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""" |
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This module does sanity checks for both the eGon2035 and the eGon100RE scenario |
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separately where a percentage error is given to showcase difference in output |
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and input values. Please note that there are missing input technologies in the |
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supply tables. |
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Authors: @ALonso, @dana |
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""" |
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from sqlalchemy import Numeric |
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from sqlalchemy.sql import and_, cast, func, or_ |
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import numpy as np |
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import pandas as pd |
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from egon.data import config, db |
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from egon.data.datasets import Dataset |
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from egon.data.datasets.emobility.motorized_individual_travel.db_classes import ( |
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EgonEvCountMunicipality, |
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EgonEvCountMvGridDistrict, |
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EgonEvCountRegistrationDistrict, |
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EgonEvMvGridDistrict, |
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EgonEvPool, |
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EgonEvTrip, |
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) |
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from egon.data.datasets.emobility.motorized_individual_travel.helpers import ( |
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DATASET_CFG, |
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read_simbev_metadata_file, |
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) |
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from egon.data.datasets.etrago_setup import ( |
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EgonPfHvLink, |
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EgonPfHvLinkTimeseries, |
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EgonPfHvLoad, |
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EgonPfHvLoadTimeseries, |
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EgonPfHvStore, |
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EgonPfHvStoreTimeseries, |
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) |
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from egon.data.datasets.scenario_parameters import get_sector_parameters |
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TESTMODE_OFF = ( |
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config.settings()["egon-data"]["--dataset-boundary"] == "Everything" |
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) |
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class SanityChecks(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="SanityChecks", |
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version="0.0.4", |
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dependencies=dependencies, |
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tasks={ |
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etrago_eGon2035_electricity, |
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etrago_eGon2035_heat, |
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residential_electricity_annual_sum, |
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residential_electricity_hh_refinement, |
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sanitycheck_emobility_mit, |
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}, |
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) |
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def etrago_eGon2035_electricity(): |
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"""Execute basic sanity checks. |
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Returns print statements as sanity checks for the electricity sector in |
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the eGon2035 scenario. |
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Parameters |
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---------- |
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None |
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Returns |
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------- |
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None |
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""" |
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scn = "eGon2035" |
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# Section to check generator capacities |
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print(f"Sanity checks for scenario {scn}") |
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print( |
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"For German electricity generators the following deviations between " |
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"the inputs and outputs can be observed:" |
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) |
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carriers_electricity = [ |
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"other_non_renewable", |
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"other_renewable", |
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"reservoir", |
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"run_of_river", |
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"oil", |
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"wind_onshore", |
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"wind_offshore", |
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"solar", |
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"solar_rooftop", |
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"biomass", |
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] |
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for carrier in carriers_electricity: |
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if carrier == "biomass": |
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sum_output = db.select_dataframe( |
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"""SELECT scn_name, SUM(p_nom::numeric) as output_capacity_mw |
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FROM grid.egon_etrago_generator |
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WHERE bus IN ( |
