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Merge branch 'master' into custom-extra-functionality

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Fabian Neumann 2024-01-04 08:32:29 +01:00
commit b4fb395158
34 changed files with 594 additions and 208 deletions
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2
.pre-commit-config.yaml
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@ -50,7 +50,7 @@ repos:
- id: blackdoc - id: blackdoc
# Formatting with "black" coding style # Formatting with "black" coding style
- repo: https://github.com/psf/black - repo: https://github.com/psf/black-pre-commit-mirror
rev: 23.12.1 rev: 23.12.1
hooks: hooks:
# Format Python files # Format Python files

2
Snakefile
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@ -14,7 +14,7 @@ from snakemake.utils import min_version
min_version("7.7") min_version("7.7")
if not exists("config/config.yaml"): if not exists("config/config.yaml") and exists("config/config.default.yaml"):
copyfile("config/config.default.yaml", "config/config.yaml") copyfile("config/config.default.yaml", "config/config.yaml")

40
config/config.default.yaml
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@ -158,6 +158,7 @@ renewable:
resource: resource:
method: wind method: wind
turbine: Vestas_V112_3MW turbine: Vestas_V112_3MW
add_cutout_windspeed: true
capacity_per_sqkm: 3 capacity_per_sqkm: 3
# correction_factor: 0.93 # correction_factor: 0.93
corine: corine:
@ -166,13 +167,13 @@ renewable:
distance_grid_codes: [1, 2, 3, 4, 5, 6] distance_grid_codes: [1, 2, 3, 4, 5, 6]
natura: true natura: true
excluder_resolution: 100 excluder_resolution: 100
potential: simple # or conservative
clip_p_max_pu: 1.e-2 clip_p_max_pu: 1.e-2
offwind-ac: offwind-ac:
cutout: europe-2013-era5 cutout: europe-2013-era5
resource: resource:
method: wind method: wind
turbine: NREL_ReferenceTurbine_5MW_offshore turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
add_cutout_windspeed: true
capacity_per_sqkm: 2 capacity_per_sqkm: 2
correction_factor: 0.8855 correction_factor: 0.8855
corine: [44, 255] corine: [44, 255]
@ -181,13 +182,13 @@ renewable:
max_depth: 50 max_depth: 50
max_shore_distance: 30000 max_shore_distance: 30000
excluder_resolution: 200 excluder_resolution: 200
potential: simple # or conservative
clip_p_max_pu: 1.e-2 clip_p_max_pu: 1.e-2
offwind-dc: offwind-dc:
cutout: europe-2013-era5 cutout: europe-2013-era5
resource: resource:
method: wind method: wind
turbine: NREL_ReferenceTurbine_5MW_offshore turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
add_cutout_windspeed: true
capacity_per_sqkm: 2 capacity_per_sqkm: 2
correction_factor: 0.8855 correction_factor: 0.8855
corine: [44, 255] corine: [44, 255]
@ -196,7 +197,6 @@ renewable:
max_depth: 50 max_depth: 50
min_shore_distance: 30000 min_shore_distance: 30000
excluder_resolution: 200 excluder_resolution: 200
potential: simple # or conservative
clip_p_max_pu: 1.e-2 clip_p_max_pu: 1.e-2
solar: solar:
cutout: europe-2013-sarah cutout: europe-2013-sarah
@ -211,7 +211,6 @@ renewable:
corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32] corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
natura: true natura: true
excluder_resolution: 100 excluder_resolution: 100
potential: simple # or conservative
clip_p_max_pu: 1.e-2 clip_p_max_pu: 1.e-2
hydro: hydro:
cutout: europe-2013-era5 cutout: europe-2013-era5
@ -448,7 +447,6 @@ sector:
solar_cf_correction: 0.788457 # = >>> 1/1.2683 solar_cf_correction: 0.788457 # = >>> 1/1.2683
marginal_cost_storage: 0. #1e-4 marginal_cost_storage: 0. #1e-4
methanation: true methanation: true
helmeth: false
coal_cc: false coal_cc: false
dac: true dac: true
co2_vent: false co2_vent: false
@ -477,14 +475,28 @@ sector:
- nearshore # within 50 km of sea - nearshore # within 50 km of sea
# - offshore # - offshore
ammonia: false ammonia: false
min_part_load_fischer_tropsch: 0.9 min_part_load_fischer_tropsch: 0.7
min_part_load_methanolisation: 0.5 min_part_load_methanolisation: 0.3
min_part_load_methanation: 0.3
use_fischer_tropsch_waste_heat: true use_fischer_tropsch_waste_heat: true
use_haber_bosch_waste_heat: true
use_methanolisation_waste_heat: true
use_methanation_waste_heat: true
use_fuel_cell_waste_heat: true use_fuel_cell_waste_heat: true
use_electrolysis_waste_heat: false use_electrolysis_waste_heat: true
electricity_distribution_grid: true electricity_distribution_grid: true
electricity_distribution_grid_cost_factor: 1.0 electricity_distribution_grid_cost_factor: 1.0
electricity_grid_connection: true electricity_grid_connection: true
transmission_efficiency:
DC:
efficiency_static: 0.98
efficiency_per_1000km: 0.977
H2 pipeline:
efficiency_per_1000km: 1 # 0.979
compression_per_1000km: 0.019
gas pipeline:
efficiency_per_1000km: 1 #0.977
compression_per_1000km: 0.01
H2_network: true H2_network: true
gas_network: false gas_network: false
H2_retrofit: false H2_retrofit: false
@ -494,6 +506,7 @@ sector:
gas_distribution_grid_cost_factor: 1.0 gas_distribution_grid_cost_factor: 1.0
biomass_spatial: false biomass_spatial: false
biomass_transport: false biomass_transport: false
biogas_upgrading_cc: false
conventional_generation: conventional_generation:
OCGT: gas OCGT: gas
biomass_to_liquid: false biomass_to_liquid: false
@ -544,8 +557,8 @@ industry:
MWh_NH3_per_tNH3: 5.166 MWh_NH3_per_tNH3: 5.166
MWh_CH4_per_tNH3_SMR: 10.8 MWh_CH4_per_tNH3_SMR: 10.8
MWh_elec_per_tNH3_SMR: 0.7 MWh_elec_per_tNH3_SMR: 0.7
MWh_H2_per_tNH3_electrolysis: 6.5 MWh_H2_per_tNH3_electrolysis: 5.93
MWh_elec_per_tNH3_electrolysis: 1.17 MWh_elec_per_tNH3_electrolysis: 0.2473
MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
NH3_process_emissions: 24.5 NH3_process_emissions: 24.5
petrochemical_process_emissions: 25.5 petrochemical_process_emissions: 25.5
@ -776,6 +789,7 @@ plotting:
fossil gas: '#e05b09' fossil gas: '#e05b09'
natural gas: '#e05b09' natural gas: '#e05b09'
biogas to gas: '#e36311' biogas to gas: '#e36311'
biogas to gas CC: '#e51245'
CCGT: '#a85522' CCGT: '#a85522'
CCGT marginal: '#a85522' CCGT marginal: '#a85522'
allam: '#B98F76' allam: '#B98F76'
@ -877,6 +891,7 @@ plotting:
# heat demand # heat demand
Heat load: '#cc1f1f' Heat load: '#cc1f1f'
heat: '#cc1f1f' heat: '#cc1f1f'
heat vent: '#aa3344'
heat demand: '#cc1f1f' heat demand: '#cc1f1f'
rural heat: '#ff5c5c' rural heat: '#ff5c5c'
residential rural heat: '#ff7c7c' residential rural heat: '#ff7c7c'
@ -946,7 +961,6 @@ plotting:
Sabatier: '#9850ad' Sabatier: '#9850ad'
methanation: '#c44ce6' methanation: '#c44ce6'
methane: '#c44ce6' methane: '#c44ce6'
helmeth: '#e899ff'
# synfuels # synfuels
Fischer-Tropsch: '#25c49a' Fischer-Tropsch: '#25c49a'
liquid: '#25c49a' liquid: '#25c49a'

1
doc/configtables/offwind-ac.csv
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@ -12,5 +12,4 @@ ship_threshold,--,float,"Ship density threshold from which areas are excluded."
max_depth,m,float,"Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential." max_depth,m,float,"Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential."
min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential." min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential."
max_shore_distance,m,float,"Maximum distance to the shore above which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential." max_shore_distance,m,float,"Maximum distance to the shore above which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential."
potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero." clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."

1 Unit Values Description
12 max_depth m float Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential.
13 min_shore_distance m float Minimum distance to the shore below which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential.
14 max_shore_distance m float Maximum distance to the shore above which wind turbines cannot be build. Such areas close to the shore are excluded in the process of calculating the AC-connected offshore wind potential.
potential -- One of {'simple', 'conservative'} Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`
15 clip_p_max_pu p.u. float To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.

1
doc/configtables/offwind-dc.csv
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@ -12,5 +12,4 @@ ship_threshold,--,float,"Ship density threshold from which areas are excluded."
max_depth,m,float,"Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential." max_depth,m,float,"Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential."
min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build." min_shore_distance,m,float,"Minimum distance to the shore below which wind turbines cannot be build."
max_shore_distance,m,float,"Maximum distance to the shore above which wind turbines cannot be build." max_shore_distance,m,float,"Maximum distance to the shore above which wind turbines cannot be build."
potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero." clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."

1 Unit Values Description
12 max_depth m float Maximum sea water depth at which wind turbines can be build. Maritime areas with deeper waters are excluded in the process of calculating the AC-connected offshore wind potential.
13 min_shore_distance m float Minimum distance to the shore below which wind turbines cannot be build.
14 max_shore_distance m float Maximum distance to the shore above which wind turbines cannot be build.
potential -- One of {'simple', 'conservative'} Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`
15 clip_p_max_pu p.u. float To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.

1
doc/configtables/onwind.csv
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@ -9,7 +9,6 @@ corine,,,
-- distance,m,float,"Distance to keep from areas specified in ``distance_grid_codes``" -- distance,m,float,"Distance to keep from areas specified in ``distance_grid_codes``"
-- distance_grid_codes,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_","Specifies areas according to CORINE Land Cover codes to which wind turbines must maintain a distance specified in the setting ``distance``." -- distance_grid_codes,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_","Specifies areas according to CORINE Land Cover codes to which wind turbines must maintain a distance specified in the setting ``distance``."
natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``." natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``."
potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero." clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
correction_factor,--,float,"Correction factor for capacity factor time series." correction_factor,--,float,"Correction factor for capacity factor time series."
excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis." excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."

1 Unit Values Description
9 -- distance m float Distance to keep from areas specified in ``distance_grid_codes``
10 -- distance_grid_codes -- Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_ Specifies areas according to CORINE Land Cover codes to which wind turbines must maintain a distance specified in the setting ``distance``.
11 natura bool {true, false} Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``.
potential -- One of {'simple', 'conservative'} Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`
12 clip_p_max_pu p.u. float To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.
13 correction_factor -- float Correction factor for capacity factor time series.
14 excluder_resolution m float Resolution on which to perform geographical elibility analysis.

