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Make CCS optional for SMR and industry process emissions

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Tom Brown 2019-12-13 18:06:38 +01:00
parent 49a68bdd35
commit 41f7f44dcf
4 changed files with 125 additions and 59 deletions
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4
config.yaml
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@ -2,7 +2,7 @@ logging_level: INFO
results_dir: 'results/'
summary_dir: results
run: '191212-chp'
run: '191212-ccs'
scenario:
sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
@ -10,7 +10,7 @@ scenario:
lv: [1.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
clusters: [50] #[90, 128, 181] #[45, 64, 90, 128, 181, 256] #, 362] # (2**np.r_[5.5:9:.5]).astype(int) minimum is 37
opts: [''] #for pypsa-eur
sector_opts: [Co2L0-3H-T-H-B-I]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H] #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
sector_opts: [Co2L0-3H-T-H-B-I,Co2L0p2-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#,Co2L0p1-3H-T-H-B-I,Co2L0p25-3H-T-H-B-I,Co2L0p5-3H-T-H-B-I]#[Co2L0-3H-T-H-B-I-onwind0-solar3,Co2L0-3H-T-H-B-I-onwind0p125-solar3,Co2L0-3H-T-H-B-I-onwind0p25-solar3,Co2L0-3H-T-H-B-I-onwind0p50-solar3,Co2L0-3H-T-H-B-I-solar3]#,Co2L0-3H-T-H-B-I-onwind0p25-solar3]#,Co2L0p05-3H-T-H-B-I,Co2L0p10-3H-T-H-B-I,Co2L0p20-3H-T-H-B-I,Co2L0p30-3H-T-H-B-I,Co2L0p50-3H-T-H-B-I]#[Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0-3H-T-H,Co2L0p20-3H-T-H] #Co2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p20-3H-T-HCo2L-3H-T-H,Co2L0p10-3H-T-H,Co2L0p30-3H-T-H,Co2L0p50-3H-T-H] #Co2L-3H,Co2L-3H-T,, LC-FL, LC-T, Ep-T, Co2L-T]
# Co2L will give default (5%); Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions

50
data/costs.csv
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@ -73,15 +73,15 @@ CCGT,2030,efficiency,0.5,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
biomass,2030,efficiency,0.468,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
geothermal,2030,efficiency,0.239,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
nuclear,2030,efficiency,0.337,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
gas,2030,CO2 intensity,0.187,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
gas,2030,CO2 intensity,0.187,tCO2/MWhth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
coal,2030,efficiency,0.464,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
lignite,2030,efficiency,0.447,per unit,DIW DataDoc http://hdl.handle.net/10419/80348
oil,2030,efficiency,0.393,per unit,DIW DataDoc http://hdl.handle.net/10419/80348 CT
coal,2030,CO2 intensity,0.354,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
lignite,2030,CO2 intensity,0.4,tCO2/MWth,German sources
oil,2030,CO2 intensity,0.248,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
geothermal,2030,CO2 intensity,0.026,tCO2/MWth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
solid biomass,2030,CO2 intensity,0.3,tCO2/MWth,TODO
coal,2030,CO2 intensity,0.354,tCO2/MWhth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
lignite,2030,CO2 intensity,0.4,tCO2/MWhth,German sources
oil,2030,CO2 intensity,0.248,tCO2/MWhth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
geothermal,2030,CO2 intensity,0.026,tCO2/MWhth,https://www.eia.gov/environment/emissions/co2_vol_mass.php
solid biomass,2030,CO2 intensity,0.3,tCO2/MWhth,TODO
