plot_p_nom_max: Add plots for the cumulative renewable expansion potential

The wildcards `clusters` and `technology` accept lists of values separated by ','

Snakefile

@@ -275,6 +275,15 @@ rule plot_summary:
     output: "results/plots/summary_{summary}_{network}_s{simpl}_{clusters}_l{ll}_{opts}_{country}.{ext}"
     script: "scripts/plot_summary.py"
 
+def input_plot_p_nom_max(wildcards):
+    return [('networks/{network}_s{simpl}{maybe_cluster}.nc'
+             .format(maybe_cluster=('' if c == 'full' else ('_' + c)), **wildcards))
+            for c in wildcards.clusters.split(",")]
+rule plot_p_nom_max:
+    input: input_plot_p_nom_max
+    output: "results/plots/{network}_s{simpl}_cum_p_nom_max_{clusters}_{technology}_{country}.{ext}"
+    script: "scripts/plot_p_nom_max.py"
+
 # Local Variables:
 # mode: python
 # End:

scripts/plot_p_nom_max.py

@@ -0,0 +1,70 @@
+import pypsa
+import pandas as pd
+import matplotlib.pyplot as plt
+
+def cum_p_nom_max(net, tech, country=None):
+    carrier_b = net.generators.carrier == tech
+
+    generators = \
+    pd.DataFrame(dict(
+        p_nom_max=net.generators.loc[carrier_b, 'p_nom_max'],
+        p_max_pu=net.generators_t.p_max_pu.loc[:,carrier_b].mean(),
+        country=net.generators.loc[carrier_b, 'bus'].map(net.buses.country)
+    )).sort_values("p_max_pu", ascending=False)
+
+    if country is not None:
+        generators = generators.loc[generators.country == country]
+
+    generators["cum_p_nom_max"] = generators["p_nom_max"].cumsum() / 1e6
+
+    return generators
+
+
+if __name__ == __main__:
+    # Detect running outside of snakemake and mock snakemake for testing
+    if 'snakemake' not in globals():
+        from vresutils.snakemake import MockSnakemake, Dict
+        snakemake = MockSnakemake(
+            path='..',
+            wildcards={'clusters': '45,90,181,full',
+                       'country': 'all'},
+            params=dict(techs=['onwind', 'offwind-ac', 'offwind-dc', 'solar']),
+            input=Dict(
+                **{
+                    'full': 'networks/elec_s.nc',
+                    '45': 'networks/elec_s_45.nc',
+                    '90': 'networks/elec_s_90.nc',
+                    '181': 'networks/elec_s_181.nc',
+                }
+            ),
+            output=['results/plots/cum_p_nom_max_{clusters}_{country}.pdf']
+        )
+
+    logging.basicConfig(level=snakemake.config['logging_level'])
+
+    plot_kwds = dict(drawstyle="steps-post")
+
+    clusters = snakemake.wildcards.clusters.split(',')
+    techs = snakemake.params.techs
+    country = snakemake.wildcards.country
+    if country == 'all':
+        country = None
+    else:
+        plot_kwds['marker'] = 'x'
+
+    fig, axes = plt.subplots(1, len(techs))
+
+    for cluster in clusters:
+        net = pypsa.Network(getattr(snakemake.input, cluster))
+
+        for i, tech in enumerate(techs):
+            cum_p_nom_max(net, tech, country).plot(x="p_max_pu", y="c_p_nom_max", label=cluster, ax=axes[0][i], **plot_kwds)
+
+    for i, tech in enumerate(techs):
+        ax = axes[0][i]
+        ax.set_xlabel(f"Capacity factor of {tech}")
+        ax.set_ylabel("Cumulative installable capacity / TW")
+
+    plt.legend(title="Cluster level")
+
+    fig.savefig(snakemake.output[0], transparent=True, bbox_inches='tight')