chp

The central module containing all code dealing with combined heat and power (CHP) plants.

class Chp(dependencies)[source]

Bases: Dataset

name: str = 'Chp'
sources: DatasetSources = DatasetSources(tables={'list_conv_pp': 'supply.egon_nep_2021_conventional_powerplants', 'egon_mv_grid_district': 'grid.egon_mv_grid_district', 'ehv_voronoi': 'grid.egon_ehv_substation_voronoi', 'etrago_buses': 'grid.egon_etrago_bus', 'osm_landuse': 'openstreetmap.osm_landuse', 'osm_polygon': 'openstreetmap.osm_polygon', 'district_heating_areas': 'demand.egon_district_heating_areas', 'industrial_demand_osm': 'demand.egon_demandregio_osm_ind_electricity', 'vg250_lan': 'boundaries.vg250_lan', 'scenario_capacities': 'supply.egon_scenario_capacities'}, files={'mastr_combustion': './bnetza_mastr/dump_2025-02-09/bnetza_mastr_combustion_cleaned.csv', 'mastr_location': './bnetza_mastr/dump_2025-02-09/location_elec_generation_raw.csv', 'mastr_biomass': './bnetza_mastr/dump_2025-02-09/bnetza_mastr_biomass_cleaned.csv'}, urls={})

The sources used by the datasets. Could be tables, files and urls

targets: DatasetTargets = DatasetTargets(tables={'chp_table': 'supply.egon_chp_plants', 'mastr_conventional_without_chp': 'supply.egon_mastr_conventional_without_chp'}, files={})

Extract combined heat and power plants for each scenario

This dataset creates combined heat and power (CHP) plants for each scenario and defines their use case. The method bases on existing CHP plants from Marktstammdatenregister. For the eGon2035 scenario, a list of CHP plans from the grid operator is used for new largescale CHP plants. CHP < 10MW are randomly distributed. Depending on the distance to a district heating grid, it is decided if the CHP is used to supply a district heating grid or used by an industrial site.

Dependencies
Resulting tables
version: str = '0.0.12'
class EgonChp(**kwargs)[source]

Bases: Base

carrier
ch4_bus_id
district_heating
district_heating_area_id
el_capacity
electrical_bus_id
geom
id
scenario
source_id
sources
th_capacity
voltage_level
class EgonMaStRConventinalWithoutChp(**kwargs)[source]

Bases: Base

EinheitMastrNummer
carrier
city
el_capacity
federal_state
geometry
id
plz
assign_heat_bus()[source]

Selects heat_bus for chps used in district heating.

Parameters:

scenario (str, optional) – Name of the corresponding scenario. The default is ‘eGon2035’.

Returns:

None.

create_tables()[source]

Create tables for chp data :returns: None.

extension_BB()[source]
extension_BE()[source]
extension_BW()[source]
extension_BY()[source]
extension_HB()[source]
extension_HE()[source]
extension_HH()[source]
extension_MV()[source]
extension_NS()[source]
extension_NW()[source]
extension_RP()[source]
extension_SH()[source]
extension_SL()[source]
extension_SN()[source]
extension_ST()[source]
extension_TH()[source]
insert_biomass_chp(scenario)[source]

Insert biomass chp plants of future scenario

Parameters:

scenario (str) – Name of scenario.

Returns:

None.

insert_chp_egon100re()[source]

Insert CHP plants for eGon100RE considering results from pypsa-eur-sec

Returns:

None.

insert_chp_egon2035()[source]

Insert CHP plants for eGon2035 considering NEP and MaStR data

Returns:

None.

insert_chp_statusquo(scn='status2019')[source]
metadata()[source]

Write metadata for heat supply tables

Returns:

None.

nearest(row, df, centroid=False, row_geom_col='geometry', df_geom_col='geometry', src_column=None)[source]

Finds the nearest point and returns the specified column values

Parameters:

  • row (pandas.Series) – Data to which the nearest data of df is assigned.

  • df (pandas.DataFrame) – Data which includes all options for the nearest neighbor alogrithm.

  • centroid (boolean) – Use centroid geoemtry. The default is False.

  • row_geom_col (str, optional) – Name of row’s geometry column. The default is ‘geometry’.

  • df_geom_col (str, optional) – Name of df’s geometry column. The default is ‘geometry’.

  • src_column (str, optional) – Name of returned df column. The default is None.

Returns:

value (pandas.Series) – Values of specified column of df