rename central_fraction->district heating potential, restructure district heating share implementation
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lisazeyen
parent
8322350fee
commit
854bd80818
@ -26,7 +26,7 @@ spatial = SimpleNamespace()
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def define_spatial(nodes):
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"""
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Namespace for spatial
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Parameters
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----------
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nodes : list-like
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@ -36,7 +36,7 @@ def define_spatial(nodes):
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global options
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spatial.nodes = nodes
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# biomass
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spatial.biomass = SimpleNamespace()
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@ -53,11 +53,11 @@ def define_spatial(nodes):
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spatial.biomass.industry_cc = ["solid biomass for industry CC"]
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spatial.biomass.df = pd.DataFrame(vars(spatial.biomass), index=nodes)
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# co2
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spatial.co2 = SimpleNamespace()
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if options["co2_network"]:
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spatial.co2.nodes = nodes + " co2 stored"
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spatial.co2.locations = nodes
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@ -72,7 +72,7 @@ def define_spatial(nodes):
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def emission_sectors_from_opts(opts):
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sectors = ["electricity"]
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sectors = ["electricity"]
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if "T" in opts:
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sectors += [
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"rail non-elec",
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@ -107,13 +107,13 @@ def get(item, investment_year=None):
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def create_network_topology(n, prefix, connector=" -> "):
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"""
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Create a network topology like the power transmission network.
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Parameters
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----------
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n : pypsa.Network
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prefix : str
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connector : str
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Returns
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-------
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pd.DataFrame with columns bus0, bus1 and length
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@ -228,7 +228,7 @@ def add_lifetime_wind_solar(n, costs):
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def create_network_topology(n, prefix, connector=" -> ", bidirectional=True):
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"""
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Create a network topology like the power transmission network.
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Parameters
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----------
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n : pypsa.Network
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@ -237,7 +237,7 @@ def create_network_topology(n, prefix, connector=" -> ", bidirectional=True):
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bidirectional : bool, default True
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True: one link for each connection
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False: one link for each connection and direction (back and forth)
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Returns
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-------
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pd.DataFrame with columns bus0, bus1 and length
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@ -256,19 +256,19 @@ def create_network_topology(n, prefix, connector=" -> ", bidirectional=True):
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swap_buses = {"bus0": "bus1", "bus1": "bus0"}
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candidates_n = candidates[~positive_order].rename(columns=swap_buses)
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candidates = pd.concat([candidates_p, candidates_n])
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def make_index(c):
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return prefix + c.bus0 + connector + c.bus1
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topo = candidates.groupby(["bus0", "bus1"], as_index=False).mean()
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topo.index = topo.apply(make_index, axis=1)
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if not bidirectional:
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topo_reverse = topo.copy()
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topo_reverse.rename(columns=swap_buses, inplace=True)
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topo_reverse.index = topo_reverse.apply(make_index, axis=1)
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topo = topo.append(topo_reverse)
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return topo
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@ -439,7 +439,7 @@ def add_co2_tracking(n, options):
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n.madd("Store",
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spatial.co2.nodes,
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e_nom_extendable=True,
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e_nom_max=np.inf,
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e_nom_max=np.inf,
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capital_cost=options['co2_sequestration_cost'],
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carrier="co2 stored",
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bus=spatial.co2.nodes
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@ -458,14 +458,14 @@ def add_co2_tracking(n, options):
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def add_co2_network(n, costs):
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logger.info("Adding CO2 network.")
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co2_links = create_network_topology(n, "CO2 pipeline ")
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cost_onshore = (1 - co2_links.underwater_fraction) * costs.at['CO2 pipeline', 'fixed'] * co2_links.length
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cost_submarine = co2_links.underwater_fraction * costs.at['CO2 submarine pipeline', 'fixed'] * co2_links.length
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capital_cost = cost_onshore + cost_submarine
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n.madd("Link",
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co2_links.index,
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bus0=co2_links.bus0.values + " co2 stored",
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@ -636,6 +636,9 @@ def prepare_data(n):
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nodal_energy_totals = energy_totals.loc[pop_layout.ct].fillna(0.)
