Merge branch 'master' into custom-extra-functionality
This commit is contained in:
Fabian Neumann
commit
b4fb395158
@ -50,7 +50,7 @@ repos:
|
||||
- id: blackdoc
|
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|
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# Formatting with "black" coding style
|
||||
- repo: https://github.com/psf/black
|
||||
- repo: https://github.com/psf/black-pre-commit-mirror
|
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rev: 23.12.1
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hooks:
|
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# Format Python files
|
||||
|
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@ -14,7 +14,7 @@ from snakemake.utils import min_version
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min_version("7.7")
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|
||||
|
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if not exists("config/config.yaml"):
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if not exists("config/config.yaml") and exists("config/config.default.yaml"):
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copyfile("config/config.default.yaml", "config/config.yaml")
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|
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|
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|
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@ -158,6 +158,7 @@ renewable:
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resource:
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method: wind
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turbine: Vestas_V112_3MW
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add_cutout_windspeed: true
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capacity_per_sqkm: 3
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# correction_factor: 0.93
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corine:
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@ -166,13 +167,13 @@ renewable:
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distance_grid_codes: [1, 2, 3, 4, 5, 6]
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natura: true
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excluder_resolution: 100
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potential: simple # or conservative
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clip_p_max_pu: 1.e-2
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offwind-ac:
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cutout: europe-2013-era5
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resource:
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method: wind
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turbine: NREL_ReferenceTurbine_5MW_offshore
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turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
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add_cutout_windspeed: true
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capacity_per_sqkm: 2
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correction_factor: 0.8855
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corine: [44, 255]
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@ -181,13 +182,13 @@ renewable:
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max_depth: 50
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max_shore_distance: 30000
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excluder_resolution: 200
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potential: simple # or conservative
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clip_p_max_pu: 1.e-2
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offwind-dc:
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cutout: europe-2013-era5
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resource:
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method: wind
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turbine: NREL_ReferenceTurbine_5MW_offshore
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turbine: NREL_ReferenceTurbine_2020ATB_5.5MW
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add_cutout_windspeed: true
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capacity_per_sqkm: 2
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correction_factor: 0.8855
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corine: [44, 255]
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@ -196,7 +197,6 @@ renewable:
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max_depth: 50
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min_shore_distance: 30000
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excluder_resolution: 200
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potential: simple # or conservative
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clip_p_max_pu: 1.e-2
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solar:
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cutout: europe-2013-sarah
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@ -211,7 +211,6 @@ renewable:
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corine: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 26, 31, 32]
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natura: true
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excluder_resolution: 100
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potential: simple # or conservative
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clip_p_max_pu: 1.e-2
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hydro:
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cutout: europe-2013-era5
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@ -448,7 +447,6 @@ sector:
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solar_cf_correction: 0.788457 # = >>> 1/1.2683
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marginal_cost_storage: 0. #1e-4
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methanation: true
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helmeth: false
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coal_cc: false
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dac: true
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co2_vent: false
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@ -477,14 +475,28 @@ sector:
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- nearshore # within 50 km of sea
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# - offshore
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ammonia: false
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min_part_load_fischer_tropsch: 0.9
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min_part_load_methanolisation: 0.5
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min_part_load_fischer_tropsch: 0.7
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min_part_load_methanolisation: 0.3
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min_part_load_methanation: 0.3
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use_fischer_tropsch_waste_heat: true
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use_haber_bosch_waste_heat: true
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use_methanolisation_waste_heat: true
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use_methanation_waste_heat: true
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use_fuel_cell_waste_heat: true
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use_electrolysis_waste_heat: false
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use_electrolysis_waste_heat: true
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electricity_distribution_grid: true
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electricity_distribution_grid_cost_factor: 1.0
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electricity_grid_connection: true
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transmission_efficiency:
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DC:
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efficiency_static: 0.98
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efficiency_per_1000km: 0.977
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H2 pipeline:
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efficiency_per_1000km: 1 # 0.979
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compression_per_1000km: 0.019
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gas pipeline:
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efficiency_per_1000km: 1 #0.977
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compression_per_1000km: 0.01
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H2_network: true
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gas_network: false
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H2_retrofit: false
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@ -494,6 +506,7 @@ sector:
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gas_distribution_grid_cost_factor: 1.0
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biomass_spatial: false
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biomass_transport: false
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biogas_upgrading_cc: false
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conventional_generation:
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OCGT: gas
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biomass_to_liquid: false
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@ -544,8 +557,8 @@ industry:
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MWh_NH3_per_tNH3: 5.166
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MWh_CH4_per_tNH3_SMR: 10.8
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MWh_elec_per_tNH3_SMR: 0.7
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MWh_H2_per_tNH3_electrolysis: 6.5
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MWh_elec_per_tNH3_electrolysis: 1.17
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MWh_H2_per_tNH3_electrolysis: 5.93
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MWh_elec_per_tNH3_electrolysis: 0.2473
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MWh_NH3_per_MWh_H2_cracker: 1.46 # https://github.com/euronion/trace/blob/44a5ff8401762edbef80eff9cfe5a47c8d3c8be4/data/efficiencies.csv
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NH3_process_emissions: 24.5
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petrochemical_process_emissions: 25.5
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@ -776,6 +789,7 @@ plotting:
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fossil gas: '#e05b09'
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natural gas: '#e05b09'
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biogas to gas: '#e36311'
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biogas to gas CC: '#e51245'
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CCGT: '#a85522'
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CCGT marginal: '#a85522'
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allam: '#B98F76'
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@ -877,6 +891,7 @@ plotting:
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# heat demand
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Heat load: '#cc1f1f'
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heat: '#cc1f1f'
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heat vent: '#aa3344'
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heat demand: '#cc1f1f'
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rural heat: '#ff5c5c'
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residential rural heat: '#ff7c7c'
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@ -946,7 +961,6 @@ plotting:
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Sabatier: '#9850ad'
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methanation: '#c44ce6'
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methane: '#c44ce6'
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helmeth: '#e899ff'
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# synfuels
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Fischer-Tropsch: '#25c49a'
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liquid: '#25c49a'
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|
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@ -12,5 +12,4 @@ ship_threshold,--,float,"Ship density threshold from which areas are excluded."