7
doc/configtables/sector.csv
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@ -71,7 +71,6 @@ solar_thermal,--,"{true, false}",Add option for using solar thermal to generate
solar_cf_correction,--,float,The correction factor for the value provided by the solar thermal profile calculations solar_cf_correction,--,float,The correction factor for the value provided by the solar thermal profile calculations
marginal_cost_storage,currency/MWh ,float,The marginal cost of discharging batteries in distributed grids marginal_cost_storage,currency/MWh ,float,The marginal cost of discharging batteries in distributed grids
methanation,--,"{true, false}",Add option for transforming hydrogen and CO2 into methane using methanation. methanation,--,"{true, false}",Add option for transforming hydrogen and CO2 into methane using methanation.
helmeth,--,"{true, false}",Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion)
coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture
dac,--,"{true, false}",Add option for Direct Air Capture (DAC) dac,--,"{true, false}",Add option for Direct Air Capture (DAC)
co2_vent,--,"{true, false}",Add option for vent out CO2 from storages to the atmosphere. co2_vent,--,"{true, false}",Add option for vent out CO2 from storages to the atmosphere.
@ -108,6 +107,11 @@ electricity_distribution _grid,--,"{true, false}",Add a simplified representatio
electricity_distribution _grid_cost_factor,,,Multiplies the investment cost of the electricity distribution grid electricity_distribution _grid_cost_factor,,,Multiplies the investment cost of the electricity distribution grid
,,, ,,,
electricity_grid _connection,--,"{true, false}",Add the cost of electricity grid connection for onshore wind and solar electricity_grid _connection,--,"{true, false}",Add the cost of electricity grid connection for onshore wind and solar
transmission_efficiency,,,Section to specify transmission losses or compression energy demands of bidirectional links. Splits them into two capacity-linked unidirectional links.
-- {carrier},--,str,The carrier of the link.
-- -- efficiency_static,p.u.,float,Length-independent transmission efficiency.
-- -- efficiency_per_1000km,p.u. per 1000 km,float,Length-dependent transmission efficiency ($\eta^{\text{length}}$)
-- -- compression_per_1000km,p.u. per 1000 km,float,Length-dependent electricity demand for compression ($\eta \cdot \text{length}$) implemented as multi-link to local electricity bus.
H2_network,--,"{true, false}",Add option for new hydrogen pipelines H2_network,--,"{true, false}",Add option for new hydrogen pipelines
gas_network,--,"{true, false}","Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted `k-edge augmentation algorithm <https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation>`_ can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well." gas_network,--,"{true, false}","Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted `k-edge augmentation algorithm <https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation>`_ can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well."
H2_retrofit,--,"{true, false}",Add option for retrofiting existing pipelines to transport hydrogen. H2_retrofit,--,"{true, false}",Add option for retrofiting existing pipelines to transport hydrogen.
@ -118,6 +122,7 @@ gas_distribution_grid _cost_factor,,,Multiplier for the investment cost of the g
,,, ,,,
biomass_spatial,--,"{true, false}",Add option for resolving biomass demand regionally biomass_spatial,--,"{true, false}",Add option for resolving biomass demand regionally
biomass_transport,--,"{true, false}",Add option for transporting solid biomass between nodes biomass_transport,--,"{true, false}",Add option for transporting solid biomass between nodes
biogas_upgrading_cc,--,"{true, false}",Add option to capture CO2 from biomass upgrading
conventional_generation,,,Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel. conventional_generation,,,Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel.
biomass_to_liquid,--,"{true, false}",Add option for transforming solid biomass into liquid fuel with the same properties as oil biomass_to_liquid,--,"{true, false}",Add option for transforming solid biomass into liquid fuel with the same properties as oil
biosng,--,"{true, false}",Add option for transforming solid biomass into synthesis gas with the same properties as natural gas biosng,--,"{true, false}",Add option for transforming solid biomass into synthesis gas with the same properties as natural gas

1 Unit Values Description
71 solar_cf_correction -- float The correction factor for the value provided by the solar thermal profile calculations
72 marginal_cost_storage currency/MWh float The marginal cost of discharging batteries in distributed grids
73 methanation -- {true, false} Add option for transforming hydrogen and CO2 into methane using methanation.
helmeth -- {true, false} Add option for transforming power into gas using HELMETH (Integrated High-Temperature ELectrolysis and METHanation for Effective Power to Gas Conversion)
74 coal_cc -- {true, false} Add option for coal CHPs with carbon capture
75 dac -- {true, false} Add option for Direct Air Capture (DAC)
76 co2_vent -- {true, false} Add option for vent out CO2 from storages to the atmosphere.
107 electricity_distribution _grid_cost_factor Multiplies the investment cost of the electricity distribution grid
108
109 electricity_grid _connection -- {true, false} Add the cost of electricity grid connection for onshore wind and solar
110 transmission_efficiency Section to specify transmission losses or compression energy demands of bidirectional links. Splits them into two capacity-linked unidirectional links.
111 -- {carrier} -- str The carrier of the link.
112 -- -- efficiency_static p.u. float Length-independent transmission efficiency.
113 -- -- efficiency_per_1000km p.u. per 1000 km float Length-dependent transmission efficiency ($\eta^{\text{length}}$)
114 -- -- compression_per_1000km p.u. per 1000 km float Length-dependent electricity demand for compression ($\eta \cdot \text{length}$) implemented as multi-link to local electricity bus.
115 H2_network -- {true, false} Add option for new hydrogen pipelines
116 gas_network -- {true, false} Add existing natural gas infrastructure, incl. LNG terminals, production and entry-points. The existing gas network is added with a lossless transport model. A length-weighted `k-edge augmentation algorithm <https://networkx.org/documentation/stable/reference/algorithms/generated/networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation.html#networkx.algorithms.connectivity.edge_augmentation.k_edge_augmentation>`_ can be run to add new candidate gas pipelines such that all regions of the model can be connected to the gas network. When activated, all the gas demands are regionally disaggregated as well.
117 H2_retrofit -- {true, false} Add option for retrofiting existing pipelines to transport hydrogen.
122
123 biomass_spatial -- {true, false} Add option for resolving biomass demand regionally
124 biomass_transport -- {true, false} Add option for transporting solid biomass between nodes
125 biogas_upgrading_cc -- {true, false} Add option to capture CO2 from biomass upgrading
126 conventional_generation Add a more detailed description of conventional carriers. Any power generation requires the consumption of fuel from nodes representing that fuel.
127 biomass_to_liquid -- {true, false} Add option for transforming solid biomass into liquid fuel with the same properties as oil
128 biosng -- {true, false} Add option for transforming solid biomass into synthesis gas with the same properties as natural gas

1
doc/configtables/solar.csv
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@ -10,6 +10,5 @@ capacity_per_sqkm,:math:`MW/km^2`,float,"Allowable density of solar panel placem
correction_factor,--,float,"A correction factor for the capacity factor (availability) time series." correction_factor,--,float,"A correction factor for the capacity factor (availability) time series."
corine,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_","Specifies areas according to CORINE Land Cover codes which are generally eligible for solar panel placement." corine,--,"Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_","Specifies areas according to CORINE Land Cover codes which are generally eligible for solar panel placement."
natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``." natura,bool,"{true, false}","Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``."
potential,--,"One of {'simple', 'conservative'}","Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`"
clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero." clip_p_max_pu,p.u.,float,"To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero."
excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis." excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."

1 Unit Values Description
10 correction_factor -- float A correction factor for the capacity factor (availability) time series.
11 corine -- Any subset of the `CORINE Land Cover code list <http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-1/corine-land-cover-classes-and/clc_legend.csv/at_download/file>`_ Specifies areas according to CORINE Land Cover codes which are generally eligible for solar panel placement.
12 natura bool {true, false} Switch to exclude `Natura 2000 <https://en.wikipedia.org/wiki/Natura_2000>`_ natural protection areas. Area is excluded if ``true``.
potential -- One of {'simple', 'conservative'} Method to compute the maximal installable potential for a node; confer :ref:`renewableprofiles`
13 clip_p_max_pu p.u. float To avoid too small values in the renewables` per-unit availability time series values below this threshold are set to zero.
14 excluder_resolution m float Resolution on which to perform geographical elibility analysis.

2
doc/index.rst
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@ -116,7 +116,7 @@ of the individual parts.
topics we are working on. Please feel free to help or make suggestions. topics we are working on. Please feel free to help or make suggestions.
This project is currently maintained by the `Department of Digital This project is currently maintained by the `Department of Digital
Transformation in Energy Systems <https:/www.ensys.tu-berlin.de>`_ at the Transformation in Energy Systems <https://www.tu.berlin/en/ensys>`_ at the
`Technische Universität Berlin <https://www.tu.berlin>`_. Previous versions were `Technische Universität Berlin <https://www.tu.berlin>`_. Previous versions were
developed within the `IAI <http://www.iai.kit.edu>`_ at the `Karlsruhe Institute developed within the `IAI <http://www.iai.kit.edu>`_ at the `Karlsruhe Institute
of Technology (KIT) <http://www.kit.edu/english/index.php>`_ which was funded by of Technology (KIT) <http://www.kit.edu/english/index.php>`_ which was funded by

38
doc/release_notes.rst
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@ -10,6 +10,13 @@ Release Notes
Upcoming Release Upcoming Release
================ ================
* Add option to specify losses for bidirectional links, e.g. pipelines or HVDC
links, in configuration file under ``sector: transmission_efficiency:``. Users
can specify static or length-dependent values as well as a length-dependent
electricity demand for compression, which is implemented as a multi-link to
the local electricity buses. The bidirectional links will then be split into
two unidirectional links with linked capacities.
* Pin ``snakemake`` version to below 8.0.0, as the new version is not yet * Pin ``snakemake`` version to below 8.0.0, as the new version is not yet
supported by ``pypsa-eur``. supported by ``pypsa-eur``.
@ -38,12 +45,30 @@ Upcoming Release
* Split configuration to enable SMR and SMR CC. * Split configuration to enable SMR and SMR CC.
* Bugfix: The unit of the capital cost of Haber-Bosch plants was corrected.
* The configuration setting for country focus weights when clustering the * The configuration setting for country focus weights when clustering the
network has been moved from ``focus_weights:`` to ``clustering: network has been moved from ``focus_weights:`` to ``clustering:
focus_weights:``. Backwards compatibility to old config files is maintained. focus_weights:``. Backwards compatibility to old config files is maintained.
* Extend options for waste usage from Haber-Bosch, methanolisation and methanation.
* Use electrolysis waste heat by default.
* Add new ``sector_opts`` wildcard option "nowasteheat" to disable all waste heat usage.
* Set minimum part loads for PtX processes to 30% for methanolisation and methanation, and to 70% for Fischer-Tropsch synthesis.
* Add VOM as marginal cost to PtX processes.
* Add pelletizing costs for biomass boilers.
* The ``mock_snakemake`` function can now be used with a Snakefile from a different directory using the new ``root_dir`` argument. * The ``mock_snakemake`` function can now be used with a Snakefile from a different directory using the new ``root_dir`` argument.
* Switch to using hydrogen and electricity inputs for Haber-Bosch from https://github.com/PyPSA/technology-data.
* Add option to capture CO2 contained in biogas when upgrading (``sector: biogas_to_gas_cc``).
* Merged option to extend geographical scope to Ukraine and Moldova. These * Merged option to extend geographical scope to Ukraine and Moldova. These
countries are excluded by default and is currently constrained to power-sector countries are excluded by default and is currently constrained to power-sector
only parts of the workflow. A special config file only parts of the workflow. A special config file
@ -59,6 +84,17 @@ Upcoming Release
default setting points to an empty hull at default setting points to an empty hull at
``data/custom_extra_functionality.py``. ``data/custom_extra_functionality.py``.
* Validate downloads from Zenodo using MD5 checksums. This identifies corrupted
or incomplete downloads.
* Add locations, capacities and costs of existing gas storage using Global
Energy Monitor's `Europe Gas Tracker
<https://globalenergymonitor.org/projects/europe-gas-tracker>`_.
* Remove HELMETH option.
* Print Irreducible Infeasible Subset (IIS) if model is infeasible. Only for
solvers with IIS support.
**Bugs and Compatibility** **Bugs and Compatibility**
@ -190,6 +226,8 @@ PyPSA-Eur 0.8.1 (27th July 2023)
(https://github.com/PyPSA/pypsa-eur/pull/672) (https://github.com/PyPSA/pypsa-eur/pull/672)
* Addressed deprecation warnings for ``pandas=2.0``. ``pandas=2.0`` is now minimum requirement.
PyPSA-Eur 0.8.0 (18th March 2023) PyPSA-Eur 0.8.0 (18th March 2023)
================================= =================================

4
rules/build_sector.smk
View File

@ -85,12 +85,12 @@ if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]:
rule build_gas_input_locations: rule build_gas_input_locations:
input: input:
lng=HTTP.remote( gem=HTTP.remote(
"https://globalenergymonitor.org/wp-content/uploads/2023/07/Europe-Gas-Tracker-2023-03-v3.xlsx", "https://globalenergymonitor.org/wp-content/uploads/2023/07/Europe-Gas-Tracker-2023-03-v3.xlsx",
keep_local=True, keep_local=True,
), ),
entry="data/gas_network/scigrid-gas/data/IGGIELGN_BorderPoints.geojson", entry="data/gas_network/scigrid-gas/data/IGGIELGN_BorderPoints.geojson",
production="data/gas_network/scigrid-gas/data/IGGIELGN_Productions.geojson", storage="data/gas_network/scigrid-gas/data/IGGIELGN_Storages.geojson",
regions_onshore=RESOURCES regions_onshore=RESOURCES
+ "regions_onshore_elec_s{simpl}_{clusters}.geojson", + "regions_onshore_elec_s{simpl}_{clusters}.geojson",
regions_offshore=RESOURCES regions_offshore=RESOURCES