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SELECT bus_id FROM grid.egon_etrago_bus |
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WHERE scn_name = 'eGon2035' |
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AND country = 'DE') |
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AND carrier IN ('biomass', 'industrial_biomass_CHP', |
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'central_biomass_CHP') |
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GROUP BY (scn_name); |
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""", |
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warning=False, |
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) |
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else: |
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sum_output = db.select_dataframe( |
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f"""SELECT scn_name, |
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SUM(p_nom::numeric) as output_capacity_mw |
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FROM grid.egon_etrago_generator |
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WHERE scn_name = '{scn}' |
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AND carrier IN ('{carrier}') |
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AND bus IN |
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(SELECT bus_id |
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FROM grid.egon_etrago_bus |
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WHERE scn_name = 'eGon2035' |
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AND country = 'DE') |
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GROUP BY (scn_name); |
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""", |
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warning=False, |
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) |
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sum_input = db.select_dataframe( |
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f"""SELECT carrier, SUM(capacity::numeric) as input_capacity_mw |
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FROM supply.egon_scenario_capacities |
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WHERE carrier= '{carrier}' |
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AND scenario_name ='{scn}' |
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GROUP BY (carrier); |
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""", |
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warning=False, |
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) |
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View Code Duplication |
if ( |
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sum_output.output_capacity_mw.sum() == 0 |
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and sum_input.input_capacity_mw.sum() == 0 |
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): |
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print( |
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f"No capacity for carrier '{carrier}' needed to be" |
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f" distributed. Everything is fine" |
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) |
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elif ( |
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sum_input.input_capacity_mw.sum() > 0 |
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and sum_output.output_capacity_mw.sum() == 0 |
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): |
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print( |
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f"Error: Capacity for carrier '{carrier}' was not distributed " |
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f"at all!" |
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) |
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elif ( |
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sum_output.output_capacity_mw.sum() > 0 |
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and sum_input.input_capacity_mw.sum() == 0 |
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): |
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print( |
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f"Error: Eventhough no input capacity was provided for carrier" |
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f"'{carrier}' a capacity got distributed!" |
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) |
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else: |
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sum_input["error"] = ( |
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(sum_output.output_capacity_mw - sum_input.input_capacity_mw) |
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/ sum_input.input_capacity_mw |
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) * 100 |
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g = sum_input["error"].values[0] |
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print(f"{carrier}: " + str(round(g, 2)) + " %") |
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# Section to check storage units |
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print(f"Sanity checks for scenario {scn}") |
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print( |
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"For German electrical storage units the following deviations between" |
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"the inputs and outputs can be observed:" |
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) |
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carriers_electricity = ["pumped_hydro"] |
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for carrier in carriers_electricity: |
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sum_output = db.select_dataframe( |
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f"""SELECT scn_name, SUM(p_nom::numeric) as output_capacity_mw |
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FROM grid.egon_etrago_storage |
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WHERE scn_name = '{scn}' |
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AND carrier IN ('{carrier}') |
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AND bus IN |
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(SELECT bus_id |
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FROM grid.egon_etrago_bus |
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WHERE scn_name = 'eGon2035' |
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AND country = 'DE') |
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GROUP BY (scn_name); |
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""", |
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warning=False, |
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) |