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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."
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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."
|
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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`"
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||||
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."
|
||||
|
||||
|
@ -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."
|
||||
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."
|
||||
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."
|
||||
|
||||
|
@ -9,7 +9,6 @@ corine,,,
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-- 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``."
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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."
|
||||
correction_factor,--,float,"Correction factor for capacity factor time series."
|
||||
excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."
|
||||
|
||||
|
@ -71,7 +71,6 @@ solar_thermal,--,"{true, false}",Add option for using solar thermal to generate
|
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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
|
||||
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)
|
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coal_cc,--,"{true, false}",Add option for coal CHPs with carbon capture
|
||||
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.
|
||||
@ -108,6 +107,11 @@ electricity_distribution _grid,--,"{true, false}",Add a simplified representatio
|
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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
|
||||
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.
|
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-- -- efficiency_static,p.u.,float,Length-independent transmission efficiency.
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-- -- efficiency_per_1000km,p.u. per 1000 km,float,Length-dependent transmission efficiency ($\eta^{\text{length}}$)
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-- -- 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.
|
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H2_network,--,"{true, false}",Add option for new hydrogen pipelines
|
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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.
|
||||
@ -118,6 +122,7 @@ gas_distribution_grid _cost_factor,,,Multiplier for the investment cost of the g
|
||||
,,,
|
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biomass_spatial,--,"{true, false}",Add option for resolving biomass demand regionally
|
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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.
|
||||
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
|
||||
|
||||
|
@ -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."
|
||||
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``."
|
||||
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."
|
||||
excluder_resolution,m,float,"Resolution on which to perform geographical elibility analysis."
|
||||
|
||||
|
@ -116,7 +116,7 @@ of the individual parts.
|
||||
topics we are working on. Please feel free to help or make suggestions.
|
||||
|
||||
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
|
||||
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
|
||||
|
||||
@ -10,6 +10,13 @@ Release Notes
|
||||
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
|
||||
supported by ``pypsa-eur``.
|
||||
|
||||
@ -38,12 +45,30 @@ Upcoming Release
|
||||
|
||||
* 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
|
||||
network has been moved from ``focus_weights:`` to ``clustering:
|
||||
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.
|
||||
|
||||
* 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
|
||||
countries are excluded by default and is currently constrained to power-sector
|
||||
only parts of the workflow. A special config file
|
||||
@ -59,6 +84,17 @@ Upcoming Release
|
||||
default setting points to an empty hull at
|
||||
``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**
|
||||
|
||||
@ -190,6 +226,8 @@ PyPSA-Eur 0.8.1 (27th July 2023)
|
||||
(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)
|
||||
=================================
|
||||
|
||||
|
||||
@ -85,12 +85,12 @@ if config["sector"]["gas_network"] or config["sector"]["H2_retrofit"]:
|
||||
|
||||
rule build_gas_input_locations:
|
||||
input:
|
||||
lng=HTTP.remote(
|
||||
gem=HTTP.remote(
|
||||
"https://globalenergymonitor.org/wp-content/uploads/2023/07/Europe-Gas-Tracker-2023-03-v3.xlsx",
|
||||
keep_local=True,
|
||||
),
|
||||
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_elec_s{simpl}_{clusters}.geojson",
|
||||
regions_offshore=RESOURCES
|
||||
|
||||
@ -2,6 +2,11 @@
|
||||
#
|
||||
# SPDX-License-Identifier: MIT
|
||||
|
||||
import os, sys
|
||||
|
||||
sys.path.insert(0, os.path.abspath("scripts"))
|
||||
from _helpers import validate_checksum
|
||||
|
||||
|
||||
def memory(w):
|
||||
factor = 3.0
|
||||
|
||||
@ -77,6 +77,7 @@ if config["enable"]["retrieve"] and config["enable"].get("retrieve_cutout", True
|
||||
retries: 2
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
validate_checksum(output[0], input[0])
|
||||
|
||||
|
||||
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
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
validate_checksum(output[0], input[0])
|
||||
|
||||
|
||||
if config["enable"]["retrieve"] and config["enable"].get(
|
||||
@ -167,6 +169,7 @@ if config["enable"]["retrieve"] and (
|
||||
"IGGIELGN_LNGs.geojson",
|
||||
"IGGIELGN_BorderPoints.geojson",
|
||||
"IGGIELGN_Productions.geojson",
|
||||
"IGGIELGN_Storages.geojson",
|
||||
"IGGIELGN_PipeSegments.geojson",
|
||||
]
|
||||
|
||||
@ -226,6 +229,7 @@ if config["enable"]["retrieve"]:
|
||||
retries: 2
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
validate_checksum(output[0], input[0])
|
||||
|
||||
|
||||
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",
|
||||
run:
|
||||
move(input[0], output[0])
|
||||
validate_checksum(output[0], input[0])
|
||||
|
||||
|
||||
if config["enable"]["retrieve"]:
|
||||
|
||||
@ -4,6 +4,7 @@
|
||||
# SPDX-License-Identifier: MIT
|
||||
|
||||
import contextlib
|
||||
import hashlib
|
||||
import logging
|
||||
import os
|
||||
import urllib
|
||||
@ -11,6 +12,7 @@ from pathlib import Path
|
||||
|
||||
import pandas as pd
|
||||
import pytz
|
||||
import requests
|
||||
import yaml
|
||||
from pypsa.components import component_attrs, components
|
||||
from pypsa.descriptors import Dict
|
||||
@ -318,3 +320,63 @@ def update_config_with_sector_opts(config, sector_opts):
|
||||
if o.startswith("CF+"):
|
||||
l = o.split("+")[1:]
|
||||
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."
