diff --git a/Snakefile b/Snakefile index de34f386..d747b8fe 100644 --- a/Snakefile +++ b/Snakefile @@ -1,4 +1,7 @@ +from snakemake.remote.HTTP import RemoteProvider as HTTPRemoteProvider +HTTP = HTTPRemoteProvider() + configfile: "config.yaml" @@ -180,6 +183,21 @@ rule build_biomass_potentials: script: 'scripts/build_biomass_potentials.py' +if config["sector"]["biomass_transport"]: + rule build_biomass_transport_costs: + input: + transport_cost_data=HTTP.remote("publications.jrc.ec.europa.eu/repository/bitstream/JRC98626/biomass potentials in europe_web rev.pdf", keep_local=True) + output: + biomass_transport_costs="resources/biomass_transport_costs.csv", + threads: 1 + resources: mem_mb=1000 + benchmark: "benchmarks/build_biomass_transport_costs" + script: 'scripts/build_biomass_transport_costs.py' + build_biomass_transport_costs_output = rules.build_biomass_transport_costs.output +else: + build_biomass_transport_costs_output = {} + + rule build_ammonia_production: input: usgs="data/myb1-2017-nitro.xls" @@ -321,8 +339,8 @@ rule prepare_sector_network: energy_totals_name='resources/energy_totals.csv', co2_totals_name='resources/co2_totals.csv', transport_name='resources/transport_data.csv', - traffic_data_KFZ = "data/emobility/KFZ__count", - traffic_data_Pkw = "data/emobility/Pkw__count", + traffic_data_KFZ="data/emobility/KFZ__count", + traffic_data_Pkw="data/emobility/Pkw__count", biomass_potentials='resources/biomass_potentials.csv', heat_profile="data/heat_load_profile_BDEW.csv", costs=CDIR + "costs_{planning_horizons}.csv", @@ -352,7 +370,8 @@ rule prepare_sector_network: solar_thermal_total="resources/solar_thermal_total_elec_s{simpl}_{clusters}.nc", solar_thermal_urban="resources/solar_thermal_urban_elec_s{simpl}_{clusters}.nc", solar_thermal_rural="resources/solar_thermal_rural_elec_s{simpl}_{clusters}.nc", - **build_retro_cost_output + **build_retro_cost_output, + **build_biomass_transport_costs_output output: RDIR + '/prenetworks/elec_s{simpl}_{clusters}_lv{lv}_{opts}_{sector_opts}_{planning_horizons}.nc' threads: 1 resources: mem_mb=2000 diff --git a/config.default.yaml b/config.default.yaml index 747e8023..5734e52a 100644 --- a/config.default.yaml +++ b/config.default.yaml @@ -234,6 +234,7 @@ sector: electricity_grid_connection: true # only applies to onshore wind and utility PV gas_distribution_grid: true gas_distribution_grid_cost_factor: 1.0 #multiplies cost in data/costs.csv + biomass_transport: false # biomass transport between nodes conventional_generation: # generator : carrier OCGT: gas @@ -275,7 +276,6 @@ industry: hotmaps_locate_missing: false reference_year: 2015 - costs: lifetime: 25 #default lifetime # From a Lion Hirth paper, also reflects average of Noothout et al 2016 @@ -509,5 +509,6 @@ plotting: shipping oil: "#6495ED" shipping oil emissions: "#6495ED" electricity distribution grid: '#333333' + solid biomass transport: green H2 for industry: "#222222" H2 for shipping: "#6495ED" diff --git a/doc/release_notes.rst b/doc/release_notes.rst index f838544c..6361563b 100644 --- a/doc/release_notes.rst +++ b/doc/release_notes.rst @@ -76,6 +76,12 @@ Future release * The share of shipping transformed into hydrogen fuel cell can be now defined for different years in the ``config.yaml`` file. The carbon emission from the remaining share is treated as a negative load on the atmospheric carbon dioxide bus, just like aviation and land transport emissions. * The transformation of the Steel and Aluminium production can be now defined for different years in the ``config.yaml`` file. * Include the option to alter the maximum energy capacity of a store via the ``carrier+factor`` in