5
rules/common.smk
View File

@ -2,6 +2,11 @@
# #
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
import os, sys
sys.path.insert(0, os.path.abspath("scripts"))
from _helpers import validate_checksum
def memory(w): def memory(w):
factor = 3.0 factor = 3.0

5
rules/retrieve.smk
View File

@ -77,6 +77,7 @@ if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True
retries: 2 retries: 2
run: run:
move(input[0], output[0]) move(input[0], output[0])
validate_checksum(output[0], input[0])
if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", True): if config["enable"]["retrieve"] and config["enable"].get("retrieve_cost_data", True):
@ -121,6 +122,7 @@ if config["enable"]["retrieve"] and config["enable"].get(
retries: 2 retries: 2
run: run:
move(input[0], output[0]) move(input[0], output[0])
validate_checksum(output[0], input[0])
if config["enable"]["retrieve"] and config["enable"].get( if config["enable"]["retrieve"] and config["enable"].get(
@ -167,6 +169,7 @@ if config["enable"]["retrieve"] and (
"IGGIELGN_LNGs.geojson", "IGGIELGN_LNGs.geojson",
"IGGIELGN_BorderPoints.geojson", "IGGIELGN_BorderPoints.geojson",
"IGGIELGN_Productions.geojson", "IGGIELGN_Productions.geojson",
"IGGIELGN_Storages.geojson",
"IGGIELGN_PipeSegments.geojson", "IGGIELGN_PipeSegments.geojson",
] ]
@ -226,6 +229,7 @@ if config["enable"]["retrieve"]:
retries: 2 retries: 2
run: run:
move(input[0], output[0]) move(input[0], output[0])
validate_checksum(output[0], input[0])
if config["enable"]["retrieve"]: if config["enable"]["retrieve"]:
@ -242,6 +246,7 @@ if config["enable"]["retrieve"]:
"data/Copernicus_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif", "data/Copernicus_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif",
run: run:
move(input[0], output[0]) move(input[0], output[0])
validate_checksum(output[0], input[0])
if config["enable"]["retrieve"]: if config["enable"]["retrieve"]:

62
scripts/_helpers.py
View File

@ -4,6 +4,7 @@
# SPDX-License-Identifier: MIT # SPDX-License-Identifier: MIT
import contextlib import contextlib
import hashlib
import logging import logging
import os import os
import urllib import urllib
@ -11,6 +12,7 @@ from pathlib import Path
import pandas as pd import pandas as pd
import pytz import pytz
import requests
import yaml import yaml
from pypsa.components import component_attrs, components from pypsa.components import component_attrs, components
from pypsa.descriptors import Dict from pypsa.descriptors import Dict
@ -318,3 +320,63 @@ def update_config_with_sector_opts(config, sector_opts):
if o.startswith("CF+"): if o.startswith("CF+"):
l = o.split("+")[1:] l = o.split("+")[1:]
update_config(config, parse(l)) update_config(config, parse(l))
def get_checksum_from_zenodo(file_url):
parts = file_url.split("/")
record_id = parts[parts.index("record") + 1]
filename = parts[-1]
response = requests.get(f"https://zenodo.org/api/records/{record_id}", timeout=30)
response.raise_for_status()
data = response.json()
for file in data["files"]:
if file["key"] == filename:
return file["checksum"]
return None
def validate_checksum(file_path, zenodo_url=None, checksum=None):
"""
Validate file checksum against provided or Zenodo-retrieved checksum.
Calculates the hash of a file using 64KB chunks. Compares it against a
given checksum or one from a Zenodo URL.
Parameters
----------
file_path : str
Path to the file for checksum validation.
zenodo_url : str, optional
URL of the file on Zenodo to fetch the checksum.
checksum : str, optional
Checksum (format 'hash_type:checksum_value') for validation.
Raises
------
AssertionError
If the checksum does not match, or if neither `checksum` nor `zenodo_url` is provided.
Examples
--------
>>> validate_checksum("/path/to/file", checksum="md5:abc123...")
>>> validate_checksum(
... "/path/to/file",
... zenodo_url="https://zenodo.org/record/12345/files/example.txt",
... )
If the checksum is invalid, an AssertionError will be raised.
"""
assert checksum or zenodo_url, "Either checksum or zenodo_url must be provided"
if zenodo_url:
checksum = get_checksum_from_zenodo(zenodo_url)
hash_type, checksum = checksum.split(":")
hasher = hashlib.new(hash_type)
with open(file_path, "rb") as f:
for chunk in iter(lambda: f.read(65536), b""): # 64kb chunks
hasher.update(chunk)
calculated_checksum = hasher.hexdigest()
assert (
calculated_checksum == checksum
), "Checksum is invalid. This may be due to an incomplete download. Delete the file and re-execute the rule."

29
scripts/add_brownfield.py
View File

@ -120,6 +120,33 @@ def add_brownfield(n, n_p, year):
n.links.loc[new_pipes, "p_nom_min"] = 0.0 n.links.loc[new_pipes, "p_nom_min"] = 0.0
def disable_grid_expansion_if_LV_limit_hit(n):
if not "lv_limit" in n.global_constraints.index:
return
total_expansion = (
n.lines.eval("s_nom_min * length").sum()
+ n.links.query("carrier == 'DC'").eval("p_nom_min * length").sum()
).sum()
lv_limit = n.global_constraints.at["lv_limit", "constant"]
# allow small numerical differences
if lv_limit - total_expansion < 1:
logger.info(
f"LV is already reached (gap {diff} MWkm), disabling expansion and LV limit"
)
extendable_acs = n.lines.query("s_nom_extendable").index
n.lines.loc[extendable_acs, "s_nom_extendable"] = False
n.lines.loc[extendable_acs, "s_nom"] = n.lines.loc[extendable_acs, "s_nom_min"]
extendable_dcs = n.links.query("carrier == 'DC' and p_nom_extendable").index
n.links.loc[extendable_dcs, "p_nom_extendable"] = False
n.links.loc[extendable_dcs, "p_nom"] = n.links.loc[extendable_dcs, "p_nom_min"]
n.global_constraints.drop("lv_limit", inplace=True)
if __name__ == "__main__": if __name__ == "__main__":
if "snakemake" not in globals(): if "snakemake" not in globals():
from _helpers import mock_snakemake from _helpers import mock_snakemake
@ -150,5 +177,7 @@ if __name__ == "__main__":
add_brownfield(n, n_p, year) add_brownfield(n, n_p, year)
disable_grid_expansion_if_LV_limit_hit(n)
n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards))) n.meta = dict(snakemake.config, **dict(wildcards=dict(snakemake.wildcards)))
n.export_to_netcdf(snakemake.output[0]) n.export_to_netcdf(snakemake.output[0])

2
scripts/build_biomass_potentials.py
View File

@ -134,7 +134,7 @@ def disaggregate_nuts0(bio):
# get population in nuts2 # get population in nuts2
pop_nuts2 = pop.loc[pop.index.str.len() == 4] pop_nuts2 = pop.loc[pop.index.str.len() == 4]
by_country = pop_nuts2.total.groupby(pop_nuts2.ct).sum() by_country = pop_nuts2.total.groupby(pop_nuts2.ct).sum()
pop_nuts2["fraction"] = pop_nuts2.total / pop_nuts2.ct.map(by_country) pop_nuts2.loc[:, "fraction"] = pop_nuts2.total / pop_nuts2.ct.map(by_country)
# distribute nuts0 data to nuts2 by population # distribute nuts0 data to nuts2 by population
bio_nodal = bio.loc[pop_nuts2.ct] bio_nodal = bio.loc[pop_nuts2.ct]

5
scripts/build_clustered_population_layouts.py
View File

@ -25,10 +25,7 @@ if __name__ == "__main__":
cutout = atlite.Cutout(snakemake.input.cutout) cutout = atlite.Cutout(snakemake.input.cutout)
clustered_regions = ( clustered_regions = (
gpd.read_file(snakemake.input.regions_onshore) gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
.set_index("name")
.buffer(0)
.squeeze()
) )
I = cutout.indicatormatrix(clustered_regions) I = cutout.indicatormatrix(clustered_regions)

2
scripts/build_electricity_demand.py
View File

@ -81,7 +81,7 @@ def load_timeseries(fn, years, countries, powerstatistics=True):
return s[: -len(pattern)] return s[: -len(pattern)]
return ( return (
pd.read_csv(fn, index_col=0, parse_dates=[0]) pd.read_csv(fn, index_col=0, parse_dates=[0], date_format="%Y-%m-%dT%H:%M:%SZ")
.tz_localize(None) .tz_localize(None)
.filter(like=pattern) .filter(like=pattern)
.rename(columns=rename) .rename(columns=rename)

