Fix examples, postprocessing, facades in storage

src/oemof/tabular/examples/scripting/dispatch.py

@@ -32,49 +32,61 @@
 es = EnergySystem(timeindex=timeseries.index)
 
 bus = Bus(label='DE')
-
-wind = fc.Volatile(
-    label='wind',
-    carrier="wind",
-    tech="onshore",
-    capacity=150,
-    bus=bus,
-    profile=timeseries['onshore'])
-
-ccgt = fc.Dispatchable(
-    label='ccgt',
-    bus=bus,
-    carrier="gas",
-    tech="ccgt",
-    capacity=100,
-    marginal_cost=25)
-
-sto = fc.Storage(
-    label='storage',
-    bus=bus,
-    carrier="lithium",
-    tech="battery",
-    capacity=20,
-    storage_capacity=100,
-    capacity_ratio=1/6
-    )
-
-load = fc.Load(
-    label='load',
-    bus=bus,
-    amount=500e3,
-    profile=timeseries['load'])
-
-curtailment = fc.Excess(
-    label="excess",
-    bus=bus)
-
-# add the components to the energy system object
-es.add(wind, load, sto, ccgt, bus, curtailment)
+es.add(bus)
+
+es.add(
+    fc.Volatile(
+        label='wind',
+        carrier="wind",
+        tech="onshore",
+        capacity=150,
+        bus=bus,
+        profile=timeseries['onshore'])
+)
+
+es.add(
+    fc.Dispatchable(
+        label='ccgt',
+        bus=bus,
+        carrier="gas",
+        tech="ccgt",
+        capacity=100,
+        marginal_cost=25)
+)
+
+es.add(
+    fc.Storage(
+        label='storage',
+        bus=bus,
+        carrier="lithium",
+        tech="battery",
+        capacity=20,
+        balanced=False,
+        initial_storage_capacity=1,
+        storage_capacity=100)
+)
+
+es.add(
+    fc.Load(
+        label='load',
+        bus=bus,
+        amount=500e3,
+        profile=timeseries['load'])
+)
+
+es.add(
+    fc.Excess(
+        label="excess",
+        bus=bus)
+)
 
 # create model based on energy system and its components
 m = Model(es)
 
+# write lp file
+m.write(os.path.join(results_path, 'dispatch.lp'),
+        io_options={'symbolic_solver_labels': True})
+
 #  solve the model using cbc solver
 m.solve('cbc')
 

src/oemof/tabular/examples/scripting/plotting.py

@@ -26,11 +26,11 @@
 
 
 # plot results with plotly
-offline.plot(
-    stacked_plot(
-        name,
-        os.path.join(
-            os.path.expanduser('~'),
-            "oemof-results")
-        ),
-    filename=os.path.join(results_path, 'stacked-plot.html'))
+# offline.plot(
+#     stacked_plot(
+#         name,
+#         os.path.join(
+#             os.path.expanduser('~'),
+#             "oemof-results")
+#         ),
+#     filename=os.path.join(results_path, 'stacked-plot.html'))

src/oemof/tabular/facades.py

@@ -572,7 +572,7 @@ class Storage(GenericStorage, Facade):
         Investment costs for the storage unit e.g in €/MW-capacity
     loss: numeric
         Standing loss per timestep in % of capacity. Default: 0
-    storage_capacity_initial: numeric
+    initial_storage_capacity: numeric
         The state of the storage capacity in the first (and last) time step of
         optimization. Default: 0.5
     input_parameters: dict (optional)
@@ -604,8 +604,8 @@ def __init__(self, *args, **kwargs):
 
         self.loss = sequence(kwargs.get('loss', 0))
 
-        self.storage_capacity_initial = kwargs.get(
-            'storage_capacity_initial', 0.5)
+        self.initial_storage_capacity = kwargs.get(
+            'initial_storage_capacity', 0.5)
 
         self.input_parameters = kwargs.get('input_parameters', {})
 
@@ -620,7 +620,7 @@ def build_solph_components(self):
         """
         self.nominal_storage_capacity = self.storage_capacity
 
-        self.initial_storage_level = self.storage_capacity_initial
+        self.initial_storage_level = self.initial_storage_capacity
 
         self.loss_rate = self.loss
 

src/oemof/tabular/tools/postprocessing.py

@@ -246,9 +246,11 @@ def save(df, name, path=output_path):
         duals.columns = duals.columns.droplevel(1)
         duals = (duals.T / m.objective_weighting).T
         save(duals, "shadow_prices")
-
-    filling_levels = views.node_weight_by_type(
-        m.results, GenericStorage
-    )
-    filling_levels.columns = filling_levels.columns.droplevel(1)
-    save(filling_levels, "filling_levels")
+
+    # check if storages exist in energy system nodes
+    if [n for n in m.es.nodes if isinstance(n, GenericStorage)]:
+        filling_levels = views.node_weight_by_type(
+            m.results, GenericStorage
+        )
+        filling_levels.columns = filling_levels.columns.droplevel(1)
+        save(filling_levels, "filling_levels")