|
||||
|
||||
@ -120,6 +120,33 @@ def add_brownfield(n, n_p, year):
|
||||
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 "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
@ -150,5 +177,7 @@ if __name__ == "__main__":
|
||||
|
||||
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.export_to_netcdf(snakemake.output[0])
|
||||
|
||||
@ -134,7 +134,7 @@ def disaggregate_nuts0(bio):
|
||||
# get population in nuts2
|
||||
pop_nuts2 = pop.loc[pop.index.str.len() == 4]
|
||||
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
|
||||
bio_nodal = bio.loc[pop_nuts2.ct]
|
||||
|
||||
@ -25,10 +25,7 @@ if __name__ == "__main__":
|
||||
cutout = atlite.Cutout(snakemake.input.cutout)
|
||||
|
||||
clustered_regions = (
|
||||
gpd.read_file(snakemake.input.regions_onshore)
|
||||
.set_index("name")
|
||||
.buffer(0)
|
||||
.squeeze()
|
||||
gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
|
||||
)
|
||||
|
||||
I = cutout.indicatormatrix(clustered_regions)
|
||||
|
||||
@ -81,7 +81,7 @@ def load_timeseries(fn, years, countries, powerstatistics=True):
|
||||
return s[: -len(pattern)]
|
||||
|
||||
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)
|
||||
.filter(like=pattern)
|
||||
.rename(columns=rename)
|
||||
|
||||
@ -189,12 +189,12 @@ def idees_per_country(ct, year, base_dir):
|
||||
ct_totals["total residential water"] = df.at["Water heating"]
|
||||
|
||||
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"]
|
||||
|
||||
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]
|
||||
|
||||
@ -202,13 +202,13 @@ def idees_per_country(ct, year, base_dir):
|
||||
ct_totals["total residential"] = df[row]
|
||||
|
||||
assert df.index[47] == "Electricity"
|
||||
ct_totals["electricity residential"] = df[47]
|
||||
ct_totals["electricity residential"] = df.iloc[47]
|
||||
|
||||
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"
|
||||
ct_totals["thermal uses residential"] = df[50]
|
||||
ct_totals["thermal uses residential"] = df.iloc[50]
|
||||
|
||||
# services
|
||||
|
||||
@ -222,12 +222,12 @@ def idees_per_country(ct, year, base_dir):
|
||||
ct_totals["total services water"] = df["Hot water"]
|
||||
|
||||
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"]
|
||||
|
||||
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]
|
||||
|
||||
@ -235,13 +235,13 @@ def idees_per_country(ct, year, base_dir):
|
||||
ct_totals["total services"] = df[row]
|
||||
|
||||
assert df.index[50] == "Electricity"
|
||||
ct_totals["electricity services"] = df[50]
|
||||
ct_totals["electricity services"] = df.iloc[50]
|
||||
|
||||
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"
|
||||
ct_totals["thermal uses services"] = df[53]
|
||||
ct_totals["thermal uses services"] = df.iloc[53]
|
||||
|
||||
# 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)"]
|
||||
|
||||
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"
|
||||
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"
|
||||
ct_totals["total other road passenger"] = df[31]
|
||||
ct_totals["total other road passenger"] = df.iloc[31]
|
||||
|
||||
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"
|
||||
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"
|
||||
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)"
|
||||
ct_totals["total heavy duty road freight"] = df[row]
|
||||
|
||||
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]
|
||||
|
||||
@ -312,39 +312,39 @@ def idees_per_country(ct, year, base_dir):
|
||||
ct_totals["electricity rail"] = df["Electricity"]
|
||||
|
||||
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[19] == "Electric"
|
||||
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"
|
||||
ct_totals["total rail freight"] = df[21]
|
||||
ct_totals["total rail freight"] = df.iloc[21]
|
||||
|
||||
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]
|
||||
|
||||
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"
|
||||
ct_totals["total aviation freight"] = df[10]
|
||||
ct_totals["total aviation freight"] = df.iloc[10]
|
||||
|
||||
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[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"
|
||||
ct_totals["total domestic aviation freight"] = df[11]
|
||||
ct_totals["total domestic aviation freight"] = df.iloc[11]
|
||||
|
||||
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 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]
|
||||
|
||||
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)
|
||||
|
||||
|
||||
@ -23,11 +23,10 @@ def read_scigrid_gas(fn):
|
||||
return df
|
||||
|
||||
|
||||
def build_gem_lng_data(lng_fn):
|
||||
df = pd.read_excel(lng_fn[0], sheet_name="LNG terminals - data")
|
||||
def build_gem_lng_data(fn):
|
||||
df = pd.read_excel(fn[0], sheet_name="LNG terminals - data")
|
||||
df = df.set_index("ComboID")
|
||||
|
||||