56
scripts/build_energy_totals.py
View File

@ -189,12 +189,12 @@ def idees_per_country(ct, year, base_dir):
ct_totals["total residential water"] = df.at["Water heating"] ct_totals["total residential water"] = df.at["Water heating"]
assert df.index[23] == "Electricity" assert df.index[23] == "Electricity"
ct_totals["electricity residential water"] = df[23] ct_totals["electricity residential water"] = df.iloc[23]
ct_totals["total residential cooking"] = df["Cooking"] ct_totals["total residential cooking"] = df["Cooking"]
assert df.index[30] == "Electricity" assert df.index[30] == "Electricity"
ct_totals["electricity residential cooking"] = df[30] ct_totals["electricity residential cooking"] = df.iloc[30]
df = pd.read_excel(fn_residential, "RES_summary", index_col=0)[year] df = pd.read_excel(fn_residential, "RES_summary", index_col=0)[year]
@ -202,13 +202,13 @@ def idees_per_country(ct, year, base_dir):
ct_totals["total residential"] = df[row] ct_totals["total residential"] = df[row]
assert df.index[47] == "Electricity" assert df.index[47] == "Electricity"
ct_totals["electricity residential"] = df[47] ct_totals["electricity residential"] = df.iloc[47]
assert df.index[46] == "Derived heat" assert df.index[46] == "Derived heat"
ct_totals["derived heat residential"] = df[46] ct_totals["derived heat residential"] = df.iloc[46]
assert df.index[50] == "Thermal uses" assert df.index[50] == "Thermal uses"
ct_totals["thermal uses residential"] = df[50] ct_totals["thermal uses residential"] = df.iloc[50]
# services # services
@ -222,12 +222,12 @@ def idees_per_country(ct, year, base_dir):
ct_totals["total services water"] = df["Hot water"] ct_totals["total services water"] = df["Hot water"]
assert df.index[24] == "Electricity" assert df.index[24] == "Electricity"
ct_totals["electricity services water"] = df[24] ct_totals["electricity services water"] = df.iloc[24]
ct_totals["total services cooking"] = df["Catering"] ct_totals["total services cooking"] = df["Catering"]
assert df.index[31] == "Electricity" assert df.index[31] == "Electricity"
ct_totals["electricity services cooking"] = df[31] ct_totals["electricity services cooking"] = df.iloc[31]
df = pd.read_excel(fn_tertiary, "SER_summary", index_col=0)[year] df = pd.read_excel(fn_tertiary, "SER_summary", index_col=0)[year]
@ -235,13 +235,13 @@ def idees_per_country(ct, year, base_dir):
ct_totals["total services"] = df[row] ct_totals["total services"] = df[row]
assert df.index[50] == "Electricity" assert df.index[50] == "Electricity"
ct_totals["electricity services"] = df[50] ct_totals["electricity services"] = df.iloc[50]
assert df.index[49] == "Derived heat" assert df.index[49] == "Derived heat"
ct_totals["derived heat services"] = df[49] ct_totals["derived heat services"] = df.iloc[49]
assert df.index[53] == "Thermal uses" assert df.index[53] == "Thermal uses"
ct_totals["thermal uses services"] = df[53] ct_totals["thermal uses services"] = df.iloc[53]
# agriculture, forestry and fishing # agriculture, forestry and fishing
@ -282,28 +282,28 @@ def idees_per_country(ct, year, base_dir):
ct_totals["total two-wheel"] = df["Powered 2-wheelers (Gasoline)"] ct_totals["total two-wheel"] = df["Powered 2-wheelers (Gasoline)"]
assert df.index[19] == "Passenger cars" assert df.index[19] == "Passenger cars"
ct_totals["total passenger cars"] = df[19] ct_totals["total passenger cars"] = df.iloc[19]
assert df.index[30] == "Battery electric vehicles" assert df.index[30] == "Battery electric vehicles"
ct_totals["electricity passenger cars"] = df[30] ct_totals["electricity passenger cars"] = df.iloc[30]
assert df.index[31] == "Motor coaches, buses and trolley buses" assert df.index[31] == "Motor coaches, buses and trolley buses"
ct_totals["total other road passenger"] = df[31] ct_totals["total other road passenger"] = df.iloc[31]
assert df.index[39] == "Battery electric vehicles" assert df.index[39] == "Battery electric vehicles"
ct_totals["electricity other road passenger"] = df[39] ct_totals["electricity other road passenger"] = df.iloc[39]
assert df.index[41] == "Light duty vehicles" assert df.index[41] == "Light duty vehicles"
ct_totals["total light duty road freight"] = df[41] ct_totals["total light duty road freight"] = df.iloc[41]
assert df.index[49] == "Battery electric vehicles" assert df.index[49] == "Battery electric vehicles"
ct_totals["electricity light duty road freight"] = df[49] ct_totals["electricity light duty road freight"] = df.iloc[49]
row = "Heavy duty vehicles (Diesel oil incl. biofuels)" row = "Heavy duty vehicles (Diesel oil incl. biofuels)"
ct_totals["total heavy duty road freight"] = df[row] ct_totals["total heavy duty road freight"] = df[row]
assert df.index[61] == "Passenger cars" assert df.index[61] == "Passenger cars"
ct_totals["passenger car efficiency"] = df[61] ct_totals["passenger car efficiency"] = df.iloc[61]
df = pd.read_excel(fn_transport, "TrRail_ene", index_col=0)[year] df = pd.read_excel(fn_transport, "TrRail_ene", index_col=0)[year]
@ -312,39 +312,39 @@ def idees_per_country(ct, year, base_dir):
ct_totals["electricity rail"] = df["Electricity"] ct_totals["electricity rail"] = df["Electricity"]
assert df.index[15] == "Passenger transport" assert df.index[15] == "Passenger transport"
ct_totals["total rail passenger"] = df[15] ct_totals["total rail passenger"] = df.iloc[15]
assert df.index[16] == "Metro and tram, urban light rail" assert df.index[16] == "Metro and tram, urban light rail"
assert df.index[19] == "Electric" assert df.index[19] == "Electric"
assert df.index[20] == "High speed passenger trains" assert df.index[20] == "High speed passenger trains"
ct_totals["electricity rail passenger"] = df[[16, 19, 20]].sum() ct_totals["electricity rail passenger"] = df.iloc[[16, 19, 20]].sum()
assert df.index[21] == "Freight transport" assert df.index[21] == "Freight transport"
ct_totals["total rail freight"] = df[21] ct_totals["total rail freight"] = df.iloc[21]
assert df.index[23] == "Electric" assert df.index[23] == "Electric"
ct_totals["electricity rail freight"] = df[23] ct_totals["electricity rail freight"] = df.iloc[23]
df = pd.read_excel(fn_transport, "TrAvia_ene", index_col=0)[year] df = pd.read_excel(fn_transport, "TrAvia_ene", index_col=0)[year]
assert df.index[6] == "Passenger transport" assert df.index[6] == "Passenger transport"
ct_totals["total aviation passenger"] = df[6] ct_totals["total aviation passenger"] = df.iloc[6]
assert df.index[10] == "Freight transport" assert df.index[10] == "Freight transport"
ct_totals["total aviation freight"] = df[10] ct_totals["total aviation freight"] = df.iloc[10]
assert df.index[7] == "Domestic" assert df.index[7] == "Domestic"
ct_totals["total domestic aviation passenger"] = df[7] ct_totals["total domestic aviation passenger"] = df.iloc[7]
assert df.index[8] == "International - Intra-EU" assert df.index[8] == "International - Intra-EU"
assert df.index[9] == "International - Extra-EU" assert df.index[9] == "International - Extra-EU"
ct_totals["total international aviation passenger"] = df[[8, 9]].sum() ct_totals["total international aviation passenger"] = df.iloc[[8, 9]].sum()
assert df.index[11] == "Domestic and International - Intra-EU" assert df.index[11] == "Domestic and International - Intra-EU"
ct_totals["total domestic aviation freight"] = df[11] ct_totals["total domestic aviation freight"] = df.iloc[11]
assert df.index[12] == "International - Extra-EU" assert df.index[12] == "International - Extra-EU"
ct_totals["total international aviation freight"] = df[12] ct_totals["total international aviation freight"] = df.iloc[12]
ct_totals["total domestic aviation"] = ( ct_totals["total domestic aviation"] = (
ct_totals["total domestic aviation freight"] ct_totals["total domestic aviation freight"]
@ -364,7 +364,7 @@ def idees_per_country(ct, year, base_dir):
df = pd.read_excel(fn_transport, "TrRoad_act", index_col=0)[year] df = pd.read_excel(fn_transport, "TrRoad_act", index_col=0)[year]
assert df.index[85] == "Passenger cars" assert df.index[85] == "Passenger cars"
ct_totals["passenger cars"] = df[85] ct_totals["passenger cars"] = df.iloc[85]
return pd.Series(ct_totals, name=ct) return pd.Series(ct_totals, name=ct)

87
scripts/build_gas_input_locations.py
View File

@ -23,11 +23,10 @@ def read_scigrid_gas(fn):
return df return df
def build_gem_lng_data(lng_fn): def build_gem_lng_data(fn):
df = pd.read_excel(lng_fn[0], sheet_name="LNG terminals - data") df = pd.read_excel(fn[0], sheet_name="LNG terminals - data")
df = df.set_index("ComboID") df = df.set_index("ComboID")
remove_status = ["Cancelled"]
remove_country = ["Cyprus", "Turkey"] remove_country = ["Cyprus", "Turkey"]
remove_terminal = ["Puerto de la Luz LNG Terminal", "Gran Canaria LNG Terminal"] remove_terminal = ["Puerto de la Luz LNG Terminal", "Gran Canaria LNG Terminal"]
@ -42,9 +41,50 @@ def build_gem_lng_data(lng_fn):
return gpd.GeoDataFrame(df, geometry=geometry, crs="EPSG:4326") return gpd.GeoDataFrame(df, geometry=geometry, crs="EPSG:4326")
def build_gas_input_locations(lng_fn, entry_fn, prod_fn, countries): def build_gem_prod_data(fn):
df = pd.read_excel(fn[0], sheet_name="Gas extraction - main")
df = df.set_index("GEM Unit ID")
remove_country = ["Cyprus", "Türkiye"]
remove_fuel_type = ["oil"]
df = df.query(
"Status != 'shut in' \
& 'Fuel type' != 'oil' \
& Country != @remove_country \
& ~Latitude.isna() \
& ~Longitude.isna()"
).copy()
p = pd.read_excel(fn[0], sheet_name="Gas extraction - production")
p = p.set_index("GEM Unit ID")
p = p[p["Fuel description"] == "gas"]
capacities = pd.DataFrame(index=df.index)
for key in ["production", "production design capacity", "reserves"]:
cap = (
p.loc[p["Production/reserves"] == key, "Quantity (converted)"]
.groupby("GEM Unit ID")
.sum()
.reindex(df.index)
)
# assume capacity such that 3% of reserves can be extracted per year (25% quantile)
annualization_factor = 0.03 if key == "reserves" else 1.0
capacities[key] = cap * annualization_factor
df["mcm_per_year"] = (
capacities["production"]
.combine_first(capacities["production design capacity"])
.combine_first(capacities["reserves"])
)
geometry = gpd.points_from_xy(df["Longitude"], df["Latitude"])
return gpd.GeoDataFrame(df, geometry=geometry, crs="EPSG:4326")
def build_gas_input_locations(gem_fn, entry_fn, sto_fn, countries):
# LNG terminals # LNG terminals
lng = build_gem_lng_data(lng_fn) lng = build_gem_lng_data(gem_fn)
# Entry points from outside the model scope # Entry points from outside the model scope
entry = read_scigrid_gas(entry_fn) entry = read_scigrid_gas(entry_fn)
@ -55,25 +95,30 @@ def build_gas_input_locations(lng_fn, entry_fn, prod_fn, countries):
| (entry.from_country == "NO") # malformed datapoint # entries from NO to GB | (entry.from_country == "NO") # malformed datapoint # entries from NO to GB
] ]
sto = read_scigrid_gas(sto_fn)
remove_country = ["RU", "UA", "TR", "BY"]
sto = sto.query("country_code != @remove_country")
# production sites inside the model scope # production sites inside the model scope
prod = read_scigrid_gas(prod_fn) prod = build_gem_prod_data(gem_fn)
prod = prod.loc[
(prod.geometry.y > 35) & (prod.geometry.x < 30) & (prod.country_code != "DE")
]
mcm_per_day_to_mw = 437.5 # MCM/day to MWh/h mcm_per_day_to_mw = 437.5 # MCM/day to MWh/h
mcm_per_year_to_mw = 1.199 # MCM/year to MWh/h
mtpa_to_mw = 1649.224 # mtpa to MWh/h mtpa_to_mw = 1649.224 # mtpa to MWh/h
lng["p_nom"] = lng["CapacityInMtpa"] * mtpa_to_mw mcm_to_gwh = 11.36 # MCM to GWh
entry["p_nom"] = entry["max_cap_from_to_M_m3_per_d"] * mcm_per_day_to_mw lng["capacity"] = lng["CapacityInMtpa"] * mtpa_to_mw
prod["p_nom"] = prod["max_supply_M_m3_per_d"] * mcm_per_day_to_mw entry["capacity"] = entry["max_cap_from_to_M_m3_per_d"] * mcm_per_day_to_mw
prod["capacity"] = prod["mcm_per_year"] * mcm_per_year_to_mw
sto["capacity"] = sto["max_cushionGas_M_m3"] * mcm_to_gwh
lng["type"] = "lng" lng["type"] = "lng"
entry["type"] = "pipeline" entry["type"] = "pipeline"
prod["type"] = "production" prod["type"] = "production"
sto["type"] = "storage"
sel = ["geometry", "p_nom", "type"] sel = ["geometry", "capacity", "type"]
return pd.concat([prod[sel], entry[sel], lng[sel]], ignore_index=True) return pd.concat([prod[sel], entry[sel], lng[sel], sto[sel]], ignore_index=True)
if __name__ == "__main__": if __name__ == "__main__":
@ -83,7 +128,7 @@ if __name__ == "__main__":
snakemake = mock_snakemake( snakemake = mock_snakemake(
"build_gas_input_locations", "build_gas_input_locations",
simpl="", simpl="",
clusters="37", clusters="128",
) )
logging.basicConfig(level=snakemake.config["logging"]["level"]) logging.basicConfig(level=snakemake.config["logging"]["level"])
@ -104,9 +149,9 @@ if __name__ == "__main__":
countries = regions.index.str[:2].unique().str.replace("GB", "UK") countries = regions.index.str[:2].unique().str.replace("GB", "UK")
gas_input_locations = build_gas_input_locations( gas_input_locations = build_gas_input_locations(
snakemake.input.lng, snakemake.input.gem,
snakemake.input.entry, snakemake.input.entry,
snakemake.input.production, snakemake.input.storage,
countries, countries,
) )
@ -116,9 +161,13 @@ if __name__ == "__main__":
gas_input_nodes.to_file(snakemake.output.gas_input_nodes, driver="GeoJSON") gas_input_nodes.to_file(snakemake.output.gas_input_nodes, driver="GeoJSON")
ensure_columns = ["lng", "pipeline", "production", "storage"]
gas_input_nodes_s = ( gas_input_nodes_s = (
gas_input_nodes.groupby(["bus", "type"])["p_nom"].sum().unstack() gas_input_nodes.groupby(["bus", "type"])["capacity"]
.sum()
.unstack()
.reindex(columns=ensure_columns)
) )
gas_input_nodes_s.columns.name = "p_nom" gas_input_nodes_s.columns.name = "capacity"
gas_input_nodes_s.to_csv(snakemake.output.gas_input_nodes_simplified) gas_input_nodes_s.to_csv(snakemake.output.gas_input_nodes_simplified)