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nodal_energy_totals.index = pop_layout.index
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# district heat share not weighted by population
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district_heat_share = round(nodal_energy_totals["district heat share"],
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ndigits=2)
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nodal_energy_totals = nodal_energy_totals.multiply(pop_layout.fraction, axis=0)
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# copy forward the daily average heat demand into each hour, so it can be multipled by the intraday profile
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@ -758,7 +761,7 @@ def prepare_data(n):
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)
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return nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data
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return nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data, district_heat_share
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# TODO checkout PyPSA-Eur script
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@ -1386,7 +1389,7 @@ def add_heat(n, costs):
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heat_load = heat_demand[[sector + " water",sector + " space"]].groupby(level=1,axis=1).sum()[nodes[name]].multiply(factor)
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if name == "urban central":
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heat_load = heat_demand.groupby(level=1,axis=1).sum()[nodes[name]].multiply(factor * (1 + options['district_heating_loss']))
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heat_load = heat_demand.groupby(level=1,axis=1).sum()[nodes[name]].multiply(factor * (1 + options['district_heating']['district_heating_loss']))
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n.madd("Load",
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nodes[name],
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@ -1671,10 +1674,6 @@ def create_nodes_for_heat_sector():
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# distribution of urban population within a country
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pop_layout["urban_ct_fraction"] = pop_layout["urban"] / \
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pop_layout["ct"].map(ct_urban.get)
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# todays district heating share per country
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dist_heat_share_ct = pd.read_csv(snakemake.input.dh_share, index_col=0,
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usecols=[0,1]).dropna()/100
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dist_heat_share = pop_layout.ct.map(dist_heat_share_ct["district heating share"])
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sectors = ["residential", "services"]
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@ -1686,36 +1685,29 @@ def create_nodes_for_heat_sector():
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nodes[sector + " rural"] = pop_layout.index
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nodes[sector + " urban decentral"] = pop_layout.index
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if options["central"] and not options['district_heating_increase']:
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central_fraction = options['central_fraction']
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dist_fraction = central_fraction * urban_fraction
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nodes["urban central"] = dist_fraction.index
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# maximum potential of urban demand covered by district heating
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central_fraction = options['district_heating']["potential"]
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# district heating share at each node
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dist_fraction_node = district_heat_share * pop_layout["urban_ct_fraction"] / pop_layout["fraction"]
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nodes["urban central"] = dist_fraction_node.index
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# if district heating share larger than urban fraction -> set urban
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# fraction to district heating share
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urban_fraction = pd.concat([urban_fraction, dist_fraction_node],
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axis=1).max(axis=1)
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# difference of max potential and today's share of district heating
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diff = (urban_fraction * central_fraction) - dist_fraction_node
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progress = get(options["district_heating"]["potential"], investment_year)
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dist_fraction_node += diff * progress
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print("************************************")
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print(
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"the current DH share compared to the maximum possible is increased \
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\n by a progress factor of ",
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progress,
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"resulting DH share: ",
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dist_fraction_node)
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print("**********************************")
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# take current district heating share
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if options['district_heating_increase']:
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dist_fraction = dist_heat_share * \
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pop_layout["urban_ct_fraction"] / pop_layout["fraction"]
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nodes["urban central"] = dist_fraction.index
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# if district heating share larger than urban fraction -> set urban
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# fraction to district heating share
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urban_fraction = pd.concat([urban_fraction, dist_fraction],
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axis=1).max(axis=1)
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diff = urban_fraction - dist_fraction
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dist_fraction += diff * get(options["dh_strength"], investment_year)
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print("************************************")
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print(
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"the current DH share compared to the maximum possible is increased \
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\n by a factor of ",
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get(options["dh_strength"], investment_year),
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"resulting DH share: ",
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dist_fraction)
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print("**********************************")
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else:
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dist_fraction = urban_fraction * 0
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nodes["urban central"] = dist_fraction.index
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return nodes, dist_fraction, urban_fraction
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return nodes, dist_fraction_node, urban_fraction
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def add_biomass(n, costs):
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@ -1788,7 +1780,7 @@ def add_biomass(n, costs):
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index_col=0,
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squeeze=True
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)
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# add biomass transport
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biomass_transport = create_network_topology(n, "biomass transport ", bidirectional=False)
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@ -2246,7 +2238,6 @@ if __name__ == "__main__":
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opts="",
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clusters="37",
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lv=1.0,
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opts='',
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sector_opts='Co2L0-168H-T-H-B-I-solar3-dist1',
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planning_horizons="2030",
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)
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@ -2300,10 +2291,10 @@ if __name__ == "__main__":
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if o == "biomasstransport":
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options["biomass_transport"] = True
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nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data = prepare_data(n)
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nodal_energy_totals, heat_demand, ashp_cop, gshp_cop, solar_thermal, transport, avail_profile, dsm_profile, nodal_transport_data, district_heat_share = prepare_data(n)
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if "nodistrict" in opts:
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options["central"] = False
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options["district_heating"]["progress"] = 0.0
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if "T" in opts:
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add_land_transport(n, costs)
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