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203
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sum_input = db.select_dataframe( |
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f"""SELECT carrier, SUM(capacity::numeric) as input_capacity_mw |
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FROM supply.egon_scenario_capacities |
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WHERE carrier= '{carrier}' |
207
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AND scenario_name ='{scn}' |
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GROUP BY (carrier); |
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""", |
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warning=False, |
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) |
212
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213
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View Code Duplication |
if ( |
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214
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sum_output.output_capacity_mw.sum() == 0 |
215
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and sum_input.input_capacity_mw.sum() == 0 |
216
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): |
217
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print( |
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f"No capacity for carrier '{carrier}' needed to be " |
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f"distributed. Everything is fine" |
220
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) |
221
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222
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elif ( |
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sum_input.input_capacity_mw.sum() > 0 |
224
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and sum_output.output_capacity_mw.sum() == 0 |
225
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): |
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print( |
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f"Error: Capacity for carrier '{carrier}' was not distributed" |
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f" at all!" |
229
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) |
230
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231
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elif ( |
232
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sum_output.output_capacity_mw.sum() > 0 |
233
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and sum_input.input_capacity_mw.sum() == 0 |
234
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): |
235
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print( |
236
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f"Error: Eventhough no input capacity was provided for carrier" |
237
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f" '{carrier}' a capacity got distributed!" |
238
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) |
239
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240
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else: |
241
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sum_input["error"] = ( |
242
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(sum_output.output_capacity_mw - sum_input.input_capacity_mw) |
243
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/ sum_input.input_capacity_mw |
244
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) * 100 |
245
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g = sum_input["error"].values[0] |
246
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247
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print(f"{carrier}: " + str(round(g, 2)) + " %") |
248
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249
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# Section to check loads |
250
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|
251
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print( |
252
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"For German electricity loads the following deviations between the" |
253
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" input and output can be observed:" |
254
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) |
255
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|
256
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output_demand = db.select_dataframe( |
257
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"""SELECT a.scn_name, a.carrier, SUM((SELECT SUM(p) |
258
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FROM UNNEST(b.p_set) p))/1000000::numeric as load_twh |
259
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FROM grid.egon_etrago_load a |
260
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JOIN grid.egon_etrago_load_timeseries b |
261
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ON (a.load_id = b.load_id) |
262
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JOIN grid.egon_etrago_bus c |
263
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ON (a.bus=c.bus_id) |
264
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AND b.scn_name = 'eGon2035' |
265
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AND a.scn_name = 'eGon2035' |
266
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AND a.carrier = 'AC' |
267
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AND c.scn_name= 'eGon2035' |
268
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AND c.country='DE' |
269
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GROUP BY (a.scn_name, a.carrier); |
270
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271
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""", |
272
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warning=False, |
273
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)["load_twh"].values[0] |
274
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|
275
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input_cts_ind = db.select_dataframe( |
276
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"""SELECT scenario, |
277
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SUM(demand::numeric/1000000) as demand_mw_regio_cts_ind |
278
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FROM demand.egon_demandregio_cts_ind |
279
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WHERE scenario= 'eGon2035' |
280
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AND year IN ('2035') |
281
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GROUP BY (scenario); |
282
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|
283
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""", |
284
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warning=False, |
285
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)["demand_mw_regio_cts_ind"].values[0] |
286