5
scripts/build_heat_demand.py
View File

@ -31,10 +31,7 @@ if __name__ == "__main__":
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
clustered_regions = ( clustered_regions = (
gpd.read_file(snakemake.input.regions_onshore) gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
.set_index("name")
.buffer(0)
.squeeze()
) )
I = cutout.indicatormatrix(clustered_regions) I = cutout.indicatormatrix(clustered_regions)

2
scripts/build_line_rating.py
View File

@ -119,7 +119,7 @@ def calculate_line_rating(n, cutout):
.apply(lambda x: int(re.findall(r"(\d+)-bundle", x)[0])) .apply(lambda x: int(re.findall(r"(\d+)-bundle", x)[0]))
) )
# Set default number of bundles per line # Set default number of bundles per line
relevant_lines["n_bundle"].fillna(1, inplace=True) relevant_lines["n_bundle"] = relevant_lines["n_bundle"].fillna(1)
R *= relevant_lines["n_bundle"] R *= relevant_lines["n_bundle"]
R = calculate_resistance(T=353, R_ref=R) R = calculate_resistance(T=353, R_ref=R)
Imax = cutout.line_rating(shapes, R, D=0.0218, Ts=353, epsilon=0.8, alpha=0.8) Imax = cutout.line_rating(shapes, R, D=0.0218, Ts=353, epsilon=0.8, alpha=0.8)

109
scripts/build_renewable_profiles.py
View File

@ -26,20 +26,9 @@ Relevant settings
renewable: renewable:
{technology}: {technology}:
cutout: cutout: corine: grid_codes: distance: natura: max_depth:
corine: max_shore_distance: min_shore_distance: capacity_per_sqkm:
grid_codes: correction_factor: min_p_max_pu: clip_p_max_pu: resource:
distance:
natura:
max_depth:
max_shore_distance:
min_shore_distance:
capacity_per_sqkm:
correction_factor:
potential:
min_p_max_pu:
clip_p_max_pu:
resource:
.. seealso:: .. seealso::
Documentation of the configuration file ``config/config.yaml`` at Documentation of the configuration file ``config/config.yaml`` at
@ -48,21 +37,30 @@ Relevant settings
Inputs Inputs
------ ------
- ``data/bundle/corine/g250_clc06_V18_5.tif``: `CORINE Land Cover (CLC) <https://land.copernicus.eu/pan-european/corine-land-cover>`_ inventory on `44 classes <https://wiki.openstreetmap.org/wiki/Corine_Land_Cover#Tagging>`_ of land use (e.g. forests, arable land, industrial, urban areas). - ``data/bundle/corine/g250_clc06_V18_5.tif``: `CORINE Land Cover (CLC)
<https://land.copernicus.eu/pan-european/corine-land-cover>`_ inventory on `44
classes <https://wiki.openstreetmap.org/wiki/Corine_Land_Cover#Tagging>`_ of
land use (e.g. forests, arable land, industrial, urban areas).
.. image:: img/corine.png .. image:: img/corine.png
:scale: 33 % :scale: 33 %
- ``data/bundle/GEBCO_2014_2D.nc``: A `bathymetric <https://en.wikipedia.org/wiki/Bathymetry>`_ data set with a global terrain model for ocean and land at 15 arc-second intervals by the `General Bathymetric Chart of the Oceans (GEBCO) <https://www.gebco.net/data_and_products/gridded_bathymetry_data/>`_. - ``data/bundle/GEBCO_2014_2D.nc``: A `bathymetric
<https://en.wikipedia.org/wiki/Bathymetry>`_ data set with a global terrain
model for ocean and land at 15 arc-second intervals by the `General
Bathymetric Chart of the Oceans (GEBCO)
<https://www.gebco.net/data_and_products/gridded_bathymetry_data/>`_.
.. image:: img/gebco_2019_grid_image.jpg .. image:: img/gebco_2019_grid_image.jpg
:scale: 50 % :scale: 50 %
**Source:** `GEBCO <https://www.gebco.net/data_and_products/images/gebco_2019_grid_image.jpg>`_ **Source:** `GEBCO
<https://www.gebco.net/data_and_products/images/gebco_2019_grid_image.jpg>`_
- ``resources/natura.tiff``: confer :ref:`natura` - ``resources/natura.tiff``: confer :ref:`natura`
- ``resources/offshore_shapes.geojson``: confer :ref:`shapes` - ``resources/offshore_shapes.geojson``: confer :ref:`shapes`
- ``resources/regions_onshore.geojson``: (if not offshore wind), confer :ref:`busregions` - ``resources/regions_onshore.geojson``: (if not offshore wind), confer
:ref:`busregions`
- ``resources/regions_offshore.geojson``: (if offshore wind), :ref:`busregions` - ``resources/regions_offshore.geojson``: (if offshore wind), :ref:`busregions`
- ``"cutouts/" + params["renewable"][{technology}]['cutout']``: :ref:`cutout` - ``"cutouts/" + params["renewable"][{technology}]['cutout']``: :ref:`cutout`
- ``networks/base.nc``: :ref:`base` - ``networks/base.nc``: :ref:`base`
@ -128,25 +126,25 @@ Description
This script functions at two main spatial resolutions: the resolution of the This script functions at two main spatial resolutions: the resolution of the
network nodes and their `Voronoi cells network nodes and their `Voronoi cells
<https://en.wikipedia.org/wiki/Voronoi_diagram>`_, and the resolution of the <https://en.wikipedia.org/wiki/Voronoi_diagram>`_, and the resolution of the
cutout grid cells for the weather data. Typically the weather data grid is cutout grid cells for the weather data. Typically the weather data grid is finer
finer than the network nodes, so we have to work out the distribution of than the network nodes, so we have to work out the distribution of generators
generators across the grid cells within each Voronoi cell. This is done by across the grid cells within each Voronoi cell. This is done by taking account
taking account of a combination of the available land at each grid cell and the of a combination of the available land at each grid cell and the capacity factor
capacity factor there. there.
First the script computes how much of the technology can be installed at each First the script computes how much of the technology can be installed at each
cutout grid cell and each node using the `GLAES cutout grid cell and each node using the `GLAES
<https://github.com/FZJ-IEK3-VSA/glaes>`_ library. This uses the CORINE land use data, <https://github.com/FZJ-IEK3-VSA/glaes>`_ library. This uses the CORINE land use
Natura2000 nature reserves and GEBCO bathymetry data. data, Natura2000 nature reserves and GEBCO bathymetry data.
.. image:: img/eligibility.png .. image:: img/eligibility.png
:scale: 50 % :scale: 50 %
:align: center :align: center
To compute the layout of generators in each node's Voronoi cell, the To compute the layout of generators in each node's Voronoi cell, the installable
installable potential in each grid cell is multiplied with the capacity factor potential in each grid cell is multiplied with the capacity factor at each grid
at each grid cell. This is done since we assume more generators are installed cell. This is done since we assume more generators are installed at cells with a
at cells with a higher capacity factor. higher capacity factor.
.. image:: img/offwinddc-gridcell.png .. image:: img/offwinddc-gridcell.png
:scale: 50 % :scale: 50 %
@ -164,20 +162,14 @@ at cells with a higher capacity factor.
:scale: 50 % :scale: 50 %
:align: center :align: center
This layout is then used to compute the generation availability time series This layout is then used to compute the generation availability time series from
from the weather data cutout from ``atlite``. the weather data cutout from ``atlite``.
Two methods are available to compute the maximal installable potential for the The maximal installable potential for the node (`p_nom_max`) is computed by
node (`p_nom_max`): ``simple`` and ``conservative``: adding up the installable potentials of the individual grid cells.
- ``simple`` adds up the installable potentials of the individual grid cells.
If the model comes close to this limit, then the time series may slightly If the model comes close to this limit, then the time series may slightly
overestimate production since it is assumed the geographical distribution is overestimate production since it is assumed the geographical distribution is
proportional to capacity factor. proportional to capacity factor.
- ``conservative`` assertains the nodal limit by increasing capacities
proportional to the layout until the limit of an individual grid cell is
reached.
""" """
import functools import functools
import logging import logging
@ -210,7 +202,6 @@ if __name__ == "__main__":
resource = params["resource"] # pv panel params / wind turbine params resource = params["resource"] # pv panel params / wind turbine params
correction_factor = params.get("correction_factor", 1.0) correction_factor = params.get("correction_factor", 1.0)
capacity_per_sqkm = params["capacity_per_sqkm"] capacity_per_sqkm = params["capacity_per_sqkm"]
p_nom_max_meth = params.get("potential", "conservative")
if isinstance(params.get("corine", {}), list): if isinstance(params.get("corine", {}), list):
params["corine"] = {"grid_codes": params["corine"]} params["corine"] = {"grid_codes": params["corine"]}
@ -277,15 +268,14 @@ if __name__ == "__main__":
snakemake.input.country_shapes, buffer=buffer, invert=True snakemake.input.country_shapes, buffer=buffer, invert=True
) )
kwargs = dict(nprocesses=nprocesses, disable_progressbar=noprogress) logger.info("Calculate landuse availability...")
if noprogress:
logger.info("Calculate landuse availabilities...")
start = time.time() start = time.time()
kwargs = dict(nprocesses=nprocesses, disable_progressbar=noprogress)
availability = cutout.availabilitymatrix(regions, excluder, **kwargs) availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
duration = time.time() - start duration = time.time() - start
logger.info(f"Completed availability calculation ({duration:2.2f}s)") logger.info(f"Completed landuse availability calculation ({duration:2.2f}s)")
else:
availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
# For Moldova and Ukraine: Overwrite parts not covered by Corine with # For Moldova and Ukraine: Overwrite parts not covered by Corine with
# externally determined available areas # externally determined available areas
@ -304,8 +294,19 @@ if __name__ == "__main__":
func = getattr(cutout, resource.pop("method")) func = getattr(cutout, resource.pop("method"))
if client is not None: if client is not None:
resource["dask_kwargs"] = {"scheduler": client} resource["dask_kwargs"] = {"scheduler": client}
logger.info("Calculate average capacity factor...")
start = time.time()
capacity_factor = correction_factor * func(capacity_factor=True, **resource) capacity_factor = correction_factor * func(capacity_factor=True, **resource)
layout = capacity_factor * area * capacity_per_sqkm layout = capacity_factor * area * capacity_per_sqkm
duration = time.time() - start
logger.info(f"Completed average capacity factor calculation ({duration:2.2f}s)")
logger.info("Calculate weighted capacity factor time series...")
start = time.time()
profile, capacities = func( profile, capacities = func(
matrix=availability.stack(spatial=["y", "x"]), matrix=availability.stack(spatial=["y", "x"]),
layout=layout, layout=layout,
@ -315,18 +316,14 @@ if __name__ == "__main__":
**resource, **resource,
) )
logger.info(f"Calculating maximal capacity per bus (method '{p_nom_max_meth}')") duration = time.time() - start
if p_nom_max_meth == "simple": logger.info(
p_nom_max = capacity_per_sqkm * availability @ area f"Completed weighted capacity factor time series calculation ({duration:2.2f}s)"
elif p_nom_max_meth == "conservative":
max_cap_factor = capacity_factor.where(availability != 0).max(["x", "y"])
p_nom_max = capacities / max_cap_factor
else:
raise AssertionError(
'Config key `potential` should be one of "simple" '
f'(default) or "conservative", not "{p_nom_max_meth}"'
) )
logger.info(f"Calculating maximal capacity per bus")
p_nom_max = capacity_per_sqkm * availability @ area
logger.info("Calculate average distances.") logger.info("Calculate average distances.")
layoutmatrix = (layout * availability).stack(spatial=["y", "x"]) layoutmatrix = (layout * availability).stack(spatial=["y", "x"])