the ``{sector_opts}`` wildcard. This can be useful for sensitivity analyses. Example: ``co2 stored+e2`` multiplies the ``e_nom_max`` by factor 2. In this example, ``e_nom_max`` represents the CO2 sequestration potential in Europe. +* Add option to regionally disaggregate biomass potential to individual nodes + (currently given per country, then distributed by population density within) + and allow the transport of solid biomass. + The transport costs are determined based on the `JRC-EU-Times Bioenergy report `_ + in the new optional rule ``build_biomass_transport_costs``. + Biomass transport can be activated with the setting ``sector: biomass_transport: true``. * Compatibility with ``xarray`` version 0.19. PyPSA-Eur-Sec 0.5.0 (21st May 2021) diff --git a/doc/spatial_resolution.rst b/doc/spatial_resolution.rst index 13e94543..83a33f73 100644 --- a/doc/spatial_resolution.rst +++ b/doc/spatial_resolution.rst @@ -44,8 +44,10 @@ Hydrogen network: nodal. Methane network: single node for Europe, since future demand is so low and no bottlenecks are expected. -Solid biomass: single node for Europe, until transport costs can be -incorporated. +Solid biomass: choice between single node for Europe and nodal where biomass +potential is regionally disaggregated (currently given per country, +then distributed by population density within) +and transport of solid biomass is possible. CO2: single node for Europe, but a transport and storage cost is added for sequestered CO2. Optionally: nodal, with CO2 transport via pipelines. diff --git a/scripts/build_biomass_transport_costs.py b/scripts/build_biomass_transport_costs.py new file mode 100644 index 00000000..aaec215b --- /dev/null +++ b/scripts/build_biomass_transport_costs.py @@ -0,0 +1,90 @@ +""" +Reads biomass transport costs for different countries of the JRC report + + "The JRC-EU-TIMES model. + Bioenergy potentials + for EU and neighbouring countries." + (2015) + +converts them from units 'EUR per km/ton' -> 'EUR/ (km MWh)' + +assuming as an approximation energy content of wood pellets + +@author: bw0928 +""" + +import pandas as pd +import tabula as tbl + +ENERGY_CONTENT = 4.8 # unit MWh/t (wood pellets) + +def get_countries(): + + pandas_options = dict( + skiprows=range(6), + header=None, + index_col=0 + ) + + return tbl.read_pdf( + str(snakemake.input.transport_cost_data), + pages="145", + multiple_tables=False, + pandas_options=pandas_options + )[0].index + + +def get_cost_per_tkm(page, countries): + + pandas_options = dict( + skiprows=range(6), + header=0, + sep=' |,', + engine='python', + index_col=False, + ) + + sc = tbl.read_pdf( + str(snakemake.input.transport_cost_data), + pages=page, + multiple_tables=False, + pandas_options=pandas_options + )[0] + sc.index = countries + sc.columns = sc.columns.str.replace("€", "EUR") + + return sc + + +def build_biomass_transport_costs(): + + countries = get_countries() + + sc1 = get_cost_per_tkm(146, countries) + sc2 = get_cost_per_tkm(147, countries) + + # take mean of both supply chains + to_concat = [sc1["EUR/km/ton"], sc2["EUR/km/ton"]] + transport_costs = pd.concat(to_concat, axis=1).mean(axis=1) + + # convert tonnes to MWh + transport_costs /= ENERGY_CONTENT + transport_costs.name = "EUR/km/MWh" + + # rename country names + to_rename = { + "UK": "GB", + "XK": "KO", + "EL": "GR" + } + transport_costs.rename(to_rename, inplace=True) + + # add missing Norway with data from Sweden + transport_costs["NO"] = transport_costs["SE"] + + transport_costs.to_csv(snakemake.output[0]) + + +if __name__ == "__main__": + + build_biomass_transport_costs() diff --git a/scripts/prepare_sector_network.py b/scripts/prepare_sector_network.py