electrolysis,2030,investment,350,EUR/kWel,Palzer Thesis
electrolysis,2030,FOM,4,%/year,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
electrolysis,2030,lifetime,18,years,NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
@ -109,6 +109,14 @@ SMR,2030,investment,540.56,EUR/kWCH4,https://www.gov.uk/government/publications/
SMR,2030,lifetime,25,years,TODO
SMR,2030,FOM,5.4,%/year,https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
SMR,2030,efficiency,0.74,per unit,https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
SMR CCS,2030,investment,1032,EUR/kWCH4,https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030; GBP 466 exchange 1.16; CCS costed at 300 EUR/tCO2/a
SMR CCS,2030,lifetime,25,years,TODO
SMR CCS,2030,FOM,5.4,%/year,https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
SMR CCS,2030,efficiency,0.67,per unit,https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030; CCS uses 10% of gas
industry CCS,2030,investment,300,EUR/tCO2/a,Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
industry CCS,2030,FOM,2,%/year,Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
industry CCS,2030,lifetime,25,years,Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
industry CCS,2030,efficiency,0.9,per unit,Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
Fischer-Tropsch,2030,investment,677.6,EUR/kWH2,Fasihi doi:10.3390/su9020306 (60 kEUR/bpd = 847 EUR/kWL (1b = 1.7 MWh) 847*0.8 = 677.6)
Fischer-Tropsch,2030,lifetime,30,years,doi:10.3390/su9020306
Fischer-Tropsch,2030,FOM,3,%/year,doi:10.3390/su9020306
@ -118,7 +126,7 @@ DAC,2030,lifetime,30,years,Fasihi
DAC,2030,FOM,4,%/year,Fasihi
battery inverter,2030,investment,411,USD/kWel,budischak2013
battery inverter,2030,lifetime,20,years,budischak2013
battery inverter,2030,efficiency,0.81,per unit,budischak2013; Lund and Kempton (2008) http://dx.doi.org/10.1016/j.enpol.2008.06.007
battery inverter,2030,efficiency,0.81,per unit,budischak2013; Lund and Kempton (2008) https://doi.org/10.1016/j.enpol.2008.06.007
battery inverter,2030,FOM,3,%/year,budischak2013
battery storage,2030,investment,192,USD/kWh,budischak2013
battery storage,2030,lifetime,15,years,budischak2013
@ -191,22 +199,22 @@ central gas CHP CCS,2030,c_b,0.7,per unit,DEA (backpressure ratio)
central gas CHP CCS,2030,c_v,0.17,per unit,DEA (loss of fuel for additional heat)
central gas CHP CCS,2030,p_nom_ratio,1.,per unit,
central gas CHP CCS,2030,VOM,0.82,EUR/MWh,DEA
central solid biomass CHP,2030,lifetime,40,years,DEA
central solid biomass CHP,2030,investment,1990,EUR/kWel,DEA
central solid biomass CHP,2030,FOM,3,%/year,DEA
central solid biomass CHP,2030,efficiency,0.52,per unit,DEA (condensation mode)
central solid biomass CHP,2030,c_b,1.01,per unit,DEA (backpressure ratio)
central solid biomass CHP,2030,c_v,0.15,per unit,DEA (loss of fuel for additional heat)
central solid biomass CHP,2030,lifetime,40,years,DEA for wood pellets CHP
central solid biomass CHP,2030,investment,1990,EUR/kWel,DEA for wood pellets CHP
central solid biomass CHP,2030,FOM,3,%/year,DEA for wood pellets CHP
central solid biomass CHP,2030,efficiency,0.52,per unit,DEA for wood pellets CHP (condensation mode)
central solid biomass CHP,2030,c_b,1.01,per unit,DEA for wood pellets CHP (backpressure ratio)
central solid biomass CHP,2030,c_v,0.15,per unit,DEA for wood pellets CHP (loss of fuel for additional heat)
