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@@ 1514-1587 (lines=74) @@
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log.info(f"Peak load for {scenario} exported to DB!") |
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def get_cts_heat_peak_load(): |
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""" |
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Get heat peak load of all CTS buildings for both scenarios and store in DB. |
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""" |
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log.info("Start logging!") |
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BuildingHeatPeakLoads.__table__.create(bind=engine, checkfirst=True) |
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# Delete rows with cts demand |
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with db.session_scope() as session: |
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session.query(BuildingHeatPeakLoads).filter( |
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BuildingHeatPeakLoads.sector == "cts" |
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).delete() |
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log.info("Cts heat peak load removed from DB!") |
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for scenario in ["eGon2035", "eGon100RE"]: |
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with db.session_scope() as session: |
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cells_query = session.query( |
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EgonCtsElectricityDemandBuildingShare |
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).filter( |
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EgonCtsElectricityDemandBuildingShare.scenario == scenario |
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) |
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df_demand_share = pd.read_sql( |
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cells_query.statement, cells_query.session.bind, index_col=None |
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) |
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log.info(f"Retrieved demand share for scenario: {scenario}") |
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with db.session_scope() as session: |
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cells_query = session.query(EgonEtragoHeatCts).filter( |
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EgonEtragoHeatCts.scn_name == scenario |
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) |
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df_cts_profiles = pd.read_sql( |
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cells_query.statement, |
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cells_query.session.bind, |
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) |
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log.info(f"Retrieved substation profiles for scenario: {scenario}") |
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df_cts_profiles = pd.DataFrame.from_dict( |
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df_cts_profiles.set_index("bus_id")["p_set"].to_dict(), |
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orient="columns", |
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) |
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df_peak_load = pd.merge( |
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left=df_cts_profiles.max().astype(float).rename("max"), |
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right=df_demand_share, |
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left_index=True, |
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right_on="bus_id", |
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) |
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# Convert unit from MWh to W |
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df_peak_load["max"] = df_peak_load["max"] * 1e6 |
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df_peak_load["peak_load_in_w"] = ( |
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df_peak_load["max"] * df_peak_load["profile_share"] |
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) |
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log.info(f"Peak load for {scenario} determined!") |
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# TODO remove after #772 |
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df_peak_load.rename(columns={"id": "building_id"}, inplace=True) |
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df_peak_load["sector"] = "cts" |
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# # Write peak loads into db |
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write_table_to_postgres( |
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df_peak_load, |
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BuildingHeatPeakLoads, |
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engine=engine, |
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drop=False, |
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index=False, |
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if_exists="append", |
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) |
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log.info(f"Peak load for {scenario} exported to DB!") |
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@@ 1440-1511 (lines=72) @@
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log.info("Profile share exported to DB!") |
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def get_cts_electricity_peak_load(): |
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""" |
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Get electricity peak load of all CTS buildings for both scenarios and |
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store in DB. |
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""" |
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log.info("Start logging!") |
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BuildingElectricityPeakLoads.__table__.create(bind=engine, checkfirst=True) |
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# Delete rows with cts demand |
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with db.session_scope() as session: |
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session.query(BuildingElectricityPeakLoads).filter( |
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BuildingElectricityPeakLoads.sector == "cts" |
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).delete() |
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log.info("Cts electricity peak load removed from DB!") |
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for scenario in ["eGon2035", "eGon100RE"]: |
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with db.session_scope() as session: |
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cells_query = session.query( |
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EgonCtsElectricityDemandBuildingShare |
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).filter( |
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EgonCtsElectricityDemandBuildingShare.scenario == scenario |
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) |
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df_demand_share = pd.read_sql( |
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cells_query.statement, cells_query.session.bind, index_col=None |
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) |
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with db.session_scope() as session: |
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cells_query = session.query(EgonEtragoElectricityCts).filter( |
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EgonEtragoElectricityCts.scn_name == scenario |
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) |
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df_cts_profiles = pd.read_sql( |
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cells_query.statement, |
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cells_query.session.bind, |
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) |
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df_cts_profiles = pd.DataFrame.from_dict( |
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df_cts_profiles.set_index("bus_id")["p_set"].to_dict(), |
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orient="columns", |
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) |
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df_peak_load = pd.merge( |
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left=df_cts_profiles.max().astype(float).rename("max"), |
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right=df_demand_share, |
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left_index=True, |
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right_on="bus_id", |
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) |
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# Convert unit from MWh to W |
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df_peak_load["max"] = df_peak_load["max"] * 1e6 |
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df_peak_load["peak_load_in_w"] = ( |
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df_peak_load["max"] * df_peak_load["profile_share"] |
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) |
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log.info(f"Peak load for {scenario} determined!") |
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# TODO remove after #772 |
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df_peak_load.rename(columns={"id": "building_id"}, inplace=True) |
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df_peak_load["sector"] = "cts" |
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# # Write peak loads into db |
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write_table_to_postgres( |
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df_peak_load, |
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BuildingElectricityPeakLoads, |
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engine=engine, |
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drop=False, |
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index=False, |
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if_exists="append", |
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) |
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log.info(f"Peak load for {scenario} exported to DB!") |
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def get_cts_heat_peak_load(): |
openego /
eGon-data
