Allow space heating to be linearly reduced (without cost so far)
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@ -2,7 +2,7 @@ logging_level: INFO
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results_dir: 'results/'
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summary_dir: results
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run: '190726-microchp'
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run: '190728-space0p5'
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scenario:
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sectors: [E] # ,E+EV,E+BEV,E+BEV+V2G] # [ E+EV, E+BEV, E+BEV+V2G ]
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@ -10,7 +10,7 @@ scenario:
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lv: [1.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
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clusters: [128] #[90, 128, 181] #[45, 64, 90, 128, 181, 256] #, 362] # (2**np.r_[5.5:9:.5]).astype(int) minimum is 37
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opts: [''] #for pypsa-eur
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sector_opts: [Co2L0-3H-T-H-B-I,Co2L0-3H-T-H-B-I-nodistrict]#,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]
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sector_opts: [Co2L0-3H-T-H-B-I-space0p5,Co2L0-3H-T-H-B-I-nodistrict-space0p5]#,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]
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# Co2L will give default (5%); Co2L0p25 will give 25% CO2 emissions; Co2Lm0p05 will give 5% negative emissions
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@ -64,6 +64,7 @@ sector:
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'transport_fuel_cell_share' : 0. #0 means all EVs, 1 means all FCs
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'shipping_average_efficiency' : 0.4 #For conversion of fuel oil to propulsion in 2011
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'time_dep_hp_cop' : True
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'space_heating_fraction' : 1.0 #fraction of space heating active
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'retrofitting' : False
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'retroI-fraction' : 0.25
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'retroI-fraction' : 0.55
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@ -309,7 +309,7 @@ def prepare_data(network):
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sectors = ["residential","services"]
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nodal_energy_totals["Space Heating"] = nodal_energy_totals[["total {sector} space".format(sector=sector) for sector in sectors]].sum(axis=1)
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nodal_energy_totals["Space Heating"] = options['space_heating_fraction']*nodal_energy_totals[["total {sector} space".format(sector=sector) for sector in sectors]].sum(axis=1)
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nodal_energy_totals["Water Heating"] = nodal_energy_totals[["total {sector} water".format(sector=sector) for sector in sectors]].sum(axis=1)
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space_heat_demand = (heat_demand_df/heat_demand_df.sum()).multiply(nodal_energy_totals["Space Heating"])*1e6*Nyears
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@ -1425,6 +1425,12 @@ if __name__ == "__main__":
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add_storage(n)
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for o in opts:
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if "space" in o:
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limit = o[o.find("space")+5:]
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limit = float(limit.replace("p",".").replace("m","-"))
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print(o,limit)
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options['space_heating_fraction'] = limit
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nodal_energy_totals, heat_demand, space_heat_demand, water_heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, co2_totals, nodal_transport_data = prepare_data(n)
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