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|
287
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input_hh = db.select_dataframe( |
288
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"""SELECT scenario, SUM(demand::numeric/1000000) as demand_mw_regio_hh |
289
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FROM demand.egon_demandregio_hh |
290
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WHERE scenario= 'eGon2035' |
291
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AND year IN ('2035') |
292
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GROUP BY (scenario); |
293
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""", |
294
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warning=False, |
295
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)["demand_mw_regio_hh"].values[0] |
296
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|
|
|
297
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input_demand = input_hh + input_cts_ind |
298
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|
299
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e = round((output_demand - input_demand) / input_demand, 2) * 100 |
300
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|
|
|
301
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print(f"electricity demand: {e} %") |
302
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|
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|
303
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|
304
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|
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def etrago_eGon2035_heat(): |
305
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|
|
"""Execute basic sanity checks. |
306
|
|
|
|
307
|
|
|
Returns print statements as sanity checks for the heat sector in |
308
|
|
|
the eGon2035 scenario. |
309
|
|
|
|
310
|
|
|
Parameters |
311
|
|
|
---------- |
312
|
|
|
None |
313
|
|
|
|
314
|
|
|
Returns |
315
|
|
|
------- |
316
|
|
|
None |
317
|
|
|
""" |
318
|
|
|
|
319
|
|
|
# Check input and output values for the carriers "other_non_renewable", |
320
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|
|
# "other_renewable", "reservoir", "run_of_river" and "oil" |
321
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|
|
|
322
|
|
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scn = "eGon2035" |
323
|
|
|
|
324
|
|
|
# Section to check generator capacities |
325
|
|
|
print(f"Sanity checks for scenario {scn}") |
326
|
|
|
print( |
327
|
|
|
"For German heat demands the following deviations between the inputs" |
328
|
|
|
" and outputs can be observed:" |
329
|
|
|
) |
330
|
|
|
|
331
|
|
|
# Sanity checks for heat demand |
332
|
|
|
|
333
|
|
|
output_heat_demand = db.select_dataframe( |
334
|
|
|
"""SELECT a.scn_name, |
335
|
|
|
(SUM( |
336
|
|
|
(SELECT SUM(p) FROM UNNEST(b.p_set) p))/1000000)::numeric as load_twh |
337
|
|
|
FROM grid.egon_etrago_load a |
338
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|
|
JOIN grid.egon_etrago_load_timeseries b |
339
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|
|
ON (a.load_id = b.load_id) |
340
|
|
|
JOIN grid.egon_etrago_bus c |
341
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|
|
ON (a.bus=c.bus_id) |
342
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|
|
AND b.scn_name = 'eGon2035' |
343
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|
|
AND a.scn_name = 'eGon2035' |
344
|
|
|
AND c.scn_name= 'eGon2035' |
345
|
|
|
AND c.country='DE' |
346
|
|
|
AND a.carrier IN ('rural_heat', 'central_heat') |
347
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|
|
GROUP BY (a.scn_name); |
348
|
|
|
""", |
349
|
|
|
warning=False, |
350
|
|
|
)["load_twh"].values[0] |
351
|
|
|
|
352
|
|
|
input_heat_demand = db.select_dataframe( |
353
|
|
|
"""SELECT scenario, SUM(demand::numeric/1000000) as demand_mw_peta_heat |
354
|
|
|
FROM demand.egon_peta_heat |
355
|
|
|
WHERE scenario= 'eGon2035' |
356
|
|
|
GROUP BY (scenario); |
357
|
|
|
""", |
358
|
|
|
warning=False, |
359
|
|
|
)["demand_mw_peta_heat"].values[0] |
360
|
|
|
|
361
|
|
|
e_demand = ( |
362
|
|
|
round((output_heat_demand - input_heat_demand) / input_heat_demand, 2) |
363
|
|
|
* 100 |
364
|
|
|
) |
365
|
|
|
|
366
|
|
|
print(f"heat demand: {e_demand} %") |
367
|
|
|
|
368
|
|
|
# Sanity checks for heat supply |
369
|
|
|
|
370
|
|
|
print( |
371
|
|
|
"For German heat supplies the following deviations between the inputs " |
372
|
|
|
"and outputs can be observed:" |
373
|
|
|
) |
374
|
|
|
|
375
|
|
|
# Comparison for central heat pumps |
376
|
|
|
heat_pump_input = db.select_dataframe( |
377
|
|
|
"""SELECT carrier, SUM(capacity::numeric) as Urban_central_heat_pump_mw |
378
|
|
|
FROM supply.egon_scenario_capacities |
379
|
|
|
WHERE carrier= 'urban_central_heat_pump' |
380
|
|
|
AND scenario_name IN ('eGon2035') |
381
|
|
|
GROUP BY (carrier); |
382
|
|
|
""", |
383
|
|
|
warning=False, |
384
|
|
|
)["urban_central_heat_pump_mw"].values[0] |
385
|
|
|
|
386
|
|
|
heat_pump_output = db.select_dataframe( |
387
|
|
|
"""SELECT carrier, SUM(p_nom::numeric) as Central_heat_pump_mw |
388
|
|
|
FROM grid.egon_etrago_link |
389
|
|
|
WHERE carrier= 'central_heat_pump' |
390
|
|
|
AND scn_name IN ('eGon2035') |
391
|
|
|
GROUP BY (carrier); |
392
|
|
|
""", |
393
|
|
|
warning=False, |
394
|
|
|
)["central_heat_pump_mw"].values[0] |
395
|
|
|
|
396
|
|
|
e_heat_pump = ( |
397
|
|
|
round((heat_pump_output - heat_pump_input) / heat_pump_output, 2) * 100 |
398
|
|
|
) |
399
|
|
|
|
400
|
|
|
print(f"'central_heat_pump': {e_heat_pump} % ") |
401
|
|
|
|
402
|
|
|
# Comparison for residential heat pumps |
403
|
|
|
|
404
|
|
|
input_residential_heat_pump = db.select_dataframe( |
405
|
|
|
"""SELECT carrier, SUM(capacity::numeric) as residential_heat_pump_mw |
406
|
|
|
FROM supply.egon_scenario_capacities |
407
|
|
|
WHERE carrier= 'residential_rural_heat_pump' |
408
|
|
|
AND scenario_name IN ('eGon2035') |
409
|
|
|
GROUP BY (carrier); |
410
|
|
|
""", |
411
|
|
|
warning=False, |
412
|
|
|
)["residential_heat_pump_mw"].values[0] |
413
|
|
|
|
414
|
|
|
output_residential_heat_pump = db.select_dataframe( |
415
|
|
|
"""SELECT carrier, SUM(p_nom::numeric) as rural_heat_pump_mw |
416
|
|
|
FROM grid.egon_etrago_link |
417
|
|
|
WHERE carrier= 'rural_heat_pump' |
418
|
|
|
AND scn_name IN ('eGon2035') |
419
|
|
|
GROUP BY (carrier); |
420
|
|
|
""", |
421
|
|
|
warning=False, |
422
|
|
|
)["rural_heat_pump_mw"].values[0] |
423
|
|
|
|
424
|
|
|
e_residential_heat_pump = ( |
425
|
|
|
round( |
426
|
|
|
(output_residential_heat_pump - input_residential_heat_pump) |
427
|
|
|
/ input_residential_heat_pump, |
428
|
|
|
2, |
429
|
|
|
) |
430
|
|
|
* 100 |
431
|
|
|
) |
432
|
|
|
print(f"'residential heat pumps': {e_residential_heat_pump} %") |
433
|
|
|
|
434
|
|
|
# Comparison for resistive heater |
435