remove_status = ["Cancelled"]
|
||||
remove_country = ["Cyprus", "Turkey"]
|
||||
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")
|
||||
|
||||
|
||||
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 = build_gem_lng_data(lng_fn)
|
||||
lng = build_gem_lng_data(gem_fn)
|
||||
|
||||
# Entry points from outside the model scope
|
||||
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
|
||||
]
|
||||
|
||||
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
|
||||
prod = read_scigrid_gas(prod_fn)
|
||||
prod = prod.loc[
|
||||
(prod.geometry.y > 35) & (prod.geometry.x < 30) & (prod.country_code != "DE")
|
||||
]
|
||||
prod = build_gem_prod_data(gem_fn)
|
||||
|
||||
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
|
||||
lng["p_nom"] = lng["CapacityInMtpa"] * mtpa_to_mw
|
||||
entry["p_nom"] = entry["max_cap_from_to_M_m3_per_d"] * mcm_per_day_to_mw
|
||||
prod["p_nom"] = prod["max_supply_M_m3_per_d"] * mcm_per_day_to_mw
|
||||
mcm_to_gwh = 11.36 # MCM to GWh
|
||||
lng["capacity"] = lng["CapacityInMtpa"] * mtpa_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"
|
||||
entry["type"] = "pipeline"
|
||||
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__":
|
||||
@ -83,7 +128,7 @@ if __name__ == "__main__":
|
||||
snakemake = mock_snakemake(
|
||||
"build_gas_input_locations",
|
||||
simpl="",
|
||||
clusters="37",
|
||||
clusters="128",
|
||||
)
|
||||
|
||||
logging.basicConfig(level=snakemake.config["logging"]["level"])
|
||||
@ -104,9 +149,9 @@ if __name__ == "__main__":
|
||||
countries = regions.index.str[:2].unique().str.replace("GB", "UK")
|
||||
|
||||
gas_input_locations = build_gas_input_locations(
|
||||
snakemake.input.lng,
|
||||
snakemake.input.gem,
|
||||
snakemake.input.entry,
|
||||
snakemake.input.production,
|
||||
snakemake.input.storage,
|
||||
countries,
|
||||
)
|
||||
|
||||
@ -116,9 +161,13 @@ if __name__ == "__main__":
|
||||
|
||||
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.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)
|
||||
|
||||
@ -31,10 +31,7 @@ if __name__ == "__main__":
|
||||
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
|
||||
|
||||
clustered_regions = (
|
||||
gpd.read_file(snakemake.input.regions_onshore)
|
||||
.set_index("name")
|
||||
.buffer(0)
|
||||
.squeeze()
|
||||
gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
|
||||
)
|
||||
|
||||
I = cutout.indicatormatrix(clustered_regions)
|
||||
|
||||
@ -119,7 +119,7 @@ def calculate_line_rating(n, cutout):
|
||||
.apply(lambda x: int(re.findall(r"(\d+)-bundle", x)[0]))
|
||||
)
|
||||
# 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 = calculate_resistance(T=353, R_ref=R)
|
||||
Imax = cutout.line_rating(shapes, R, D=0.0218, Ts=353, epsilon=0.8, alpha=0.8)
|
||||
|
||||
@ -26,20 +26,9 @@ Relevant settings
|
||||
|
||||
renewable:
|
||||
{technology}:
|
||||
cutout:
|
||||
corine:
|
||||
grid_codes:
|
||||
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:
|
||||
cutout: corine: grid_codes: distance: natura: max_depth:
|
||||
max_shore_distance: min_shore_distance: capacity_per_sqkm:
|
||||
correction_factor: min_p_max_pu: clip_p_max_pu: resource:
|
||||
|
||||
.. seealso::
|
||||
Documentation of the configuration file ``config/config.yaml`` at
|
||||
@ -48,21 +37,30 @@ Relevant settings
|
||||
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
|
||||
: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
|
||||
: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/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`
|
||||
- ``"cutouts/" + params["renewable"][{technology}]['cutout']``: :ref:`cutout`
|
||||
- ``networks/base.nc``: :ref:`base`
|
||||
@ -128,25 +126,25 @@ Description
|
||||
This script functions at two main spatial resolutions: the resolution of the
|
||||
network nodes and their `Voronoi cells
|
||||
<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
|
||||
finer than the network nodes, so we have to work out the distribution of
|
||||
generators across the grid cells within each Voronoi cell. This is done by
|
||||
taking account of a combination of the available land at each grid cell and the
|
||||
capacity factor there.
|
||||
cutout grid cells for the weather data. Typically the weather data grid is finer
|
||||
than the network nodes, so we have to work out the distribution of generators
|
||||
across the grid cells within each Voronoi cell. This is done by taking account
|
||||
of a combination of the available land at each grid cell and the capacity factor
|
||||
there.
|
||||
|
||||
First the script computes how much of the technology can be installed at each
|
||||
cutout grid cell and each node using the `GLAES
|
||||
<https://github.com/FZJ-IEK3-VSA/glaes>`_ library. This uses the CORINE land use data,
|
||||
Natura2000 nature reserves and GEBCO bathymetry data.