central solid biomass CHP,2030,p_nom_ratio,1.,per unit,
central solid biomass CHP,2030,VOM,2.2,EUR/MWh,DEA
central solid biomass CHP CCS,2030,lifetime,40,years,DEA
central solid biomass CHP CCS,2030,investment,2590,EUR/kWel,DEA + DIW extra for CCS on gas plant
central solid biomass CHP CCS,2030,FOM,3,%/year,DEA
central solid biomass CHP CCS,2030,efficiency,0.468,per unit,DEA (condensation mode + efficiency loss due to capture)
central solid biomass CHP CCS,2030,c_b,1.01,per unit,DEA (backpressure ratio)
central solid biomass CHP CCS,2030,c_v,0.15,per unit,DEA (loss of fuel for additional heat)
central solid biomass CHP,2030,VOM,2.2,EUR/MWh,DEA for wood pellets CHP
central solid biomass CHP CCS,2030,lifetime,40,years,DEA for wood pellets CHP
central solid biomass CHP CCS,2030,investment,2590,EUR/kWel,DEA for wood pellets CHP + DIW extra for CCS on gas plant
central solid biomass CHP CCS,2030,FOM,3,%/year,DEA for wood pellets CHP
central solid biomass CHP CCS,2030,efficiency,0.468,per unit,DEA for wood pellets CHP (condensation mode + efficiency loss due to capture)
central solid biomass CHP CCS,2030,c_b,1.01,per unit,DEA for wood pellets CHP (backpressure ratio)
central solid biomass CHP CCS,2030,c_v,0.15,per unit,DEA for wood pellets CHP (loss of fuel for additional heat)
central solid biomass CHP CCS,2030,p_nom_ratio,1.,per unit,
central solid biomass CHP CCS,2030,VOM,2.2,EUR/MWh,DEA
central solid biomass CHP CCS,2030,VOM,2.2,EUR/MWh,DEA for wood pellets CHP
micro CHP,2030,lifetime,20,years,DEA for PEMFC with methane (for unit consuming 2kW CH4)
micro CHP,2030,investment,4500,EUR/kWCH4,DEA for PEMFC with methane (for unit consuming 2kW CH4)
micro CHP,2030,FOM,6,%/year,DEA for PEMFC with methane (for unit consuming 2kW CH4)

1 technology year parameter value unit source
73 biomass 2030 efficiency 0.468 per unit DIW DataDoc http://hdl.handle.net/10419/80348
74 geothermal 2030 efficiency 0.239 per unit DIW DataDoc http://hdl.handle.net/10419/80348
75 nuclear 2030 efficiency 0.337 per unit DIW DataDoc http://hdl.handle.net/10419/80348
76 gas 2030 CO2 intensity 0.187 tCO2/MWth tCO2/MWhth https://www.eia.gov/environment/emissions/co2_vol_mass.php
77 coal 2030 efficiency 0.464 per unit DIW DataDoc http://hdl.handle.net/10419/80348 PC (Advanced/SuperC)
78 lignite 2030 efficiency 0.447 per unit DIW DataDoc http://hdl.handle.net/10419/80348
79 oil 2030 efficiency 0.393 per unit DIW DataDoc http://hdl.handle.net/10419/80348 CT
80 coal 2030 CO2 intensity 0.354 tCO2/MWth tCO2/MWhth https://www.eia.gov/environment/emissions/co2_vol_mass.php
81 lignite 2030 CO2 intensity 0.4 tCO2/MWth tCO2/MWhth German sources
82 oil 2030 CO2 intensity 0.248 tCO2/MWth tCO2/MWhth https://www.eia.gov/environment/emissions/co2_vol_mass.php
83 geothermal 2030 CO2 intensity 0.026 tCO2/MWth tCO2/MWhth https://www.eia.gov/environment/emissions/co2_vol_mass.php
84 solid biomass 2030 CO2 intensity 0.3 tCO2/MWth tCO2/MWhth TODO
85 electrolysis 2030 investment 350 EUR/kWel Palzer Thesis
86 electrolysis 2030 FOM 4 %/year NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
87 electrolysis 2030 lifetime 18 years NREL http://www.nrel.gov/docs/fy09osti/45873.pdf; budischak2013
109 SMR 2030 lifetime 25 years TODO
110 SMR 2030 FOM 5.4 %/year https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
111 SMR 2030 efficiency 0.74 per unit https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