|
|
|
resistive_heater_input = db.select_dataframe( |
436
|
|
|
"""SELECT carrier, |
437
|
|
|
SUM(capacity::numeric) as Urban_central_resistive_heater_MW |
438
|
|
|
FROM supply.egon_scenario_capacities |
439
|
|
|
WHERE carrier= 'urban_central_resistive_heater' |
440
|
|
|
AND scenario_name IN ('eGon2035') |
441
|
|
|
GROUP BY (carrier); |
442
|
|
|
""", |
443
|
|
|
warning=False, |
444
|
|
|
)["urban_central_resistive_heater_mw"].values[0] |
445
|
|
|
|
446
|
|
|
resistive_heater_output = db.select_dataframe( |
447
|
|
|
"""SELECT carrier, SUM(p_nom::numeric) as central_resistive_heater_MW |
448
|
|
|
FROM grid.egon_etrago_link |
449
|
|
|
WHERE carrier= 'central_resistive_heater' |
450
|
|
|
AND scn_name IN ('eGon2035') |
451
|
|
|
GROUP BY (carrier); |
452
|
|
|
""", |
453
|
|
|
warning=False, |
454
|
|
|
)["central_resistive_heater_mw"].values[0] |
455
|
|
|
|
456
|
|
|
e_resistive_heater = ( |
457
|
|
|
round( |
458
|
|
|
(resistive_heater_output - resistive_heater_input) |
459
|
|
|
/ resistive_heater_input, |
460
|
|
|
2, |
461
|
|
|
) |
462
|
|
|
* 100 |
463
|
|
|
) |
464
|
|
|
|
465
|
|
|
print(f"'resistive heater': {e_resistive_heater} %") |
466
|
|
|
|
467
|
|
|
# Comparison for solar thermal collectors |
468
|
|
|
|
469
|
|
|
input_solar_thermal = db.select_dataframe( |
470
|
|
|
"""SELECT carrier, SUM(capacity::numeric) as solar_thermal_collector_mw |
471
|
|
|
FROM supply.egon_scenario_capacities |
472
|
|
|
WHERE carrier= 'urban_central_solar_thermal_collector' |
473
|
|
|
AND scenario_name IN ('eGon2035') |
474
|
|
|
GROUP BY (carrier); |
475
|
|
|
""", |
476
|
|
|
warning=False, |
477
|
|
|
)["solar_thermal_collector_mw"].values[0] |
478
|
|
|
|
479
|
|
|
output_solar_thermal = db.select_dataframe( |
480
|
|
|
"""SELECT carrier, SUM(p_nom::numeric) as solar_thermal_collector_mw |
481
|
|
|
FROM grid.egon_etrago_generator |
482
|
|
|
WHERE carrier= 'solar_thermal_collector' |
483
|
|
|
AND scn_name IN ('eGon2035') |
484
|
|
|
GROUP BY (carrier); |
485
|
|
|
""", |
486
|
|
|
warning=False, |
487
|
|
|
)["solar_thermal_collector_mw"].values[0] |
488
|
|
|
|
489
|
|
|
e_solar_thermal = ( |
490
|
|
|
round( |
491
|
|
|
(output_solar_thermal - input_solar_thermal) / input_solar_thermal, |
492
|
|
|
2, |
493
|
|
|
) |
494
|
|
|
* 100 |
495
|
|
|
) |
496
|
|
|
print(f"'solar thermal collector': {e_solar_thermal} %") |
497
|
|
|
|
498
|
|
|
# Comparison for geothermal |
499
|
|
|
|
500
|
|
|
input_geo_thermal = db.select_dataframe( |
501
|
|
|
"""SELECT carrier, |
502
|
|
|
SUM(capacity::numeric) as Urban_central_geo_thermal_MW |
503
|
|
|
FROM supply.egon_scenario_capacities |
504
|
|
|
WHERE carrier= 'urban_central_geo_thermal' |
505
|
|
|
AND scenario_name IN ('eGon2035') |
506
|
|
|
GROUP BY (carrier); |
507
|
|
|
""", |
508
|
|
|
warning=False, |
509
|
|
|
)["urban_central_geo_thermal_mw"].values[0] |
510
|
|
|
|
511
|
|
|
output_geo_thermal = db.select_dataframe( |
512
|
|
|
"""SELECT carrier, SUM(p_nom::numeric) as geo_thermal_MW |
513
|
|
|
FROM grid.egon_etrago_generator |
514
|
|
|
WHERE carrier= 'geo_thermal' |
515
|
|
|
AND scn_name IN ('eGon2035') |
516
|
|
|
GROUP BY (carrier); |
517
|
|
|
""", |
518
|
|
|
warning=False, |
519
|
|
|
)["geo_thermal_mw"].values[0] |
520
|
|
|
|
521
|
|
|
e_geo_thermal = ( |
522
|
|
|
round((output_geo_thermal - input_geo_thermal) / input_geo_thermal, 2) |
523
|
|
|
* 100 |
524
|
|
|
) |
525
|
|
|
print(f"'geothermal': {e_geo_thermal} %") |
526
|
|
|
|
527
|
|
|
|
528
|
|
|
def sanitycheck_emobility_mit(): |
529
|
|
|
"""Execute sanity checks for eMobility: motorized individual travel |
530
|
|
|
|
531
|
|
|
Checks data integrity for eGon2035, eGon2035_lowflex and eGon100RE scenario |
532
|
|
|
using assertions: |
533
|
|
|
1. Allocated EV numbers and EVs allocated to grid districts |
534
|
|
|
2. Trip data (original inout data from simBEV) |
535
|
|
|
3. Model data in eTraGo PF tables (grid.egon_etrago_*) |
536
|
|
|
|
537
|
|
|
Parameters |
538
|
|
|
---------- |
539
|
|
|
None |
540
|
|
|
|
541
|
|
|
Returns |
542
|
|
|
------- |
543
|
|
|
None |
544
|
|
|
""" |
545
|
|
|
|
546
|
|
|
def check_ev_allocation(): |
547
|
|
|
# Get target number for scenario |
548
|
|
|
ev_count_target = scenario_variation_parameters["ev_count"] |
549
|
|
|
print(f" Target count: {str(ev_count_target)}") |
550
|
|
|
|
551
|
|
|
# Get allocated numbers |
552
|
|
|
ev_counts_dict = {} |
553
|
|
|
with db.session_scope() as session: |
554
|
|
|
for table, level in zip( |
555
|
|
|
[ |
556
|
|
|
EgonEvCountMvGridDistrict, |
557
|
|
|
EgonEvCountMunicipality, |
558
|
|
|
EgonEvCountRegistrationDistrict, |
559
|
|
|
], |
560
|
|
|
["Grid District", "Municipality", "Registration District"], |
561
|
|
|
): |
562
|
|
|
query = session.query( |
563
|
|
|
func.sum( |
564
|
|
|
table.bev_mini |
565
|
|
|
+ table.bev_medium |
566
|
|
|
+ table.bev_luxury |
567
|
|
|
+ table.phev_mini |
568
|
|
|
+ table.phev_medium |
569
|
|
|
+ table.phev_luxury |
570
|
|
|
).label("ev_count") |
571
|
|
|
).filter( |
572
|
|
|
table.scenario == scenario_name, |
573
|
|
|
table.scenario_variation == scenario_var_name, |
574
|
|
|
) |
575
|
|
|
|
576
|
|
|
ev_counts = pd.read_sql( |
577
|
|
|
query.statement, query.session.bind, index_col=None |
578
|
|
|
) |
579
|
|
|
ev_counts_dict[level] = ev_counts.iloc[0].ev_count |
580
|
|
|
print( |
581
|
|
|
f" Count table: Total count for level {level} " |
582
|
|
|
f"(table: {table.__table__}): " |
583
|
|
|
f"{str(ev_counts_dict[level])}" |
584
|
|
|
) |
585
|
|
|
|
586
|
|
|
# Compare with scenario target (only if not in testmode) |
587
|
|
|
if TESTMODE_OFF: |
588
|
|
|
for level, count in ev_counts_dict.items(): |
589
|
|
|
np.testing.assert_allclose( |
590
|
|
|
count, |
591
|
|
|
ev_count_target, |
592
|
|
|
rtol=0.0001, |
593
|
|
|
err_msg=f"EV numbers in {level} seems to be flawed.", |
594
|
|
|
) |
595
|
|
|
else: |
596
|
|
|
print(" Testmode is on, skipping sanity check...") |
597
|
|
|
|
598
|
|
|
# Get allocated EVs in grid districts |
599
|
|
|
with db.session_scope() as session: |
600
|
|
|
query = session.query( |
601
|
|
|
func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
602
|
|
|
"ev_count" |
603
|
|
|
), |
604
|
|
|
).filter( |
605
|
|
|
EgonEvMvGridDistrict.scenario == scenario_name, |
606
|
|
|
EgonEvMvGridDistrict.scenario_variation == scenario_var_name, |
607
|
|
|
) |
608
|
|
|
ev_count_alloc = ( |
609
|
|
|
pd.read_sql(query.statement, query.session.bind, index_col=None) |
610
|
|
|
.iloc[0] |
611
|
|
|
.ev_count |
612
|
|
|
) |
613
|
|
|
print( |
614
|
|
|
f" EVs allocated to Grid Districts " |
615
|
|
|
f"(table: {EgonEvMvGridDistrict.__table__}) total count: " |
616
|
|
|
f"{str(ev_count_alloc)}" |
617
|
|
|
) |
618
|
|
|
|
619
|
|
|
# Compare with scenario target (only if not in testmode) |
620
|
|
|
if TESTMODE_OFF: |
621
|
|
|
np.testing.assert_allclose( |
622
|
|
|
ev_count_alloc, |