|
||||
<https://github.com/FZJ-IEK3-VSA/glaes>`_ library. This uses the CORINE land use
|
||||
data, Natura2000 nature reserves and GEBCO bathymetry data.
|
||||
|
||||
.. image:: img/eligibility.png
|
||||
:scale: 50 %
|
||||
:align: center
|
||||
|
||||
To compute the layout of generators in each node's Voronoi cell, the
|
||||
installable potential in each grid cell is multiplied with the capacity factor
|
||||
at each grid cell. This is done since we assume more generators are installed
|
||||
at cells with a higher capacity factor.
|
||||
To compute the layout of generators in each node's Voronoi cell, the installable
|
||||
potential in each grid cell is multiplied with the capacity factor at each grid
|
||||
cell. This is done since we assume more generators are installed at cells with a
|
||||
higher capacity factor.
|
||||
|
||||
.. image:: img/offwinddc-gridcell.png
|
||||
:scale: 50 %
|
||||
@ -164,20 +162,14 @@ at cells with a higher capacity factor.
|
||||
:scale: 50 %
|
||||
:align: center
|
||||
|
||||
This layout is then used to compute the generation availability time series
|
||||
from the weather data cutout from ``atlite``.
|
||||
This layout is then used to compute the generation availability time series from
|
||||
the weather data cutout from ``atlite``.
|
||||
|
||||
Two methods are available to compute the maximal installable potential for the
|
||||
node (`p_nom_max`): ``simple`` and ``conservative``:
|
||||
|
||||
- ``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
|
||||
overestimate production since it is assumed the geographical distribution is
|
||||
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.
|
||||
The maximal installable potential for the node (`p_nom_max`) is computed by
|
||||
adding up the installable potentials of the individual grid cells.
|
||||
If the model comes close to this limit, then the time series may slightly
|
||||
overestimate production since it is assumed the geographical distribution is
|
||||
proportional to capacity factor.
|
||||
"""
|
||||
import functools
|
||||
import logging
|
||||
@ -210,7 +202,6 @@ if __name__ == "__main__":
|
||||
resource = params["resource"] # pv panel params / wind turbine params
|
||||
correction_factor = params.get("correction_factor", 1.0)
|
||||
capacity_per_sqkm = params["capacity_per_sqkm"]
|
||||
p_nom_max_meth = params.get("potential", "conservative")
|
||||
|
||||
if isinstance(params.get("corine", {}), list):
|
||||
params["corine"] = {"grid_codes": params["corine"]}
|
||||
@ -277,15 +268,14 @@ if __name__ == "__main__":
|
||||
snakemake.input.country_shapes, buffer=buffer, invert=True
|
||||
)
|
||||
|
||||
kwargs = dict(nprocesses=nprocesses, disable_progressbar=noprogress)
|
||||
if noprogress:
|
||||
logger.info("Calculate landuse availabilities...")
|
||||
logger.info("Calculate landuse availability...")
|
||||
start = time.time()
|
||||
|
||||
kwargs = dict(nprocesses=nprocesses, disable_progressbar=noprogress)
|
||||
availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
|
||||
|
||||
duration = time.time() - start
|
||||
logger.info(f"Completed availability calculation ({duration:2.2f}s)")
|
||||
else:
|
||||
availability = cutout.availabilitymatrix(regions, excluder, **kwargs)
|
||||
logger.info(f"Completed landuse availability calculation ({duration:2.2f}s)")
|
||||
|
||||
# For Moldova and Ukraine: Overwrite parts not covered by Corine with
|
||||
# externally determined available areas
|
||||
@ -304,8 +294,19 @@ if __name__ == "__main__":
|
||||
func = getattr(cutout, resource.pop("method"))
|
||||
if client is not None:
|
||||
resource["dask_kwargs"] = {"scheduler": client}
|
||||
|
||||
logger.info("Calculate average capacity factor...")
|
||||
start = time.time()
|
||||
|
||||
capacity_factor = correction_factor * func(capacity_factor=True, **resource)
|
||||
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(
|
||||
matrix=availability.stack(spatial=["y", "x"]),
|
||||
layout=layout,
|
||||
@ -315,18 +316,14 @@ if __name__ == "__main__":
|
||||
**resource,
|
||||
)
|
||||
|
||||
logger.info(f"Calculating maximal capacity per bus (method '{p_nom_max_meth}')")
|
||||
if p_nom_max_meth == "simple":
|
||||
p_nom_max = capacity_per_sqkm * availability @ area
|
||||
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}"'
|
||||
duration = time.time() - start
|
||||
logger.info(
|
||||
f"Completed weighted capacity factor time series calculation ({duration:2.2f}s)"
|
||||
)
|
||||
|
||||
logger.info(f"Calculating maximal capacity per bus")
|
||||
p_nom_max = capacity_per_sqkm * availability @ area
|
||||
|
||||
logger.info("Calculate average distances.")