112 SMR CCS 2030 investment 1032 EUR/kWCH4 https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030; GBP 466 exchange 1.16; CCS costed at 300 EUR/tCO2/a
113 SMR CCS 2030 lifetime 25 years TODO
114 SMR CCS 2030 FOM 5.4 %/year https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030
115 SMR CCS 2030 efficiency 0.67 per unit https://www.gov.uk/government/publications/hydrogen-supply-chain-evidence-base; slide 42 assumption for 2030; CCS uses 10% of gas
116 industry CCS 2030 investment 300 EUR/tCO2/a Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
117 industry CCS 2030 FOM 2 %/year Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
118 industry CCS 2030 lifetime 25 years Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
119 industry CCS 2030 efficiency 0.9 per unit Saygin et al 2013 https://doi.org/10.1016/j.ijggc.2013.05.032
120 Fischer-Tropsch 2030 investment 677.6 EUR/kWH2 Fasihi doi:10.3390/su9020306 (60 kEUR/bpd = 847 EUR/kWL (1b = 1.7 MWh) 847*0.8 = 677.6)
121 Fischer-Tropsch 2030 lifetime 30 years doi:10.3390/su9020306
122 Fischer-Tropsch 2030 FOM 3 %/year doi:10.3390/su9020306
126 DAC 2030 FOM 4 %/year Fasihi
127 battery inverter 2030 investment 411 USD/kWel budischak2013
128 battery inverter 2030 lifetime 20 years budischak2013
129 battery inverter 2030 efficiency 0.81 per unit budischak2013; Lund and Kempton (2008) http://dx.doi.org/10.1016/j.enpol.2008.06.007 budischak2013; Lund and Kempton (2008) https://doi.org/10.1016/j.enpol.2008.06.007
130 battery inverter 2030 FOM 3 %/year budischak2013
131 battery storage 2030 investment 192 USD/kWh budischak2013
132 battery storage 2030 lifetime 15 years budischak2013
199 central gas CHP CCS 2030 c_v 0.17 per unit DEA (loss of fuel for additional heat)
200 central gas CHP CCS 2030 p_nom_ratio 1. per unit
201 central gas CHP CCS 2030 VOM 0.82 EUR/MWh DEA
202 central solid biomass CHP 2030 lifetime 40 years DEA DEA for wood pellets CHP
203 central solid biomass CHP 2030 investment 1990 EUR/kWel DEA DEA for wood pellets CHP
204 central solid biomass CHP 2030 FOM 3 %/year DEA DEA for wood pellets CHP
205 central solid biomass CHP 2030 efficiency 0.52 per unit DEA (condensation mode) DEA for wood pellets CHP (condensation mode)
206 central solid biomass CHP 2030 c_b 1.01 per unit DEA (backpressure ratio) DEA for wood pellets CHP (backpressure ratio)
207 central solid biomass CHP 2030 c_v 0.15 per unit DEA (loss of fuel for additional heat) DEA for wood pellets CHP (loss of fuel for additional heat)
208 central solid biomass CHP 2030 p_nom_ratio 1. per unit
209 central solid biomass CHP 2030 VOM 2.2 EUR/MWh DEA DEA for wood pellets CHP
210 central solid biomass CHP CCS 2030 lifetime 40 years DEA DEA for wood pellets CHP
211 central solid biomass CHP CCS 2030 investment 2590 EUR/kWel DEA + DIW extra for CCS on gas plant DEA for wood pellets CHP + DIW extra for CCS on gas plant
212 central solid biomass CHP CCS 2030 FOM 3 %/year DEA DEA for wood pellets CHP
213 central solid biomass CHP CCS 2030 efficiency 0.468 per unit DEA (condensation mode + efficiency loss due to capture) DEA for wood pellets CHP (condensation mode + efficiency loss due to capture)
214 central solid biomass CHP CCS 2030 c_b 1.01 per unit DEA (backpressure ratio) DEA for wood pellets CHP (backpressure ratio)