623
|
|
|
ev_count_target, |
624
|
|
|
rtol=0.0001, |
625
|
|
|
err_msg=( |
626
|
|
|
"EV numbers allocated to Grid Districts seems to be " |
627
|
|
|
"flawed." |
628
|
|
|
), |
629
|
|
|
) |
630
|
|
|
else: |
631
|
|
|
print(" Testmode is on, skipping sanity check...") |
632
|
|
|
|
633
|
|
|
return ev_count_alloc |
634
|
|
|
|
635
|
|
|
def check_trip_data(): |
636
|
|
|
# Check if trips start at timestep 0 and have a max. of 35040 steps |
637
|
|
|
# (8760h in 15min steps) |
638
|
|
|
print(" Checking timeranges...") |
639
|
|
|
with db.session_scope() as session: |
640
|
|
|
query = session.query( |
641
|
|
|
func.count(EgonEvTrip.event_id).label("cnt") |
642
|
|
|
).filter( |
643
|
|
|
or_( |
644
|
|
|
and_( |
645
|
|
|
EgonEvTrip.park_start > 0, |
646
|
|
|
EgonEvTrip.simbev_event_id == 0, |
647
|
|
|
), |
648
|
|
|
EgonEvTrip.park_end |
649
|
|
|
> (60 / int(meta_run_config.stepsize)) * 8760, |
650
|
|
|
), |
651
|
|
|
EgonEvTrip.scenario == scenario_name, |
652
|
|
|
) |
653
|
|
|
invalid_trips = pd.read_sql( |
654
|
|
|
query.statement, query.session.bind, index_col=None |
655
|
|
|
) |
656
|
|
|
np.testing.assert_equal( |
657
|
|
|
invalid_trips.iloc[0].cnt, |
658
|
|
|
0, |
659
|
|
|
err_msg=( |
660
|
|
|
f"{str(invalid_trips.iloc[0].cnt)} trips in table " |
661
|
|
|
f"{EgonEvTrip.__table__} have invalid timesteps." |
662
|
|
|
), |
663
|
|
|
) |
664
|
|
|
|
665
|
|
|
# Check if charging demand can be covered by available charging energy |
666
|
|
|
# while parking |
667
|
|
|
print(" Compare charging demand with available power...") |
668
|
|
|
with db.session_scope() as session: |
669
|
|
|
query = session.query( |
670
|
|
|
func.count(EgonEvTrip.event_id).label("cnt") |
671
|
|
|
).filter( |
672
|
|
|
func.round( |
673
|
|
|
cast( |
674
|
|
|
(EgonEvTrip.park_end - EgonEvTrip.park_start + 1) |
675
|
|
|
* EgonEvTrip.charging_capacity_nominal |
676
|
|
|
* (int(meta_run_config.stepsize) / 60), |
677
|
|
|
Numeric, |
678
|
|
|
), |
679
|
|
|
3, |
680
|
|
|
) |
681
|
|
|
< cast(EgonEvTrip.charging_demand, Numeric), |
682
|
|
|
EgonEvTrip.scenario == scenario_name, |
683
|
|
|
) |
684
|
|
|
invalid_trips = pd.read_sql( |
685
|
|
|
query.statement, query.session.bind, index_col=None |
686
|
|
|
) |
687
|
|
|
np.testing.assert_equal( |
688
|
|
|
invalid_trips.iloc[0].cnt, |
689
|
|
|
0, |
690
|
|
|
err_msg=( |
691
|
|
|
f"In {str(invalid_trips.iloc[0].cnt)} trips (table: " |
692
|
|
|
f"{EgonEvTrip.__table__}) the charging demand cannot be " |
693
|
|
|
f"covered by available charging power." |
694
|
|
|
), |
695
|
|
|
) |
696
|
|
|
|
697
|
|
|
def check_model_data(): |
698
|
|
|
# Check if model components were fully created |
699
|
|
|
print(" Check if all model components were created...") |
700
|
|
|
# Get MVGDs which got EV allocated |
701
|
|
|
with db.session_scope() as session: |
702
|
|
|
query = ( |
703
|
|
|
session.query( |
704
|
|
|
EgonEvMvGridDistrict.bus_id, |
705
|
|
|
) |
706
|
|
|
.filter( |
707
|
|
|
EgonEvMvGridDistrict.scenario == scenario_name, |
708
|
|
|
EgonEvMvGridDistrict.scenario_variation |
709
|
|
|
== scenario_var_name, |
710
|
|
|
) |
711
|
|
|
.group_by(EgonEvMvGridDistrict.bus_id) |
712
|
|
|
) |
713
|
|
|
mvgds_with_ev = ( |
714
|
|
|
pd.read_sql(query.statement, query.session.bind, index_col=None) |
715
|
|
|
.bus_id.sort_values() |
716
|
|
|
.to_list() |
717
|
|
|
) |
718
|
|
|
|
719
|
|
|
# Load model components |
720
|
|
|
with db.session_scope() as session: |
721
|
|
|
query = ( |
722
|
|
|
session.query( |
723
|
|
|
EgonPfHvLink.bus0.label("mvgd_bus_id"), |
724
|
|
|
EgonPfHvLoad.bus.label("emob_bus_id"), |
725
|
|
|
EgonPfHvLoad.load_id.label("load_id"), |
726
|
|
|
EgonPfHvStore.store_id.label("store_id"), |
727
|
|
|
) |
728
|
|
|
.select_from(EgonPfHvLoad, EgonPfHvStore) |
729
|
|
|
.join( |
730
|
|
|
EgonPfHvLoadTimeseries, |
731
|
|
|
EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
732
|
|
|
) |
733
|
|
|
.join( |
734
|
|
|
EgonPfHvStoreTimeseries, |
735
|
|
|
EgonPfHvStoreTimeseries.store_id == EgonPfHvStore.store_id, |
736
|
|
|
) |
737
|
|
|
.filter( |
738
|
|
|
EgonPfHvLoad.carrier == "land transport EV", |
739
|
|
|
EgonPfHvLoad.scn_name == scenario_name, |
740
|
|
|
EgonPfHvLoadTimeseries.scn_name == scenario_name, |
741
|
|
|
EgonPfHvStore.carrier == "battery storage", |
742
|
|
|
EgonPfHvStore.scn_name == scenario_name, |
743
|
|
|
EgonPfHvStoreTimeseries.scn_name == scenario_name, |
744
|
|
|
EgonPfHvLink.scn_name == scenario_name, |
745
|
|
|
EgonPfHvLink.bus1 == EgonPfHvLoad.bus, |
746
|
|
|
EgonPfHvLink.bus1 == EgonPfHvStore.bus, |
747
|
|
|
) |
748
|
|
|
) |
749
|
|
|
model_components = pd.read_sql( |
750
|
|
|
query.statement, query.session.bind, index_col=None |
751
|
|
|
) |
752
|
|
|
|
753
|
|
|
# Check number of buses with model components connected |
754
|
|
|
mvgd_buses_with_ev = model_components.loc[ |
755
|
|
|
model_components.mvgd_bus_id.isin(mvgds_with_ev) |
756
|
|
|
] |
757
|
|
|
np.testing.assert_equal( |
758
|
|
|
len(mvgds_with_ev), |
759
|
|
|
len(mvgd_buses_with_ev), |
760
|
|
|
err_msg=( |
761
|
|
|
f"Number of Grid Districts with connected model components " |
762
|
|
|
f"({str(len(mvgd_buses_with_ev))} in tables egon_etrago_*) " |
763
|
|
|
f"differ from number of Grid Districts that got EVs " |
764
|
|
|
f"allocated ({len(mvgds_with_ev)} in table " |
765
|
|
|
f"{EgonEvMvGridDistrict.__table__})." |
766
|
|
|
), |
767
|
|
|
) |
768
|
|
|
|
769
|
|
|
# Check if all required components exist (if no id is NaN) |
770
|
|
|
np.testing.assert_equal( |
771
|
|
|
model_components.drop_duplicates().isna().any().any(), |
772
|
|
|
False, |
773
|
|
|
err_msg=( |
774
|
|
|
f"Some components are missing (see True values): " |
775
|
|
|
f"{model_components.drop_duplicates().isna().any()}" |
776
|
|
|
), |
777
|
|
|
) |
778
|
|
|
|
779
|
|
|
# Get all model timeseries |
780
|
|
|
print(" Loading model timeseries...") |
781
|
|
|
# Get all model timeseries |
782
|
|
|
model_ts_dict = { |
783
|
|
|
"Load": { |
784
|
|
|
"carrier": "land transport EV", |
785
|
|
|
"table": EgonPfHvLoad, |
786
|
|
|
"table_ts": EgonPfHvLoadTimeseries, |
787
|
|
|
"column_id": "load_id", |
788
|
|
|
"columns_ts": ["p_set"], |
789
|
|
|
"ts": None, |
790
|
|
|
}, |
791
|
|
|
"Link": { |
792
|
|
|
"carrier": "BEV charger", |
793
|
|
|
"table": EgonPfHvLink, |
794
|
|
|
"table_ts": EgonPfHvLinkTimeseries, |
795
|
|
|
"column_id": "link_id", |
796
|
|
|
"columns_ts": ["p_max_pu"], |
797
|
|
|
"ts": None, |
798
|
|
|
}, |
799
|
|
|
"Store": { |
800
|
|
|
"carrier": "battery storage", |
801
|
|
|
"table": EgonPfHvStore, |
802
|
|
|
"table_ts": EgonPfHvStoreTimeseries, |
803
|
|
|
"column_id": "store_id", |
804
|
|
|
"columns_ts": ["e_min_pu", "e_max_pu"], |
805
|
|
|
"ts": None, |
806
|
|
|
}, |
807
|
|
|
} |
808
|
|
|
|
809
|
|
|
with db.session_scope() as session: |
810
|
|
|
for node, attrs in model_ts_dict.items(): |
