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 powertoh2 demand per foreign node

calculate_ch4_grid_capacities
()[source]¶ Calculates CH4 grid capacities for foreign countries based on TYNDPdata
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 PyPSAeursec 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 powertoh2 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:
 CH4
 Calculation of the global CH4 demand in Norway and the
CH4 demand profile by executing the function
import_ch4_demandTS()
 Calculation of the global CH4 demands by executing the
function
calc_global_ch4_demand()
 Insertion of the CH4 loads and their associated time
series in the database by executing the function
insert_ch4_demand()
 Calculation of the global CH4 demand in Norway and the
CH4 demand profile by executing the function
 H2
 Calculation of the global power demand abroad linked
to H2 production by executing the function
calc_global_power_to_h2_demand()
 Insertion of these loads in the database by executing the
function
insert_power_to_h2_demand()
 Calculation of the global power demand abroad linked
to H2 production by executing the function
Returns: None