Plot summary; take account of snapshot weightings correctly

config.yaml

@@ -180,6 +180,13 @@ plotting:
       linewidth_factor: 3.e+3 # 1.e+3  #3.e+3
 
   costs_max: 800
+  costs_threshold: 1
+
+
+  energy_max: 15000.
+  energy_min: -10000.
+  energy_threshold: 50.
+
 
   vre_techs: ["onwind", "offwind", "solar", "ror"]
   conv_techs: ["OCGT", "CCGT", "Nuclear", "Coal"]
@@ -193,60 +200,73 @@ plotting:
                "central CHP electric", "central gas boiler"]
   heat_generators: ["gas boiler", "central gas boiler", "solar thermal collector", "central solar thermal collector"]
   tech_colors:
-    onwind: "xkcd:azure"
+    "onwind" : "b"
-    offwind: "blue"
+    "onshore wind" : "b"
-    hydro: "g"
+    'offwind' : "c"
-    ror: "lightgreen"
+    'offshore wind' : "c"
-    PHS: "g"
+    "hydro" : "#3B5323"
-    hydro+PHS: "g"
+    "hydro reservoir" : "#3B5323"
-    solar: "yellow"
+    "ror" : "#78AB46"
-    OCGT: "brown"
+    "run of river" : "#78AB46"
-    OCGT marginal: "sandybrown"
+    'hydroelectricity' : '#006400'
-    OCGT-heat: "orange"
+    'solar' : "y"
-    central gas boiler: "orange"
+    'solar PV' : "y"
-    gas boiler: "orange"
+    'solar thermal' : 'coral'
-    gas boilers: "orange"
+    "OCGT" : "wheat"
-    gas boiler marginal: "orange"
+    "OCGT marginal" : "sandybrown"
-    gas: "brown"
+    "OCGT-heat" : "orange"
-    lines: "k"
+    "gas boiler" : "orange"
-    AC line: "k"
+    "gas boilers" : "orange"
-    AC-AC: "k"
+    "gas boiler marginal" : "orange"
-    transmission lines: "k"
+    "gas" : "brown"
-    H2: "m"
+    "natural gas" : "brown"
-    hydrogen storage: "m"
+    "lines" : "k"
-    battery: "slategray"
+    "transmission lines" : "k"
-    battery storage: "slategray"
+    "H2" : "m"
-    CAES: "lightgray"
+    "hydrogen storage" : "m"
-    nuclear: "r"
+    "battery" : "slategray"
-    nuclear marginal: "r"
+    "battery storage" : "slategray"
-    coal: "k"
+    "Nuclear" : "r"
-    coal marginal: "k"
+    "Nuclear marginal" : "r"
-    lignite: "grey"
+    "Coal" : "k"
-    lignite marginal: "grey"
+    "Coal marginal" : "k"
-    CCGT: "orange"
+    "Lignite" : "grey"
-    CCGT marginal: "orange"
+    "Lignite marginal" : "grey"
-    diesel: "darkred"
+    "CCGT" : "orange"
-    diesel marginal: "darkred"
+    "CCGT marginal" : "orange"
-    heat pumps: "green"
+    "heat pumps" : "#76EE00"
-    heat pump: "green"
+    "heat pump" : "#76EE00"
-    central heat pump: "green"
+    "air heat pump" : "#76EE00"
-    resistive heater: "pink"
+    "ground heat pump" : "#40AA00"
-    central resistive heater: "pink"
+    "resistive heater" : "pink"
-    Sabatier: "turquoise"
+    "Sabatier" : "#FF1493"
-    water tanks: "w"
+    "methanation" : "#FF1493"
-    CHP: "r"
+    "helmeth" : "#7D0552"
-    CHP heat: "r"
+    "helmeth" : "#7D0552"
-    CHP electric: "r"
+    "DAC" : "#E74C3C"
-    central CHP heat: "r"
+    "nuclear" : "#303030"
-    central CHP electric: "r"
+    "water tanks" : "#BBBBBB"
-    Pumped storage: "g"
+    "hot water storage" : "#BBBBBB"
-    Ambient: "k"
+    "hot water charging" : "#BBBBBB"
-    AC load: "b"
+    "hot water discharging" : "#999999"
-    Heat load: "r"
+    "CHP" : "r"
-    Li ion load: "grey"
+    "CHP heat" : "r"
-    heat: "r"
+    "CHP electric" : "r"
-    Li ion: "grey"
+    "PHS" : "g"
-    district heating: "#CC4E5C"
+    "Ambient" : "k"
+    "Electric load" : "b"
+    "Heat load" : "r"
+    "Transport load" : "grey"
+    "heat" : "r"
+    "Li ion" : "grey"
+    "district heating" : "#CC4E5C"
+    "retrofitting" : "purple"
+    "building retrofitting" : "purple"
+    "BEV charger" : "grey"
+    "V2G" : "grey"
+    "transport" : "grey"
+    "electricity" : "k"
+    "transport fuel cell" : "#AAAAAA"
   nice_names:
     # OCGT: "Gas"
     # OCGT marginal: "Gas (marginal)"