215 central solid biomass CHP CCS 2030 c_v 0.15 per unit DEA (loss of fuel for additional heat) DEA for wood pellets CHP (loss of fuel for additional heat)
216 central solid biomass CHP CCS 2030 p_nom_ratio 1. per unit
217 central solid biomass CHP CCS 2030 VOM 2.2 EUR/MWh DEA DEA for wood pellets CHP
218 micro CHP 2030 lifetime 20 years DEA for PEMFC with methane (for unit consuming 2kW CH4)
219 micro CHP 2030 investment 4500 EUR/kWCH4 DEA for PEMFC with methane (for unit consuming 2kW CH4)
220 micro CHP 2030 FOM 6 %/year DEA for PEMFC with methane (for unit consuming 2kW CH4)

128
scripts/prepare_sector_network.py
View File

@ -623,16 +623,27 @@ def add_storage(network):
if options['SMR']:
network.madd("Link",
nodes + " SMR",
nodes + " SMR CCS",
bus0=["EU gas"]*len(nodes),
bus1=nodes+" H2",
bus2="co2 atmosphere",
bus3="co2 stored",
p_nom_extendable=True,
carrier="SMR",
efficiency=costs.at["SMR","efficiency"],
carrier="SMR CCS",
efficiency=costs.at["SMR CCS","efficiency"],
efficiency2=costs.at['gas','CO2 intensity']*(1-options["ccs_fraction"]),
efficiency3=costs.at['gas','CO2 intensity']*options["ccs_fraction"],
capital_cost=costs.at["SMR CCS","fixed"])
network.madd("Link",
nodes + " SMR",
bus0=["EU gas"]*len(nodes),
bus1=nodes+" H2",
bus2="co2 atmosphere",
p_nom_extendable=True,
carrier="SMR",
efficiency=costs.at["SMR","efficiency"],
efficiency2=costs.at['gas','CO2 intensity'],
capital_cost=costs.at["SMR","fixed"])
@ -1123,43 +1134,70 @@ def add_industry(network):
solid_biomass_by_country = industrial_demand["solid biomass"].groupby(pop_layout.ct).sum()
countries = solid_biomass_by_country.index
network.madd("Bus",
["solid biomass for industry"],
carrier="solid biomass for industry")
network.madd("Load",
["solid biomass for industry"],
bus="EU solid biomass",
bus="solid biomass for industry",
carrier="solid biomass for industry",
p_set=solid_biomass_by_country.sum()/8760.)
#Net transfer of CO2 from atmosphere to stored
network.madd("Load",
["solid biomass for industry co2 from atmosphere"],
bus="co2 atmosphere",
carrier="solid biomass for industry co2 from atmosphere",
p_set=solid_biomass_by_country.sum()*costs.at['solid biomass','CO2 intensity']*options["ccs_fraction"]/8760.)
network.madd("Link",
["solid biomass for industry"],
bus0="EU solid biomass",
bus1="solid biomass for industry",
carrier="solid biomass for industry",
p_nom_extendable=True,
efficiency=1.)
network.madd("Load",
["solid biomass for industry co2 to stored"],
bus="co2 stored",
carrier="solid biomass for industry co2 to stored",
p_set=-solid_biomass_by_country.sum()*costs.at['solid biomass','CO2 intensity']*options["ccs_fraction"]/8760.)
network.madd("Link",
["solid biomass for industry CCS"],
bus0="EU solid biomass",
bus1="solid biomass for industry",
bus2="co2 atmosphere",
bus3="co2 stored",
carrier="solid biomass for industry CCS",
p_nom_extendable=True,
capital_cost=costs.at["industry CCS","fixed"]*costs.at['solid biomass','CO2 intensity']*8760, #8760 converts EUR/(tCO2/a) to EUR/(tCO2/h)
efficiency=0.9,
efficiency2=-costs.at['solid biomass','CO2 intensity']*options["ccs_fraction"],
efficiency3=costs.at['solid biomass','CO2 intensity']*options["ccs_fraction"])
network.madd("Bus",
["gas for industry"],
carrier="gas for industry")
network.madd("Load",
["gas for industry"],
bus="EU gas",
bus="gas for industry",
carrier="gas for industry",
p_set=industrial_demand.loc[nodes,"methane"].sum()/8760.)
