Fix transmission map for nomopyomo outputs; plot also H2 network
Use s_nom_min for the reference point for the transmission reinforcement not s_nom, since s_nom is now overwritten for LV > 1.0 (the old pyomo code kept the s_nom variable fixed in the pyomo model rather than via pypsa setting s_nom_extendable = False, like the nomopyomo code now does). The legend scale of the H2 network electrolyzers is wrong. I don't yet understand why. Possibly the cost scale in the other map is also wrong.
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Tom Brown
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@ -2,15 +2,15 @@ logging_level: INFO
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results_dir: 'results/'
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summary_dir: results
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run: '200111-wave'
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run: '191222-181-lv'
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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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simpl: ['']
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lv: [1.0]#, 1.125, 1.25, 1.5, 2.0]# or opt
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clusters: [50] #[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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lv: [1.0, 1.125, 1.25, 1.5, 2.0]# or opt
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clusters: [181] #[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-wave0p25,Co2L0-3H-T-H-B-I-wave0p5,Co2L0-3H-T-H-B-I-wave0p6,Co2L0-3H-T-H-B-I-wave0p75]#,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]
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sector_opts: [Co2L0-3H-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]#,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]
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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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@ -148,7 +148,11 @@ def plot_map(components=["links","stores","storage_units","generators"],bus_size
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n.links.drop(n.links.index[(n.links.carrier != "DC") & (n.links.carrier != "B2B")],inplace=True)
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom_opt-n.lines.s_nom), Link=(n.links.p_nom_opt-n.links.p_nom)))
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if snakemake.wildcards.lv == "1.0":
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#should be zero
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom_opt-n.lines.s_nom), Link=(n.links.p_nom_opt-n.links.p_nom)))
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else:
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom_opt-n.lines.s_nom_min), Link=(n.links.p_nom_opt-n.links.p_nom_min)))
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#PDF has minimum width, so set these to zero
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line_threshold = 500.
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@ -204,6 +208,87 @@ def plot_map(components=["links","stores","storage_units","generators"],bus_size
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fig.savefig(snakemake.output.map,transparent=True)
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def plot_h2_map():
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n = pypsa.Network(snakemake.input.network,
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override_component_attrs=override_component_attrs)
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if "H2 pipeline" not in n.links.carrier.unique():
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return
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assign_location(n)
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bus_size_factor=5e2
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linewidth_factor=1e4
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#MW below which not drawn
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line_threshold=1e3
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bus_color="m"
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link_color="c"
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#Drop non-electric buses so they don't clutter the plot
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n.buses.drop(n.buses.index[n.buses.carrier != "AC"],inplace=True)
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elec = n.links.index[n.links.carrier == "H2 Electrolysis"]
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bus_sizes = pd.Series(0., index=n.buses.index)
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bus_sizes.loc[elec.str.replace(" H2 Electrolysis","")] = n.links.loc[elec,"p_nom_opt"].values/bus_size_factor
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n.links.drop(n.links.index[n.links.carrier != "H2 pipeline"],inplace=True)
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link_widths = n.links.p_nom_opt/linewidth_factor
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link_widths[n.links.p_nom_opt < line_threshold] = 0.
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n.links.bus0 = n.links.bus0.str.replace(" H2","")
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n.links.bus1 = n.links.bus1.str.replace(" H2","")
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print(link_widths.sort_values())
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print(n.links[["bus0","bus1"]])
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fig, ax = plt.subplots(subplot_kw={"projection":ccrs.PlateCarree()})
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fig.set_size_inches(7,6)
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n.plot(bus_sizes=bus_sizes,
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bus_colors=bus_color,
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line_colors=dict(Link=link_color),
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line_widths={"Link" : link_widths},
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branch_components=["Link"],
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ax=ax)
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handles = make_legend_circles_for([50, 10], scale=bus_size_factor, facecolor=bus_color)
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labels = ["{} GW".format(s) for s in (50, 10)]
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l2 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.01, 1.01),
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labelspacing=1.0,
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framealpha=1.,
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title='Electrolyzer capacity',
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handler_map=make_handler_map_to_scale_circles_as_in(ax))
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ax.add_artist(l2)
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handles = []
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labels = []
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for s in (50, 10):
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handles.append(plt.Line2D([0],[0],color=link_color,
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linewidth=s*1e3/linewidth_factor))
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labels.append("{} GW".format(s))
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l1 = l1_1 = ax.legend(handles, labels,
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loc="upper left", bbox_to_anchor=(0.30, 1.01),
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framealpha=1,
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labelspacing=0.8, handletextpad=1.5,
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title='H2 pipeline capacity')
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ax.add_artist(l1_1)
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#ax.set_title("Scenario {} with {} transmission".format(snakemake.config['plotting']['scenario_names'][flex],"optimal" if line_limit == "opt" else "no"))
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fig.tight_layout()
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fig.savefig(snakemake.output.map.replace("-costs-all","-h2_network"),transparent=True)
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def plot_map_without():
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n = pypsa.Network(snakemake.input.network,
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@ -228,7 +313,10 @@ def plot_map_without():
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n.links.drop(n.links.index[(n.links.carrier != "DC") & (n.links.carrier != "B2B")],inplace=True)
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom), Link=(n.links.p_nom)))
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if snakemake.wildcards.lv == "1.0":
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom), Link=(n.links.p_nom)))
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else:
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line_widths_exp = pd.concat(dict(Line=(n.lines.s_nom_min), Link=(n.links.p_nom_min)))
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#PDF has minimum width, so set these to zero
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line_threshold = 0.
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@ -393,6 +481,8 @@ if __name__ == "__main__":
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plot_map(components=["generators","links","stores","storage_units"],bus_size_factor=1.5e10)
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plot_h2_map()
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plot_map_without()
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#plot_map(components=["generators"],bus_size_factor=1.7e10,suffix="generators")
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