Merge branch 'update-district-heating-cops' into country-specific-dh-forward-temperatures

README.md

@@ -65,10 +65,10 @@ The dataset consists of:
   (alternating current lines at and above 220kV voltage level and all high
   voltage direct current lines) and 3803 substations.
 - The open power plant database
-  [powerplantmatching](https://github.com/FRESNA/powerplantmatching).
+  [powerplantmatching](https://github.com/PyPSA/powerplantmatching).
 - Electrical demand time series from the
   [OPSD project](https://open-power-system-data.org/).
-- Renewable time series based on ERA5 and SARAH, assembled using the [atlite tool](https://github.com/FRESNA/atlite).
+- Renewable time series based on ERA5 and SARAH, assembled using the [atlite tool](https://github.com/PyPSA/atlite).
 - Geographical potentials for wind and solar generators based on land use (CORINE) and excluding nature reserves (Natura2000) are computed with the [atlite library](https://github.com/PyPSA/atlite).
 
 A sector-coupled extension adds demand

config/config.default.yaml

@@ -355,7 +355,6 @@ biomass:
     - Secondary Forestry residues - woodchips
     - Sawdust
     - Residues from landscape care
-    - Municipal waste
     not included:
     - Sugar from sugar beet
     - Rape seed
@@ -369,6 +368,8 @@ biomass:
     biogas:
     - Manure solid, liquid
     - Sludge
+    municipal solid waste:
+    - Municipal waste
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#solar-thermal
 solar_thermal:
@@ -397,6 +398,7 @@ sector:
   biomass: true
   industry: true
   agriculture: true
+  fossil_fuels: true
   district_heating:
     potential: 0.6
     progress:
@@ -426,6 +428,14 @@ sector:
       heat_exchanger_pinch_point_temperature_difference: 5 #K
       isentropic_compressor_efficiency: 0.8
       heat_loss: 0.0
+  heat_pump_sources:
+    urban central:
+    - air
+    urban decentral:
+    - air
+    rural:
+    - air
+    - ground
   cluster_heat_buses: true
   heat_demand_cutout: default
   bev_dsm_restriction_value: 0.75
@@ -614,7 +624,9 @@ sector:
   conventional_generation:
     OCGT: gas
   biomass_to_liquid: false
+  electrobiofuels: false
   biosng: false
+  municipal_solid_waste: false
   limit_max_growth:
     enable: false
     # allowing 30% larger than max historic growth
@@ -636,6 +648,12 @@ sector:
     max_boost: 0.25
     var_cf: true
     sustainability_factor: 0.0025
+  solid_biomass_import:
+    enable: false
+    price: 54 #EUR/MWh
+    max_amount: 1390 # TWh
+    upstream_emissions_factor: .1 #share of solid biomass CO2 emissions at full combustion
+
 
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#industry
 industry:
@@ -1033,6 +1051,8 @@ plotting:
     biogas: '#e3d37d'
     biomass: '#baa741'
     solid biomass: '#baa741'
+    municipal solid waste: '#91ba41'
+    solid biomass import: '#d5ca8d'
     solid biomass transport: '#baa741'
     solid biomass for industry: '#7a6d26'
     solid biomass for industry CC: '#47411c'
@@ -1046,6 +1066,7 @@ plotting:
     services rural biomass boiler: '#c6cf98'
     services urban decentral biomass boiler: '#dde5b5'
     biomass to liquid: '#32CD32'
+    electrobiofuels: 'red'
     BioSNG: '#123456'
     # power transmission
     lines: '#6c9459'
@@ -1072,7 +1093,7 @@ plotting:
     V2G: '#e5ffa8'
     land transport EV: '#baf238'
     land transport demand: '#38baf2'
-    Li ion: '#baf238'
+    EV battery: '#baf238'
     # hot water storage
     water tanks: '#e69487'
     residential rural water tanks: '#f7b7a3'

data/links_p_nom.csv

@@ -23,7 +23,7 @@ Visby-Nas,Sweden - Nas 57°05′58″N 18°14′27″E / 57.09944°N 18.24
 SwePol,Poland - Wierzbięcin 54°30′8″N 16°53′28″E / 54.50222°N 16.89111°E,Sweden - Stärnö 56°9′11″N 14°50′29″E / 56.15306°N 14.84139°E,245(245/0),450,600.0,2000,Thyr,Supplier: ABB,[38],16.891111111111112,54.50222222222222,14.841388888888888,56.153055555555554
 Tjæreborg,Denmark - Tjæreborg/Enge 55°26′52″N 8°35′34″E / 55.44778°N 8.59278°E,Denmark - Tjæreborg/Substation 55°28′07″N 8°33′36″E / 55.46861°N 8.56000°E,4.3(4.3/0),9,7.0,2000,IGBT,Interconnection to wind power generating stations,,8.592777777777778,55.44777777777778,8.56,55.46861111111111
 Italy-Greece,Greece - Arachthos 39°11′00″N 20°57′48″E / 39.18333°N 20.96333°E,Italy - Galatina 40°9′53″N 18°7′49″E / 40.16472°N 18.13028°E,310(200/110),400,500.0,2001,Thyr,,,20.963333333333335,39.18333333333333,18.130277777777778,40.164722222222224
-Moyle,UK - Auchencrosh 55°04′10″N 4°58′50″W / 55.06944°N 4.98056°W,UK - N. Ireland- Ballycronan More 54°50′34″N 5°46′11″W / 54.84278°N 5.76972°W,63.5(63.5/0),250,2501.0,2001,Thyr,"Supplier: Siemens- Nexans",[39],-4.980555555555556,55.06944444444444,-5.769722222222223,54.842777777777776
+Moyle,UK - Auchencrosh 55°04′10″N 4°58′50″W / 55.06944°N 4.98056°W,UK - N. Ireland- Ballycronan More 54°50′34″N 5°46′11″W / 54.84278°N 5.76972°W,63.5(63.5/0),250,500.0,2001,Thyr,"Supplier: Siemens- Nexans",[39],-4.980555555555556,55.06944444444444,-5.769722222222223,54.842777777777776
 HVDC Troll,Norway - Kollsnes 60°33′01″N 4°50′26″E / 60.55028°N 4.84056°E,Norway - Offshore platform Troll A 60°40′00″N 3°40′00″E / 60.66667°N 3.66667°E,70(70/0),60,80.0,2004,IGBT,Power supply for offshore gas compressor Supplier: ABB,[40],4.8405555555555555,60.55027777777778,3.6666666666666665,60.666666666666664
 Estlink,Finland - Espoo 60°12′14″N 24°33′06″E / 60.20389°N 24.55167°E,Estonia - Harku 59°23′5″N 24°33′37″E / 59.38472°N 24.56028°E,105(105/0),150,350.0,2006,IGBT,Supplier: ABB,[40],24.551666666666666,60.20388888888889,24.560277777777777,59.38472222222222
 NorNed,Netherlands - Eemshaven 53°26′4″N 6°51′57″E / 53.43444°N 6.86583°E,Norway - Feda 58°16′58″N 6°51′55″E / 58.28278°N 6.86528°E,580(580/0),450,700.0,2008,Thyr,"Supplier: ABB- Nexans",[40],6.865833333333334,53.434444444444445,6.865277777777778,58.28277777777778

doc/configtables/sector.csv

@@ -4,18 +4,23 @@ heating,--,"{true, false}",Flag to include heating sector.
 biomass,--,"{true, false}",Flag to include biomass sector.
 industry,--,"{true, false}",Flag to include industry sector.
 agriculture,--,"{true, false}",Flag to include agriculture sector.
+fossil_fuels,--,"{true, false}","Flag to include imports of fossil fuels ( [""coal"", ""gas"", ""oil"", ""lignite""])"
 district_heating,--,,`prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/prepare_sector_network.py>`_
-#NAME?,--,float,maximum fraction of urban demand which can be supplied by district heating. Ignored where below current fraction.
+-- potential,--,float,maximum fraction of urban demand which can be supplied by district heating
-#NAME?,--,Dictionary with planning horizons as keys., Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating
+-- progress,--,Dictionary with planning horizons as keys., Increase of today's district heating demand to potential maximum district heating share. Progress = 0 means today's district heating share. Progress = 1 means maximum fraction of urban demand is supplied by district heating
-#NAME?,--,float,Share increase in district heat demand in urban central due to heat losses
+-- district_heating_loss,--,float,Share increase in district heat demand in urban central due to heat losses
-#NAME?,°C,float,Forward temperature in district heating
+-- forward_temperature,°C,float,Forward temperature in district heating
-#NAME?,°C,float,Return temperature in district heating. Must be lower than forward temperature
+-- return_temperature,°C,float,Return temperature in district heating. Must be lower than forward temperature
-#NAME?,K,float,Cooling of heat source for heat pumps
+-- heat_source_cooling,K,float,Cooling of heat source for heat pumps
-#NAME?,,,
+-- heat_pump_cop_approximation,,,
-#NAME?,--,"{ammonia, isobutane}",Heat pump refrigerant assumed for COP approximation
+-- -- refrigerant,--,"{ammonia, isobutane}",Heat pump refrigerant assumed for COP approximation
-#NAME?,K,float,Heat pump pinch point temperature difference in heat exchangers assumed for approximation.
+-- -- heat_exchanger_pinch_point_temperature_difference,K,float,Heat pump pinch point temperature difference in heat exchangers assumed for approximation.
-#NAME?,--,float,Isentropic efficiency of heat pump compressor assumed for approximation. Must be between 0 and 1.
+-- -- isentropic_compressor_efficiency,--,float,Isentropic efficiency of heat pump compressor assumed for approximation. Must be between 0 and 1.
-#NAME?,--,float,Heat pump heat loss assumed for approximation. Must be between 0 and 1.
+-- -- heat_loss,--,float,Heat pump heat loss assumed for approximation. Must be between 0 and 1.
+-- heat_pump_sources,--,,
+-- -- urban central,--,List of heat sources for heat pumps in urban central heating,
+-- -- urban decentral,--,List of heat sources for heat pumps in urban decentral heating,
+-- -- rural,--,List of heat sources for heat pumps in rural heating,
 cluster_heat_buses,--,"{true, false}",Cluster residential and service heat buses in `prepare_sector_network.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/prepare_sector_network.py>`_  to one to save memory.
 ,,,
 bev_dsm_restriction _value,--,float,Adds a lower state of charge (SOC) limit for battery electric vehicles (BEV) to manage its own energy demand (DSM). Located in `build_transport_demand.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_transport_demand.py>`_. Set to 0 for no restriction on BEV DSM
@@ -65,16 +70,16 @@ heat_pump_sink_T,°C,float,The temperature heat sink used in heat pumps based on
 reduce_space_heat _exogenously,--,"{true, false}",Influence on space heating demand by a certain factor (applied before losses in district heating).
 reduce_space_heat _exogenously_factor,--,Dictionary with planning horizons as keys.,"A positive factor can mean renovation or demolition of a building. If the factor is negative, it can mean an increase in floor area, increased thermal comfort, population growth. The default factors are determined by the `Eurocalc Homes and buildings decarbonization scenario <http://tool.european-calculator.eu/app/buildings/building-types-area/?levers=1ddd4444421213bdbbbddd44444ffffff11f411111221111211l212221>`_"
 retrofitting,,,
-#NAME?,--,"{true, false}",Add retrofitting as an endogenous system which co-optimise space heat savings.
+-- retro_endogen,--,"{true, false}",Add retrofitting as an endogenous system which co-optimise space heat savings.
-#NAME?,--,float,Weight costs for building renovation
+-- cost_factor,--,float,Weight costs for building renovation
-#NAME?,--,float,The interest rate for investment in building components
+-- interest_rate,--,float,The interest rate for investment in building components
-#NAME?,--,"{true, false}",Annualise the investment costs of retrofitting
+-- annualise_cost,--,"{true, false}",Annualise the investment costs of retrofitting
-#NAME?,--,"{true, false}",Weight the costs of retrofitting depending on taxes in countries
+-- tax_weighting,--,"{true, false}",Weight the costs of retrofitting depending on taxes in countries
-#NAME?,--,"{true, false}",Weight the costs of retrofitting depending on labour/material costs per country
+-- construction_index,--,"{true, false}",Weight the costs of retrofitting depending on labour/material costs per country
 tes,--,"{true, false}",Add option for storing thermal energy in large water pits associated with district heating systems and individual thermal energy storage (TES)
 tes_tau,,,The time constant used to calculate the decay of thermal energy in thermal energy storage (TES): 1- :math:`e^{-1/24τ}`.
-#NAME?,days,float,The time constant in decentralized thermal energy storage (TES)
+-- decentral,days,float,The time constant in decentralized thermal energy storage (TES)
-#NAME?,days,float,The time constant in centralized thermal energy storage (TES)
+-- central,days,float,The time constant in centralized thermal energy storage (TES)
 boilers,--,"{true, false}",Add option for transforming gas into heat using gas boilers
 resistive_heaters,--,"{true, false}",Add option for transforming electricity into heat using resistive heaters (independently from gas boilers)
 oil_boilers,--,"{true, false}",Add option for transforming oil into heat using boilers
@@ -97,12 +102,12 @@ SMR CC,--,"{true, false}",Add option for transforming natural gas into hydrogen
 regional_methanol_demand,--,"{true, false}",Spatially resolve methanol demand. Set to true if regional CO2 constraints needed.
 regional_oil_demand,--,"{true, false}",Spatially resolve oil demand. Set to true if regional CO2 constraints needed.
 regional_co2 _sequestration_potential,,,
-#NAME?,--,"{true, false}",Add option for regionally-resolved geological carbon dioxide sequestration potentials based on `CO2StoP <https://setis.ec.europa.eu/european-co2-storage-database_en>`_.
+-- enable,--,"{true, false}",Add option for regionally-resolved geological carbon dioxide sequestration potentials based on `CO2StoP <https://setis.ec.europa.eu/european-co2-storage-database_en>`_.
-#NAME?,--,string or list,Name (or list of names) of the attribute(s) for the sequestration potential
+-- attribute,--,string or list,Name (or list of names) of the attribute(s) for the sequestration potential
-#NAME?,--,"{true, false}",Add options for including onshore sequestration potentials
+-- include_onshore,--,"{true, false}",Add options for including onshore sequestration potentials
-#NAME?,Gt ,float,Any sites with lower potential than this value will be excluded
+-- min_size,Gt ,float,Any sites with lower potential than this value will be excluded
-#NAME?,Gt ,float,The maximum sequestration potential for any one site.
+-- max_size,Gt ,float,The maximum sequestration potential for any one site.
-#NAME?,years,float,The years until potential exhausted at optimised annual rate
+-- years_of_storage,years,float,The years until potential exhausted at optimised annual rate
 co2_sequestration_potential,MtCO2/a,float,The potential of sequestering CO2 in Europe per year
 co2_sequestration_cost,currency/tCO2,float,The cost of sequestering a ton of CO2
 co2_sequestration_lifetime,years,int,The lifetime of a CO2 sequestration site
@@ -129,9 +134,9 @@ electricity_distribution _grid_cost_factor,,,Multiplies the investment cost of t
 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.
-#NAME?,p.u.,float,Length-independent transmission efficiency.
+-- -- efficiency_static,p.u.,float,Length-independent transmission efficiency.
-#NAME?,p.u. per 1000 km,float,Length-dependent transmission efficiency ($\eta^{\text{length}}$)
+-- -- efficiency_per_1000km,p.u. per 1000 km,float,Length-dependent transmission efficiency ($\eta^{\text{length}}$)
-#NAME?,p.u. per 1000 km,float,Length-dependent electricity demand for compression ($\eta \cdot \text{length}$) implemented as multi-link to local electricity bus.
+-- -- 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
 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.
@@ -146,18 +151,24 @@ biogas_upgrading_cc,--,"{true, false}",Add option to capture CO2 from biomass up
 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
+municipal_solid_waste,--,"{true, false}",Add option for municipal solid waste
 limit_max_growth,,,
-#NAME?,--,"{true, false}",Add option to limit the maximum growth of a carrier
+-- enable,--,"{true, false}",Add option to limit the maximum growth of a carrier
-#NAME?,p.u.,float,The maximum growth factor of a carrier (e.g. 1.3 allows  30% larger than max historic growth)
+-- factor,p.u.,float,The maximum growth factor of a carrier (e.g. 1.3 allows  30% larger than max historic growth)
-#NAME?,,,
+-- max_growth,,,
 -- -- {carrier},GW,float,The historic maximum growth of a carrier
-#NAME?,,,
+-- max_relative_growth,,,
 -- -- {carrier},p.u.,float,The historic maximum relative growth of a carrier
 ,,,
 enhanced_geothermal,,,
-#NAME?,--,"{true, false}",Add option to include Enhanced Geothermal Systems
+-- enable,--,"{true, false}",Add option to include Enhanced Geothermal Systems
-#NAME?,--,"{true, false}",Add option for flexible operation (see Ricks et al. 2024)
+-- flexible,--,"{true, false}",Add option for flexible operation (see Ricks et al. 2024)
-#NAME?,--,int,The maximum hours the reservoir can be charged under flexible operation
+-- max_hours,--,int,The maximum hours the reservoir can be charged under flexible operation
-#NAME?,--,float,The maximum boost in power output under flexible operation
+-- max_boost,--,float,The maximum boost in power output under flexible operation
-#NAME?,--,"{true, false}",Add option for variable capacity factor (see Ricks et al. 2024)
+-- var_cf,--,"{true, false}",Add option for variable capacity factor (see Ricks et al. 2024)
-#NAME?,--,float,Share of sourced heat that is replenished by the earth's core (see details in `build_egs_potentials.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_egs_potentials.py>`_)
+-- sustainability_factor,--,float,Share of sourced heat that is replenished by the earth's core (see details in `build_egs_potentials.py <https://github.com/PyPSA/pypsa-eur-sec/blob/master/scripts/build_egs_potentials.py>`_)
+solid_biomass_import,,,
+-- enable,--,"{true, false}",Add option to include solid biomass imports
+-- price,currency/MWh,float,Price for importing solid biomass
+-- max_amount,Twh,float,Maximum solid biomass import potential
+-- upstream_emissions_factor,p.u.,float,Upstream emissions of solid biomass imports

