Create cumulative distribution plots

Author: staadecker

papers/Martin_Staadecker_et_al_2022/figure-s4-analysis-of-4-factors.py

@@ -156,6 +156,7 @@ def get_data(tools):
 
 def create_secondary_y_axis(ax, include_label, y_lim, y_label, color="grey", offset=-0.2):
     rax = ax.twinx()
+    rax.grid(False)
     rax.set_ylim(0, y_lim)
     if include_label:
         rax.spines["left"].set_position(("axes", offset))

papers/Martin_Staadecker_et_al_2022/figure-s5-duration-cdf-cost-scenarios.py

@@ -0,0 +1,65 @@
+# %%
+import matplotlib.pyplot as plt
+import labellines
+
+from papers.Martin_Staadecker_et_al_2022.util import (
+    set_style,
+    get_scenario, save_figure
+)
+from switch_model.tools.graph.main import GraphTools
+
+# Prepare graph tools
+tools = GraphTools(scenarios=[
+    get_scenario("C21", 0.5),
+    get_scenario("C18", 1),
+    get_scenario("C22", 2),
+    get_scenario("C23", 5),
+    get_scenario("C26", 7),
+    get_scenario("C17", 10),
+    get_scenario("C24", 15),
+    get_scenario("1342", 22.43),
+    get_scenario("C25", 40),
+    get_scenario("C19", 70),
+    get_scenario("C20", 102)
+], set_style=False)
+tools.pre_graphing(multi_scenario=True)
+
+set_style()
+plt.close()
+fig = plt.figure()
+ax = fig.gca()
+# %% Get DATA
+ax.clear()
+duration = tools.get_dataframe("storage_capacity.csv")
+duration["duration"] = duration["duration"] = (
+        duration["OnlineEnergyCapacityMWh"] / duration["OnlinePowerCapacityMW"]
+)
+
+duration = duration.sort_values("duration")
+duration = duration[["duration", "OnlinePowerCapacityMW", "scenario_name"]]
+duration.OnlinePowerCapacityMW /= 1e3  # Change to GW
+
+for scenario_name in duration.scenario_name.unique():
+    duration_scenario = duration[duration.scenario_name == scenario_name]
+    duration_scenario["cuml_power"] = duration_scenario.OnlinePowerCapacityMW.cumsum()
+    duration_scenario = duration_scenario.set_index("cuml_power")
+    duration_scenario = duration_scenario["duration"]
+    line = ax.plot(duration_scenario.index, duration_scenario, drawstyle="steps", label=scenario_name)
+    if float(int(scenario_name)) == scenario_name:
+        label = str(int(scenario_name))
+    else:
+        label = str(scenario_name)
+    labellines.labelLine(line[0], duration_scenario.index.max(), outline_width=2, label=label + "$/KWh", align=False,
+                         fontsize="small")
+
+ax.set_yscale("log")
+ax.set_xlabel("Storage Power Capacity (GW)")
+ax.set_ylabel("Storage Duration (h)")
+ax.set_yticks([10, 100, 1000])
+ax.set_yticks([2, 3, 4, 5, 6, 7, 8, 9, 20, 30, 40, 50, 60, 70, 80, 90, 200, 300, 400, 500, 600, 700, 800, 900],
+              minor=True)
+ax.set_yticklabels(["10", "100", "1000"])
+plt.tight_layout()
+
+# %%
+save_figure("figure-s5-duration-cdf-cost-scenarios.png")

papers/Martin_Staadecker_et_al_2022/figure-s6-duration-cdf-cost-scenarios-ca-only.py

@@ -0,0 +1,67 @@
+# %%
+import matplotlib.pyplot as plt
+import labellines
+
+from papers.Martin_Staadecker_et_al_2022.util import (
+    set_style,
+    get_scenario, save_figure
+)
+from switch_model.tools.graph.main import GraphTools
+
+# Prepare graph tools
+tools = GraphTools(scenarios=[
+    get_scenario("C21", 0.5),
+    get_scenario("C18", 1),
+    get_scenario("C22", 2),
+    get_scenario("C23", 5),
+    get_scenario("C26", 7),
+    get_scenario("C17", 10),
+    get_scenario("C24", 15),
+    get_scenario("1342", 22.43),
+    get_scenario("C25", 40),
+    get_scenario("C19", 70),
+    get_scenario("C20", 102)
+], set_style=False)
+tools.pre_graphing(multi_scenario=True)
+
+set_style()
+plt.close()
+fig = plt.figure()
+ax = fig.gca()
+# %% Get DATA
+ax.clear()
+duration = tools.get_dataframe("storage_capacity.csv")
+duration = tools.transform.load_zone(duration)
+duration = duration[duration.region == "CA"]
+duration["duration"] = duration["duration"] = (
+        duration["OnlineEnergyCapacityMWh"] / duration["OnlinePowerCapacityMW"]
+)
+
+duration = duration.sort_values("duration")
+duration = duration[["duration", "OnlinePowerCapacityMW", "scenario_name"]]
+duration.OnlinePowerCapacityMW /= 1e3  # Change to GW
+
+for scenario_name in duration.scenario_name.unique():
+    duration_scenario = duration[duration.scenario_name == scenario_name]
+    duration_scenario["cuml_power"] = duration_scenario.OnlinePowerCapacityMW.cumsum()
+    duration_scenario = duration_scenario.set_index("cuml_power")
+    duration_scenario = duration_scenario["duration"]
+    line = ax.plot(duration_scenario.index, duration_scenario, drawstyle="steps", label=scenario_name)
+    if float(int(scenario_name)) == scenario_name:
+        label = str(int(scenario_name))
+    else:
+        label = str(scenario_name)
+    labellines.labelLine(line[0], duration_scenario.index.max(), outline_width=2, label=label + "$/KWh", align=False,
+                         fontsize="small")
+
+ax.set_yscale("log")
+ax.set_xlabel("Storage Power Capacity (GW)")
+ax.set_ylabel("Storage Duration (h)")
+ax.set_yticks([10, 100, 1000])
+ax.set_yticks([2, 3, 4, 5, 6, 7, 8, 9, 20, 30, 40, 50, 60, 70, 80, 90, 200, 300, 400, 500, 600, 700, 800, 900],
+              minor=True)
+ax.set_yticklabels(["10", "100", "1000"])
+plt.tight_layout()
+
+# %%
+save_figure("figure-s6-duration-cdf-cost-scenarios-ca-only.png")