index 36d9aec7..99afc5d6 100644 --- a/scripts/prepare_sector_network.py +++ b/scripts/prepare_sector_network.py @@ -31,12 +31,31 @@ def define_spatial(nodes): ---------- nodes : list-like """ - + global spatial global options - + spatial.nodes = nodes + # biomass + + spatial.biomass = SimpleNamespace() + + if 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" + 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.biomass.df = pd.DataFrame(vars(spatial.biomass), index=nodes) + + # co2 + spatial.co2 = SimpleNamespace() if options["co2_network"]: @@ -53,7 +72,7 @@ def define_spatial(nodes): def emission_sectors_from_opts(opts): - sectors = ["electricity"] + sectors = ["electricity"] if "T" in opts: sectors += [ "rail non-elec", @@ -206,6 +225,53 @@ def add_lifetime_wind_solar(n, costs): n.generators.loc[gen_i, "lifetime"] = costs.at[carrier, 'lifetime'] +def create_network_topology(n, prefix, connector=" -> ", bidirectional=True): + """ + Create a network topology like the power transmission network. + + Parameters + ---------- + n : pypsa.Network + prefix : str + connector : str + bidirectional : bool, default True + True: one link for each connection + False: one link for each connection and direction (back and forth) + + Returns + ------- + pd.DataFrame with columns bus0, bus1 and length + """ + + ln_attrs = ["bus0", "bus1", "length"] + lk_attrs = ["bus0", "bus1", "length", "underwater_fraction"] + + candidates = pd.concat([ + n.lines[ln_attrs], + n.links.loc[n.links.carrier == "DC", lk_attrs] + ]).fillna(0) + + positive_order = candidates.bus0 < candidates.bus1 + candidates_p = candidates[positive_order] + swap_buses = {"bus0": "bus1", "bus1": "bus0"} + candidates_n = candidates[~positive_order].rename(columns=swap_buses) + candidates = pd.concat([candidates_p, candidates_n]) + + def make_index(c): + return prefix + c.bus0 + connector + c.bus1 + + topo = candidates.groupby(["bus0", "bus1"], as_index=False).mean() + topo.index = topo.apply(make_index, axis=1) + + if not bidirectional: + topo_reverse = topo.copy() + topo_reverse.rename(columns=swap_buses, inplace=True) + topo_reverse.index = topo_reverse.apply(make_index, axis=1) + topo = topo.append(topo_reverse) + + return topo + + # TODO merge issue with PyPSA-Eur def update_wind_solar_costs(n, costs): """ @@ -1623,8 +1689,16 @@ def add_biomass(n, costs): biomass_potentials = pd.read_csv(snakemake.input.biomass_potentials, index_col=0) - n.add("Carrier", "biogas") + if options["biomass_transport"]: + # potential per node distributed within country by population + biomass_potentials_spatial = (biomass_potentials.loc[pop_layout.ct] + .set_index(pop_layout.index) + .mul(pop_layout.fraction, axis="index") + .rename(index=lambda x: x + " solid biomass")) + else: + biomass_potentials_spatial = biomass_potentials.sum() + n.add("Carrier", "biogas") n.add("Carrier", "solid biomass") n.add("Bus", @@ -1633,9 +1707,9 @@ def add_biomass(n, costs): carrier="biogas" ) - n.add("Bus", - "EU solid biomass", - location="EU", + n.madd("Bus", + spatial.biomass.nodes, + location=spatial.biomass.locations, carrier="solid biomass" ) @@ -1648,13 +1722,13 @@ def add_biomass(n, costs): e_initial=biomass_potentials.loc[countries, "biogas"].sum() ) - n.add("Store", - "EU solid biomass", - bus="EU solid biomass", + n.madd("Store", + spatial.biomass.nodes, + bus=spatial.biomass.nodes, carrier="solid biomass", - e_nom=biomass_potentials.loc[countries, "solid biomass"].sum(), + e_nom=biomass_potentials_spatial["solid biomass"], marginal_cost=costs.at['solid biomass', 'fuel'], - e_initial=biomass_potentials.loc[countries, "solid