811
|
|
|
print(f" Loading {node} timeseries...") |
812
|
|
|
subquery = ( |
813
|
|
|
session.query(getattr(attrs["table"], attrs["column_id"])) |
814
|
|
|
.filter(attrs["table"].carrier == attrs["carrier"]) |
815
|
|
|
.filter(attrs["table"].scn_name == scenario_name) |
816
|
|
|
.subquery() |
817
|
|
|
) |
818
|
|
|
|
819
|
|
|
cols = [ |
820
|
|
|
getattr(attrs["table_ts"], c) for c in attrs["columns_ts"] |
821
|
|
|
] |
822
|
|
|
query = session.query( |
823
|
|
|
getattr(attrs["table_ts"], attrs["column_id"]), *cols |
824
|
|
|
).filter( |
825
|
|
|
getattr(attrs["table_ts"], attrs["column_id"]).in_( |
826
|
|
|
subquery |
827
|
|
|
), |
828
|
|
|
attrs["table_ts"].scn_name == scenario_name, |
829
|
|
|
) |
830
|
|
|
attrs["ts"] = pd.read_sql( |
831
|
|
|
query.statement, |
832
|
|
|
query.session.bind, |
833
|
|
|
index_col=attrs["column_id"], |
834
|
|
|
) |
835
|
|
|
|
836
|
|
|
# Check if all timeseries have 8760 steps |
837
|
|
|
print(" Checking timeranges...") |
838
|
|
|
for node, attrs in model_ts_dict.items(): |
839
|
|
|
for col in attrs["columns_ts"]: |
840
|
|
|
ts = attrs["ts"] |
841
|
|
|
invalid_ts = ts.loc[ts[col].apply(lambda _: len(_)) != 8760][ |
842
|
|
|
col |
843
|
|
|
].apply(len) |
844
|
|
|
np.testing.assert_equal( |
845
|
|
|
len(invalid_ts), |
846
|
|
|
0, |
847
|
|
|
err_msg=( |
848
|
|
|
f"{str(len(invalid_ts))} rows in timeseries do not " |
849
|
|
|
f"have 8760 timesteps. Table: " |
850
|
|
|
f"{attrs['table_ts'].__table__}, Column: {col}, IDs: " |
851
|
|
|
f"{str(list(invalid_ts.index))}" |
852
|
|
|
), |
853
|
|
|
) |
854
|
|
|
|
855
|
|
|
# Compare total energy demand in model with some approximate values |
856
|
|
|
# (per EV: 14,000 km/a, 0.17 kWh/km) |
857
|
|
|
print(" Checking energy demand in model...") |
858
|
|
|
total_energy_model = ( |
859
|
|
|
model_ts_dict["Load"]["ts"].p_set.apply(lambda _: sum(_)).sum() |
860
|
|
|
/ 1e6 |
861
|
|
|
) |
862
|
|
|
print(f" Total energy amount in model: {total_energy_model} TWh") |
863
|
|
|
total_energy_scenario_approx = ev_count_alloc * 14000 * 0.17 / 1e9 |
864
|
|
|
print( |
865
|
|
|
f" Total approximated energy amount in scenario: " |
866
|
|
|
f"{total_energy_scenario_approx} TWh" |
867
|
|
|
) |
868
|
|
|
np.testing.assert_allclose( |
869
|
|
|
total_energy_model, |
870
|
|
|
total_energy_scenario_approx, |
871
|
|
|
rtol=0.1, |
872
|
|
|
err_msg=( |
873
|
|
|
"The total energy amount in the model deviates heavily " |
874
|
|
|
"from the approximated value for current scenario." |
875
|
|
|
), |
876
|
|
|
) |
877
|
|
|
|
878
|
|
|
# Compare total storage capacity |
879
|
|
|
print(" Checking storage capacity...") |
880
|
|
|
# Load storage capacities from model |
881
|
|
|
with db.session_scope() as session: |
882
|
|
|
query = session.query( |
883
|
|
|
func.sum(EgonPfHvStore.e_nom).label("e_nom") |
884
|
|
|
).filter( |
885
|
|
|
EgonPfHvStore.scn_name == scenario_name, |
886
|
|
|
EgonPfHvStore.carrier == "battery storage", |
887
|
|
|
) |
888
|
|
|
storage_capacity_model = ( |
889
|
|
|
pd.read_sql( |
890
|
|
|
query.statement, query.session.bind, index_col=None |
891
|
|
|
).e_nom.sum() |
892
|
|
|
/ 1e3 |
893
|
|
|
) |
894
|
|
|
print( |
895
|
|
|
f" Total storage capacity ({EgonPfHvStore.__table__}): " |
896
|
|
|
f"{round(storage_capacity_model, 1)} GWh" |
897
|
|
|
) |
898
|
|
|
|
899
|
|
|
# Load occurences of each EV |
900
|
|
|
with db.session_scope() as session: |
901
|
|
|
query = ( |
902
|
|
|
session.query( |
903
|
|
|
EgonEvMvGridDistrict.bus_id, |
904
|
|
|
EgonEvPool.type, |
905
|
|
|
func.count(EgonEvMvGridDistrict.egon_ev_pool_ev_id).label( |
906
|
|
|
"count" |
907
|
|
|
), |
908
|
|
|
) |
909
|
|
|
.join( |
910
|
|
|
EgonEvPool, |
911
|
|
|
EgonEvPool.ev_id |
912
|
|
|
== EgonEvMvGridDistrict.egon_ev_pool_ev_id, |
913
|
|
|
) |
914
|
|
|
.filter( |
915
|
|
|
EgonEvMvGridDistrict.scenario == scenario_name, |
916
|
|
|
EgonEvMvGridDistrict.scenario_variation |
917
|
|
|
== scenario_var_name, |
918
|
|
|
EgonEvPool.scenario == scenario_name, |
919
|
|
|
) |
920
|
|
|
.group_by(EgonEvMvGridDistrict.bus_id, EgonEvPool.type) |
921
|
|
|
) |
922
|
|
|
count_per_ev_all = pd.read_sql( |
923
|
|
|
query.statement, query.session.bind, index_col="bus_id" |
924
|
|
|
) |
925
|
|
|
count_per_ev_all["bat_cap"] = count_per_ev_all.type.map( |
926
|
|
|
meta_tech_data.battery_capacity |
927
|
|
|
) |
928
|
|
|
count_per_ev_all["bat_cap_total_MWh"] = ( |
929
|
|
|
count_per_ev_all["count"] * count_per_ev_all.bat_cap / 1e3 |
930
|
|
|
) |
931
|
|
|
storage_capacity_simbev = count_per_ev_all.bat_cap_total_MWh.div( |
932
|
|
|
1e3 |
933
|
|
|
).sum() |
934
|
|
|
print( |
935
|
|
|
f" Total storage capacity (simBEV): " |
936
|
|
|
f"{round(storage_capacity_simbev, 1)} GWh" |
937
|
|
|
) |
938
|
|
|
|
939
|
|
|
np.testing.assert_allclose( |
940
|
|
|
storage_capacity_model, |
941
|
|
|
storage_capacity_simbev, |
942
|
|
|
rtol=0.01, |
943
|
|
|
err_msg=( |
944
|
|
|
"The total storage capacity in the model deviates heavily " |
945
|
|
|
"from the input data provided by simBEV for current scenario." |
946
|
|
|
), |
947
|
|
|
) |
948
|
|
|
|
949
|
|
|
# Check SoC storage constraint: e_min_pu < e_max_pu for all timesteps |
950
|
|
|
print(" Validating SoC constraints...") |
951
|
|
|
stores_with_invalid_soc = [] |
952
|
|
|
for idx, row in model_ts_dict["Store"]["ts"].iterrows(): |
953
|
|
|
ts = row[["e_min_pu", "e_max_pu"]] |
954
|
|
|
x = np.array(ts.e_min_pu) > np.array(ts.e_max_pu) |
955
|
|
|
if x.any(): |
956
|
|
|
stores_with_invalid_soc.append(idx) |
957
|
|
|
|
958
|
|
|
np.testing.assert_equal( |
959
|
|
|
len(stores_with_invalid_soc), |
960
|
|
|
0, |
961
|
|
|
err_msg=( |
962
|
|
|
f"The store constraint e_min_pu < e_max_pu does not apply " |
963
|
|
|
f"for some storages in {EgonPfHvStoreTimeseries.__table__}. " |
964
|
|
|
f"Invalid store_ids: {stores_with_invalid_soc}" |
965
|
|
|
), |
966
|
|
|
) |
967
|
|
|
|
968
|
|
|
def check_model_data_lowflex_eGon2035(): |
969
|
|
|
# TODO: Add eGon100RE_lowflex |
970
|
|
|
print("") |
971
|
|
|
print("SCENARIO: eGon2035_lowflex") |
972
|
|
|
|
973
|
|
|
# Compare driving load and charging load |
974
|
|
|
print(" Loading eGon2035 model timeseries: driving load...") |
975
|
|
|
with db.session_scope() as session: |
976
|
|
|
query = ( |
977
|
|
|
session.query( |
978
|
|
|
EgonPfHvLoad.load_id, |
979
|
|
|
EgonPfHvLoadTimeseries.p_set, |
980
|
|
|
) |
981
|
|
|
.join( |
982
|
|
|
EgonPfHvLoadTimeseries, |
983
|
|
|
EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
984
|
|
|
) |
985
|
|
|
.filter( |
986
|
|
|
EgonPfHvLoad.carrier == "land transport EV", |
987
|
|
|
EgonPfHvLoad.scn_name == "eGon2035", |
988
|
|
|
EgonPfHvLoadTimeseries.scn_name == "eGon2035", |
989
|
|
|
) |
990
|
|
|
) |
991
|
|
|
model_driving_load = pd.read_sql( |
992
|
|
|
query.statement, query.session.bind, index_col=None |
993
|
|
|
) |
994
|
|
|