|
||||
layoutmatrix = (layout * availability).stack(spatial=["y", "x"])
|
||||
|
||||
|
||||
@ -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)
|
||||
|
||||
Q_ht = (
|
||||
heat_transfer_perm2.groupby(level=1, axis=1)
|
||||
heat_transfer_perm2.T.groupby(level=1)
|
||||
.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)
|
||||
)
|
||||
|
||||
@ -878,7 +878,7 @@ def calculate_gain_utilisation_factor(heat_transfer_perm2, Q_ht, Q_gain):
|
||||
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]
|
||||
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)
|
||||
# heat balance ratio
|
||||
gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0)
|
||||
|
||||
@ -64,7 +64,7 @@ if __name__ == "__main__":
|
||||
with zipfile.ZipFile(snakemake.input.ship_density) as zip_f:
|
||||
zip_f.extract("shipdensity_global.tif")
|
||||
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))
|
||||
)
|
||||
ship_density.rio.to_raster(snakemake.output[0])
|
||||
|
||||
@ -33,10 +33,7 @@ if __name__ == "__main__":
|
||||
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
|
||||
|
||||
clustered_regions = (
|
||||
gpd.read_file(snakemake.input.regions_onshore)
|
||||
.set_index("name")
|
||||
.buffer(0)
|
||||
.squeeze()
|
||||
gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
|
||||
)
|
||||
|
||||
I = cutout.indicatormatrix(clustered_regions)
|
||||
|
||||
@ -31,10 +31,7 @@ if __name__ == "__main__":
|
||||
cutout = atlite.Cutout(snakemake.input.cutout).sel(time=time)
|
||||
|
||||
clustered_regions = (
|
||||
gpd.read_file(snakemake.input.regions_onshore)
|
||||
.set_index("name")
|
||||
.buffer(0)
|
||||
.squeeze()
|
||||
gpd.read_file(snakemake.input.regions_onshore).set_index("name").buffer(0)
|
||||
)
|
||||
|
||||
I = cutout.indicatormatrix(clustered_regions)
|
||||
|
||||
@ -31,7 +31,7 @@ def rename_techs_tyndp(tech):
|
||||
tech = rename_techs(tech)
|
||||
if "heat pump" in tech or "resistive heater" in tech:
|
||||
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"
|
||||
elif tech == "H2":
|
||||
return "H2 storage"
|
||||
@ -495,7 +495,7 @@ def plot_ch4_map(network):
|
||||
# make a fake MultiIndex so that area is correct for legend
|
||||
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 = (
|
||||
abs(
|
||||
n.links_t.p1.loc[:, methanation_i].mul(
|
||||
|
||||
@ -121,7 +121,6 @@ preferred_order = pd.Index(
|
||||
"gas boiler",
|
||||
"gas",
|
||||
"natural gas",
|
||||
"helmeth",
|
||||
"methanation",
|
||||
"ammonia",
|
||||
"hydrogen storage",
|
||||
|
||||
@ -95,12 +95,14 @@ def define_spatial(nodes, options):
|
||||
spatial.gas.industry = nodes + " gas for industry"
|
||||
spatial.gas.industry_cc = nodes + " gas for industry CC"
|
||||
spatial.gas.biogas_to_gas = nodes + " biogas to gas"
|
||||
spatial.gas.biogas_to_gas_cc = nodes + "biogas to gas CC"
|
||||
else:
|
||||
spatial.gas.nodes = ["EU gas"]
|
||||
spatial.gas.locations = ["EU"]
|
||||
spatial.gas.biogas = ["EU biogas"]
|
||||
spatial.gas.industry = ["gas for industry"]
|
||||
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"]):
|
||||
spatial.gas.industry_cc = nodes + " gas for industry CC"
|
||||
else:
|
||||
@ -452,10 +454,11 @@ def add_carrier_buses(n, carrier, nodes=None):
|
||||
n.add("Carrier", carrier)
|
||||
|
||||
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)
|
||||
|
||||
# capital cost could be corrected to e.g. 0.2 EUR/kWh * annuity and O&M
|
||||
n.madd(
|
||||
"Store",
|
||||
nodes + " Store",
|
||||
@ -463,8 +466,7 @@ def add_carrier_buses(n, carrier, nodes=None):
|
||||
e_nom_extendable=True,
|
||||
e_cyclic=True,
|
||||
carrier=carrier,
|
||||
capital_cost=0.2
|
||||
* costs.at[carrier, "discount rate"], # preliminary value to avoid zeros
|
||||
capital_cost=capital_cost,
|
||||
)
|
||||
|
||||
n.madd(
|
||||
@ -805,14 +807,13 @@ def add_ammonia(n, costs):
|
||||
bus2=nodes + " H2",
|
||||
p_nom_extendable=True,
|
||||
carrier="Haber-Bosch",
|
||||
efficiency=1
|
||||
/ (
|
||||
cf_industry["MWh_elec_per_tNH3_electrolysis"]
|
||||
/ cf_industry["MWh_NH3_per_tNH3"]
|
||||
), # output: MW_NH3 per MW_elec
|
||||
efficiency2=-cf_industry["MWh_H2_per_tNH3_electrolysis"]
|
||||
/ cf_industry["MWh_elec_per_tNH3_electrolysis"], # input: MW_H2 per MW_elec
|
||||
capital_cost=costs.at["Haber-Bosch", "fixed"],
|
||||
efficiency=1 / costs.at["Haber-Bosch", "electricity-input"],
|
||||
efficiency2=-costs.at["Haber-Bosch", "hydrogen-input"]
|
||||
/ costs.at["Haber-Bosch", "electricity-input"],
|
||||
capital_cost=costs.at["Haber-Bosch", "fixed"]
|
||||
/ costs.at["Haber-Bosch", "electricity-input"],
|
||||
marginal_cost=costs.at["Haber-Bosch", "VOM"]
|
||||
/ costs.at["Haber-Bosch", "electricity-input"],
|
||||
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}"
|
||||
)
|
||||
|
||||
capital_cost = costs.loc["electricity distribution grid"]["fixed"] * f_costs
|
||||
