Protect storage level constraint example

The example had no __name__ == "__main__" protector, so it was run on import. Ths lead to a failure in building docs on systems without cbc installed.
oemof · Aug 11, 2023 · 72d1b3b · 72d1b3b
1 parent cf84e31
commit 72d1b3b
Showing 1 changed file with 92 additions and 87 deletions.
diff --git a/examples/storage_level_constraint/storage_level_constraint.py b/examples/storage_level_constraint/storage_level_constraint.py
@@ -46,90 +46,95 @@
 from oemof.solph.constraints import storage_level_constraint
 from oemof.solph.processing import results
 
-es = EnergySystem(
-    timeindex=pd.date_range("2022-01-01", freq="1H", periods=24),
-    infer_last_interval=True,
-)
-
-multiplexer = Bus(
-    label="multiplexer",
-)
-
-storage = GenericStorage(
-    label="storage",
-    nominal_storage_capacity=3,
-    initial_storage_level=1,
-    balanced=True,
-    loss_rate=0.05,
-    inputs={multiplexer: Flow()},
-    outputs={multiplexer: Flow()},
-)
-
-es.add(multiplexer, storage)
-
-in_0 = Source(
-    label="in_0",
-    outputs={multiplexer: Flow(nominal_value=0.5, variable_costs=0.15)},
-)
-es.add(in_0)
-
-in_1 = Source(label="in_1", outputs={multiplexer: Flow(nominal_value=0.1)})
-es.add(in_1)
-
-out_0 = Sink(
-    label="out_0",
-    inputs={multiplexer: Flow(nominal_value=0.25, variable_costs=-0.1)},
-)
-es.add(out_0)
-
-out_1 = Sink(
-    label="out_1",
-    inputs={multiplexer: Flow(nominal_value=0.15, variable_costs=-0.1)},
-)
-es.add(out_1)
-
-
-model = Model(es)
-
-storage_level_constraint(
-    model=model,
-    name="multiplexer",
-    storage_component=storage,
-    multiplexer_bus=multiplexer,
-    input_levels={in_1: 1 / 3},  # in_0 is always active
-    output_levels={out_0: 1 / 6, out_1: 1 / 2},
-)
-model.solve()
-
-my_results = results(model)
-
-df = pd.DataFrame(my_results[(storage, None)]["sequences"])
-df["in1_status"] = my_results[(in_1, None)]["sequences"]
-df["out1_status"] = my_results[(out_1, None)]["sequences"]
-df["out0_status"] = my_results[(out_0, None)]["sequences"]
-
-df["in1"] = my_results[(in_1, multiplexer)]["sequences"]
-df["in0"] = my_results[(in_0, multiplexer)]["sequences"]
-df["out0"] = my_results[(multiplexer, out_0)]["sequences"]
-df["out1"] = my_results[(multiplexer, out_1)]["sequences"]
-
-plt.step(df.index, df["in0"], where="post", label="inflow (<= 1)")
-plt.step(df.index, df["in1"], where="post", label="inflow (< 1/3)")
-plt.step(df.index, df["out0"], where="post", label="outflow (> 1/6)")
-plt.step(df.index, df["out1"], where="post", label="outflow (> 1/2)")
-
-plt.grid()
-plt.legend()
-plt.ylabel("Flow Power (arb. units)")
-plt.ylim(0, 0.5)
-
-plt.twinx()
-
-plt.plot(df.index, df["storage_content"], "k--", label="storage content")
-plt.ylim(0, 3)
-plt.legend(loc="center right")
-plt.ylabel("Stored Energy (arb. units)")
-
-print(df)
-
-plt.show()
+def storage_level_constraint_example():
+    es = EnergySystem(
+        timeindex=pd.date_range("2022-01-01", freq="1H", periods=24),
+        infer_last_interval=True,
+    )
+
+    multiplexer = Bus(
+        label="multiplexer",
+    )
+
+    storage = GenericStorage(
+        label="storage",
+        nominal_storage_capacity=3,
+        initial_storage_level=1,
+        balanced=True,
+        loss_rate=0.05,
+        inputs={multiplexer: Flow()},
+        outputs={multiplexer: Flow()},
+    )
+
+    es.add(multiplexer, storage)
+
+    in_0 = Source(
+        label="in_0",
+        outputs={multiplexer: Flow(nominal_value=0.5, variable_costs=0.15)},
+    )
+    es.add(in_0)
+
+    in_1 = Source(label="in_1", outputs={multiplexer: Flow(nominal_value=0.1)})
+    es.add(in_1)
+
+    out_0 = Sink(
+        label="out_0",
+        inputs={multiplexer: Flow(nominal_value=0.25, variable_costs=-0.1)},
+    )
+    es.add(out_0)
+
+    out_1 = Sink(
+        label="out_1",
+        inputs={multiplexer: Flow(nominal_value=0.15, variable_costs=-0.1)},
+    )
+    es.add(out_1)
+
+
+    model = Model(es)
+
+    storage_level_constraint(
+        model=model,
+        name="multiplexer",
+        storage_component=storage,
+        multiplexer_bus=multiplexer,
+        input_levels={in_1: 1 / 3},  # in_0 is always active
+        output_levels={out_0: 1 / 6, out_1: 1 / 2},
+    )
+    model.solve()
+
+    my_results = results(model)
+
+    df = pd.DataFrame(my_results[(storage, None)]["sequences"])
+    df["in1_status"] = my_results[(in_1, None)]["sequences"]
+    df["out1_status"] = my_results[(out_1, None)]["sequences"]
+    df["out0_status"] = my_results[(out_0, None)]["sequences"]
+
+    df["in1"] = my_results[(in_1, multiplexer)]["sequences"]
+    df["in0"] = my_results[(in_0, multiplexer)]["sequences"]
+    df["out0"] = my_results[(multiplexer, out_0)]["sequences"]
+    df["out1"] = my_results[(multiplexer, out_1)]["sequences"]
+
+    plt.step(df.index, df["in0"], where="post", label="inflow (<= 1)")
+    plt.step(df.index, df["in1"], where="post", label="inflow (< 1/3)")
+    plt.step(df.index, df["out0"], where="post", label="outflow (> 1/6)")
+    plt.step(df.index, df["out1"], where="post", label="outflow (> 1/2)")
+
+    plt.grid()
+    plt.legend()
+    plt.ylabel("Flow Power (arb. units)")
+    plt.ylim(0, 0.5)
+
+    plt.twinx()
+
+    plt.plot(df.index, df["storage_content"], "k--", label="storage content")
+    plt.ylim(0, 3)
+    plt.legend(loc="center right")
+    plt.ylabel("Stored Energy (arb. units)")
+
+    print(df)
+
+    plt.show()
+
+
+if __name__ == "__main__":
+    storage_level_constraint_example()