chp

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

class Chp(dependencies)[source]

Bases: egon.data.datasets.Dataset

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

supply.egon_chp_plants is created and filled
supply.egon_mastr_conventional_without_chp is created and filled

name: str = 'Chp'

version: str = '0.0.10'

class EgonChp(**kwargs)[source]

Bases: sqlalchemy.orm.decl_api.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: sqlalchemy.orm.decl_api.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