063 | query.statement, query.session.bind, index_col="bus_id" |
||
1064 | ) |
||
1065 | count_per_ev_all["bat_cap"] = count_per_ev_all.type.map( |
||
1066 | meta_tech_data.battery_capacity |
||
1067 | ) |
||
1068 | count_per_ev_all["bat_cap_total_MWh"] = ( |
||
1069 | count_per_ev_all["count"] * count_per_ev_all.bat_cap / 1e3 |
||
1070 | ) |
||
1071 | storage_capacity_simbev = count_per_ev_all.bat_cap_total_MWh.div( |
||
1072 | 1e3 |
||
1073 | ).sum() |
||
1074 | print( |
||
1075 | f" Total storage capacity (simBEV): " |
||
1076 | f"{round(storage_capacity_simbev, 1)} GWh" |
||
1077 | ) |
||
1078 | |||
1079 | np.testing.assert_allclose( |
||
1080 | storage_capacity_model, |
||
1081 | storage_capacity_simbev, |
||
1082 | rtol=0.01, |
||
1083 | err_msg=( |
||
1084 | "The total storage capacity in the model deviates heavily " |
||
1085 | "from the input data provided by simBEV for current scenario." |
||
1086 | ), |
||
1087 | ) |
||
1088 | |||
1089 | # Check SoC storage constraint: e_min_pu < e_max_pu for all timesteps |
||
1090 | print(" Validating SoC constraints...") |
||
1091 | stores_with_invalid_soc = [] |
||
1092 | for idx, row in model_ts_dict["Store"]["ts"].iterrows(): |
||
1093 | ts = row[["e_min_pu", "e_max_pu"]] |
||
1094 | x = np.array(ts.e_min_pu) > np.array(ts.e_max_pu) |
||
1095 | if x.any(): |
||
1096 | stores_with_invalid_soc.append(idx) |
||
1097 | |||
1098 | np.testing.assert_equal( |
||
1099 | len(stores_with_invalid_soc), |
||
1100 | 0, |
||
1101 | err_msg=( |
||
1102 | f"The store constraint e_min_pu < e_max_pu does not apply " |
||
1103 | f"for some storages in {EgonPfHvStoreTimeseries.__table__}. " |
||
1104 | f"Invalid store_ids: {stores_with_invalid_soc}" |
||
1105 | ), |
||
1106 | ) |
||
1107 | |||
1108 | def check_model_data_lowflex_eGon2035(): |
||
1109 | # TODO: Add eGon100RE_lowflex |
||
1110 | print("") |
||
1111 | print("SCENARIO: eGon2035_lowflex") |
||
1112 | |||
1113 | # Compare driving load and charging load |
||
1114 | print(" Loading eGon2035 model timeseries: driving load...") |
||
1115 | with db.session_scope() as session: |
||
1116 | query = ( |
||
1117 | session.query( |
||
1118 | EgonPfHvLoad.load_id, |
||
1119 | EgonPfHvLoadTimeseries.p_set, |
||
1120 | ) |
||
1121 | .join( |
||
1122 | EgonPfHvLoadTimeseries, |
||
1123 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
||
1124 | ) |
||
1125 | .filter( |
||
1126 | EgonPfHvLoad.carrier == "land transport EV", |
||
1127 | EgonPfHvLoad.scn_name == "eGon2035", |
||
1128 | EgonPfHvLoadTimeseries.scn_name == "eGon2035", |
||
1129 | ) |
||
1130 | ) |
||
1131 | model_driving_load = pd.read_sql( |
||
1132 | query.statement, query.session.bind, index_col=None |
||
1133 | ) |
||
1134 | driving_load = np.array(model_driving_load.p_set.to_list()).sum(axis=0) |
||
1135 | |||
1136 | print( |
||
1137 | " Loading eGon2035_lowflex model timeseries: dumb charging " |
||
1138 | "load..." |
||
1139 | ) |
||
1140 | with db.session_scope() as session: |
||
1141 | query = ( |
||
1142 | session.query( |
||
1143 | EgonPfHvLoad.load_id, |
||
1144 | EgonPfHvLoadTimeseries.p_set, |
||
