add network plot for perfect

rules/postprocess.smk

@@ -44,16 +44,18 @@ if config["foresight"] == "perfect":
             + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_brownfield_all_years.nc",
             regions=RESOURCES + "regions_onshore_elec_s{simpl}_{clusters}.geojson",
         output:
-            map=RESULTS
+            **{
-            + "maps/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}-costs-all_{year}.pdf",
+                f"map_{year}": RESULTS
-            today=RESULTS
+                + "maps/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}-costs-all_"
-            + "maps/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{year}-today.pdf",
+                + f"{year}.pdf"
+                for year in config["scenario"]["planning_horizons"]
+            },
         threads: 2
         resources:
             mem_mb=10000,
         benchmark:
             BENCHMARKS
-            + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_{year}_brownfield_all_years_benchmark.txt",
+            + "postnetworks/elec_s{simpl}_{clusters}_l{ll}_{opts}_{sector_opts}_brownfield_all_years_benchmark",
         conda:
             "../envs/environment.yaml"
         script:

scripts/plot_network.py

@@ -24,7 +24,7 @@ from make_summary import assign_carriers
 from plot_summary import preferred_order, rename_techs
 from pypsa.plot import add_legend_circles, add_legend_lines, add_legend_patches
 
-plt.style.use(["ggplot", "matplotlibrc"])
+plt.style.use(["ggplot"])
 
 
 def rename_techs_tyndp(tech):
@@ -913,6 +913,153 @@ def plot_series(network, carrier="AC", name="test"):
     )
 