doc/foresight.rst

@@ -242,7 +242,7 @@ Rule overview
   file
   <https://pypsa-eur.readthedocs.io/en/latest/preparation/build_powerplants.html?highlight=powerplants>`__
   generated by pypsa-eur which, in turn, is based on the `powerplantmatching
-  <https://github.com/FRESNA/powerplantmatching>`__ database.
+  <https://github.com/PyPSA/powerplantmatching>`__ database.
 
   Existing wind and solar capacities are retrieved from `IRENA annual statistics
   <https://www.irena.org/Statistics/Download-Data>`__ and distributed among the

doc/preparation.rst

@@ -25,7 +25,7 @@ With these and the externally extracted ENTSO-E online map topology
 
 Then the process continues by calculating conventional power plant capacities, potentials, and per-unit availability time series for variable renewable energy carriers and hydro power plants with the following rules:
 
-- :mod:`build_powerplants` for today's thermal power plant capacities using `powerplantmatching <https://github.com/FRESNA/powerplantmatching>`__ allocating these to the closest substation for each powerplant,
+- :mod:`build_powerplants` for today's thermal power plant capacities using `powerplantmatching <https://github.com/PyPSA/powerplantmatching>`__ allocating these to the closest substation for each powerplant,
 - :mod:`build_ship_raster` for building shipping traffic density,
 - :mod:`build_renewable_profiles` for the hourly capacity factors and installation potentials constrained by land-use in each substation's Voronoi cell for PV, onshore and offshore wind, and
 - :mod:`build_hydro_profile` for the hourly per-unit hydro power availability time series.

doc/release_notes.rst

@@ -10,7 +10,17 @@ Release Notes
 Upcoming Release
 ================
 
-* Changed heat pump COP approximation for central heating to be based on Jensen et al. 2018 and a default forward temperature of 90C. This is more realistic for district heating than the previously used approximation method.
+* Changed heat pump COP approximation for central heating to be based on `Jensen et al. (2018) <https://backend.orbit.dtu.dk/ws/portalfiles/portal/151965635/MAIN_Final.pdf>`__ and a default forward temperature of 90C. This is more realistic for district heating than the previously used approximation method.
+
+* split solid biomass potentials into solid biomass and municipal solid waste. Add option to use municipal solid waste. This option is only activated in combination with the flag ``waste_to_energy``
+
+* Add option to import solid biomass
+
+* Add option to produce electrobiofuels (flag ``electrobiofuels``) from solid biomass and hydrogen, as a combination of BtL and Fischer-Tropsch to make more use of the biogenic carbon
+
+* Add flag ``sector: fossil_fuels`` in config to remove the option of importing fossil fuels
+
+* Renamed the carrier of batteries in BEVs from `battery storage` to `EV battery` and the corresponding bus carrier from `Li ion` to `EV battery`. This is to avoid confusion with stationary battery storage.
 
 * Changed default assumptions about waste heat usage from PtX and fuel cells in district heating.
   The default value for the link efficiency scaling factor was changed from 100% to 25%.

rules/build_sector.smk

@@ -215,6 +215,15 @@ rule build_temperature_profiles:
         "../scripts/build_temperature_profiles.py"
 
 
+# def output_cop(wildcards):
+#     return {
+#         f"cop_{source}_{sink}": resources(
+#             "cop_" + source + "_" + sink + "_" + "elec_s{simpl}_{clusters}.nc"
+#         )
+#         for sink, source in config["sector"]["heat_pump_sources"].items()
+#     }
+
+
 rule build_cop_profiles:
     params:
         heat_pump_sink_T_decentral_heating=config_provider(
@@ -232,22 +241,12 @@ rule build_cop_profiles:
         heat_pump_cop_approximation_central_heating=config_provider(
             "sector", "district_heating", "heat_pump_cop_approximation"
         ),
+        heat_pump_sources=config_provider("sector", "heat_pump_sources"),
     input:
         temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
         temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
     output:
-        cop_air_decentral_heating=resources(
+        cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
-            "cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_decentral_heating=resources(
-            "cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_central_heating=resources(
-            "cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_central_heating=resources(
-            "cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
     resources:
         mem_mb=20000,
     log:
@@ -965,6 +964,8 @@ rule prepare_sector_network:
         adjustments=config_provider("adjustments", "sector"),
         emissions_scope=config_provider("energy", "emissions"),
         RDIR=RDIR,
+        heat_pump_sources=config_provider("sector", "heat_pump_sources"),
+        heat_systems=config_provider("sector", "heat_systems"),
     input:
         unpack(input_profile_offwind),
         **rules.cluster_gas_network.output,
@@ -1041,18 +1042,7 @@ rule prepare_sector_network:
         ),
         temp_soil_total=resources("temp_soil_total_elec_s{simpl}_{clusters}.nc"),
         temp_air_total=resources("temp_air_total_elec_s{simpl}_{clusters}.nc"),
-        cop_soil_decentral_heating=resources(
+        cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
-            "cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_decentral_heating=resources(
-            "cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_central_heating=resources(
-            "cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_central_heating=resources(
-            "cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
         solar_thermal_total=lambda w: (
             resources("solar_thermal_total_elec_s{simpl}_{clusters}.nc")
             if config_provider("sector", "solar_thermal")(w)

rules/solve_myopic.smk

@@ -9,6 +9,7 @@ rule add_existing_baseyear:
         sector=config_provider("sector"),
         existing_capacities=config_provider("existing_capacities"),
         costs=config_provider("costs"),
+        heat_pump_sources=config_provider("sector", "heat_pump_sources"),
     input:
         network=RESULTS
         + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
@@ -21,18 +22,7 @@ rule add_existing_baseyear:
                 config_provider("scenario", "planning_horizons", 0)(w)
             )
         ),
-        cop_soil_decentral_heating=resources(
+        cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
-            "cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_decentral_heating=resources(
-            "cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_central_heating=resources(
-            "cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_central_heating=resources(
-            "cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
         existing_heating_distribution=resources(
             "existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
         ),
@@ -79,6 +69,7 @@ rule add_brownfield:
         snapshots=config_provider("snapshots"),
         drop_leap_day=config_provider("enable", "drop_leap_day"),
         carriers=config_provider("electricity", "renewable_carriers"),
+        heat_pump_sources=config_provider("sector", "heat_pump_sources"),
     input:
         unpack(input_profile_tech_brownfield),
         simplify_busmap=resources("busmap_elec_s{simpl}.csv"),
@@ -87,18 +78,7 @@ rule add_brownfield:
         + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
         network_p=solved_previous_horizon,  #solved network at previous time step
         costs=resources("costs_{planning_horizons}.csv"),
-        cop_soil_decentral_heating=resources(
+        cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
-            "cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_decentral_heating=resources(
-            "cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_central_heating=resources(
-            "cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_central_heating=resources(
-            "cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
     output:
         RESULTS
         + "prenetworks-brownfield/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",

rules/solve_perfect.smk

@@ -7,6 +7,7 @@ rule add_existing_baseyear:
         sector=config_provider("sector"),
         existing_capacities=config_provider("existing_capacities"),
         costs=config_provider("costs"),
+        heat_pump_sources=config_provider("sector", "heat_pump_sources"),
     input:
         network=RESULTS
         + "prenetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{planning_horizons}.nc",
@@ -19,18 +20,7 @@ rule add_existing_baseyear:
                 config_provider("scenario", "planning_horizons", 0)(w)
             )
         ),
-        cop_soil_decentral_heating=resources(
+        cop_profiles=resources("cop_profiles_elec_s{simpl}_{clusters}.nc"),
-            "cop_soil_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_decentral_heating=resources(
-            "cop_air_decentral_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_air_central_heating=resources(
-            "cop_air_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
-        cop_soil_central_heating=resources(
-            "cop_soil_central_heating_elec_s{simpl}_{clusters}.nc"
-        ),
         existing_heating_distribution=resources(
             "existing_heating_distribution_elec_s{simpl}_{clusters}_{planning_horizons}.csv"
         ),

scripts/add_brownfield.py

@@ -89,10 +89,6 @@ def add_brownfield(n, n_p, year):
     # deal with gas network
     pipe_carrier = ["gas pipeline"]
     if snakemake.params.H2_retrofit:
-        # drop capacities of previous year to avoid duplicating
-        to_drop = n.links.carrier.isin(pipe_carrier) & (n.links.build_year != year)
-        n.mremove("Link", n.links.loc[to_drop].index)
-
         # subtract the already retrofitted from today's gas grid capacity
         h2_retrofitted_fixed_i = n.links[
             (n.links.carrier == "H2 pipeline retrofitted")
@@ -115,10 +111,6 @@ def add_brownfield(n, n_p, year):
             index=pipe_capacity.index
         ).fillna(0)
         n.links.loc[gas_pipes_i, "p_nom"] = remaining_capacity
-    else:
-        new_pipes = n.links.carrier.isin(pipe_carrier) & (n.links.build_year == year)
-        n.links.loc[new_pipes, "p_nom"] = 0.0
-        n.links.loc[new_pipes, "p_nom_min"] = 0.0
 
 
 def disable_grid_expansion_if_limit_hit(n):

scripts/add_electricity.py

@@ -852,7 +852,7 @@ if __name__ == "__main__":
         fuel_price = pd.read_csv(
             snakemake.input.fuel_price, index_col=0, header=0, parse_dates=True
         )
-        fuel_price = fuel_price.reindex(n.snapshots).fillna(method="ffill")
+        fuel_price = fuel_price.reindex(n.snapshots).ffill()
     else:
         fuel_price = None
 

scripts/add_existing_baseyear.py

@@ -24,6 +24,10 @@ from _helpers import (
 from add_electricity import sanitize_carriers
 from prepare_sector_network import cluster_heat_buses, define_spatial, prepare_costs
 