network.madd("Load",
["gas for industry co2 to atmosphere"],
bus="co2 atmosphere",
carrier="gas for industry co2 to atmosphere",
p_set=-industrial_demand.loc[nodes,"methane"].sum()*costs.at['gas','CO2 intensity']*(1-options["ccs_fraction"])/8760.)
network.madd("Link",
["gas for industry"],
bus0="EU gas",
bus1="gas for industry",
bus2="co2 atmosphere",
carrier="gas for industry",
p_nom_extendable=True,
efficiency=1.,
efficiency2=costs.at['gas','CO2 intensity'])
network.madd("Load",
["gas for industry co2 to stored"],
bus="co2 stored",
carrier="gas for industry co2 to stored",
p_set=-industrial_demand.loc[nodes,"methane"].sum()*costs.at['gas','CO2 intensity']*options["ccs_fraction"]/8760.)
network.madd("Link",
["gas for industry CCS"],
bus0="EU gas",
bus1="gas for industry",
bus2="co2 atmosphere",
bus3="co2 stored",
carrier="gas for industry CCS",
p_nom_extendable=True,
capital_cost=costs.at["industry CCS","fixed"]*costs.at['gas','CO2 intensity']*8760, #8760 converts EUR/(tCO2/a) to EUR/(tCO2/h)
efficiency=0.9,
efficiency2=costs.at['gas','CO2 intensity']*(1-options["ccs_fraction"]),
efficiency3=costs.at['gas','CO2 intensity']*options["ccs_fraction"])
network.madd("Load",
@ -1250,17 +1288,37 @@ def add_industry(network):
carrier="industry new electricity",
p_set = (industrial_demand.loc[nodes,"electricity"]-industrial_demand.loc[nodes,"current electricity"])/8760.)
network.madd("Load",
["process emissions to atmosphere"],
bus="co2 atmosphere",
carrier="process emissions to atmosphere",
p_set = -industrial_demand.loc[nodes,"process emission"].sum()*(1-options["ccs_fraction"])/8760.)
network.madd("Bus",
["process emissions"],
carrier="process emissions")
#this should be process emissions fossil+feedstock
#then need load on atmosphere for feedstock emissions that are currently going to atmosphere via Link Fischer-Tropsch demand
network.madd("Load",
["process emissions to stored"],
bus="co2 stored",
carrier="process emissions to stored",
p_set = -industrial_demand.loc[nodes,"process emission"].sum()*options["ccs_fraction"]/8760.)
["process emissions"],
bus="process emissions",
carrier="process emissions",
p_set = -industrial_demand.loc[nodes,"process emission"].sum()/8760.)
network.madd("Link",
["process emissions"],
bus0="process emissions",
bus1="co2 atmosphere",
carrier="process emissions",
p_nom_extendable=True,
efficiency=1.)
#assume enough local waste heat for CCS
network.madd("Link",
["process emissions CCS"],
bus0="process emissions",
bus1="co2 atmosphere",
bus2="co2 stored",
carrier="process emissions CCS",
p_nom_extendable=True,
capital_cost=costs.at["industry CCS","fixed"]*8760, #8760 converts EUR/(tCO2/a) to EUR/(tCO2/h)
efficiency=(1-options["ccs_fraction"]),
efficiency2=options["ccs_fraction"])

2
scripts/solve_network.py
View File

@ -126,7 +126,7 @@ def add_battery_constraints(n):
link_p_nom = get_var(n, "Link", "p_nom")
lhs = linexpr((1,link_p_nom[nodes + " charger"]),
(-n.links.loc[nodes + " discharger", "efficiency"],
(-n.links.loc[nodes + " discharger", "efficiency"].values,
link_p_nom[nodes + " discharger"].values))
define_constraints(n, lhs, "=", 0, 'Link', 'charger_ratio')