driving_load = np.array(model_driving_load.p_set.to_list()).sum(axis=0) |
995
|
|
|
|
996
|
|
|
print( |
997
|
|
|
" Loading eGon2035_lowflex model timeseries: dumb charging " |
998
|
|
|
"load..." |
999
|
|
|
) |
1000
|
|
|
with db.session_scope() as session: |
1001
|
|
|
query = ( |
1002
|
|
|
session.query( |
1003
|
|
|
EgonPfHvLoad.load_id, |
1004
|
|
|
EgonPfHvLoadTimeseries.p_set, |
1005
|
|
|
) |
1006
|
|
|
.join( |
1007
|
|
|
EgonPfHvLoadTimeseries, |
1008
|
|
|
EgonPfHvLoadTimeseries.load_id == EgonPfHvLoad.load_id, |
1009
|
|
|
) |
1010
|
|
|
.filter( |
1011
|
|
|
EgonPfHvLoad.carrier == "land transport EV", |
1012
|
|
|
EgonPfHvLoad.scn_name == "eGon2035_lowflex", |
1013
|
|
|
EgonPfHvLoadTimeseries.scn_name == "eGon2035_lowflex", |
1014
|
|
|
) |
1015
|
|
|
) |
1016
|
|
|
model_charging_load_lowflex = pd.read_sql( |
1017
|
|
|
query.statement, query.session.bind, index_col=None |
1018
|
|
|
) |
1019
|
|
|
charging_load = np.array( |
1020
|
|
|
model_charging_load_lowflex.p_set.to_list() |
1021
|
|
|
).sum(axis=0) |
1022
|
|
|
|
1023
|
|
|
# Ratio of driving and charging load should be 0.9 due to charging |
1024
|
|
|
# efficiency |
1025
|
|
|
print(" Compare cumulative loads...") |
1026
|
|
|
print(f" Driving load (eGon2035): {driving_load.sum() / 1e6} TWh") |
1027
|
|
|
print( |
1028
|
|
|
f" Dumb charging load (eGon2035_lowflex): " |
1029
|
|
|
f"{charging_load.sum() / 1e6} TWh" |
1030
|
|
|
) |
1031
|
|
|
driving_load_theoretical = ( |
1032
|
|
|
float(meta_run_config.eta_cp) * charging_load.sum() |
|
|
|
|
1033
|
|
|
) |
1034
|
|
|
np.testing.assert_allclose( |
1035
|
|
|
driving_load.sum(), |
1036
|
|
|
driving_load_theoretical, |
1037
|
|
|
rtol=0.01, |
1038
|
|
|
err_msg=( |
1039
|
|
|
f"The driving load (eGon2035) deviates by more than 1% " |
1040
|
|
|
f"from the theoretical driving load calculated from charging " |
1041
|
|
|
f"load (eGon2035_lowflex) with an efficiency of " |
1042
|
|
|
f"{float(meta_run_config.eta_cp)}." |
1043
|
|
|
), |
1044
|
|
|
) |
1045
|
|
|
|
1046
|
|
|
print("=====================================================") |
1047
|
|
|
print("=== SANITY CHECKS FOR MOTORIZED INDIVIDUAL TRAVEL ===") |
1048
|
|
|
print("=====================================================") |
1049
|
|
|
|
1050
|
|
|
for scenario_name in ["eGon2035", "eGon100RE"]: |
1051
|
|
|
scenario_var_name = DATASET_CFG["scenario"]["variation"][scenario_name] |
1052
|
|
|
|
1053
|
|
|
print("") |
1054
|
|
|
print(f"SCENARIO: {scenario_name}, VARIATION: {scenario_var_name}") |
1055
|
|
|
|
1056
|
|
|
# Load scenario params for scenario and scenario variation |
1057
|
|
|
scenario_variation_parameters = get_sector_parameters( |
1058
|
|
|
"mobility", scenario=scenario_name |
1059
|
|
|
)["motorized_individual_travel"][scenario_var_name] |
1060
|
|
|
|
1061
|
|
|
# Load simBEV run config and tech data |
1062
|
|
|
meta_run_config = read_simbev_metadata_file( |
1063
|
|
|
scenario_name, "config" |
1064
|
|
|
).loc["basic"] |
1065
|
|
|
meta_tech_data = read_simbev_metadata_file(scenario_name, "tech_data") |
1066
|
|
|
|
1067
|
|
|
print("") |
1068
|
|
|
print("Checking EV counts...") |
1069
|
|
|
ev_count_alloc = check_ev_allocation() |
1070
|
|
|
|
1071
|
|
|
print("") |
1072
|
|
|
print("Checking trip data...") |
1073
|
|
|
check_trip_data() |
1074
|
|
|
|
1075
|
|
|
print("") |
1076
|
|
|
print("Checking model data...") |
1077
|
|
|
check_model_data() |
1078
|
|
|
|
1079
|
|
|
print("") |
1080
|
|
|
check_model_data_lowflex_eGon2035() |
1081
|
|
|
|
1082
|
|
|
print("=====================================================") |
1083
|
|
|
|
1084
|
|
|
|
1085
|
|
|
def residential_electricity_annual_sum(rtol=1e-5): |
1086
|
|
|
"""Sanity check for dataset electricity_demand_timeseries |
1087
|
|
|
|
1088
|
|
|
Aggregate the annual demand of all census cells at NUTS3 to compare |
1089
|
|
|
with initial scaling parameters from DemandRegio. |
1090
|
|
|
""" |
1091
|
|
|
|
1092
|
|
|
df_nuts3_annual_sum = db.select_dataframe( |
1093
|
|
|
sql=""" |
1094
|
|
|
SELECT dr.nuts3, dr.scenario, dr.demand_regio_sum, profiles.profile_sum |
1095
|
|
|
FROM ( |
1096
|
|
|
SELECT scenario, SUM(demand) AS profile_sum, vg250_nuts3 |
1097
|
|
|
FROM demand.egon_demandregio_zensus_electricity AS egon, |
1098
|
|
|
boundaries.egon_map_zensus_vg250 AS boundaries |
1099
|
|
|
Where egon.zensus_population_id = boundaries.zensus_population_id |
1100
|
|
|
AND sector = 'residential' |
1101
|
|
|
GROUP BY vg250_nuts3, scenario |
1102
|
|
|
) AS profiles |
1103
|
|
|
JOIN ( |
1104
|
|
|
SELECT nuts3, scenario, sum(demand) AS demand_regio_sum |
1105
|
|
|
FROM demand.egon_demandregio_hh |
1106
|
|
|
GROUP BY year, scenario, nuts3 |
1107
|
|
|
) AS dr |
1108
|
|
|
ON profiles.vg250_nuts3 = dr.nuts3 and profiles.scenario = dr.scenario |
1109
|
|
|
""" |
1110
|
|
|
) |
1111
|
|
|
|
1112
|
|
|
np.testing.assert_allclose( |
1113
|
|
|
actual=df_nuts3_annual_sum["profile_sum"], |
1114
|
|
|
desired=df_nuts3_annual_sum["demand_regio_sum"], |
1115
|
|
|
rtol=rtol, |
1116
|
|
|
verbose=False, |
1117
|
|
|
) |
1118
|
|
|
|
1119
|
|
|
print( |
1120
|
|
|
"Aggregated annual residential electricity demand" |
1121
|
|
|
" matches with DemandRegio at NUTS-3." |
1122
|
|
|
) |
1123
|
|
|
|
1124
|
|
|
|
1125
|
|
|
def residential_electricity_hh_refinement(rtol=1e-5): |
1126
|
|
|
"""Sanity check for dataset electricity_demand_timeseries |
1127
|
|
|
|
1128
|
|
|
Check sum of aggregated household types after refinement method |
1129
|
|
|
was applied and compare it to the original census values.""" |
1130
|
|
|
|
1131
|
|
|
df_refinement = db.select_dataframe( |
1132
|
|
|
sql=""" |
1133
|
|
|
SELECT refined.nuts3, refined.characteristics_code, |
1134
|
|
|
refined.sum_refined::int, census.sum_census::int |
1135
|
|
|
FROM( |
1136
|
|
|
SELECT nuts3, characteristics_code, SUM(hh_10types) as sum_refined |
1137
|
|
|
FROM society.egon_destatis_zensus_household_per_ha_refined |
1138
|
|
|
GROUP BY nuts3, characteristics_code) |
1139
|
|
|
AS refined |
1140
|
|
|
JOIN( |
1141
|
|
|
SELECT t.nuts3, t.characteristics_code, sum(orig) as sum_census |
1142
|
|
|
FROM( |
1143
|
|
|
SELECT nuts3, cell_id, characteristics_code, |
1144
|
|
|
sum(DISTINCT(hh_5types))as orig |
1145
|
|
|
FROM society.egon_destatis_zensus_household_per_ha_refined |
1146
|
|
|
GROUP BY cell_id, characteristics_code, nuts3) AS t |
1147
|
|
|
GROUP BY t.nuts3, t.characteristics_code ) AS census |
1148
|
|
|
ON refined.nuts3 = census.nuts3 |
1149
|
|
|
AND refined.characteristics_code = census.characteristics_code |
1150
|
|
|
""" |
1151
|
|
|
) |
1152
|
|
|
|
1153
|
|
|
np.testing.assert_allclose( |
1154
|
|
|
actual=df_refinement["sum_refined"], |
1155
|
|
|
desired=df_refinement["sum_census"], |
1156
|
|
|
rtol=rtol, |
1157
|
|
|
verbose=False, |
1158
|
|
|
) |
1159
|
|
|
|
1160
|
|
|
print("All Aggregated household types match at NUTS-3.") |
1161
|
|
|
|