+from scripts.definitions.heat_sector import HeatSector
+from scripts.definitions.heat_system import HeatSystem
+from scripts.definitions.heat_system_type import HeatSystemType
+
 logger = logging.getLogger(__name__)
 cc = coco.CountryConverter()
 idx = pd.IndexSlice
@@ -416,13 +420,13 @@ def add_power_capacities_installed_before_baseyear(n, grouping_years, costs, bas
 
 
 def add_heating_capacities_installed_before_baseyear(
-    n,
+    n: pypsa.Network,
-    baseyear,
+    baseyear: int,
-    grouping_years,
+    grouping_years: list,
     cop: dict,
     time_dep_hp_cop: bool,
-    costs,
+    costs: pd.DataFrame,
-    default_lifetime,
+    default_lifetime: int,
     existing_heating: pd.DataFrame,
 ):
     """
@@ -435,35 +439,30 @@ def add_heating_capacities_installed_before_baseyear(
         currently assumed heating capacities split between residential and
         services proportional to heating load in both 50% capacities
         in rural buses 50% in urban buses
-    cop: dict
+    cop: xr.DataArray
-        Dictionary with time-dependent coefficients of performance (COPs) for air and ground heat pumps as values and keys "air decentral", "ground decentral", "air central", "ground central"
+        DataArray with time-dependent coefficients of performance (COPs) heat pumps. Coordinates are heat sources (see config), heat system types (see :file:`scripts/enums/HeatSystemType.py`), nodes and snapshots.
     time_dep_hp_cop: bool
         If True, time-dependent (dynamic) COPs are used for heat pumps
     """
     logger.debug(f"Adding heating capacities installed before {baseyear}")
 
-    for name in existing_heating.columns.get_level_values(0).unique():
+    for heat_system in existing_heating.columns.get_level_values(0).unique():
-        name_type = "central" if name == "urban central" else "decentral"
+        heat_system = HeatSystem(heat_system)
 
-        nodes = pd.Index(n.buses.location[n.buses.index.str.contains(f"{name} heat")])
+        nodes = pd.Index(
+            n.buses.location[n.buses.index.str.contains(f"{heat_system} heat")]
+        )
 
-        if (name_type != "central") and options["electricity_distribution_grid"]:
+        if (not heat_system == HeatSystem.URBAN_CENTRAL) and options[
+            "electricity_distribution_grid"
+        ]:
             nodes_elec = nodes + " low voltage"
         else:
             nodes_elec = nodes
 
-        heat_pump_type = "air" if "urban" in name else "ground"
+            too_large_grouping_years = [
-
+                gy for gy in grouping_years if gy >= int(baseyear)
-        # Add heat pumps
+            ]
-        costs_name = f"decentral {heat_pump_type}-sourced heat pump"
-
-        efficiency = (
-            cop[f"{heat_pump_type} {name_type}"][nodes]
-            if time_dep_hp_cop
-            else costs.at[costs_name, "efficiency"]
-        )
-
-        too_large_grouping_years = [gy for gy in grouping_years if gy >= int(baseyear)]
             if too_large_grouping_years:
                 logger.warning(
                     f"Grouping years >= baseyear are ignored. Dropping {too_large_grouping_years}."
@@ -487,18 +486,37 @@ def add_heating_capacities_installed_before_baseyear(
             ratios = _years / _years.sum()
 
         for ratio, grouping_year in zip(ratios, valid_grouping_years):
+            # Add heat pumps
+            for heat_source in snakemake.params.heat_pump_sources[
+                heat_system.system_type.value
+            ]:
+                costs_name = heat_system.heat_pump_costs_name(heat_source)
+
+                efficiency = (
+                    cop.sel(
+                        heat_system=heat_system.system_type.value,
+                        heat_source=heat_source,
+                        name=nodes,
+                    )
+                    .to_pandas()
+                    .reindex(index=n.snapshots)
+                    if time_dep_hp_cop
+                    else costs.at[costs_name, "efficiency"]
+                )
 
                 n.madd(
                     "Link",
                     nodes,
-                suffix=f" {name} {heat_pump_type} heat pump-{grouping_year}",
+                    suffix=f" {heat_system} {heat_source} heat pump-{grouping_year}",
                     bus0=nodes_elec,
-                bus1=nodes + " " + name + " heat",
+                    bus1=nodes + " " + heat_system.value + " heat",
-                carrier=f"{name} {heat_pump_type} heat pump",
+                    carrier=f"{heat_system} {heat_source} heat pump",
                     efficiency=efficiency,
                     capital_cost=costs.at[costs_name, "efficiency"]
                     * costs.at[costs_name, "fixed"],
-                p_nom=existing_heating.loc[nodes, (name, f"{heat_pump_type} heat pump")]
+                    p_nom=existing_heating.loc[
+                        nodes, (heat_system.value, f"{heat_source} heat pump")
+                    ]
                     * ratio
                     / costs.at[costs_name, "efficiency"],
                     build_year=int(grouping_year),
@@ -509,66 +527,70 @@ def add_heating_capacities_installed_before_baseyear(
             n.madd(
                 "Link",
                 nodes,
-                suffix=f" {name} resistive heater-{grouping_year}",
+                suffix=f" {heat_system} resistive heater-{grouping_year}",
                 bus0=nodes_elec,
-                bus1=nodes + " " + name + " heat",
+                bus1=nodes + " " + heat_system.value + " heat",
-                carrier=name + " resistive heater",
+                carrier=heat_system.value + " resistive heater",
-                efficiency=costs.at[f"{name_type} resistive heater", "efficiency"],
+                efficiency=costs.at[
+                    heat_system.resistive_heater_costs_name, "efficiency"
+                ],
                 capital_cost=(
-                    costs.at[f"{name_type} resistive heater", "efficiency"]
+                    costs.at[heat_system.resistive_heater_costs_name, "efficiency"]
-                    * costs.at[f"{name_type} resistive heater", "fixed"]
+                    * costs.at[heat_system.resistive_heater_costs_name, "fixed"]
                 ),
                 p_nom=(
-                    existing_heating.loc[nodes, (name, "resistive heater")]
+                    existing_heating.loc[nodes, (heat_system.value, "resistive heater")]
                     * ratio
-                    / costs.at[f"{name_type} resistive heater", "efficiency"]
+                    / costs.at[heat_system.resistive_heater_costs_name, "efficiency"]
                 ),
                 build_year=int(grouping_year),
-                lifetime=costs.at[f"{name_type} resistive heater", "lifetime"],
+                lifetime=costs.at[heat_system.resistive_heater_costs_name, "lifetime"],
             )
 
             n.madd(
                 "Link",
                 nodes,
-                suffix=f" {name} gas boiler-{grouping_year}",
+                suffix=f"{heat_system} gas boiler-{grouping_year}",
                 bus0="EU gas" if "EU gas" in spatial.gas.nodes else nodes + " gas",
-                bus1=nodes + " " + name + " heat",
+                bus1=nodes + " " + heat_system.value + " heat",
                 bus2="co2 atmosphere",
-                carrier=name + " gas boiler",
+                carrier=heat_system.value + " gas boiler",
-                efficiency=costs.at[f"{name_type} gas boiler", "efficiency"],
+                efficiency=costs.at[heat_system.gas_boiler_costs_name, "efficiency"],
                 efficiency2=costs.at["gas", "CO2 intensity"],
                 capital_cost=(
-                    costs.at[f"{name_type} gas boiler", "efficiency"]
+                    costs.at[heat_system.gas_boiler_costs_name, "efficiency"]
-                    * costs.at[f"{name_type} gas boiler", "fixed"]
+                    * costs.at[heat_system.gas_boiler_costs_name, "fixed"]
                 ),
                 p_nom=(
-                    existing_heating.loc[nodes, (name, "gas boiler")]
+                    existing_heating.loc[nodes, (heat_system.value, "gas boiler")]
                     * ratio
-                    / costs.at[f"{name_type} gas boiler", "efficiency"]
+                    / costs.at[heat_system.gas_boiler_costs_name, "efficiency"]
                 ),
                 build_year=int(grouping_year),
-                lifetime=costs.at[f"{name_type} gas boiler", "lifetime"],
+                lifetime=costs.at[heat_system.gas_boiler_costs_name, "lifetime"],
             )
 
             n.madd(
                 "Link",
                 nodes,
-                suffix=f" {name} oil boiler-{grouping_year}",
+                suffix=f" {heat_system} oil boiler-{grouping_year}",
                 bus0=spatial.oil.nodes,
-                bus1=nodes + " " + name + " heat",
+                bus1=nodes + " " + heat_system.value + " heat",
                 bus2="co2 atmosphere",
-                carrier=name + " oil boiler",
+                carrier=heat_system.value + " oil boiler",
-                efficiency=costs.at["decentral oil boiler", "efficiency"],
+                efficiency=costs.at[heat_system.oil_boiler_costs_name, "efficiency"],
                 efficiency2=costs.at["oil", "CO2 intensity"],
-                capital_cost=costs.at["decentral oil boiler", "efficiency"]
+                capital_cost=costs.at[heat_system.oil_boiler_costs_name, "efficiency"]
-                * costs.at["decentral oil boiler", "fixed"],
+                * costs.at[heat_system.oil_boiler_costs_name, "fixed"],
                 p_nom=(
-                    existing_heating.loc[nodes, (name, "oil boiler")]
+                    existing_heating.loc[nodes, (heat_system.value, "oil boiler")]
                     * ratio
-                    / costs.at["decentral oil boiler", "efficiency"]
+                    / costs.at[heat_system.oil_boiler_costs_name, "efficiency"]
                 ),
                 build_year=int(grouping_year),
-                lifetime=costs.at[f"{name_type} gas boiler", "lifetime"],
+                lifetime=costs.at[
+                    f"{heat_system.central_or_decentral} gas boiler", "lifetime"
+                ],
             )
 
             # delete links with p_nom=nan corresponding to extra nodes in country
@@ -643,28 +665,7 @@ if __name__ == "__main__":
             n=n,
             baseyear=baseyear,
             grouping_years=grouping_years_heat,
-            cop={
+            cop=xr.open_dataarray(snakemake.input.cop_profiles),
-                "air decentral": xr.open_dataarray(
-                    snakemake.input.cop_air_decentral_heating
-                )
-                .to_pandas()
-                .reindex(index=n.snapshots),
-                "ground decentral": xr.open_dataarray(
-                    snakemake.input.cop_soil_decentral_heating
-                )
-                .to_pandas()
-                .reindex(index=n.snapshots),
-                "air central": xr.open_dataarray(
-                    snakemake.input.cop_air_central_heating
-                )
-                .to_pandas()
-                .reindex(index=n.snapshots),
-                "ground central": xr.open_dataarray(
-                    snakemake.input.cop_soil_central_heating
-                )
-                .to_pandas()
-                .reindex(index=n.snapshots),
-            },
             time_dep_hp_cop=options["time_dep_hp_cop"],
             costs=costs,
             default_lifetime=snakemake.params.existing_capacities[

scripts/base_network.py

@@ -808,7 +808,7 @@ def voronoi(points, outline, crs=4326):
         voronoi = gpd.GeoDataFrame(geometry=voronoi)
         joined = gpd.sjoin_nearest(pts, voronoi, how="right")
 