6
scripts/build_retro_cost.py
View File

@ -836,9 +836,9 @@ def calculate_heat_losses(u_values, data_tabula, l_strength, temperature_factor)
F_red_temp = map_to_lstrength(l_strength, F_red_temp) F_red_temp = map_to_lstrength(l_strength, F_red_temp)
Q_ht = ( Q_ht = (
heat_transfer_perm2.groupby(level=1, axis=1) heat_transfer_perm2.T.groupby(level=1)
.sum() .sum()
.mul(F_red_temp.droplevel(0, axis=1)) .T.mul(F_red_temp.droplevel(0, axis=1))
.mul(temperature_factor.reindex(heat_transfer_perm2.index, level=0), axis=0) .mul(temperature_factor.reindex(heat_transfer_perm2.index, level=0), axis=0)
) )
@ -878,7 +878,7 @@ def calculate_gain_utilisation_factor(heat_transfer_perm2, Q_ht, Q_gain):
Calculates gain utilisation factor nu. Calculates gain utilisation factor nu.
""" """
# time constant of the building tau [h] = c_m [Wh/(m^2K)] * 1 /(H_tr_e+H_tb*H_ve) [m^2 K /W] # time constant of the building tau [h] = c_m [Wh/(m^2K)] * 1 /(H_tr_e+H_tb*H_ve) [m^2 K /W]
tau = c_m / heat_transfer_perm2.groupby(level=1, axis=1).sum() tau = c_m / heat_transfer_perm2.T.groupby(axis=1).sum().T
alpha = alpha_H_0 + (tau / tau_H_0) alpha = alpha_H_0 + (tau / tau_H_0)
# heat balance ratio # heat balance ratio
gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0) gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0)

2
scripts/build_ship_raster.py
View File

@ -64,7 +64,7 @@ if __name__ == "__main__":
with zipfile.ZipFile(snakemake.input.ship_density) as zip_f: with zipfile.ZipFile(snakemake.input.ship_density) as zip_f:
zip_f.extract("shipdensity_global.tif") zip_f.extract("shipdensity_global.tif")
with rioxarray.open_rasterio("shipdensity_global.tif") as ship_density: with rioxarray.open_rasterio("shipdensity_global.tif") as ship_density:
ship_density = ship_density.drop(["band"]).sel( ship_density = ship_density.drop_vars(["band"]).sel(
x=slice(min(xs), max(Xs)), y=slice(max(Ys), min(ys)) x=slice(min(xs), max(Xs)), y=slice(max(Ys), min(ys))
) )
ship_density.rio.to_raster(snakemake.output[0]) ship_density.rio.to_raster(snakemake.output[0])

5
scripts/build_solar_thermal_profiles.py
View File

@ -33,10 +33,7 @@ if __name__ == "__main__":
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
clustered_regions = ( clustered_regions = (
gpd.read_file(snakemake.input.regions_onshore) gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
.set_index("name")
.buffer(0)
.squeeze()
) )
I = cutout.indicatormatrix(clustered_regions) I = cutout.indicatormatrix(clustered_regions)

5
scripts/build_temperature_profiles.py
View File

@ -31,10 +31,7 @@ if __name__ == "__main__":
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time) cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
clustered_regions = ( clustered_regions = (
gpd.read_file(snakemake.input.regions_onshore) gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
.set_index("name")
.buffer(0)
.squeeze()
) )
I = cutout.indicatormatrix(clustered_regions) I = cutout.indicatormatrix(clustered_regions)

4
scripts/plot_network.py
View File

@ -31,7 +31,7 @@ def rename_techs_tyndp(tech):
tech = rename_techs(tech) tech = rename_techs(tech)
if "heat pump" in tech or "resistive heater" in tech: if "heat pump" in tech or "resistive heater" in tech:
return "power-to-heat" return "power-to-heat"
elif tech in ["H2 Electrolysis", "methanation", "helmeth", "H2 liquefaction"]: elif tech in ["H2 Electrolysis", "methanation", "H2 liquefaction"]:
return "power-to-gas" return "power-to-gas"
elif tech == "H2": elif tech == "H2":
return "H2 storage" return "H2 storage"
@ -495,7 +495,7 @@ def plot_ch4_map(network):
# make a fake MultiIndex so that area is correct for legend # make a fake MultiIndex so that area is correct for legend
fossil_gas.index = pd.MultiIndex.from_product([fossil_gas.index, ["fossil gas"]]) fossil_gas.index = pd.MultiIndex.from_product([fossil_gas.index, ["fossil gas"]])
methanation_i = n.links[n.links.carrier.isin(["helmeth", "Sabatier"])].index methanation_i = n.links.query("carrier == 'Sabatier'").index
methanation = ( methanation = (
abs( abs(
n.links_t.p1.loc[:, methanation_i].mul( n.links_t.p1.loc[:, methanation_i].mul(

1
scripts/plot_summary.py
View File

@ -121,7 +121,6 @@ preferred_order = pd.Index(
"gas boiler", "gas boiler",
"gas", "gas",
"natural gas", "natural gas",
"helmeth",
"methanation", "methanation",
"ammonia", "ammonia",
"hydrogen storage", "hydrogen storage",