1145 | ) |
||
1146 | .join( |
||
1147 | EgonPfHvLoadTimeseries, |
||
1148 | EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
||
1149 | ) |
||
1150 | .filter( |
||
1151 | EgonPfHvLoad.carrier == "land transport EV", |
||
1152 | EgonPfHvLoad.scn_name == "eGon2035_lowflex", |
||
1153 | EgonPfHvLoadTimeseries.scn_name == "eGon2035_lowflex", |
||
1154 | ) |
||
1155 | ) |
||
1156 | model_charging_load_lowflex = pd.read_sql( |
||
1157 | query.statement, query.session.bind, index_col=None |
||
1158 | ) |
||
1159 | charging_load = np.array( |
||
1160 | model_charging_load_lowflex.p_set.to_list() |
||
1161 | ).sum(axis=0) |
||
1162 | |||
1163 | # Ratio of driving and charging load should be 0.9 due to charging |
||
1164 | # efficiency |
||
1165 | print(" Compare cumulative loads...") |
||
1166 | print(f" Driving load (eGon2035): {driving_load.sum() / 1e6} TWh") |
||
1167 | print( |
||
1168 | f" Dumb charging load (eGon2035_lowflex): " |
||
1169 | f"{charging_load.sum() / 1e6} TWh" |
||
1170 | ) |
||
1171 | driving_load_theoretical = ( |
||
1172 | float(meta_run_config.eta_cp) * charging_load.sum() |
||
1173 | ) |
||
1174 | np.testing.assert_allclose( |
||
1175 | driving_load.sum(), |
||
1176 | driving_load_theoretical, |
||
1177 | rtol=0.01, |
||
1178 | err_msg=( |
||
1179 | f"The driving load (eGon2035) deviates by more than 1% " |
||
1180 | f"from the theoretical driving load calculated from charging " |
||
1181 | f"load (eGon2035_lowflex) with an efficiency of " |
||
1182 | f"{float(meta_run_config.eta_cp)}." |
||
1183 | ), |
||
1184 | ) |
||
1185 | |||
1186 | print("=====================================================") |
||
1187 | print("=== SANITY CHECKS FOR MOTORIZED INDIVIDUAL TRAVEL ===") |
||
1188 | print("=====================================================") |
||
1189 | |||
1190 | for scenario_name in ["eGon2035", "eGon100RE"]: |
||
1191 | scenario_var_name = DATASET_CFG["scenario"]["variation"][scenario_name] |
||
1192 | |||
1193 | print("") |
||
1194 | print(f"SCENARIO: {scenario_name}, VARIATION: {scenario_var_name}") |
||
1195 | |||
1196 | # Load scenario params for scenario and scenario variation |
||
1197 | scenario_variation_parameters = get_sector_parameters( |
||
1198 | "mobility", scenario=scenario_name |
||
1199 | )["motorized_individual_travel"][scenario_var_name] |
||
1200 | |||
1201 | # Load simBEV run config and tech data |
||
1202 | meta_run_config = read_simbev_metadata_file( |
||
1203 | scenario_name, "config" |
||
1204 | ).loc["basic"] |
||
1205 | meta_tech_data = read_simbev_metadata_file(scenario_name, "tech_data") |
||
1206 | |||
1207 | print("") |
||
1208 | print("Checking EV counts...") |
||
1209 | ev_count_alloc = check_ev_allocation() |
||
1210 | |||
1211 | print("") |
||
1212 | print("Checking trip data...") |
||
1213 | check_trip_data() |
||
1214 | |||
1215 | print("") |
||
1216 | print("Checking model data...") |
||
1217 | check_model_data() |
||
1218 | |||
1219 | print("") |
||
1220 | check_model_data_lowflex_eGon2035() |
||
1221 | |||
1222 | print("=====================================================") |
||
1223 |