-    return joined.dissolve(by="Bus").squeeze()
+    return joined.dissolve(by="Bus").reindex(points.index).squeeze()
 
 
 def build_bus_shapes(n, country_shapes, offshore_shapes, countries):

scripts/build_cop_profiles/BaseCopApproximator.py

@@ -14,6 +14,24 @@ class BaseCopApproximator(ABC):
     """
     Abstract class for approximating the coefficient of performance (COP) of a
     heat pump.
+
+    Attributes:
+    ----------
+    forward_temperature_celsius : Union[xr.DataArray, np.array]
+        The forward temperature in Celsius.
+    source_inlet_temperature_celsius : Union[xr.DataArray, np.array]
+        The source inlet temperature in Celsius.
+
+    Methods:
+    -------
+    __init__(self, forward_temperature_celsius, source_inlet_temperature_celsius)
+        Initialize CopApproximator.
+    approximate_cop(self)
+        Approximate heat pump coefficient of performance (COP).
+    celsius_to_kelvin(t_celsius)
+        Convert temperature from Celsius to Kelvin.
+    logarithmic_mean(t_hot, t_cold)
+        Calculate the logarithmic mean temperature difference.
     """
 
     def __init__(
@@ -28,8 +46,8 @@ class BaseCopApproximator(ABC):
         ----------
         forward_temperature_celsius : Union[xr.DataArray, np.array]
             The forward temperature in Celsius.
-        return_temperature_celsius : Union[xr.DataArray, np.array]
+        source_inlet_temperature_celsius : Union[xr.DataArray, np.array]
-            The return temperature in Celsius.
+            The source inlet temperature in Celsius.
         """
         pass
 
@@ -45,27 +63,23 @@ class BaseCopApproximator(ABC):
         """
         pass
 
-    def celsius_to_kelvin(
-        t_celsius: Union[float, xr.DataArray, np.array]
-    ) -> Union[float, xr.DataArray, np.array]:
-        if (np.asarray(t_celsius) > 200).any():
-            raise ValueError(
-                "t_celsius > 200. Are you sure you are using the right units?"
-            )
-        return t_celsius + 273.15
-
-    def logarithmic_mean(
-        t_hot: Union[float, xr.DataArray, np.ndarray],
-        t_cold: Union[float, xr.DataArray, np.ndarray],
-    ) -> Union[float, xr.DataArray, np.ndarray]:
-        if (np.asarray(t_hot <= t_cold)).any():
-            raise ValueError("t_hot must be greater than t_cold")
-        return (t_hot - t_cold) / np.log(t_hot / t_cold)
-
     @staticmethod
     def celsius_to_kelvin(
         t_celsius: Union[float, xr.DataArray, np.array]
     ) -> Union[float, xr.DataArray, np.array]:
+        """
+        Convert temperature from Celsius to Kelvin.
+
+        Parameters:
+        ----------
+        t_celsius : Union[float, xr.DataArray, np.array]
+            Temperature in Celsius.
+
+        Returns:
+        -------
+        Union[float, xr.DataArray, np.array]
+            Temperature in Kelvin.
+        """
         if (np.asarray(t_celsius) > 200).any():
             raise ValueError(
                 "t_celsius > 200. Are you sure you are using the right units?"
@@ -77,6 +91,21 @@ class BaseCopApproximator(ABC):
         t_hot: Union[float, xr.DataArray, np.ndarray],
         t_cold: Union[float, xr.DataArray, np.ndarray],
     ) -> Union[float, xr.DataArray, np.ndarray]:
+        """
+        Calculate the logarithmic mean temperature difference.
+
+        Parameters:
+        ----------
+        t_hot : Union[float, xr.DataArray, np.ndarray]
+            Hot temperature.
+        t_cold : Union[float, xr.DataArray, np.ndarray]
+            Cold temperature.
+
+        Returns:
+        -------
+        Union[float, xr.DataArray, np.ndarray]
+            Logarithmic mean temperature difference.
+        """
         if (np.asarray(t_hot <= t_cold)).any():
             raise ValueError("t_hot must be greater than t_cold")
         return (t_hot - t_cold) / np.log(t_hot / t_cold)

scripts/build_cop_profiles/CentralHeatingCopApproximator.py

@@ -20,6 +20,76 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
     default parameters from Pieper et al. (2020). The method is based on
     a thermodynamic heat pump model with some hard-to-know parameters
     being approximated.
+
+    Attributes:
+    ----------
+    forward_temperature_celsius : Union[xr.DataArray, np.array]
+        The forward temperature in Celsius.
+    return_temperature_celsius : Union[xr.DataArray, np.array]
+        The return temperature in Celsius.
+    source_inlet_temperature_celsius : Union[xr.DataArray, np.array]
+        The source inlet temperature in Celsius.
+    source_outlet_temperature_celsius : Union[xr.DataArray, np.array]
+        The source outlet temperature in Celsius.
+    delta_t_pinch_point : float, optional
+        The pinch point temperature difference, by default 5.
+    isentropic_compressor_efficiency : float, optional
+        The isentropic compressor efficiency, by default 0.8.
+    heat_loss : float, optional
+        The heat loss, by default 0.0.
+
+    Methods:
+    -------
+    __init__(
+        forward_temperature_celsius: Union[xr.DataArray, np.array],
+        source_inlet_temperature_celsius: Union[xr.DataArray, np.array],
+        return_temperature_celsius: Union[xr.DataArray, np.array],
+        source_outlet_temperature_celsius: Union[xr.DataArray, np.array],
+        delta_t_pinch_point: float = 5,
+        isentropic_compressor_efficiency: float = 0.8,
+        heat_loss: float = 0.0,
+    ) -> None:
+        Initializes the CentralHeatingCopApproximator object.
+
+    approximate_cop(self) -> Union[xr.DataArray, np.array]:
+        Calculate the coefficient of performance (COP) for the system.
+
+    _approximate_delta_t_refrigerant_source(
+        self, delta_t_source: Union[xr.DataArray, np.array]
+    ) -> Union[xr.DataArray, np.array]:
+        Approximates the temperature difference between the refrigerant and the source.
+
+    _approximate_delta_t_refrigerant_sink(
+        self,
+        refrigerant: str = "ammonia",
+        a: float = {"ammonia": 0.2, "isobutane": -0.0011},
+        b: float = {"ammonia": 0.2, "isobutane": 0.3},
+        c: float = {"ammonia": 0.016, "isobutane": 2.4},
+    ) -> Union[xr.DataArray, np.array]:
+        Approximates the temperature difference between the refrigerant and heat sink.
+
+    _ratio_evaporation_compression_work_approximation(
+        self,
+        refrigerant: str = "ammonia",
+        a: float = {"ammonia": 0.0014, "isobutane": 0.0035},
+    ) -> Union[xr.DataArray, np.array]:
+        Calculate the ratio of evaporation to compression work based on approximation.
+
+    _approximate_delta_t_refrigerant_sink(
+        self,
+        refrigerant: str = "ammonia",
+        a: float = {"ammonia": 0.2, "isobutane": -0.0011},
+        b: float = {"ammonia": 0.2, "isobutane": 0.3},
+        c: float = {"ammonia": 0.016, "isobutane": 2.4},
+    ) -> Union[xr.DataArray, np.array]:
+        Approximates the temperature difference between the refrigerant and heat sink.
+
+    _ratio_evaporation_compression_work_approximation(
+        self,
+        refrigerant: str = "ammonia",
+        a: float = {"ammonia": 0.0014, "isobutane": 0.0035},
+    ) -> Union[xr.DataArray, np.array]:
+        Calculate the ratio of evaporation to compression work based on approximation.
     """
 
     def __init__(
@@ -33,6 +103,7 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
         heat_loss: float = 0.0,
     ) -> None:
         """
+        Initializes the CentralHeatingCopApproximator object.
 
         Parameters:
         ----------
@@ -74,6 +145,7 @@ class CentralHeatingCopApproximator(BaseCopApproximator):
         Calculate the coefficient of performance (COP) for the system.
 
         Returns:
+        --------
             Union[xr.DataArray, np.array]: The calculated COP values.
         """
         return (

scripts/build_cop_profiles/DecentralHeatingCopApproximator.py

@@ -18,6 +18,26 @@ class DecentralHeatingCopApproximator(BaseCopApproximator):
 
     Uses a quadratic regression on the temperature difference between the source and sink based on empirical data proposed by Staffell et al. 2012.
 
+    Attributes
+    ----------
+    forward_temperature_celsius : Union[xr.DataArray, np.array]
+        The forward temperature in Celsius.
+    source_inlet_temperature_celsius : Union[xr.DataArray, np.array]
+        The source inlet temperature in Celsius.
+    source_type : str
+        The source of the heat pump. Must be either 'air' or 'ground'.
+
+    Methods
+    -------
+    __init__(forward_temperature_celsius, source_inlet_temperature_celsius, source_type)
+        Initialize the DecentralHeatingCopApproximator object.
+    approximate_cop()
+        Compute the COP values using quadratic regression for air-/ground-source heat pumps.
+    _approximate_cop_air_source()
+        Evaluate quadratic regression for an air-sourced heat pump.
+    _approximate_cop_ground_source()
+        Evaluate quadratic regression for a ground-sourced heat pump.
+
     References
     ----------
     [1] Staffell et al., Energy & Environmental Science 11 (2012): A review of domestic heat pumps, https://doi.org/10.1039/C2EE22653G.
@@ -30,34 +50,37 @@ class DecentralHeatingCopApproximator(BaseCopApproximator):
         source_type: str,
     ):
         """
-        Initialize the COPProfileBuilder object.
+        Initialize the DecentralHeatingCopApproximator object.
 
-        Parameters:
+        Parameters
         ----------
         forward_temperature_celsius : Union[xr.DataArray, np.array]
             The forward temperature in Celsius.
-        return_temperature_celsius : Union[xr.DataArray, np.array]
+        source_inlet_temperature_celsius : Union[xr.DataArray, np.array]
-            The return temperature in Celsius.
+            The source inlet temperature in Celsius.
-        source: str
+        source_type : str
-            The source of the heat pump. Must be either 'air' or 'soil'
+            The source of the heat pump. Must be either 'air' or 'ground'.
         """
 
         self.delta_t = forward_temperature_celsius - source_inlet_temperature_celsius
-        if source_type not in ["air", "soil"]:
+        if source_type not in ["air", "ground"]:
-            raise ValueError("'source' must be one of ['air', 'soil']")
+            raise ValueError("'source_type' must be one of ['air', 'ground']")
         else:
             self.source_type = source_type
 
     def approximate_cop(self) -> Union[xr.DataArray, np.array]:
         """
-        Compute output of quadratic regression for air-/ground-source heat
+        Compute the COP values using quadratic regression for air-/ground-
-        pumps.
+        source heat pumps.
 
-        Calls the appropriate method depending on `source`.
+        Returns
+        -------
+        Union[xr.DataArray, np.array]
+            The calculated COP values.
         """
         if self.source_type == "air":
             return self._approximate_cop_air_source()
-        elif self.source_type == "soil":
+        elif self.source_type == "ground":
             return self._approximate_cop_ground_source()
 
     def _approximate_cop_air_source(self) -> Union[xr.DataArray, np.array]:

scripts/build_cop_profiles/run.py

@@ -3,22 +3,29 @@
 #
 # SPDX-License-Identifier: MIT
 
+import sys
+
 import numpy as np
+import pandas as pd
 import xarray as xr
 from _helpers import get_country_from_node_name, set_scenario_config
 from CentralHeatingCopApproximator import CentralHeatingCopApproximator
 from DecentralHeatingCopApproximator import DecentralHeatingCopApproximator
 
+from scripts.definitions.heat_system_type import HeatSystemType
+
 
 def map_temperature_dict_to_onshore_regions(
-    temperature_dict: dict, onshore_regions: xr.DataArray, snapshots: xr.DataArray
+    supply_temperature_by_country: dict,
+    onshore_regions: xr.DataArray,
+    snapshots: xr.DataArray,
 ) -> xr.DataArray:
     """
     Map dictionary of temperatures to onshore regions.
 