246
scripts/prepare_sector_network.py
View File

@ -95,12 +95,14 @@ def define_spatial(nodes, options):
spatial.gas.industry = nodes + " gas for industry" spatial.gas.industry = nodes + " gas for industry"
spatial.gas.industry_cc = nodes + " gas for industry CC" spatial.gas.industry_cc = nodes + " gas for industry CC"
spatial.gas.biogas_to_gas = nodes + " biogas to gas" spatial.gas.biogas_to_gas = nodes + " biogas to gas"
spatial.gas.biogas_to_gas_cc = nodes + "biogas to gas CC"
else: else:
spatial.gas.nodes = ["EU gas"] spatial.gas.nodes = ["EU gas"]
spatial.gas.locations = ["EU"] spatial.gas.locations = ["EU"]
spatial.gas.biogas = ["EU biogas"] spatial.gas.biogas = ["EU biogas"]
spatial.gas.industry = ["gas for industry"] spatial.gas.industry = ["gas for industry"]
spatial.gas.biogas_to_gas = ["EU biogas to gas"] spatial.gas.biogas_to_gas = ["EU biogas to gas"]
spatial.gas.biogas_to_gas_cc = ["EU biogas to gas CC"]
if options.get("co2_spatial", options["co2network"]): if options.get("co2_spatial", options["co2network"]):
spatial.gas.industry_cc = nodes + " gas for industry CC" spatial.gas.industry_cc = nodes + " gas for industry CC"
else: else:
@ -452,10 +454,11 @@ def add_carrier_buses(n, carrier, nodes=None):
n.add("Carrier", carrier) n.add("Carrier", carrier)
unit = "MWh_LHV" if carrier == "gas" else "MWh_th" unit = "MWh_LHV" if carrier == "gas" else "MWh_th"
# preliminary value for non-gas carriers to avoid zeros
capital_cost = costs.at["gas storage", "fixed"] if carrier == "gas" else 0.02
n.madd("Bus", nodes, location=location, carrier=carrier, unit=unit) n.madd("Bus", nodes, location=location, carrier=carrier, unit=unit)
# capital cost could be corrected to e.g. 0.2 EUR/kWh * annuity and O&M
n.madd( n.madd(
"Store", "Store",
nodes + " Store", nodes + " Store",
@ -463,8 +466,7 @@ def add_carrier_buses(n, carrier, nodes=None):
e_nom_extendable=True, e_nom_extendable=True,
e_cyclic=True, e_cyclic=True,
carrier=carrier, carrier=carrier,
capital_cost=0.2 capital_cost=capital_cost,
* costs.at[carrier, "discount rate"], # preliminary value to avoid zeros
) )
n.madd( n.madd(
@ -805,14 +807,13 @@ def add_ammonia(n, costs):
bus2=nodes + " H2", bus2=nodes + " H2",
p_nom_extendable=True, p_nom_extendable=True,
carrier="Haber-Bosch", carrier="Haber-Bosch",
efficiency=1 efficiency=1 / costs.at["Haber-Bosch", "electricity-input"],
/ ( efficiency2=-costs.at["Haber-Bosch", "hydrogen-input"]
cf_industry["MWh_elec_per_tNH3_electrolysis"] / costs.at["Haber-Bosch", "electricity-input"],
/ cf_industry["MWh_NH3_per_tNH3"] capital_cost=costs.at["Haber-Bosch", "fixed"]
), # output: MW_NH3 per MW_elec / costs.at["Haber-Bosch", "electricity-input"],
efficiency2=-cf_industry["MWh_H2_per_tNH3_electrolysis"] marginal_cost=costs.at["Haber-Bosch", "VOM"]
/ cf_industry["MWh_elec_per_tNH3_electrolysis"], # input: MW_H2 per MW_elec / costs.at["Haber-Bosch", "electricity-input"],
capital_cost=costs.at["Haber-Bosch", "fixed"],
lifetime=costs.at["Haber-Bosch", "lifetime"], lifetime=costs.at["Haber-Bosch", "lifetime"],
) )
@ -1023,7 +1024,7 @@ def insert_gas_distribution_costs(n, costs):
f"Inserting gas distribution grid with investment cost factor of {f_costs}" f"Inserting gas distribution grid with investment cost factor of {f_costs}"
) )
capital_cost = costs.loc["electricity distribution grid"]["fixed"] * f_costs capital_cost = costs.at["electricity distribution grid", "fixed"] * f_costs
# gas boilers # gas boilers
gas_b = n.links.index[ gas_b = n.links.index[
@ -1100,6 +1101,7 @@ def add_storage_and_grids(n, costs):
efficiency=costs.at["OCGT", "efficiency"], efficiency=costs.at["OCGT", "efficiency"],
capital_cost=costs.at["OCGT", "fixed"] capital_cost=costs.at["OCGT", "fixed"]
* costs.at["OCGT", "efficiency"], # NB: fixed cost is per MWel * costs.at["OCGT", "efficiency"], # NB: fixed cost is per MWel
marginal_cost=costs.at["OCGT", "VOM"],
lifetime=costs.at["OCGT", "lifetime"], lifetime=costs.at["OCGT", "lifetime"],
) )
@ -1160,7 +1162,7 @@ def add_storage_and_grids(n, costs):
if options["gas_network"]: if options["gas_network"]:
logger.info( logger.info(
"Add natural gas infrastructure, incl. LNG terminals, production and entry-points." "Add natural gas infrastructure, incl. LNG terminals, production, storage and entry-points."
) )
if options["H2_retrofit"]: if options["H2_retrofit"]:
@ -1205,10 +1207,25 @@ def add_storage_and_grids(n, costs):
remove_i = n.generators[gas_i & internal_i].index remove_i = n.generators[gas_i & internal_i].index
n.generators.drop(remove_i, inplace=True) n.generators.drop(remove_i, inplace=True)
p_nom = gas_input_nodes.sum(axis=1).rename(lambda x: x + " gas") input_types = ["lng", "pipeline", "production"]
p_nom = gas_input_nodes[input_types].sum(axis=1).rename(lambda x: x + " gas")
n.generators.loc[gas_i, "p_nom_extendable"] = False n.generators.loc[gas_i, "p_nom_extendable"] = False
n.generators.loc[gas_i, "p_nom"] = p_nom n.generators.loc[gas_i, "p_nom"] = p_nom
# add existing gas storage capacity
gas_i = n.stores.carrier == "gas"
e_nom = (
gas_input_nodes["storage"]
.rename(lambda x: x + " gas Store")
.reindex(n.stores.index)
.fillna(0.0)
* 1e3
) # MWh_LHV
e_nom.clip(
upper=e_nom.quantile(0.98), inplace=True
) # limit extremely large storage
n.stores.loc[gas_i, "e_nom_min"] = e_nom
# add candidates for new gas pipelines to achieve full connectivity # add candidates for new gas pipelines to achieve full connectivity
G = nx.Graph() G = nx.Graph()
@ -1343,6 +1360,7 @@ def add_storage_and_grids(n, costs):
bus2=spatial.co2.nodes, bus2=spatial.co2.nodes,
p_nom_extendable=True, p_nom_extendable=True,
carrier="Sabatier", carrier="Sabatier",
p_min_pu=options.get("min_part_load_methanation", 0),
efficiency=costs.at["methanation", "efficiency"], efficiency=costs.at["methanation", "efficiency"],
efficiency2=-costs.at["methanation", "efficiency"] efficiency2=-costs.at["methanation", "efficiency"]
* costs.at["gas", "CO2 intensity"], * costs.at["gas", "CO2 intensity"],
@ -1351,23 +1369,6 @@ def add_storage_and_grids(n, costs):
lifetime=costs.at["methanation", "lifetime"], lifetime=costs.at["methanation", "lifetime"],
) )
if options["helmeth"]:
n.madd(
"Link",
spatial.nodes,
suffix=" helmeth",
bus0=nodes,
bus1=spatial.gas.nodes,
bus2=spatial.co2.nodes,
carrier="helmeth",
p_nom_extendable=True,
efficiency=costs.at["helmeth", "efficiency"],
efficiency2=-costs.at["helmeth", "efficiency"]
* costs.at["gas", "CO2 intensity"],
capital_cost=costs.at["helmeth", "fixed"],
lifetime=costs.at["helmeth", "lifetime"],
)
if options.get("coal_cc"): if options.get("coal_cc"):
n.madd( n.madd(
"Link", "Link",
@ -1630,7 +1631,7 @@ def build_heat_demand(n):
electric_nodes = n.loads.index[n.loads.carrier == "electricity"] electric_nodes = n.loads.index[n.loads.carrier == "electricity"]
n.loads_t.p_set[electric_nodes] = ( n.loads_t.p_set[electric_nodes] = (
n.loads_t.p_set[electric_nodes] n.loads_t.p_set[electric_nodes]
- electric_heat_supply.groupby(level=1, axis=1).sum()[electric_nodes] - electric_heat_supply.T.groupby(level=1).sum().T[electric_nodes]
) )
return heat_demand return heat_demand
@ -1697,6 +1698,7 @@ def add_heat(n, costs):
n.madd( n.madd(
"Generator", "Generator",
nodes[name] + f" {name} heat vent", nodes[name] + f" {name} heat vent",
bus=nodes[name] + f" {name} heat",
location=nodes[name], location=nodes[name],
carrier=name + " heat vent", carrier=name + " heat vent",
p_nom_extendable=True, p_nom_extendable=True,
@ -1723,15 +1725,17 @@ def add_heat(n, costs):
if sector in name: if sector in name:
heat_load = ( heat_load = (
heat_demand[[sector + " water", sector + " space"]] heat_demand[[sector + " water", sector + " space"]]
.groupby(level=1, axis=1) .T.groupby(level=1)
.sum()[nodes[name]] .sum()
.T[nodes[name]]
.multiply(factor) .multiply(factor)
) )
if name == "urban central": if name == "urban central":
heat_load = ( heat_load = (
heat_demand.groupby(level=1, axis=1) heat_demand.T.groupby(level=1)
.sum()[nodes[name]] .sum()
.T[nodes[name]]
.multiply( .multiply(
factor * (1 + options["district_heating"]["district_heating_loss"]) factor * (1 + options["district_heating"]["district_heating_loss"])
) )
@ -2165,12 +2169,42 @@ def add_biomass(n, costs):
bus1=spatial.gas.nodes, bus1=spatial.gas.nodes,
bus2="co2 atmosphere", bus2="co2 atmosphere",
carrier="biogas to gas", carrier="biogas to gas",
capital_cost=costs.loc["biogas upgrading", "fixed"], capital_cost=costs.at["biogas", "fixed"]
marginal_cost=costs.loc["biogas upgrading", "VOM"], + costs.at["biogas upgrading", "fixed"],
marginal_cost=costs.at["biogas upgrading", "VOM"],
efficiency=costs.at["biogas", "efficiency"],
efficiency2=-costs.at["gas", "CO2 intensity"], efficiency2=-costs.at["gas", "CO2 intensity"],
p_nom_extendable=True, p_nom_extendable=True,
) )
if options.get("biogas_upgrading_cc"):
# Assuming for costs that the CO2 from upgrading is pure, such as in amine scrubbing. I.e., with and without CC is
# equivalent. Adding biomass CHP capture because biogas is often small-scale and decentral so further
# from e.g. CO2 grid or buyers. This is a proxy for the added cost for e.g. a raw biogas pipeline to a central upgrading facility
n.madd(
"Link",
spatial.gas.biogas_to_gas_cc,
bus0=spatial.gas.biogas,
bus1=spatial.gas.nodes,
bus2="co2 stored",
bus3="co2 atmosphere",
carrier="biogas to gas CC",
capital_cost=costs.at["biogas CC", "fixed"]
+ costs.at["biogas upgrading", "fixed"]
+ costs.at["biomass CHP capture", "fixed"]
* costs.at["biogas CC", "CO2 stored"],
marginal_cost=costs.at["biogas CC", "VOM"]
+ costs.at["biogas upgrading", "VOM"],
efficiency=costs.at["biogas CC", "efficiency"],
efficiency2=costs.at["biogas CC", "CO2 stored"]
* costs.at["biogas CC", "capture rate"],
efficiency3=-costs.at["gas", "CO2 intensity"]
- costs.at["biogas CC", "CO2 stored"]
* costs.at["biogas CC", "capture rate"],
p_nom_extendable=True,
)
if options["biomass_transport"]: if options["biomass_transport"]:
# add biomass transport # add biomass transport
transport_costs = pd.read_csv( transport_costs = pd.read_csv(
@ -2296,6 +2330,7 @@ def add_biomass(n, costs):
efficiency=costs.at["biomass boiler", "efficiency"], efficiency=costs.at["biomass boiler", "efficiency"],
capital_cost=costs.at["biomass boiler", "efficiency"] capital_cost=costs.at["biomass boiler", "efficiency"]
* costs.at["biomass boiler", "fixed"], * costs.at["biomass boiler", "fixed"],
marginal_cost=costs.at["biomass boiler", "pelletizing cost"],
lifetime=costs.at["biomass boiler", "lifetime"], lifetime=costs.at["biomass boiler", "lifetime"],
) )
@ -2315,7 +2350,7 @@ def add_biomass(n, costs):
+ costs.at["BtL", "CO2 stored"], + costs.at["BtL", "CO2 stored"],
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["BtL", "fixed"], capital_cost=costs.at["BtL", "fixed"],
marginal_cost=costs.at["BtL", "efficiency"] * costs.loc["BtL", "VOM"], marginal_cost=costs.at["BtL", "efficiency"] * costs.at["BtL", "VOM"],
) )
# TODO: Update with energy penalty # TODO: Update with energy penalty
@ -2336,7 +2371,7 @@ def add_biomass(n, costs):
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["BtL", "fixed"] capital_cost=costs.at["BtL", "fixed"]
+ costs.at["biomass CHP capture", "fixed"] * costs.at["BtL", "CO2 stored"], + costs.at["biomass CHP capture", "fixed"] * costs.at["BtL", "CO2 stored"],
marginal_cost=costs.at["BtL", "efficiency"] * costs.loc["BtL", "VOM"], marginal_cost=costs.at["BtL", "efficiency"] * costs.at["BtL", "VOM"],
) )
# BioSNG from solid biomass # BioSNG from solid biomass
@ -2355,7 +2390,7 @@ def add_biomass(n, costs):
+ costs.at["BioSNG", "CO2 stored"], + costs.at["BioSNG", "CO2 stored"],
p_nom_extendable=True, p_nom_extendable=True,
capital_cost=costs.at["BioSNG", "fixed"], capital_cost=costs.at["BioSNG", "fixed"],
marginal_cost=costs.at["BioSNG", "efficiency"] * costs.loc["BioSNG", "VOM"], marginal_cost=costs.at["BioSNG", "efficiency"] * costs.at["BioSNG", "VOM"],
) )
# TODO: Update with energy penalty for CC # TODO: Update with energy penalty for CC
@ -2379,7 +2414,7 @@ def add_biomass(n, costs):
capital_cost=costs.at["BioSNG", "fixed"] capital_cost=costs.at["BioSNG", "fixed"]
+ costs.at["biomass CHP capture", "fixed"] + costs.at["biomass CHP capture", "fixed"]
* costs.at["BioSNG", "CO2 stored"], * costs.at["BioSNG", "CO2 stored"],
marginal_cost=costs.at["BioSNG", "efficiency"] * costs.loc["BioSNG", "VOM"], marginal_cost=costs.at["BioSNG", "efficiency"] * costs.at["BioSNG", "VOM"],
) )
@ -2612,6 +2647,8 @@ def add_industry(n, costs):
p_min_pu=options.get("min_part_load_methanolisation", 0), p_min_pu=options.get("min_part_load_methanolisation", 0),
capital_cost=costs.at["methanolisation", "fixed"] capital_cost=costs.at["methanolisation", "fixed"]
* options["MWh_MeOH_per_MWh_H2"], # EUR/MW_H2/a * options["MWh_MeOH_per_MWh_H2"], # EUR/MW_H2/a
marginal_cost=options["MWh_MeOH_per_MWh_H2"]
* costs.at["methanolisation", "VOM"],
lifetime=costs.at["methanolisation", "lifetime"], lifetime=costs.at["methanolisation", "lifetime"],
efficiency=options["MWh_MeOH_per_MWh_H2"], efficiency=options["MWh_MeOH_per_MWh_H2"],
efficiency2=-options["MWh_MeOH_per_MWh_H2"] / options["MWh_MeOH_per_MWh_e"], efficiency2=-options["MWh_MeOH_per_MWh_H2"] / options["MWh_MeOH_per_MWh_e"],
@ -2729,6 +2766,8 @@ def add_industry(n, costs):
efficiency=costs.at["Fischer-Tropsch", "efficiency"], efficiency=costs.at["Fischer-Tropsch", "efficiency"],
capital_cost=costs.at["Fischer-Tropsch", "fixed"] capital_cost=costs.at["Fischer-Tropsch", "fixed"]
* costs.at["Fischer-Tropsch", "efficiency"], # EUR/MW_H2/a * costs.at["Fischer-Tropsch", "efficiency"], # EUR/MW_H2/a
marginal_cost=costs.at["Fischer-Tropsch", "efficiency"]
* costs.at["Fischer-Tropsch", "VOM"],
efficiency2=-costs.at["oil", "CO2 intensity"] efficiency2=-costs.at["oil", "CO2 intensity"]
* costs.at["Fischer-Tropsch", "efficiency"], * costs.at["Fischer-Tropsch", "efficiency"],
p_nom_extendable=True, p_nom_extendable=True,
@ -2934,8 +2973,13 @@ def add_waste_heat(n):
if not urban_central.empty: if not urban_central.empty:
urban_central = urban_central.str[: -len(" urban central heat")] urban_central = urban_central.str[: -len(" urban central heat")]
link_carriers = n.links.carrier.unique()
# TODO what is the 0.95 and should it be a config option? # TODO what is the 0.95 and should it be a config option?
if options["use_fischer_tropsch_waste_heat"]: if (
options["use_fischer_tropsch_waste_heat"]
and "Fischer-Tropsch" in link_carriers
):
n.links.loc[urban_central + " Fischer-Tropsch", "bus3"] = ( n.links.loc[urban_central + " Fischer-Tropsch", "bus3"] = (
urban_central + " urban central heat" urban_central + " urban central heat"
) )
@ -2943,8 +2987,48 @@ def add_waste_heat(n):
0.95 - n.links.loc[urban_central + " Fischer-Tropsch", "efficiency"] 0.95 - n.links.loc[urban_central + " Fischer-Tropsch", "efficiency"]
) )
if options["use_methanation_waste_heat"] and "Sabatier" in link_carriers:
n.links.loc[urban_central + " Sabatier", "bus3"] = (
urban_central + " urban central heat"
)
n.links.loc[urban_central + " Sabatier", "efficiency3"] = (
0.95 - n.links.loc[urban_central + " Sabatier", "efficiency"]
)
# DEA quotes 15% of total input (11% of which are high-value heat)
if options["use_haber_bosch_waste_heat"] and "Haber-Bosch" in link_carriers:
n.links.loc[urban_central + " Haber-Bosch", "bus3"] = (
urban_central + " urban central heat"
)
total_energy_input = (
cf_industry["MWh_H2_per_tNH3_electrolysis"]
+ cf_industry["MWh_elec_per_tNH3_electrolysis"]
) / cf_industry["MWh_NH3_per_tNH3"]
electricity_input = (
cf_industry["MWh_elec_per_tNH3_electrolysis"]
/ cf_industry["MWh_NH3_per_tNH3"]
)
n.links.loc[urban_central + " Haber-Bosch", "efficiency3"] = (
0.15 * total_energy_input / electricity_input
)
if (
options["use_methanolisation_waste_heat"]
and "methanolisation" in link_carriers
):
n.links.loc[urban_central + " methanolisation", "bus4"] = (
urban_central + " urban central heat"
)
n.links.loc[urban_central + " methanolisation", "efficiency4"] = (
costs.at["methanolisation", "heat-output"]
/ costs.at["methanolisation", "hydrogen-input"]
)
# TODO integrate usable waste heat efficiency into technology-data from DEA # TODO integrate usable waste heat efficiency into technology-data from DEA
if options.get("use_electrolysis_waste_heat", False): if (
options.get("use_electrolysis_waste_heat", False)
and "H2 Electrolysis" in link_carriers
):
n.links.loc[urban_central + " H2 Electrolysis", "bus2"] = ( n.links.loc[urban_central + " H2 Electrolysis", "bus2"] = (
urban_central + " urban central heat" urban_central + " urban central heat"
) )
@ -2952,7 +3036,7 @@ def add_waste_heat(n):
0.84 - n.links.loc[urban_central + " H2 Electrolysis", "efficiency"] 0.84 - n.links.loc[urban_central + " H2 Electrolysis", "efficiency"]
) )
if options["use_fuel_cell_waste_heat"]: if options["use_fuel_cell_waste_heat"] and "H2 Fuel Cell" in link_carriers:
n.links.loc[urban_central + " H2 Fuel Cell", "bus2"] = ( n.links.loc[urban_central + " H2 Fuel Cell", "bus2"] = (
urban_central + " urban central heat" urban_central + " urban central heat"
) )
@ -3310,6 +3394,57 @@ def set_temporal_aggregation(n, opts, solver_name):
return n return n
def lossy_bidirectional_links(n, carrier, efficiencies={}):
"Split bidirectional links into two unidirectional links to include transmission losses."
carrier_i = n.links.query("carrier == @carrier").index
if (
not any((v != 1.0) or (v >= 0) for v in efficiencies.values())
or carrier_i.empty
):
return
efficiency_static = efficiencies.get("efficiency_static", 1)
efficiency_per_1000km = efficiencies.get("efficiency_per_1000km", 1)
compression_per_1000km = efficiencies.get("compression_per_1000km", 0)
logger.info(
f"Specified losses for {carrier} transmission "
f"(static: {efficiency_static}, per 1000km: {efficiency_per_1000km}, compression per 1000km: {compression_per_1000km}). "
"Splitting bidirectional links."
)
n.links.loc[carrier_i, "p_min_pu"] = 0
n.links.loc[
carrier_i, "efficiency"
] = efficiency_static * efficiency_per_1000km ** (
n.links.loc[carrier_i, "length"] / 1e3
)
rev_links = (
n.links.loc[carrier_i].copy().rename({"bus0": "bus1", "bus1": "bus0"}, axis=1)
)
rev_links["length_original"] = rev_links["length"]
rev_links["capital_cost"] = 0
rev_links["length"] = 0
rev_links["reversed"] = True
rev_links.index = rev_links.index.map(lambda x: x + "-reversed")
n.links = pd.concat([n.links, rev_links], sort=False)
n.links["reversed"] = n.links["reversed"].fillna(False)
n.links["length_original"] = n.links["length_original"].fillna(n.links.length)
# do compression losses after concatenation to take electricity consumption at bus0 in either direction
carrier_i = n.links.query("carrier == @carrier").index
if compression_per_1000km > 0:
n.links.loc[carrier_i, "bus2"] = n.links.loc[carrier_i, "bus0"].map(
n.buses.location
) # electricity
n.links.loc[carrier_i, "efficiency2"] = (
-compression_per_1000km * n.links.loc[carrier_i, "length_original"] / 1e3
)
if __name__ == "__main__": if __name__ == "__main__":
if "snakemake" not in globals(): if "snakemake" not in globals():
from _helpers import mock_snakemake from _helpers import mock_snakemake
@ -3387,6 +3522,15 @@ if __name__ == "__main__":
if "nodistrict" in opts: if "nodistrict" in opts:
options["district_heating"]["progress"] = 0.0 options["district_heating"]["progress"] = 0.0
if "nowasteheat" in opts:
logger.info("Disabling waste heat.")
options["use_fischer_tropsch_waste_heat"] = False
options["use_methanolisation_waste_heat"] = False
options["use_haber_bosch_waste_heat"] = False
options["use_methanation_waste_heat"] = False
options["use_fuel_cell_waste_heat"] = False
options["use_electrolysis_waste_heat"] = False
if "T" in opts: if "T" in opts:
add_land_transport(n, costs) add_land_transport(n, costs)
@ -3476,6 +3620,18 @@ if __name__ == "__main__":
if options["electricity_grid_connection"]: if options["electricity_grid_connection"]:
add_electricity_grid_connection(n, costs) add_electricity_grid_connection(n, costs)
for k, v in options["transmission_efficiency"].items():
lossy_bidirectional_links(n, k, v)
# Workaround: Remove lines with conflicting (and unrealistic) properties
# cf. https://github.com/PyPSA/pypsa-eur/issues/444
if snakemake.config["solving"]["options"]["transmission_losses"]:
idx = n.lines.query("num_parallel == 0").index
logger.info(
f"Removing {len(idx)} line(s) with properties conflicting with transmission losses functionality."
)
n.mremove("Line", idx)
first_year_myopic = (snakemake.params.foresight in ["myopic", "perfect"]) and ( first_year_myopic = (snakemake.params.foresight in ["myopic", "perfect"]) and (
snakemake.params.planning_horizons[0] == investment_year snakemake.params.planning_horizons[0] == investment_year
) )