capital_cost = costs.at["electricity distribution grid", "fixed"] * f_costs
|
||||
|
||||
# gas boilers
|
||||
gas_b = n.links.index[
|
||||
@ -1100,6 +1101,7 @@ def add_storage_and_grids(n, costs):
|
||||
efficiency=costs.at["OCGT", "efficiency"],
|
||||
capital_cost=costs.at["OCGT", "fixed"]
|
||||
* costs.at["OCGT", "efficiency"], # NB: fixed cost is per MWel
|
||||
marginal_cost=costs.at["OCGT", "VOM"],
|
||||
lifetime=costs.at["OCGT", "lifetime"],
|
||||
)
|
||||
|
||||
@ -1160,7 +1162,7 @@ def add_storage_and_grids(n, costs):
|
||||
|
||||
if options["gas_network"]:
|
||||
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"]:
|
||||
@ -1205,10 +1207,25 @@ def add_storage_and_grids(n, costs):
|
||||
remove_i = n.generators[gas_i & internal_i].index
|
||||
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"] = 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
|
||||
|
||||
G = nx.Graph()
|
||||
@ -1343,6 +1360,7 @@ def add_storage_and_grids(n, costs):
|
||||
bus2=spatial.co2.nodes,
|
||||
p_nom_extendable=True,
|
||||
carrier="Sabatier",
|
||||
p_min_pu=options.get("min_part_load_methanation", 0),
|
||||
efficiency=costs.at["methanation", "efficiency"],
|
||||
efficiency2=-costs.at["methanation", "efficiency"]
|
||||
* costs.at["gas", "CO2 intensity"],
|
||||
@ -1351,23 +1369,6 @@ def add_storage_and_grids(n, costs):
|
||||
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"):
|
||||
n.madd(
|
||||
"Link",
|
||||
@ -1630,7 +1631,7 @@ def build_heat_demand(n):
|
||||
electric_nodes = n.loads.index[n.loads.carrier == "electricity"]
|
||||
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
|
||||
@ -1697,6 +1698,7 @@ def add_heat(n, costs):
|
||||
n.madd(
|
||||
"Generator",
|
||||
nodes[name] + f" {name} heat vent",
|
||||
bus=nodes[name] + f" {name} heat",
|
||||
location=nodes[name],
|
||||
carrier=name + " heat vent",
|
||||
p_nom_extendable=True,
|
||||
@ -1723,15 +1725,17 @@ def add_heat(n, costs):
|
||||
if sector in name:
|
||||
heat_load = (
|
||||
heat_demand[[sector + " water", sector + " space"]]
|
||||
.groupby(level=1, axis=1)
|
||||
.sum()[nodes[name]]
|
||||
.T.groupby(level=1)
|
||||
.sum()
|
||||
.T[nodes[name]]
|
||||
.multiply(factor)
|
||||
)
|
||||
|
||||
if name == "urban central":
|
||||
heat_load = (
|
||||
heat_demand.groupby(level=1, axis=1)
|
||||
.sum()[nodes[name]]
|
||||
heat_demand.T.groupby(level=1)
|
||||
.sum()
|
||||
.T[nodes[name]]
|
||||
.multiply(
|
||||
factor * (1 + options["district_heating"]["district_heating_loss"])
|
||||
)
|
||||
@ -2165,12 +2169,42 @@ def add_biomass(n, costs):
|
||||
bus1=spatial.gas.nodes,
|
||||
bus2="co2 atmosphere",
|
||||
carrier="biogas to gas",
|
||||
capital_cost=costs.loc["biogas upgrading", "fixed"],
|
||||
marginal_cost=costs.loc["biogas upgrading", "VOM"],
|
||||
capital_cost=costs.at["biogas", "fixed"]
|
||||
+ costs.at["biogas upgrading", "fixed"],
|
||||
marginal_cost=costs.at["biogas upgrading", "VOM"],
|
||||
efficiency=costs.at["biogas", "efficiency"],
|
||||
efficiency2=-costs.at["gas", "CO2 intensity"],
|
||||
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"]:
|
||||
# add biomass transport
|
||||
transport_costs = pd.read_csv(
|
||||
@ -2296,6 +2330,7 @@ def add_biomass(n, costs):
|
||||
efficiency=costs.at["biomass boiler", "efficiency"],
|
||||
capital_cost=costs.at["biomass boiler", "efficiency"]
|
||||
* costs.at["biomass boiler", "fixed"],
|
||||
marginal_cost=costs.at["biomass boiler", "pelletizing cost"],
|
||||
lifetime=costs.at["biomass boiler", "lifetime"],
|
||||
)
|
||||
|
||||
@ -2315,7 +2350,7 @@ def add_biomass(n, costs):
|
||||
+ costs.at["BtL", "CO2 stored"],
|
||||
p_nom_extendable=True,
|
||||
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
|
||||
@ -2336,7 +2371,7 @@ def add_biomass(n, costs):
|
||||
p_nom_extendable=True,
|
||||
capital_cost=costs.at["BtL", "fixed"]
|
||||
+ 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
|
||||
@ -2355,7 +2390,7 @@ def add_biomass(n, costs):
|
||||
+ costs.at["BioSNG", "CO2 stored"],
|
||||
p_nom_extendable=True,
|
||||
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
|
||||
@ -2379,7 +2414,7 @@ def add_biomass(n, costs):
|
||||
capital_cost=costs.at["BioSNG", "fixed"]
|
||||
+ costs.at["biomass CHP capture", "fixed"]
|
||||
* 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),
|
||||
capital_cost=costs.at["methanolisation", "fixed"]
|
||||
* 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"],
|
||||
efficiency=options["MWh_MeOH_per_MWh_H2"],
|
||||
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"],
|
||||
capital_cost=costs.at["Fischer-Tropsch", "fixed"]
|
||||
* 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"]
|
||||
* costs.at["Fischer-Tropsch", "efficiency"],
|
||||
p_nom_extendable=True,
|
||||
@ -2934,8 +2973,13 @@ def add_waste_heat(n):
|
||||
if not urban_central.empty:
|
||||
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?