     Parameters:
     ----------
-    temperature_dict : dictionary
+    supply_temperature_by_country : dictionary
         Dictionary with temperatures as values and country keys as keys. One key must be named "default"
     onshore_regions : xr.DataArray
         Names of onshore regions
@@ -32,9 +39,10 @@ def map_temperature_dict_to_onshore_regions(
         [
             [
                 (
-                    temperature_dict[get_country_from_node_name(node_name)]
+                    supply_temperature_by_country[get_country_from_node_name(node_name)]
-                    if get_country_from_node_name(node_name) in temperature_dict.keys()
+                    if get_country_from_node_name(node_name)
-                    else temperature_dict["default"]
+                    in supply_temperature_by_country.keys()
+                    else supply_temperature_by_country["default"]
                 )
                 for node_name in onshore_regions["name"].values
             ]
@@ -46,6 +54,47 @@ def map_temperature_dict_to_onshore_regions(
     )
 
 
+def get_cop(
+    heat_system_type: str,
+    heat_source: str,
+    source_inlet_temperature_celsius: xr.DataArray,
+    forward_temperature_by_node_and_time: xr.DataArray = None,
+    return_temperature_by_node_and_time: xr.DataArray = None,
+) -> xr.DataArray:
+    """
+    Calculate the coefficient of performance (COP) for a heating system.
+
+    Parameters
+    ----------
+    heat_system_type : str
+        The type of heating system.
+    heat_source : str
+        The heat source used in the heating system.
+    source_inlet_temperature_celsius : xr.DataArray
+        The inlet temperature of the heat source in Celsius.
+
+    Returns
+    -------
+    xr.DataArray
+        The calculated coefficient of performance (COP) for the heating system.
+    """
+    if HeatSystemType(heat_system_type).is_central:
+        return CentralHeatingCopApproximator(
+            forward_temperature_celsius=forward_temperature_by_node_and_time,
+            return_temperature_celsius=return_temperature_by_node_and_time,
+            source_inlet_temperature_celsius=source_inlet_temperature_celsius,
+            source_outlet_temperature_celsius=source_inlet_temperature_celsius
+            - snakemake.params.heat_source_cooling_central_heating,
+        ).approximate_cop()
+
+    else:
+        return DecentralHeatingCopApproximator(
+            forward_temperature_celsius=snakemake.params.heat_pump_sink_T_decentral_heating,
+            source_inlet_temperature_celsius=source_inlet_temperature_celsius,
+            source_type=heat_source,
+        ).approximate_cop()
+
+
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
@@ -58,47 +107,46 @@ if __name__ == "__main__":
 
     set_scenario_config(snakemake)
 
-    for source_type in ["air", "soil"]:
-        # source inlet temperature (air/soil) is based on weather data
-        source_inlet_temperature_celsius: xr.DataArray = xr.open_dataarray(
-            snakemake.input[f"temp_{source_type}_total"]
-        )
-
-        # Approximate COP for decentral (individual) heating
-        cop_individual_heating: xr.DataArray = DecentralHeatingCopApproximator(
-            forward_temperature_celsius=snakemake.params.heat_pump_sink_T_decentral_heating,
-            source_inlet_temperature_celsius=source_inlet_temperature_celsius,
-            source_type=source_type,
-        ).approximate_cop()
-        cop_individual_heating.to_netcdf(
-            snakemake.output[f"cop_{source_type}_decentral_heating"]
-        )
-
     # map forward and return temperatures specified on country-level to onshore regions
     onshore_regions: xr.DataArray = source_inlet_temperature_celsius["name"]
-        forward_temperature_central_heating: xr.DataArray = (
+    forward_temperature_central_heating_by_node_and_time: xr.DataArray = (
         map_temperature_dict_to_onshore_regions(
             temperature_dict=snakemake.params.forward_temperature_central_heating,
             onshore_regions=onshore_regions,
             snapshots=source_inlet_temperature_celsius["time"],
         )
     )
-        return_temperature_central_heating: xr.DataArray = (
+    return_temperature_central_heating_by_node_and_time: xr.DataArray = (
         map_temperature_dict_to_onshore_regions(
             temperature_dict=snakemake.params.return_temperature_central_heating,
             onshore_regions=onshore_regions,
             snapshots=source_inlet_temperature_celsius["time"],
         )
     )
-
+    cop_all_system_types = []
-        # Approximate COP for central (district) heating
+    for heat_system_type, heat_sources in snakemake.params.heat_pump_sources.items():
-        cop_central_heating: xr.DataArray = CentralHeatingCopApproximator(
+        cop_this_system_type = []
-            forward_temperature_celsius=forward_temperature_central_heating,
+        for heat_source in heat_sources:
-            return_temperature_celsius=return_temperature_central_heating,
+            source_inlet_temperature_celsius = xr.open_dataarray(
-            source_inlet_temperature_celsius=source_inlet_temperature_celsius,
+                snakemake.input[f"temp_{heat_source.replace('ground', 'soil')}_total"]
-            source_outlet_temperature_celsius=source_inlet_temperature_celsius
-            - snakemake.params.heat_source_cooling_central_heating,
-        ).approximate_cop()
-        cop_central_heating.to_netcdf(
-            snakemake.output[f"cop_{source_type}_central_heating"]
             )
+            cop_da = get_cop(
+                heat_system_type=heat_system_type,
+                heat_source=heat_source,
+                source_inlet_temperature_celsius=source_inlet_temperature_celsius,
+                forward_temperature_by_node_and_time=forward_temperature_central_heating_by_node_and_time,
+                return_temperature_by_node_and_time=return_temperature_central_heating_by_node_and_time,
+            )
+            cop_this_system_type.append(cop_da)
+        cop_all_system_types.append(
+            xr.concat(
+                cop_this_system_type, dim=pd.Index(heat_sources, name="heat_source")
+            )
+        )
+
+    cop_dataarray = xr.concat(
+        cop_all_system_types,
+        dim=pd.Index(snakemake.params.heat_pump_sources.keys(), name="heat_system"),
+    )
+
+    cop_dataarray.to_netcdf(snakemake.output.cop_profiles)

scripts/build_powerplants.py

@@ -6,7 +6,7 @@
 # coding: utf-8
 """
 Retrieves conventional powerplant capacities and locations from
-`powerplantmatching <https://github.com/FRESNA/powerplantmatching>`_, assigns
+`powerplantmatching <https://github.com/PyPSA/powerplantmatching>`_, assigns
 these to buses and creates a ``.csv`` file. It is possible to amend the
 powerplant database with custom entries provided in
 ``data/custom_powerplants.csv``.
@@ -30,17 +30,17 @@ Inputs
 ------
 
 - ``networks/base.nc``: confer :ref:`base`.
-- ``data/custom_powerplants.csv``: custom powerplants in the same format as `powerplantmatching <https://github.com/FRESNA/powerplantmatching>`_ provides
+- ``data/custom_powerplants.csv``: custom powerplants in the same format as `powerplantmatching <https://github.com/PyPSA/powerplantmatching>`_ provides
 
 Outputs
 -------
 
-- ``resource/powerplants.csv``: A list of conventional power plants (i.e. neither wind nor solar) with fields for name, fuel type, technology, country, capacity in MW, duration, commissioning year, retrofit year, latitude, longitude, and dam information as documented in the `powerplantmatching README <https://github.com/FRESNA/powerplantmatching/blob/master/README.md>`_; additionally it includes information on the closest substation/bus in ``networks/base.nc``.
+- ``resource/powerplants.csv``: A list of conventional power plants (i.e. neither wind nor solar) with fields for name, fuel type, technology, country, capacity in MW, duration, commissioning year, retrofit year, latitude, longitude, and dam information as documented in the `powerplantmatching README <https://github.com/PyPSA/powerplantmatching/blob/master/README.md>`_; additionally it includes information on the closest substation/bus in ``networks/base.nc``.
 
     .. image:: img/powerplantmatching.png
         :scale: 30 %
 
-    **Source:** `powerplantmatching on GitHub <https://github.com/FRESNA/powerplantmatching>`_
+    **Source:** `powerplantmatching on GitHub <https://github.com/PyPSA/powerplantmatching>`_
 
 Description
 -----------

scripts/build_retro_cost.py

@@ -890,7 +890,7 @@ 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.T.groupby(axis=1).sum().T
+    tau = c_m / heat_transfer_perm2.groupby().sum()
     alpha = alpha_H_0 + (tau / tau_H_0)
     # heat balance ratio
     gamma = (1 / Q_ht).mul(Q_gain.sum(axis=1), axis=0)

scripts/cluster_gas_network.py

@@ -58,6 +58,9 @@ def build_clustered_gas_network(df, bus_regions, length_factor=1.25):
     # drop pipes within the same region
     df = df.loc[df.bus1 != df.bus0]
 
+    if df.empty:
+        return df
+
     # recalculate lengths as center to center * length factor
     df["length"] = df.apply(
         lambda p: length_factor

scripts/definitions/heat_sector.py

@@ -0,0 +1,28 @@
+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+
+from enum import Enum
+
+
+class HeatSector(Enum):
+    """
+    Enumeration class representing different heat sectors.
+
+    Attributes:
+        RESIDENTIAL (str): Represents the residential heat sector.
+        SERVICES (str): Represents the services heat sector.
+    """
+
+    RESIDENTIAL = "residential"
+    SERVICES = "services"
+
+    def __str__(self) -> str:
+        """
+        Returns the string representation of the heat sector.
+
+        Returns:
+            str: The string representation of the heat sector.
+        """
+        return self.value

scripts/definitions/heat_system.py

@@ -0,0 +1,267 @@
+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+
+from enum import Enum
+
+from scripts.definitions.heat_sector import HeatSector
+from scripts.definitions.heat_system_type import HeatSystemType
+
+
+class HeatSystem(Enum):
+    """
+    Enumeration representing different heat systems.
+
+    Attributes
+    ----------
+    RESIDENTIAL_RURAL : str
+        Heat system for residential areas in rural locations.
+    SERVICES_RURAL : str
+        Heat system for service areas in rural locations.
+    RESIDENTIAL_URBAN_DECENTRAL : str
+        Heat system for residential areas in urban decentralized locations.
+    SERVICES_URBAN_DECENTRAL : str
+        Heat system for service areas in urban decentralized locations.
+    URBAN_CENTRAL : str
+        Heat system for urban central areas.
+
+    Methods
+    -------
+    __str__()
+        Returns the string representation of the heat system.
+    central_or_decentral()
+        Returns whether the heat system is central or decentralized.
+    system_type()
+        Returns the type of the heat system.
+    sector()
+        Returns the sector of the heat system.
+    rural()
+        Returns whether the heat system is for rural areas.
+    urban_decentral()
+        Returns whether the heat system is for urban decentralized areas.
+    urban()
+        Returns whether the heat system is for urban areas.
+    heat_demand_weighting(urban_fraction=None, dist_fraction=None)
+        Calculates the heat demand weighting based on urban fraction and distribution fraction.
+    heat_pump_costs_name(heat_source)
+        Generates the name for the heat pump costs based on the heat source.
+    """
+
+    RESIDENTIAL_RURAL = "residential rural"
+    SERVICES_RURAL = "services rural"
+    RESIDENTIAL_URBAN_DECENTRAL = "residential urban decentral"
+    SERVICES_URBAN_DECENTRAL = "services urban decentral"
+    URBAN_CENTRAL = "urban central"
+
+    def __init__(self, *args):
+        super().__init__(*args)
+
+    def __str__(self) -> str:
+        """
+        Returns the string representation of the heat system.
+
+        Returns
+        -------
+        str
+            The string representation of the heat system.
+        """
+        return self.value
+
+    @property
+    def central_or_decentral(self) -> str:
+        """
+        Returns whether the heat system is central or decentralized.
+
+        Returns
+        -------
+        str
+            "central" if the heat system is central, "decentral" otherwise.
+        """
+        if self == HeatSystem.URBAN_CENTRAL:
+            return "central"
+        else:
+            return "decentral"
+
+    @property
+    def system_type(self) -> HeatSystemType:
+        """
+        Returns the type of the heat system.
+
+        Returns
+        -------
+        str
+            The type of the heat system.
+
+        Raises
+        ------
+        RuntimeError
+            If the heat system is invalid.
+        """
+        if self == HeatSystem.URBAN_CENTRAL:
+            return HeatSystemType.URBAN_CENTRAL
+        elif (
+            self == HeatSystem.RESIDENTIAL_URBAN_DECENTRAL
+            or self == HeatSystem.SERVICES_URBAN_DECENTRAL
+        ):
+            return HeatSystemType.URBAN_DECENTRAL
+        elif self == HeatSystem.RESIDENTIAL_RURAL or self == HeatSystem.SERVICES_RURAL:
+            return HeatSystemType.RURAL
+        else:
+            raise RuntimeError(f"Invalid heat system: {self}")
+
+    @property
+    def sector(self) -> HeatSector:
+        """
+        Returns the sector of the heat system.
+
+        Returns
+        -------
+        HeatSector
+            The sector of the heat system.
+        """
+        if (
+            self == HeatSystem.RESIDENTIAL_RURAL
+            or self == HeatSystem.RESIDENTIAL_URBAN_DECENTRAL
+        ):
+            return HeatSector.RESIDENTIAL
+        elif (
+            self == HeatSystem.SERVICES_RURAL
+            or self == HeatSystem.SERVICES_URBAN_DECENTRAL
+        ):
+            return HeatSector.SERVICES
+        else:
+            "tot"
+
+    @property
+    def is_rural(self) -> bool:
+        """
+        Returns whether the heat system is for rural areas.
+
+        Returns
+        -------
+        bool
+            True if the heat system is for rural areas, False otherwise.
+        """
+        if self == HeatSystem.RESIDENTIAL_RURAL or self == HeatSystem.SERVICES_RURAL:
+            return True
+        else:
+            return False
+
+    @property
+    def is_urban_decentral(self) -> bool:
+        """
+        Returns whether the heat system is for urban decentralized areas.
+
+        Returns
+        -------
+        bool
+            True if the heat system is for urban decentralized areas, False otherwise.
+        """
+        if (
+            self == HeatSystem.RESIDENTIAL_URBAN_DECENTRAL
+            or self == HeatSystem.SERVICES_URBAN_DECENTRAL
+        ):
+            return True
+        else:
+            return False
+
+    @property
+    def is_urban(self) -> bool:
+        """
+        Returns whether the heat system is for urban areas.
+
+        Returns
+        -------
+        bool True if the heat system is for urban areas, False otherwise.
+        """
+        return not self.is_rural
+
+    def heat_demand_weighting(self, urban_fraction=None, dist_fraction=None) -> float:
+        """
+        Calculates the heat demand weighting based on urban fraction and
+        distribution fraction.
+
+        Parameters
+        ----------
+        urban_fraction : float, optional
+            The fraction of urban heat demand.
+        dist_fraction : float, optional
+            The fraction of distributed heat demand.
+
+        Returns
+        -------
+        float
+            The heat demand weighting.
+
+        Raises
+        ------
+        RuntimeError
+            If the heat system is invalid.
+        """
+        if "rural" in self.value:
+            return 1 - urban_fraction
+        elif "urban central" in self.value:
+            return dist_fraction
+        elif "urban decentral" in self.value:
+            return urban_fraction - dist_fraction
+        else:
+            raise RuntimeError(f"Invalid heat system: {self}")
+
+    def heat_pump_costs_name(self, heat_source: str) -> str:
+        """
+        Generates the name for the heat pump costs based on the heat source and
+        system.
+        Used to retrieve data from `technology-data <https://github.com/PyPSA/technology-data>`.
+
+        Parameters
+        ----------
+        heat_source : str
+            The heat source.
+
+        Returns
+        -------
+        str
+            The name for the heat pump costs.
+        """
+        return f"{self.central_or_decentral} {heat_source}-sourced heat pump"
+
+    @property
+    def resistive_heater_costs_name(self) -> str:
+        """
+        Generates the name for the resistive heater costs based on the heat
+        system.
+        Used to retrieve data from `technology-data <https://github.com/PyPSA/technology-data>`.
+
+        Returns
+        -------
+        str
+            The name for the heater costs.
+        """
+        return f"{self.central_or_decentral} resistive heater"
+
+    @property
+    def gas_boiler_costs_name(self) -> str:
+        """
+        Generates the name for the gas boiler costs based on the heat system.
+        Used to retrieve data from `technology-data <https://github.com/PyPSA/technology-data>`.
+
+        Returns
+        -------
+        str
+            The name for the gas boiler costs.
+        """
+        return f"{self.central_or_decentral} gas boiler"
+
+    @property
+    def oil_boiler_costs_name(self) -> str:
+        """
+        Generates the name for the oil boiler costs based on the heat system.
+        Used to retrieve data from `technology-data <https://github.com/PyPSA/technology-data>`.
+
+        Returns
+        -------
+        str
+            The name for the oil boiler costs.
+        """
+        return "decentral oil boiler"