scripts/make_summary.py

@@ -50,15 +50,15 @@ def calculate_costs(n,label,costs):
         costs.loc[idx[c.list_name,"capital",list(capital_costs_grouped.index)],label] = capital_costs_grouped.values
 
         if c.name == "Link":
-            p = c.pnl.p0.sum()
+            p = c.pnl.p0.multiply(n.snapshot_weightings,axis=0).sum()
         elif c.name == "Line":
             continue
         elif c.name == "StorageUnit":
-            p_all = c.pnl.p.copy()
+            p_all = c.pnl.p.multiply(n.snapshot_weightings,axis=0)
             p_all[p_all < 0.] = 0.
             p = p_all.sum()
         else:
-            p = c.pnl.p.sum()
+            p = c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum()
 
         marginal_costs = p*c.df.marginal_cost
 
@@ -97,9 +97,9 @@ def calculate_energy(n,label,energy):
     for c in n.iterate_components(n.one_port_components|n.branch_components):
 
         if c.name in n.one_port_components:
-            c_energies = c.pnl.p.sum().multiply(c.df.sign).groupby(c.df.carrier).sum()
+            c_energies = c.pnl.p.multiply(n.snapshot_weightings,axis=0).sum().multiply(c.df.sign).groupby(c.df.carrier).sum()
         else:
-            c_energies = (-c.pnl.p1.sum() - c.pnl.p0.sum()).groupby(c.df.carrier).sum()
+            c_energies = (-c.pnl.p1.multiply(n.snapshot_weightings,axis=0).sum() - c.pnl.p0.multiply(n.snapshot_weightings,axis=0).sum()).groupby(c.df.carrier).sum()
 
         energy = energy.reindex(energy.index|pd.MultiIndex.from_product([[c.list_name],c_energies.index]))
 