 
+def plot_map_perfect(network, components=["Link", "Store", "StorageUnit", "Generator"],
+             bus_size_factor=1.7e10):
+
+    n = network.copy()
+    assign_location(n)
+    # Drop non-electric buses so they don't clutter the plot
+    n.buses.drop(n.buses.index[n.buses.carrier != "AC"], inplace=True)
+    # investment periods
+    investments = n.snapshots.levels[0]
+
+    costs = {}
+    for comp in components:
+        df_c = n.df(comp)
+        if df_c.empty: continue
+        df_c["nice_group"] = df_c.carrier.map(rename_techs_tyndp)
+
+        attr = "e_nom_opt" if comp == "Store" else "p_nom_opt"
+
+        active = pd.concat(
+            [
+                n.get_active_assets(comp, inv_p).rename(inv_p)
+                for inv_p in investments
+            ],
+            axis=1,
+        ).astype(int)
+        capital_cost = n.df(comp)[attr] * n.df(comp).capital_cost
+        capital_cost_t = ((active.mul(capital_cost, axis=0))
+                 .groupby([n.df(comp).location,
+                           n.df(comp).nice_group]).sum())
+
+        capital_cost_t.drop("load", level=1, inplace=True, errors="ignore")
+
+        costs[comp] = capital_cost_t
+
+    costs = pd.concat(costs).groupby(level=[1,2]).sum()
+    costs.drop(costs[costs.sum(axis=1)==0].index, inplace=True)
+
+    new_columns = (preferred_order.intersection(costs.index.levels[1])
+                   .append(costs.index.levels[1].difference(preferred_order)))
+    costs = costs.reindex(new_columns, level=1)
+
+    for item in new_columns:
+        if item not in snakemake.config['plotting']['tech_colors']:
+            print("Warning!",item,"not in config/plotting/tech_colors, assign random color")
+            snakemake.config['plotting']['tech_colors'] = "pink"
+   
+    n.links.drop(n.links.index[(n.links.carrier != "DC") & (
+        n.links.carrier != "B2B")], inplace=True)
+
+    # drop non-bus
+    to_drop = costs.index.levels[0].symmetric_difference(n.buses.index)
+    if len(to_drop) != 0:
+        print("dropping non-buses", to_drop)
+        costs.drop(to_drop, level=0, inplace=True, axis=0, errors="ignore")
+
+    # make sure they are removed from index
+    costs.index = pd.MultiIndex.from_tuples(costs.index.values)
+
+    # PDF has minimum width, so set these to zero
+    line_lower_threshold = 500.
+    line_upper_threshold = 1e4
+    linewidth_factor = 2e3
+    ac_color = "gray"
+    dc_color = "m"
+
+    line_widths = n.lines.s_nom_opt
+    link_widths = n.links.p_nom_opt
+    linewidth_factor = 2e3
+    line_lower_threshold = 0.
+    title = "Today's transmission"
+
+    line_widths[line_widths < line_lower_threshold] = 0.
+    link_widths[link_widths < line_lower_threshold] = 0.
+
+    line_widths[line_widths > line_upper_threshold] = line_upper_threshold
+    link_widths[link_widths > line_upper_threshold] = line_upper_threshold
+
+    for year in costs.columns:
+
+        fig, ax = plt.subplots(subplot_kw={"projection": ccrs.PlateCarree()})
+        fig.set_size_inches(7, 6)
+        fig.suptitle(year)
+
+        n.plot(
+            bus_sizes=costs[year] / bus_size_factor,
+            bus_colors=snakemake.config['plotting']['tech_colors'],
+            line_colors=ac_color,
+            link_colors=dc_color,
+            line_widths=line_widths / linewidth_factor,
+            link_widths=link_widths / linewidth_factor,
+            ax=ax,  **map_opts
+        )
+
+        sizes = [20, 10, 5]
+        labels = [f"{s} bEUR/a" for s in sizes]
+        sizes = [s / bus_size_factor * 1e9 for s in sizes]
+
+        legend_kw = dict(
+            loc="upper left",
+            bbox_to_anchor=(0.01, 1.06),
+            labelspacing=0.8,
+            frameon=False,
+            handletextpad=0,
+            title="system cost",
+        )
+
+        add_legend_circles(
+            ax,
+            sizes,
+            labels,
+            srid=n.srid,
+            patch_kw=dict(facecolor="lightgrey"),
+            legend_kw=legend_kw,
+        )
+
+        sizes = [10, 5]
+        labels = [f"{s} GW" for s in sizes]
+        scale = 1e3 / linewidth_factor
+        sizes = [s * scale for s in sizes]
+
+        legend_kw = dict(
+            loc="upper left",
+            bbox_to_anchor=(0.27, 1.06),
+            frameon=False,
+            labelspacing=0.8,
+            handletextpad=1,
+            title=title,
+        )
+
+        add_legend_lines(
+            ax, sizes, labels, patch_kw=dict(color="lightgrey"), legend_kw=legend_kw
+        )
+
+        legend_kw = dict(
+            bbox_to_anchor=(1.52, 1.04),
+            frameon=False,
+        )
+
+            
+        fig.savefig(
+            snakemake.output[f"map_{year}"],
+            transparent=True,
+            bbox_inches="tight"
+        )
+
+
+#%%
 if __name__ == "__main__":
     if "snakemake" not in globals():
         from _helpers import mock_snakemake
@@ -921,10 +1068,9 @@ if __name__ == "__main__":
             "plot_network",
             simpl="",
             opts="",
-            clusters="5",
+            clusters="37",
-            ll="v1.5",
+            ll="v1.0",
-            sector_opts="CO2L0-1H-T-H-B-I-A-solar+p3-dist1",
+            sector_opts="4380H-T-H-B-I-A-solar+p3-dist1",
-            planning_horizons="2030",
         )
 
     logging.basicConfig(level=snakemake.config["logging"]["level"])
@@ -937,17 +1083,22 @@ if __name__ == "__main__":
 
     if map_opts["boundaries"] is None:
         map_opts["boundaries"] = regions.total_bounds[[0, 2, 1, 3]] + [-1, 1, -1, 1]
-
+    
-    plot_map(
+    if snakemake.params["foresight"] == "perfect":
-        n,
+        plot_map_perfect(n,
-        components=["generators", "links", "stores", "storage_units"],
+                         components=["Link", "Store", "StorageUnit", "Generator"],
-        bus_size_factor=2e10,
+                         bus_size_factor=2e10)
-        transmission=False,
+    else:
-    )
+        plot_map(
-
+            n,
-    plot_h2_map(n, regions)
+            components=["generators", "links", "stores", "storage_units"],
-    plot_ch4_map(n)
+            bus_size_factor=2e10,
-    plot_map_without(n)
+            transmission=False,
+        )
+    
+        plot_h2_map(n, regions)
+        plot_ch4_map(n)
+        plot_map_without(n)
 
     # plot_series(n, carrier="AC", name=suffix)
     # plot_series(n, carrier="heat", name=suffix)