scripts/definitions/heat_system_type.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+# SPDX-FileCopyrightText: : 2020-2024 The PyPSA-Eur Authors
+#
+# SPDX-License-Identifier: MIT
+
+from enum import Enum
+
+
+class HeatSystemType(Enum):
+    """
+    Enumeration representing different types of heat systems.
+    """
+
+    URBAN_CENTRAL = "urban central"
+    URBAN_DECENTRAL = "urban decentral"
+    RURAL = "rural"
+
+    def __str__(self) -> str:
+        """
+        Returns the string representation of the heat system type.
+
+        Returns:
+            str: The string representation of the heat system type.
+        """
+        return self.value
+
+    @property
+    def is_central(self) -> bool:
+        """
+        Returns whether the heat system type is central.
+
+        Returns:
+            bool: True if the heat system type is central, False otherwise.
+        """
+        return self == HeatSystemType.URBAN_CENTRAL

scripts/make_summary_perfect.py

@@ -631,7 +631,7 @@ def calculate_co2_emissions(n, label, df):
     weightings = n.snapshot_weightings.generators.mul(
         n.investment_period_weightings["years"]
         .reindex(n.snapshots)
-        .fillna(method="bfill")
+        .bfill()
         .fillna(1.0),
         axis=0,
     )

scripts/plot_validation_electricity_production.py

@@ -70,7 +70,7 @@ if __name__ == "__main__":
     optimized = optimized[["Generator", "StorageUnit"]].droplevel(0, axis=1)
     optimized = optimized.rename(columns=n.buses.country, level=0)
     optimized = optimized.rename(columns=carrier_groups, level=1)
-    optimized = optimized.groupby(axis=1, level=[0, 1]).sum()
+    optimized = optimized.T.groupby(level=[0, 1]).sum().T
 
     data = pd.concat([historic, optimized], keys=["Historic", "Optimized"], axis=1)
     data.columns.names = ["Kind", "Country", "Carrier"]

scripts/prepare_network.py

@@ -137,9 +137,7 @@ def add_emission_prices(n, emission_prices={"co2": 0.0}, exclude_co2=False):
 def add_dynamic_emission_prices(n):
     co2_price = pd.read_csv(snakemake.input.co2_price, index_col=0, parse_dates=True)
     co2_price = co2_price[~co2_price.index.duplicated()]
-    co2_price = (
+    co2_price = co2_price.reindex(n.snapshots).ffill().bfill()
-        co2_price.reindex(n.snapshots).fillna(method="ffill").fillna(method="bfill")
-    )
 
     emissions = (
         n.generators.carrier.map(n.carriers.co2_emissions) / n.generators.efficiency

scripts/prepare_perfect_foresight.py

@@ -250,7 +250,7 @@ def adjust_stores(n):
     n.stores.loc[cyclic_i, "e_cyclic_per_period"] = True
     n.stores.loc[cyclic_i, "e_cyclic"] = False
     # non cyclic store assumptions
-    non_cyclic_store = ["co2", "co2 stored", "solid biomass", "biogas", "Li ion"]
+    non_cyclic_store = ["co2", "co2 stored", "solid biomass", "biogas", "EV battery"]
     co2_i = n.stores[n.stores.carrier.isin(non_cyclic_store)].index
     n.stores.loc[co2_i, "e_cyclic_per_period"] = False
     n.stores.loc[co2_i, "e_cyclic"] = False

scripts/prepare_sector_network.py

@@ -37,6 +37,10 @@ from pypsa.geo import haversine_pts
 from pypsa.io import import_components_from_dataframe
 from scipy.stats import beta
 
+from scripts.definitions.heat_sector import HeatSector
+from scripts.definitions.heat_system import HeatSystem
+from scripts.definitions.heat_system_type import HeatSystemType
+
 spatial = SimpleNamespace()
 logger = logging.getLogger(__name__)
 
@@ -56,19 +60,25 @@ def define_spatial(nodes, options):
     # biomass
 
     spatial.biomass = SimpleNamespace()
+    spatial.msw = SimpleNamespace()
 
     if options.get("biomass_spatial", options["biomass_transport"]):
         spatial.biomass.nodes = nodes + " solid biomass"
         spatial.biomass.locations = nodes
         spatial.biomass.industry = nodes + " solid biomass for industry"
         spatial.biomass.industry_cc = nodes + " solid biomass for industry CC"
+        spatial.msw.nodes = nodes + " municipal solid waste"
+        spatial.msw.locations = nodes
     else:
         spatial.biomass.nodes = ["EU solid biomass"]
         spatial.biomass.locations = ["EU"]
         spatial.biomass.industry = ["solid biomass for industry"]
         spatial.biomass.industry_cc = ["solid biomass for industry CC"]
+        spatial.msw.nodes = ["EU municipal solid waste"]
+        spatial.msw.locations = ["EU"]
 
     spatial.biomass.df = pd.DataFrame(vars(spatial.biomass), index=nodes)
+    spatial.msw.df = pd.DataFrame(vars(spatial.msw), index=nodes)
 
     # co2
 
@@ -542,6 +552,9 @@ def add_carrier_buses(n, carrier, nodes=None):
         capital_cost=capital_cost,
     )
 
+    fossils = ["coal", "gas", "oil", "lignite"]
+    if options.get("fossil_fuels", True) and carrier in fossils:
+
         n.madd(
             "Generator",
             nodes,
@@ -1238,12 +1251,14 @@ def add_storage_and_grids(n, costs):
             gas_pipes["p_nom_min"] = 0.0
             # 0.1 EUR/MWkm/a to prefer decommissioning to address degeneracy
             gas_pipes["capital_cost"] = 0.1 * gas_pipes.length
+            gas_pipes["p_nom_extendable"] = True
         else:
             gas_pipes["p_nom_max"] = np.inf
             gas_pipes["p_nom_min"] = gas_pipes.p_nom
             gas_pipes["capital_cost"] = (
                 gas_pipes.length * costs.at["CH4 (g) pipeline", "fixed"]
             )
+            gas_pipes["p_nom_extendable"] = False
 
         n.madd(
             "Link",
@@ -1252,14 +1267,14 @@ def add_storage_and_grids(n, costs):
             bus1=gas_pipes.bus1 + " gas",
             p_min_pu=gas_pipes.p_min_pu,
             p_nom=gas_pipes.p_nom,
-            p_nom_extendable=True,
+            p_nom_extendable=gas_pipes.p_nom_extendable,
             p_nom_max=gas_pipes.p_nom_max,
             p_nom_min=gas_pipes.p_nom_min,
             length=gas_pipes.length,
             capital_cost=gas_pipes.capital_cost,
             tags=gas_pipes.name,
             carrier="gas pipeline",
-            lifetime=costs.at["CH4 (g) pipeline", "lifetime"],
+            lifetime=np.inf,
         )
 
         # remove fossil generators where there is neither
@@ -1541,14 +1556,14 @@ def add_EVs(
     temperature,
 ):
 
-    n.add("Carrier", "Li ion")
+    n.add("Carrier", "EV battery")
 
     n.madd(
         "Bus",
         spatial.nodes,
         suffix=" EV battery",
         location=spatial.nodes,
-        carrier="Li ion",
+        carrier="EV battery",
         unit="MWh_el",
     )
 
@@ -1621,9 +1636,9 @@ def add_EVs(
         n.madd(
             "Store",
             spatial.nodes,
-            suffix=" battery storage",
+            suffix=" EV battery",
             bus=spatial.nodes + " EV battery",
-            carrier="battery storage",
+            carrier="EV battery",
             e_cyclic=True,
             e_nom=e_nom,
             e_max_pu=1,
@@ -1765,7 +1780,7 @@ def build_heat_demand(n):
         .unstack(level=1)
     )
 
-    sectors = ["residential", "services"]
+    sectors = [sector.value for sector in HeatSector]
     uses = ["water", "space"]
 
     heat_demand = {}
@@ -1793,10 +1808,21 @@ def build_heat_demand(n):
     return heat_demand
 
 
-def add_heat(n, costs):
+def add_heat(n: pypsa.Network, costs: pd.DataFrame, cop: xr.DataArray):
+    """
+    Add heat sector to the network.
+
+    Parameters:
+        n (pypsa.Network): The PyPSA network object.
+        costs (pd.DataFrame): DataFrame containing cost information.
+        cop (xr.DataArray): DataArray containing coefficient of performance (COP) values.
+
+    Returns:
+        None
+    """
     logger.info("Add heat sector")
 
-    sectors = ["residential", "services"]
+    sectors = [sector.value for sector in HeatSector]
 
     heat_demand = build_heat_demand(n)
 
@@ -1815,31 +1841,6 @@ def add_heat(n, costs):
         for sector in sectors:
             heat_demand[sector + " space"] = (1 - dE) * heat_demand[sector + " space"]
 
-    heat_systems = [
-        "residential rural",
-        "services rural",
-        "residential urban decentral",
-        "services urban decentral",
-        "urban central",
-    ]
-
-    cop = {
-        "air decentral": xr.open_dataarray(snakemake.input.cop_air_decentral_heating)
-        .to_pandas()
-        .reindex(index=n.snapshots),
-        "ground decentral": xr.open_dataarray(
-            snakemake.input.cop_soil_decentral_heating
-        )
-        .to_pandas()
-        .reindex(index=n.snapshots),
-        "air central": xr.open_dataarray(snakemake.input.cop_air_central_heating)
-        .to_pandas()
-        .reindex(index=n.snapshots),
-        "ground central": xr.open_dataarray(snakemake.input.cop_soil_central_heating)
-        .to_pandas()
-        .reindex(index=n.snapshots),
-    }
-
     if options["solar_thermal"]:
         solar_thermal = (
             xr.open_dataarray(snakemake.input.solar_thermal_total)
@@ -1849,31 +1850,34 @@ def add_heat(n, costs):
         # 1e3 converts from W/m^2 to MW/(1000m^2) = kW/m^2
         solar_thermal = options["solar_cf_correction"] * solar_thermal / 1e3
 
-    for name in heat_systems:
+    for (
-        name_type = "central" if name == "urban central" else "decentral"
+        heat_system
+    ) in (
+        HeatSystem
+    ):  # this loops through all heat systems defined in _entities.HeatSystem
 
-        if name == "urban central":
+        if heat_system == HeatSystem.URBAN_CENTRAL:
             nodes = dist_fraction.index[dist_fraction > 0]
         else:
             nodes = pop_layout.index
 
-        n.add("Carrier", name + " heat")
+        n.add("Carrier", f"{heat_system} heat")
 
         n.madd(
             "Bus",
-            nodes + f" {name} heat",
+            nodes + f" {heat_system.value} heat",
             location=nodes,
-            carrier=name + " heat",
+            carrier=f"{heat_system.value} heat",
             unit="MWh_th",
         )
 
-        if name == "urban central" and options.get("central_heat_vent"):
+        if heat_system == HeatSystem.URBAN_CENTRAL and options.get("central_heat_vent"):
             n.madd(
                 "Generator",
-                nodes + f" {name} heat vent",
+                nodes + f" {heat_system} heat vent",
-                bus=nodes + f" {name} heat",
+                bus=nodes + f" {heat_system} heat",
                 location=nodes,
-                carrier=name + " heat vent",
+                carrier=f"{heat_system} heat vent",
                 p_nom_extendable=True,
                 p_max_pu=0,
                 p_min_pu=-1,
@@ -1881,30 +1885,24 @@ def add_heat(n, costs):
             )
 