scripts/plot_summary.py

@@ -0,0 +1,185 @@
+
+
+
+import pandas as pd
+
+#allow plotting without Xwindows
+import matplotlib
+matplotlib.use('Agg')
+
+import matplotlib.pyplot as plt
+
+
+
+#consolidate and rename
+def rename_techs(label):
+    if label[:8] == "central ":
+        label = label[8:]
+    if label[:6] == "urban ":
+        label = label[6:]
+
+    if "retrofitting" in label:
+        label = "building retrofitting"
+    if "H2" in label:
+        label = "hydrogen storage"
+    if "CHP" in label:
+        label = "CHP"
+    if "water tank" in label:
+        label = "water tanks"
+    if label=="water tanks":
+        label = "hot water storage"
+    if "gas" in label and label != "gas boiler":
+        label = "natural gas"
+    if "solar thermal" in label:
+        label = "solar thermal"
+    if label == "solar":
+        label = "solar PV"
+    if label == "heat pump":
+        label = "air heat pump"
+    if label == "Sabatier":
+        label = "methanation"
+    if label == "offwind":
+        label = "offshore wind"
+    if label == "onwind":
+        label = "onshore wind"
+    if label == "ror":
+        label = "hydroelectricity"
+    if label == "hydro":
+        label = "hydroelectricity"
+    if label == "PHS":
+        label = "hydroelectricity"
+    if label == "co2 Store":
+        label = "DAC"
+    if "battery" in label:
+        label = "battery storage"
+
+    return label
+
+
+preferred_order = pd.Index(["transmission lines","hydroelectricity","hydro reservoir","run of river","pumped hydro storage","onshore wind","offshore wind","solar PV","solar thermal","building retrofitting","ground heat pump","air heat pump","resistive heater","CHP","OCGT","gas boiler","gas","natural gas","methanation","hydrogen storage","battery storage","hot water storage"])
+
+def plot_costs():
+
+
+    cost_df = pd.read_csv(snakemake.input.costs,index_col=list(range(3)),header=[0,1,2])
+
+
+    df = cost_df.groupby(cost_df.index.get_level_values(2)).sum()
+
+    #convert to billions
+    df = df/1e9
+
+    df = df.groupby(df.index.map(rename_techs)).sum()
+
+    to_drop = df.index[df.max(axis=1) < snakemake.config['plotting']['costs_threshold']]
+
+    print("dropping")
+
+    print(df.loc[to_drop])
+
+    df = df.drop(to_drop)
+
+    print(df.sum())
+
+    new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
+
+    new_columns = df.sum().sort_values().index
+
+    fig, ax = plt.subplots()
+    fig.set_size_inches((12,8))
+
+    df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
+
+
+    handles,labels = ax.get_legend_handles_labels()
+
+    handles.reverse()
+    labels.reverse()
+
+    ax.set_ylim([0,snakemake.config['plotting']['costs_max']])
+
+    ax.set_ylabel("System Cost [EUR billion per year]")
+
+    ax.set_xlabel("")
+
+    ax.grid(axis="y")
+
+    ax.legend(handles,labels,ncol=4,loc="upper left")
+
+
+    fig.tight_layout()
+
+    fig.savefig(snakemake.output.costs,transparent=True)
+
+
+def plot_energy():
+
+    energy_df = pd.read_csv(snakemake.input.energy,index_col=list(range(2)),header=[0,1,2])
+
+    df = energy_df.groupby(energy_df.index.get_level_values(1)).sum()
+
+    #convert MWh to TWh
+    df = df/1e6
+
+    df = df.groupby(df.index.map(rename_techs)).sum()
+
+    to_drop = df.index[df.abs().max(axis=1) < snakemake.config['plotting']['energy_threshold']]
+
+    print("dropping")
+
+    print(df.loc[to_drop])
+
+    df = df.drop(to_drop)
+
+    print(df.sum())
+
+    new_index = (preferred_order&df.index).append(df.index.difference(preferred_order))
+
+    new_columns = df.columns.sort_values()
+
+    fig, ax = plt.subplots()
+    fig.set_size_inches((12,8))
+
+    df.loc[new_index,new_columns].T.plot(kind="bar",ax=ax,stacked=True,color=[snakemake.config['plotting']['tech_colors'][i] for i in new_index])
+
+
+    handles,labels = ax.get_legend_handles_labels()
+
+    handles.reverse()
+    labels.reverse()
+
+    ax.set_ylim([snakemake.config['plotting']['energy_min'],snakemake.config['plotting']['energy_max']])
+
+    ax.set_ylabel("Energy [TWh/a]")
+
+    ax.set_xlabel("")
+
+    ax.grid(axis="y")
+
+    ax.legend(handles,labels,ncol=4,loc="upper left")
+
+
+    fig.tight_layout()
+
+    fig.savefig(snakemake.output.energy,transparent=True)
+
+
+if __name__ == "__main__":
+    # Detect running outside of snakemake and mock snakemake for testing
+    if 'snakemake' not in globals():
+        from vresutils import Dict
+        import yaml
+        snakemake = Dict()
+        with open('config.yaml') as f:
+            snakemake.config = yaml.load(f)
+        snakemake.input = Dict()
+        snakemake.output = Dict()
+        name = "37-lv"
+
+        for item in ["costs","energy"]:
+            snakemake.input[item] = snakemake.config['summary_dir'] + '/{name}/csvs/{item}.csv'.format(name=name,item=item)
+            snakemake.output[item] = snakemake.config['summary_dir'] + '/{name}/graphs/{item}.pdf'.format(name=name,item=item)
+
+    plot_costs()
+
+    plot_energy()