|
||||
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"] = (
|
||||
urban_central + " urban central heat"
|
||||
)
|
||||
@ -2943,8 +2987,48 @@ def add_waste_heat(n):
|
||||
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
|
||||
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"] = (
|
||||
urban_central + " urban central heat"
|
||||
)
|
||||
@ -2952,7 +3036,7 @@ def add_waste_heat(n):
|
||||
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"] = (
|
||||
urban_central + " urban central heat"
|
||||
)
|
||||
@ -3310,6 +3394,57 @@ def set_temporal_aggregation(n, opts, solver_name):
|
||||
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 "snakemake" not in globals():
|
||||
from _helpers import mock_snakemake
|
||||
@ -3387,6 +3522,15 @@ if __name__ == "__main__":
|
||||
if "nodistrict" in opts:
|
||||
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:
|
||||
add_land_transport(n, costs)
|
||||
|
||||
@ -3476,6 +3620,18 @@ if __name__ == "__main__":
|
||||
if options["electricity_grid_connection"]:
|
||||
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 (
|
||||
snakemake.params.planning_horizons[0] == investment_year
|
||||
)
|
||||
|
||||
@ -36,7 +36,7 @@ import logging
|
||||
import tarfile
|
||||
from pathlib import Path
|
||||
|
||||
from _helpers import configure_logging, progress_retrieve
|
||||
from _helpers import configure_logging, progress_retrieve, validate_checksum
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@ -65,6 +65,8 @@ if __name__ == "__main__":
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
progress_retrieve(url, tarball_fn, disable=disable_progress)
|
||||
|
||||
validate_checksum(tarball_fn, url)
|
||||
|
||||
logger.info("Extracting databundle.")
|
||||
tarfile.open(tarball_fn).extractall(to_fn)
|
||||
|
||||
|
||||
@ -11,7 +11,7 @@ import logging
|
||||
import zipfile
|
||||
from pathlib import Path
|
||||
|
||||
from _helpers import progress_retrieve
|
||||
from _helpers import progress_retrieve, validate_checksum
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@ -35,6 +35,8 @@ if __name__ == "__main__":
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
progress_retrieve(url, zip_fn, disable=disable_progress)
|
||||
|
||||
validate_checksum(zip_fn, url)
|
||||
|
||||
logger.info("Extracting databundle.")
|
||||
zipfile.ZipFile(zip_fn).extractall(to_fn)
|
||||
|
||||
|
||||
@ -13,7 +13,7 @@ logger = logging.getLogger(__name__)
|
||||
import tarfile
|
||||
from pathlib import Path
|
||||
|
||||
from _helpers import configure_logging, progress_retrieve
|
||||
from _helpers import configure_logging, progress_retrieve, validate_checksum
|
||||
|
||||
if __name__ == "__main__":
|
||||
if "snakemake" not in globals():
|
||||
@ -34,6 +34,8 @@ if __name__ == "__main__":
|
||||
disable_progress = snakemake.config["run"].get("disable_progressbar", False)
|
||||
progress_retrieve(url, tarball_fn, disable=disable_progress)
|
||||
|
||||
validate_checksum(tarball_fn, url)
|
||||
|
||||
logger.info("Extracting databundle.")
|
||||
tarfile.open(tarball_fn).extractall(to_fn)
|
||||
|
||||
|
||||
@ -689,6 +689,35 @@ def add_battery_constraints(n):
|
||||
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):
|
||||
electric = (
|
||||
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.
|
||||
"""
|
||||
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(
|
||||
"carrier == 'H2 pipeline retrofitted' and p_nom_extendable"
|
||||
"carrier == 'H2 pipeline retrofitted' and p_nom_extendable and ~reversed"
|
||||
).index
|
||||
|
||||
if h2_retrofitted_i.empty or gas_pipes_i.empty:
|
||||
@ -788,6 +821,7 @@ def extra_functionality(n, snapshots):
|
||||
if "EQ" in o:
|
||||
add_EQ_constraints(n, o)
|
||||
add_battery_constraints(n)
|
||||
add_lossy_bidirectional_link_constraints(n)
|
||||
add_pipe_retrofit_constraint(n)
|
||||
if n._multi_invest:
|
||||
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}'"
|
||||
)
|
||||
if "infeasible" in condition:
|
||||
labels = n.model.compute_infeasibilities()
|
||||
logger.info("Labels:\n" + labels)
|
||||
n.model.print_infeasibilities()
|
||||
raise RuntimeError("Solving status 'infeasible'")
|
||||
|
||||
return n
|
||||
|
||||
Loading…
Reference in New Issue
Block a user