         ## Add heat load
-
+        factor = heat_system.heat_demand_weighting(
-        for sector in sectors:
+            urban_fraction=urban_fraction[nodes], dist_fraction=dist_fraction[nodes]
-            # heat demand weighting
-            if "rural" in name:
-                factor = 1 - urban_fraction[nodes]
-            elif "urban central" in name:
-                factor = dist_fraction[nodes]
-            elif "urban decentral" in name:
-                factor = urban_fraction[nodes] - dist_fraction[nodes]
-            else:
-                raise NotImplementedError(
-                    f" {name} not in " f"heat systems: {heat_systems}"
         )
-
+        if not heat_system == HeatSystem.URBAN_CENTRAL:
-            if sector in name:
             heat_load = (
-                    heat_demand[[sector + " water", sector + " space"]]
+                heat_demand[
+                    [
+                        heat_system.sector.value + " water",
+                        heat_system.sector.value + " space",
+                    ]
+                ]
                 .T.groupby(level=1)
                 .sum()
                 .T[nodes]
                 .multiply(factor)
             )
 
-        if name == "urban central":
+        if heat_system == HeatSystem.URBAN_CENTRAL:
             heat_load = (
                 heat_demand.T.groupby(level=1)
                 .sum()
@@ -1917,20 +1915,25 @@ def add_heat(n, costs):
         n.madd(
             "Load",
             nodes,
-            suffix=f" {name} heat",
+            suffix=f" {heat_system} heat",
-            bus=nodes + f" {name} heat",
+            bus=nodes + f" {heat_system} heat",
-            carrier=name + " heat",
+            carrier=f"{heat_system} heat",
             p_set=heat_load,
         )
 
         ## Add heat pumps
-
+        for heat_source in snakemake.params.heat_pump_sources[
-        heat_pump_types = ["air"] if "urban" in name else ["ground", "air"]
+            heat_system.system_type.value
-
+        ]:
-        for heat_pump_type in heat_pump_types:
+            costs_name = heat_system.heat_pump_costs_name(heat_source)
-            costs_name = f"{name_type} {heat_pump_type}-sourced heat pump"
             efficiency = (
-                cop[f"{heat_pump_type} {name_type}"][nodes]
+                cop.sel(
+                    heat_system=heat_system.system_type.value,
+                    heat_source=heat_source,
+                    name=nodes,
+                )
+                .to_pandas()
+                .reindex(index=n.snapshots)
                 if options["time_dep_hp_cop"]
                 else costs.at[costs_name, "efficiency"]
             )
@@ -1938,10 +1941,10 @@ def add_heat(n, costs):
             n.madd(
                 "Link",
                 nodes,
-                suffix=f" {name} {heat_pump_type} heat pump",
+                suffix=f" {heat_system} {heat_source} heat pump",
                 bus0=nodes,
-                bus1=nodes + f" {name} heat",
+                bus1=nodes + f" {heat_system} heat",
-                carrier=f"{name} {heat_pump_type} heat pump",
+                carrier=f"{heat_system} {heat_source} heat pump",
                 efficiency=efficiency,
                 capital_cost=costs.at[costs_name, "efficiency"]
                 * costs.at[costs_name, "fixed"]
@@ -1951,59 +1954,65 @@ def add_heat(n, costs):
             )
 
         if options["tes"]:
-            n.add("Carrier", name + " water tanks")
+            n.add("Carrier", f"{heat_system} water tanks")
 
             n.madd(
                 "Bus",
-                nodes + f" {name} water tanks",
+                nodes + f" {heat_system} water tanks",
                 location=nodes,
-                carrier=name + " water tanks",
+                carrier=f"{heat_system} water tanks",
                 unit="MWh_th",
             )
 
             n.madd(
                 "Link",
-                nodes + f" {name} water tanks charger",
+                nodes + f" {heat_system} water tanks charger",
-                bus0=nodes + f" {name} heat",
+                bus0=nodes + f" {heat_system} heat",
-                bus1=nodes + f" {name} water tanks",
+                bus1=nodes + f" {heat_system} water tanks",
                 efficiency=costs.at["water tank charger", "efficiency"],
-                carrier=name + " water tanks charger",
+                carrier=f"{heat_system} water tanks charger",
                 p_nom_extendable=True,
             )
 
             n.madd(
                 "Link",
-                nodes + f" {name} water tanks discharger",
+                nodes + f" {heat_system} water tanks discharger",
-                bus0=nodes + f" {name} water tanks",
+                bus0=nodes + f" {heat_system} water tanks",
-                bus1=nodes + f" {name} heat",
+                bus1=nodes + f" {heat_system} heat",
-                carrier=name + " water tanks discharger",
+                carrier=f"{heat_system} water tanks discharger",
                 efficiency=costs.at["water tank discharger", "efficiency"],
                 p_nom_extendable=True,
             )
 
-            tes_time_constant_days = options["tes_tau"][name_type]
+            tes_time_constant_days = options["tes_tau"][
+                heat_system.central_or_decentral
+            ]
 
             n.madd(
                 "Store",
-                nodes + f" {name} water tanks",
+                nodes + f" {heat_system} water tanks",
-                bus=nodes + f" {name} water tanks",
+                bus=nodes + f" {heat_system} water tanks",
                 e_cyclic=True,
                 e_nom_extendable=True,
-                carrier=name + " water tanks",
+                carrier=f"{heat_system} water tanks",
                 standing_loss=1 - np.exp(-1 / 24 / tes_time_constant_days),
-                capital_cost=costs.at[name_type + " water tank storage", "fixed"],
+                capital_cost=costs.at[
-                lifetime=costs.at[name_type + " water tank storage", "lifetime"],
+                    heat_system.central_or_decentral + " water tank storage", "fixed"
+                ],
+                lifetime=costs.at[
+                    heat_system.central_or_decentral + " water tank storage", "lifetime"
+                ],
             )
 
         if options["resistive_heaters"]:
-            key = f"{name_type} resistive heater"
+            key = f"{heat_system.central_or_decentral} resistive heater"
 
             n.madd(
                 "Link",
-                nodes + f" {name} resistive heater",
+                nodes + f" {heat_system} resistive heater",
                 bus0=nodes,
-                bus1=nodes + f" {name} heat",
+                bus1=nodes + f" {heat_system} heat",
-                carrier=name + " resistive heater",
+                carrier=f"{heat_system} resistive heater",
                 efficiency=costs.at[key, "efficiency"],
                 capital_cost=costs.at[key, "efficiency"]
                 * costs.at[key, "fixed"]
@@ -2013,16 +2022,16 @@ def add_heat(n, costs):
             )
 
         if options["boilers"]:
-            key = f"{name_type} gas boiler"
+            key = f"{heat_system.central_or_decentral} gas boiler"
 
             n.madd(
                 "Link",
-                nodes + f" {name} gas boiler",
+                nodes + f" {heat_system} gas boiler",
                 p_nom_extendable=True,
                 bus0=spatial.gas.df.loc[nodes, "nodes"].values,
-                bus1=nodes + f" {name} heat",
+                bus1=nodes + f" {heat_system} heat",
                 bus2="co2 atmosphere",
-                carrier=name + " gas boiler",
+                carrier=f"{heat_system} gas boiler",
                 efficiency=costs.at[key, "efficiency"],
                 efficiency2=costs.at["gas", "CO2 intensity"],
                 capital_cost=costs.at[key, "efficiency"]
@@ -2032,22 +2041,26 @@ def add_heat(n, costs):
             )
 
         if options["solar_thermal"]:
-            n.add("Carrier", name + " solar thermal")
+            n.add("Carrier", f"{heat_system} solar thermal")
 
             n.madd(
                 "Generator",
                 nodes,
-                suffix=f" {name} solar thermal collector",
+                suffix=f" {heat_system} solar thermal collector",
-                bus=nodes + f" {name} heat",
+                bus=nodes + f" {heat_system} heat",
-                carrier=name + " solar thermal",
+                carrier=f"{heat_system} solar thermal",
                 p_nom_extendable=True,
-                capital_cost=costs.at[name_type + " solar thermal", "fixed"]
+                capital_cost=costs.at[
+                    heat_system.central_or_decentral + " solar thermal", "fixed"
+                ]
                 * overdim_factor,
                 p_max_pu=solar_thermal[nodes],
-                lifetime=costs.at[name_type + " solar thermal", "lifetime"],
+                lifetime=costs.at[
+                    heat_system.central_or_decentral + " solar thermal", "lifetime"
+                ],
             )
 
-        if options["chp"] and name == "urban central":
+        if options["chp"] and heat_system == HeatSystem.URBAN_CENTRAL:
             # add gas CHP; biomass CHP is added in biomass section
             n.madd(
                 "Link",
@@ -2104,16 +2117,20 @@ def add_heat(n, costs):
                 lifetime=costs.at["central gas CHP", "lifetime"],
             )
 
-        if options["chp"] and options["micro_chp"] and name != "urban central":
+        if (
+            options["chp"]
+            and options["micro_chp"]
+            and heat_system.value != "urban central"
+        ):
             n.madd(
                 "Link",
-                nodes + f" {name} micro gas CHP",
+                nodes + f" {heat_system} micro gas CHP",
                 p_nom_extendable=True,
                 bus0=spatial.gas.df.loc[nodes, "nodes"].values,
                 bus1=nodes,
-                bus2=nodes + f" {name} heat",
+                bus2=nodes + f" {heat_system} heat",
                 bus3="co2 atmosphere",
-                carrier=name + " micro gas CHP",
+                carrier=heat_system.value + " micro gas CHP",
                 efficiency=costs.at["micro CHP", "efficiency"],
                 efficiency2=costs.at["micro CHP", "efficiency-heat"],
                 efficiency3=costs.at["gas", "CO2 intensity"],
@@ -2149,7 +2166,7 @@ def add_heat(n, costs):
         ) / heat_demand.T.groupby(level=[1]).sum().T
 
         for name in n.loads[
-            n.loads.carrier.isin([x + " heat" for x in heat_systems])
+            n.loads.carrier.isin([x + " heat" for x in HeatSystem])
         ].index:
             node = n.buses.loc[name, "location"]
             ct = pop_layout.loc[node, "ct"]
@@ -2252,12 +2269,54 @@ def add_biomass(n, costs):
         solid_biomass_potentials_spatial = biomass_potentials["solid biomass"].rename(
             index=lambda x: x + " solid biomass"
         )
+        msw_biomass_potentials_spatial = biomass_potentials[
+            "municipal solid waste"
+        ].rename(index=lambda x: x + " municipal solid waste")
     else:
         solid_biomass_potentials_spatial = biomass_potentials["solid biomass"].sum()
+        msw_biomass_potentials_spatial = biomass_potentials[
+            "municipal solid waste"
+        ].sum()
 
     n.add("Carrier", "biogas")
     n.add("Carrier", "solid biomass")
 
+    if (
+        options["municipal_solid_waste"]
+        and not options["industry"]
+        and cf_industry["waste_to_energy"]
+        or cf_industry["waste_to_energy_cc"]
+    ):
+        logger.warning(
+            "Flag municipal_solid_waste can be only used with industry "
+            "sector waste to energy."
+            "Setting municipal_solid_waste=False."
+        )
+        options["municipal_solid_waste"] = False
+
+    if options["municipal_solid_waste"]:
+
+        n.add("Carrier", "municipal solid waste")
+
+        n.madd(
+            "Bus",
+            spatial.msw.nodes,
+            location=spatial.msw.locations,
+            carrier="municipal solid waste",
+        )
+
+        e_max_pu = pd.Series([1] * (len(n.snapshots) - 1) + [0], index=n.snapshots)
+        n.madd(
+            "Store",
+            spatial.msw.nodes,
+            bus=spatial.msw.nodes,
+            carrier="municipal solid waste",
+            e_nom=msw_biomass_potentials_spatial,
+            marginal_cost=0,  # costs.at["municipal solid waste", "fuel"],
+            e_max_pu=e_max_pu,
+            e_initial=msw_biomass_potentials_spatial,
+        )
+
     n.madd(
         "Bus",
         spatial.gas.biogas,
@@ -2294,6 +2353,54 @@ def add_biomass(n, costs):
         e_initial=solid_biomass_potentials_spatial,
     )
 
+    if options["solid_biomass_import"].get("enable", False):
+        biomass_import_price = options["solid_biomass_import"]["price"]
+        # convert TWh in MWh
+        biomass_import_max_amount = options["solid_biomass_import"]["max_amount"] * 1e6
+        biomass_import_upstream_emissions = options["solid_biomass_import"][
+            "upstream_emissions_factor"
+        ]
+
+        logger.info(
+            "Adding biomass import with cost %.2f EUR/MWh, a limit of %.2f TWh, and embedded emissions of %.2f%%",
+            biomass_import_price,
+            options["solid_biomass_import"]["max_amount"],
+            biomass_import_upstream_emissions * 100,
+        )
+
+        n.add("Carrier", "solid biomass import")
+
+        n.madd(
+            "Bus",
+            ["EU solid biomass import"],
+            location="EU",
+            carrier="solid biomass import",
+        )
+
+        n.madd(
+            "Store",
+            ["solid biomass import"],
+            bus=["EU solid biomass import"],
+            carrier="solid biomass import",
+            e_nom=biomass_import_max_amount,
+            marginal_cost=biomass_import_price,
+            e_initial=biomass_import_max_amount,
+        )
+
+        n.madd(
+            "Link",
+            spatial.biomass.nodes,
+            suffix=" solid biomass import",
+            bus0=["EU solid biomass import"],
+            bus1=spatial.biomass.nodes,
+            bus2="co2 atmosphere",
+            carrier="solid biomass import",
+            efficiency=1.0,
+            efficiency2=biomass_import_upstream_emissions
+            * costs.at["solid biomass", "CO2 intensity"],
+            p_nom_extendable=True,
+        )
+
     n.madd(
         "Link",
         spatial.gas.biogas_to_gas,
@@ -2365,6 +2472,19 @@ def add_biomass(n, costs):
             carrier="solid biomass transport",
         )
 