biomass"].sum() + e_initial=biomass_potentials_spatial["solid biomass"] ) n.add("Link", @@ -1669,6 +1743,32 @@ def add_biomass(n, costs): p_nom_extendable=True ) + if options["biomass_transport"]: + + transport_costs = pd.read_csv( + snakemake.input.biomass_transport_costs, + index_col=0, + squeeze=True + ) + + # add biomass transport + biomass_transport = create_network_topology(n, "biomass transport ", bidirectional=False) + + # costs + bus0_costs = biomass_transport.bus0.apply(lambda x: transport_costs[x[:2]]) + bus1_costs = biomass_transport.bus1.apply(lambda x: transport_costs[x[:2]]) + biomass_transport["costs"] = pd.concat([bus0_costs, bus1_costs], axis=1).mean(axis=1) + + n.madd("Link", + biomass_transport.index, + bus0=biomass_transport.bus0 + " solid biomass", + bus1=biomass_transport.bus1 + " solid biomass", + p_nom_extendable=True, + length=biomass_transport.length.values, + marginal_cost=biomass_transport.costs * biomass_transport.length.values, + capital_cost=1, + carrier="solid biomass transport" + ) #AC buses with district heating urban_central = n.buses.index[n.buses.carrier == "urban central heat"] @@ -1679,7 +1779,7 @@ def add_biomass(n, costs): n.madd("Link", urban_central + " urban central solid biomass CHP", - bus0="EU solid biomass", + bus0=spatial.biomass.df.loc[urban_central, "nodes"].values, bus1=urban_central, bus2=urban_central + " urban central heat", carrier="urban central solid biomass CHP", @@ -1693,7 +1793,7 @@ def add_biomass(n, costs): n.madd("Link", urban_central + " urban central solid biomass CHP CC", - bus0="EU solid biomass", + bus0=spatial.biomass.df.loc[urban_central, "nodes"].values, bus1=urban_central, bus2=urban_central + " urban central heat", bus3="co2 atmosphere", @@ -1719,35 +1819,37 @@ def add_industry(n, costs): # 1e6 to convert TWh to MWh industrial_demand = pd.read_csv(snakemake.input.industrial_demand, index_col=0) * 1e6 - solid_biomass_by_country = industrial_demand["solid biomass"].groupby(pop_layout.ct).sum() - - n.add("Bus", - "solid biomass for industry", - location="EU", + n.madd("Bus", + spatial.biomass.industry, + location=spatial.biomass.locations, carrier="solid biomass for industry" ) - n.add("Load", - "solid biomass for industry", - bus="solid biomass for industry", + if options["biomass_transport"]: + p_set = industrial_demand.loc[spatial.biomass.locations, "solid biomass"].rename(index=lambda x: x + " solid biomass for industry") / 8760 + else: + p_set = industrial_demand["solid biomass"].sum() / 8760 + + n.madd("Load", + spatial.biomass.industry, + bus=spatial.biomass.industry, carrier="solid biomass for industry", - p_set=solid_biomass_by_country.sum() / 8760 + p_set=p_set ) - n.add("Link", - "solid biomass for industry", - bus0="EU solid biomass", - bus1="solid biomass for industry", + n.madd("Link", + spatial.biomass.industry, + bus0=spatial.biomass.nodes, + bus1=spatial.biomass.industry, carrier="solid biomass for industry", p_nom_extendable=True, efficiency=1. ) n.madd("Link", - spatial.co2.locations, - suffix=" solid biomass for industry CC", - bus0="EU solid biomass", - bus1="solid biomass for industry", + spatial.biomass.industry_cc, + bus0=spatial.biomass.nodes, + bus1=spatial.biomass.industry, bus2="co2 atmosphere", bus3=spatial.co2.nodes, carrier="solid biomass for industry CC", @@ -2156,6 +2258,8 @@ if __name__ == "__main__": if o[:4] == "dist": options['electricity_distribution_grid'] = True options['electricity_distribution_grid_cost_factor'] = float(o[4:].replace("p", ".").replace("m", "-")) + if o == "biomasstransport": + options["biomass_transport"] = True nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data = prepare_data(n)