4
scripts/retrieve_databundle.py
View File

@ -36,7 +36,7 @@ import logging
import tarfile import tarfile
from pathlib import Path from pathlib import Path
from _helpers import configure_logging, progress_retrieve from _helpers import configure_logging, progress_retrieve, validate_checksum
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -65,6 +65,8 @@ if __name__ == "__main__":
disable_progress = snakemake.config["run"].get("disable_progressbar", False) disable_progress = snakemake.config["run"].get("disable_progressbar", False)
progress_retrieve(url, tarball_fn, disable=disable_progress) progress_retrieve(url, tarball_fn, disable=disable_progress)
validate_checksum(tarball_fn, url)
logger.info("Extracting databundle.") logger.info("Extracting databundle.")
tarfile.open(tarball_fn).extractall(to_fn) tarfile.open(tarball_fn).extractall(to_fn)

4
scripts/retrieve_gas_infrastructure_data.py
View File

@ -11,7 +11,7 @@ import logging
import zipfile import zipfile
from pathlib import Path from pathlib import Path
from _helpers import progress_retrieve from _helpers import progress_retrieve, validate_checksum
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -35,6 +35,8 @@ if __name__ == "__main__":
disable_progress = snakemake.config["run"].get("disable_progressbar", False) disable_progress = snakemake.config["run"].get("disable_progressbar", False)
progress_retrieve(url, zip_fn, disable=disable_progress) progress_retrieve(url, zip_fn, disable=disable_progress)
validate_checksum(zip_fn, url)
logger.info("Extracting databundle.") logger.info("Extracting databundle.")
zipfile.ZipFile(zip_fn).extractall(to_fn) zipfile.ZipFile(zip_fn).extractall(to_fn)

4
scripts/retrieve_sector_databundle.py
View File

@ -13,7 +13,7 @@ logger = logging.getLogger(__name__)
import tarfile import tarfile
from pathlib import Path from pathlib import Path
from _helpers import configure_logging, progress_retrieve from _helpers import configure_logging, progress_retrieve, validate_checksum
if __name__ == "__main__": if __name__ == "__main__":
if "snakemake" not in globals(): if "snakemake" not in globals():
@ -34,6 +34,8 @@ if __name__ == "__main__":
disable_progress = snakemake.config["run"].get("disable_progressbar", False) disable_progress = snakemake.config["run"].get("disable_progressbar", False)
progress_retrieve(url, tarball_fn, disable=disable_progress) progress_retrieve(url, tarball_fn, disable=disable_progress)
validate_checksum(tarball_fn, url)
logger.info("Extracting databundle.") logger.info("Extracting databundle.")
tarfile.open(tarball_fn).extractall(to_fn) tarfile.open(tarball_fn).extractall(to_fn)

41
scripts/solve_network.py
View File

@ -689,6 +689,35 @@ def add_battery_constraints(n):
n.model.add_constraints(lhs == 0, name="Link-charger_ratio") n.model.add_constraints(lhs == 0, name="Link-charger_ratio")
def add_lossy_bidirectional_link_constraints(n):
if not n.links.p_nom_extendable.any() or not "reversed" in n.links.columns:
return
n.links["reversed"] = n.links.reversed.fillna(0).astype(bool)
carriers = n.links.loc[n.links.reversed, "carrier"].unique()
forward_i = n.links.query(
"carrier in @carriers and ~reversed and p_nom_extendable"
).index
def get_backward_i(forward_i):
return pd.Index(
[
re.sub(r"-(\d{4})$", r"-reversed-\1", s)
if re.search(r"-\d{4}$", s)
else s + "-reversed"
for s in forward_i
]
)
backward_i = get_backward_i(forward_i)
lhs = n.model["Link-p_nom"].loc[backward_i]
rhs = n.model["Link-p_nom"].loc[forward_i]
n.model.add_constraints(lhs == rhs, name="Link-bidirectional_sync")
def add_chp_constraints(n): def add_chp_constraints(n):
electric = ( electric = (
n.links.index.str.contains("urban central") n.links.index.str.contains("urban central")
@ -747,9 +776,13 @@ def add_pipe_retrofit_constraint(n):
""" """
Add constraint for retrofitting existing CH4 pipelines to H2 pipelines. Add constraint for retrofitting existing CH4 pipelines to H2 pipelines.
""" """
gas_pipes_i = n.links.query("carrier == 'gas pipeline' and p_nom_extendable").index if "reversed" not in n.links.columns:
n.links["reversed"] = False
gas_pipes_i = n.links.query(
"carrier == 'gas pipeline' and p_nom_extendable and ~reversed"
).index
h2_retrofitted_i = n.links.query( h2_retrofitted_i = n.links.query(
"carrier == 'H2 pipeline retrofitted' and p_nom_extendable" "carrier == 'H2 pipeline retrofitted' and p_nom_extendable and ~reversed"
).index ).index
if h2_retrofitted_i.empty or gas_pipes_i.empty: if h2_retrofitted_i.empty or gas_pipes_i.empty:
@ -788,6 +821,7 @@ def extra_functionality(n, snapshots):
if "EQ" in o: if "EQ" in o:
add_EQ_constraints(n, o) add_EQ_constraints(n, o)
add_battery_constraints(n) add_battery_constraints(n)
add_lossy_bidirectional_link_constraints(n)
add_pipe_retrofit_constraint(n) add_pipe_retrofit_constraint(n)
if n._multi_invest: if n._multi_invest:
add_carbon_constraint(n, snapshots) add_carbon_constraint(n, snapshots)
@ -848,6 +882,9 @@ def solve_network(n, config, solving, opts="", **kwargs):
f"Solving status '{status}' with termination condition '{condition}'" f"Solving status '{status}' with termination condition '{condition}'"
) )
if "infeasible" in condition: if "infeasible" in condition:
labels = n.model.compute_infeasibilities()
logger.info("Labels:\n" + labels)
n.model.print_infeasibilities()
raise RuntimeError("Solving status 'infeasible'") raise RuntimeError("Solving status 'infeasible'")
return n return n