+        if options["municipal_solid_waste"]:
+            n.madd(
+                "Link",
+                biomass_transport.index,
+                bus0=biomass_transport.bus0 + " municipal solid waste",
+                bus1=biomass_transport.bus1 + " municipal solid waste",
+                p_nom_extendable=False,
+                p_nom=5e4,
+                length=biomass_transport.length.values,
+                marginal_cost=biomass_transport.costs * biomass_transport.length.values,
+                carrier="municipal solid waste transport",
+            )
+
     elif options["biomass_spatial"]:
         # add artificial biomass generators at nodes which include transport costs
         transport_costs = pd.read_csv(
@@ -2394,6 +2514,26 @@ def add_biomass(n, costs):
             type="operational_limit",
         )
 
+        if options["municipal_solid_waste"]:
+            # Add municipal solid waste
+            n.madd(
+                "Generator",
+                spatial.msw.nodes,
+                bus=spatial.msw.nodes,
+                carrier="municipal solid waste",
+                p_nom=10000,
+                marginal_cost=0  # costs.at["municipal solid waste", "fuel"]
+                + bus_transport_costs * average_distance,
+            )
+            n.add(
+                "GlobalConstraint",
+                "msw limit",
+                carrier_attribute="municipal solid waste",
+                sense="<=",
+                constant=biomass_potentials["municipal solid waste"].sum(),
+                type="operational_limit",
+            )
+
     # AC buses with district heating
     urban_central = n.buses.index[n.buses.carrier == "urban central heat"]
     if not urban_central.empty and options["chp"]:
@@ -2426,28 +2566,23 @@ def add_biomass(n, costs):
             bus4=spatial.co2.df.loc[urban_central, "nodes"].values,
             carrier="urban central solid biomass CHP CC",
             p_nom_extendable=True,
-            capital_cost=costs.at[key, "fixed"] * costs.at[key, "efficiency"]
+            capital_cost=costs.at[key + " CC", "fixed"]
+            * costs.at[key + " CC", "efficiency"]
             + costs.at["biomass CHP capture", "fixed"]
             * costs.at["solid biomass", "CO2 intensity"],
-            marginal_cost=costs.at[key, "VOM"],
+            marginal_cost=costs.at[key + " CC", "VOM"],
-            efficiency=costs.at[key, "efficiency"]
+            efficiency=costs.at[key + " CC", "efficiency"]
             - costs.at["solid biomass", "CO2 intensity"]
             * (
                 costs.at["biomass CHP capture", "electricity-input"]
                 + costs.at["biomass CHP capture", "compression-electricity-input"]
             ),
-            efficiency2=costs.at[key, "efficiency-heat"]
+            efficiency2=costs.at[key + " CC", "efficiency-heat"],
-            + costs.at["solid biomass", "CO2 intensity"]
-            * (
-                costs.at["biomass CHP capture", "heat-output"]
-                + costs.at["biomass CHP capture", "compression-heat-output"]
-                - costs.at["biomass CHP capture", "heat-input"]
-            ),
             efficiency3=-costs.at["solid biomass", "CO2 intensity"]
             * costs.at["biomass CHP capture", "capture_rate"],
             efficiency4=costs.at["solid biomass", "CO2 intensity"]
             * costs.at["biomass CHP capture", "capture_rate"],
-            lifetime=costs.at[key, "lifetime"],
+            lifetime=costs.at[key + " CC", "lifetime"],
         )
 
     if options["biomass_boiler"]:
@@ -2489,11 +2624,12 @@ def add_biomass(n, costs):
             efficiency2=-costs.at["solid biomass", "CO2 intensity"]
             + costs.at["BtL", "CO2 stored"],
             p_nom_extendable=True,
-            capital_cost=costs.at["BtL", "fixed"],
+            capital_cost=costs.at["BtL", "fixed"] * costs.at["BtL", "efficiency"],
-            marginal_cost=costs.at["BtL", "efficiency"] * costs.at["BtL", "VOM"],
+            marginal_cost=costs.at["BtL", "VOM"] * costs.at["BtL", "efficiency"],
         )
 
-        # TODO: Update with energy penalty
+        # Assuming that acid gas removal (incl. CO2) from syngas i performed with Rectisol
+        # process (Methanol) and that electricity demand for this is included in the base process
         n.madd(
             "Link",
             spatial.biomass.nodes,
@@ -2509,9 +2645,46 @@ def add_biomass(n, costs):
             + costs.at["BtL", "CO2 stored"] * (1 - costs.at["BtL", "capture rate"]),
             efficiency3=costs.at["BtL", "CO2 stored"] * costs.at["BtL", "capture rate"],
             p_nom_extendable=True,
-            capital_cost=costs.at["BtL", "fixed"]
+            capital_cost=costs.at["BtL", "fixed"] * costs.at["BtL", "efficiency"]
             + costs.at["biomass CHP capture", "fixed"] * costs.at["BtL", "CO2 stored"],
-            marginal_cost=costs.at["BtL", "efficiency"] * costs.at["BtL", "VOM"],
+            marginal_cost=costs.at["BtL", "VOM"] * costs.at["BtL", "efficiency"],
+        )
+
+    # Electrobiofuels (BtL with hydrogen addition to make more use of biogenic carbon).
+    # Combination of efuels and biomass to liquid, both based on Fischer-Tropsch.
+    # Experimental version - use with caution
+    if options["electrobiofuels"]:
+
+        efuel_scale_factor = costs.at["BtL", "C stored"]
+        name = (
+            pd.Index(spatial.biomass.nodes)
+            + " "
+            + pd.Index(spatial.h2.nodes.str.replace(" H2", ""))
+        )
+        n.madd(
+            "Link",
+            name,
+            suffix=" electrobiofuels",
+            bus0=spatial.biomass.nodes,
+            bus1=spatial.oil.nodes,
+            bus2=spatial.h2.nodes,
+            bus3="co2 atmosphere",
+            carrier="electrobiofuels",
+            lifetime=costs.at["electrobiofuels", "lifetime"],
+            efficiency=costs.at["electrobiofuels", "efficiency-biomass"],
+            efficiency2=-costs.at["electrobiofuels", "efficiency-hydrogen"],
+            efficiency3=-costs.at["solid biomass", "CO2 intensity"]
+            + costs.at["BtL", "CO2 stored"]
+            * (1 - costs.at["Fischer-Tropsch", "capture rate"]),
+            p_nom_extendable=True,
+            capital_cost=costs.at["BtL", "fixed"] * costs.at["BtL", "efficiency"]
+            + efuel_scale_factor
+            * costs.at["Fischer-Tropsch", "fixed"]
+            * costs.at["Fischer-Tropsch", "efficiency"],
+            marginal_cost=costs.at["BtL", "VOM"] * costs.at["BtL", "efficiency"]
+            + efuel_scale_factor
+            * costs.at["Fischer-Tropsch", "VOM"]
+            * costs.at["Fischer-Tropsch", "efficiency"],
         )
 
     # BioSNG from solid biomass
@@ -2529,11 +2702,12 @@ def add_biomass(n, costs):
             efficiency3=-costs.at["solid biomass", "CO2 intensity"]
             + costs.at["BioSNG", "CO2 stored"],
             p_nom_extendable=True,
-            capital_cost=costs.at["BioSNG", "fixed"],
+            capital_cost=costs.at["BioSNG", "fixed"] * costs.at["BioSNG", "efficiency"],
-            marginal_cost=costs.at["BioSNG", "efficiency"] * costs.at["BioSNG", "VOM"],
+            marginal_cost=costs.at["BioSNG", "VOM"] * costs.at["BioSNG", "efficiency"],
         )
 
-        # TODO: Update with energy penalty for CC
+        # Assuming that acid gas removal (incl. CO2) from syngas i performed with Rectisol
+        # process (Methanol) and that electricity demand for this is included in the base process
         n.madd(
             "Link",
             spatial.biomass.nodes,
@@ -2551,10 +2725,10 @@ def add_biomass(n, costs):
             + costs.at["BioSNG", "CO2 stored"]
             * (1 - costs.at["BioSNG", "capture rate"]),
             p_nom_extendable=True,
-            capital_cost=costs.at["BioSNG", "fixed"]
+            capital_cost=costs.at["BioSNG", "fixed"] * costs.at["BioSNG", "efficiency"]
             + costs.at["biomass CHP capture", "fixed"]
             * costs.at["BioSNG", "CO2 stored"],
-            marginal_cost=costs.at["BioSNG", "efficiency"] * costs.at["BioSNG", "VOM"],
+            marginal_cost=costs.at["BioSNG", "VOM"] * costs.at["BioSNG", "efficiency"],
         )
 
 
@@ -2781,10 +2955,11 @@ def add_industry(n, costs):
         )
 
     domestic_navigation = pop_weighted_energy_totals.loc[
-        nodes, "total domestic navigation"
+        nodes, ["total domestic navigation"]
     ].squeeze()
     international_navigation = (
-        pd.read_csv(snakemake.input.shipping_demand, index_col=0).squeeze() * nyears
+        pd.read_csv(snakemake.input.shipping_demand, index_col=0).squeeze(axis=1)
+        * nyears
     )
     all_navigation = domestic_navigation + international_navigation
     p_set = all_navigation * 1e6 / nhours
@@ -2903,7 +3078,7 @@ def add_industry(n, costs):
             carrier="oil",
         )
 
-    if "oil" not in n.generators.carrier.unique():
+    if options.get("fossil_fuels", True) and "oil" not in n.generators.carrier.unique():
         n.madd(
             "Generator",
             spatial.oil.nodes,
@@ -2949,20 +3124,16 @@ def add_industry(n, costs):
     if options["oil_boilers"]:
         nodes = pop_layout.index
 
-        for name in [
+        for heat_system in HeatSystem:
-            "residential rural",
+            if not heat_system == HeatSystem.URBAN_CENTRAL:
-            "services rural",
-            "residential urban decentral",
-            "services urban decentral",
-        ]:
                 n.madd(
                     "Link",
-                nodes + f" {name} oil boiler",
+                    nodes + f" {heat_system} oil boiler",
                     p_nom_extendable=True,
                     bus0=spatial.oil.nodes,
-                bus1=nodes + f" {name} heat",
+                    bus1=nodes + f" {heat_system} heat",
                     bus2="co2 atmosphere",
-                carrier=f"{name} oil boiler",
+                    carrier=f"{heat_system} oil boiler",
                     efficiency=costs.at["decentral oil boiler", "efficiency"],
                     efficiency2=costs.at["oil", "CO2 intensity"],
                     capital_cost=costs.at["decentral oil boiler", "efficiency"]
@@ -3064,6 +3235,17 @@ def add_industry(n, costs):
             efficiency3=process_co2_per_naphtha,
         )
 
+        if options.get("biomass", True) and options["municipal_solid_waste"]:
+            n.madd(
+                "Link",
+                spatial.msw.locations,
+                bus0=spatial.msw.nodes,
+                bus1=non_sequestered_hvc_locations,
+                carrier="municipal solid waste",
+                p_nom_extendable=True,
+                efficiency=1.0,
+            )
+
         n.madd(
             "Link",
             spatial.oil.demand_locations,
@@ -3113,7 +3295,9 @@ def add_industry(n, costs):
                 carrier="waste CHP CC",
                 p_nom_extendable=True,
                 capital_cost=costs.at["waste CHP CC", "fixed"]
-                * costs.at["waste CHP CC", "efficiency"],
+                * costs.at["waste CHP CC", "efficiency"]
+                + costs.at["biomass CHP capture", "fixed"]
+                * costs.at["oil", "CO2 intensity"],
                 marginal_cost=costs.at["waste CHP CC", "VOM"],
                 efficiency=costs.at["waste CHP CC", "efficiency"],
                 efficiency2=costs.at["waste CHP CC", "efficiency-heat"],
@@ -3952,12 +4136,11 @@ if __name__ == "__main__":
 
         snakemake = mock_snakemake(
             "prepare_sector_network",
-            # configfiles="test/config.overnight.yaml",
             simpl="",
             opts="",
             clusters="37",
-            ll="v1.0",
+            ll="vopt",
-            sector_opts="730H-T-H-B-I-A-dist1",
+            sector_opts="",
             planning_horizons="2050",
         )
 
@@ -4013,7 +4196,7 @@ if __name__ == "__main__":
         add_land_transport(n, costs)
 
     if options["heating"]:
-        add_heat(n, costs)
+        add_heat(n=n, costs=costs, cop=xr.open_dataarray(snakemake.input.cop_profiles))
 
     if options["biomass"]:
         add_biomass(n, costs)