eGon2035

Central module containing code dealing with gas neighbours for eGon2035

calc_capacities()[source]

Calculates gas production capacities of neighbouring countries

For each neigbouring country, this function calculates the gas generation capacity in 2035 using the function calc_capacity_per_year() for 2030 and 2040 and interpolates the results. These capacities include LNG import, as well as conventional and biogas production. Two conventional gas generators are added for Norway and Russia interpolating the supply potential values from the TYNPD 2020 for 2030 and 2040.

Returns:grouped_capacities (pandas.DataFrame) – Gas production capacities per foreign node
calc_capacity_per_year(df, lng, year)[source]

Calculates gas production capacities for a specified year

For a specified year and for the foreign country nodes this function calculates the gas production capacities, considering the gas (conventional and bio) production capacities from TYNDP data and the LNG import capacities from Scigrid gas data.

The columns of the returned dataframe are the following:
  • Value_bio_year: biogas production capacity (in GWh/d)
  • Value_conv_year: conventional gas production capacity including LNG imports (in GWh/d)
  • CH4_year: total gas production capacity (in GWh/d). This value is calculated using the peak production value from the TYNDP.
  • e_nom_max_year: total gas production capacity representative for the whole year (in GWh/d). This value is calculated using the average production value from the TYNDP and will then be used to limit the energy that can be generated in one year.
  • share_LNG_year: share of LGN import capacity in the total gas production capacity
  • share_conv_pipe_year: share of conventional gas extraction capacity in the total gas production capacity
  • share_bio_year: share of biogas production capacity in the total gas production capacity
Parameters:
  • df (pandas.DataFrame) – Gas (conventional and bio) production capacities from TYNDP (in GWh/d)
  • lng (pandas.Series) – LNG terminal capacities per foreign country node (in GWh/d)
  • year (int) – Year to calculate gas production capacities for
Returns:

df_year (pandas.DataFrame) – Gas production capacities (in GWh/d) per foreign country node

calc_ch4_storage_capacities()[source]

Calculate CH4 storage capacities for neighboring countries

Returns:
  • ch4_storage_capacities (pandas.DataFrame)
  • Methane gas storage capacities per country in MWh
calc_global_ch4_demand(Norway_global_demand_1y)[source]

Calculates global CH4 demands abroad for eGon2035 scenario

The data comes from TYNDP 2020 according to NEP 2021 from the scenario ‘Distributed Energy’; linear interpolates between 2030 and 2040.

Returns:pandas.DataFrame – Global (yearly) CH4 final demand per foreign node
calc_global_power_to_h2_demand()[source]

Calculate H2 demand abroad for eGon2035 scenario

Calculates global power demand abroad linked to H2 production. The data comes from TYNDP 2020 according to NEP 2021 from the scenario ‘Distributed Energy’; linear interpolate between 2030 and 2040.

Returns:global_power_to_h2_demand (pandas.DataFrame) – Global hourly power-to-h2 demand per foreign node
calculate_ch4_grid_capacities()[source]

Calculates CH4 grid capacities for foreign countries based on TYNDP-data

Returns:Neighbouring_pipe_capacities_list (pandas.DataFrame) – Table containing the CH4 grid capacity for each foreign country
calculate_ocgt_capacities()[source]

Calculate gas turbine capacities abroad for eGon2035

Calculate gas turbine capacities abroad for eGon2035 based on TYNDP 2020, scenario “Distributed Energy”; interpolated between 2030 and 2040

Returns:df_ocgt (pandas.DataFrame) – Gas turbine capacities per foreign node
get_foreign_gas_bus_id(carrier='CH4')[source]

Calculate the etrago bus id based on the geometry

Map node_ids from TYNDP and etragos bus_id

Parameters:carrier (str) – Name of the carrier
Returns:pandas.Series – List of mapped node_ids from TYNDP and etragos bus_id
grid()[source]

Insert data from TYNDP 2020 according to NEP 2021 Scenario ‘Distributed Energy; linear interpolate between 2030 and 2040

Returns:None
import_ch4_demandTS()[source]

Calculate global CH4 demand in Norway and CH4 demand profile

Import from the PyPSA-eur-sec run the time series of residential rural heat per neighbor country. This time series is used to calculate:

  • the global (yearly) heat demand of Norway (that will be supplied by CH4)
  • the normalized CH4 hourly resolved demand profile
Returns:
  • Norway_global_demand (Float) – Yearly heat demand of Norway in MWh
  • neighbor_loads_t (pandas.DataFrame) – Normalized CH4 hourly resolved demand profiles per neighbor country
insert_ch4_demand(global_demand, normalized_ch4_demandTS)[source]

Insert CH4 demands abroad into the database for eGon2035

Parameters:
  • global_demand (pandas.DataFrame) – Global CH4 demand per foreign node in 1 year
  • gas_demandTS (pandas.DataFrame) – Normalized time series of the demand per foreign country
Returns:

None

insert_generators(gen)[source]

Insert gas generators for foreign countries into the database

Insert gas generators for foreign countries into the database. The marginal cost of the methane is calculated as the sum of the imported LNG cost, the conventional natural gas cost and the biomethane cost, weighted by their share in the total import/ production capacity. LNG gas is considered to be 30% more expensive than the natural gas transported by pipelines (source: iwd, 2022).

Parameters:gen (pandas.DataFrame) – Gas production capacities per foreign node and energy carrier
Returns:None
insert_ocgt_abroad()[source]

Insert gas turbine capacities abroad for eGon2035 in the database

Parameters:df_ocgt (pandas.DataFrame) – Gas turbine capacities per foreign node
Returns:None
insert_power_to_h2_demand(global_power_to_h2_demand)[source]

Insert H2 demands into database for eGon2035

Parameters:global_power_to_h2_demand (pandas.DataFrame) – Global hourly power-to-h2 demand per foreign node
Returns:None
insert_storage(ch4_storage_capacities)[source]

Insert CH4 storage capacities into the database for eGon2035

Parameters:ch4_storage_capacities (pandas.DataFrame) – Methane gas storage capacities per country in MWh
Returns:None
read_LNG_capacities()[source]

Read LNG import capacities from Scigrid gas data

Returns:IGGIELGN_LNGs (pandas.Series) – LNG terminal capacities per foreign country node (in GWh/d)
tyndp_gas_demand()[source]

Insert gas demands abroad for eGon2035

Insert CH4 and H2 demands abroad for eGon2035 by executing the following steps:

Returns:None
tyndp_gas_generation()[source]

Insert data from TYNDP 2020 according to NEP 2021 Scenario ‘Distributed Energy’; linear interpolate between 2030 and 2040

Returns:None