create function include_busmap_area

etrago/appl.py

@@ -112,8 +112,8 @@
         "method": "kmedoids-dijkstra",  # choose clustering method: kmeans or kmedoids-dijkstra
         "n_clusters_AC": 30,  # total number of resulting AC nodes (DE+foreign)
         "cluster_foreign_AC": False,  # take foreign AC buses into account, True or False
-        "exclusion_area": False,  # False, path to shapefile or list of nuts names of not cluster area
-        "cluster_exclusion_area": False, # False or number of buses.
+        "interest_area": False,  # False, path to shapefile or list of nuts names of not cluster area
+        "cluster_interest_area": False, # False or number of buses.
         "method_gas": "kmedoids-dijkstra",  # choose clustering method: kmeans or kmedoids-dijkstra
         "n_clusters_gas": 17,  # total number of resulting CH4 nodes (DE+foreign)
         "cluster_foreign_gas": False,  # take foreign CH4 buses into account, True or False
@@ -440,15 +440,15 @@ def run_etrago(args, json_path):
             as well and included in number of clusters specified through
             ``'n_clusters_AC'``.
             Default: False.
-        * "exclusion_area": False, list, string
+        * "interest_area": False, list, string
             Area of especial interest that will be not clustered. It is by
             default set to false. When an exclusion area is provided, the given
             value for n_clusters_AC will mean the total of AC buses outside the
             area.The areas can be provided in two ways: list of
             nuts names e.G. ["Cuxhaven", "Bremerhaven", "Bremen"] or a string
             with a path to a shape file.
             Default: False.
-        * "cluster_exclusion_area": False, int
+        * "cluster_interest_area": False, int
             Number of buses to cluster all the electrical buses in the
             exclusion area. Method provided in the arg "method" is used.
             Default: False.

etrago/cluster/electrical.py

@@ -478,7 +478,7 @@ def select_elec_network(etrago):
             number of clusters used in the clustering process.
         area_network : pypsa.Network
             Contains the electric network in the area of interest defined in
-            network_clustering - exclusion_area.
+            network_clustering - interest_area.
     """
     settings = etrago.args["network_clustering"]
 
@@ -1054,6 +1054,49 @@ def calc_availability_factor(gen):
     return weight
 
 
+def include_busmap_area(etrago, busmap, medoid_idx, network_area, weight_area):
+    args = etrago.args["network_clustering"]
+
+    if not args["interest_area"]:
+        return busmap, medoid_idx
+    if not args["cluster_interest_area"]:
+        for bus in network_area.buses.index:
+            busmap[bus] = bus
+        return busmap, medoid_idx
+    else:
+        if args["method"] == "kmeans":
+            busmap_area = kmean_clustering(
+                etrago,
+                network_area,
+                weight_area,
+                args["cluster_interest_area"],
+            )
+            busmap_area = (
+                busmap_area.astype(int) + busmap.apply(int).max() + 1
+            ).apply(str)
+
+        if args["method"] == "kmedoids-dijkstra":
+            busmap_area, medoid_idx_area = kmedoids_dijkstra_clustering(
+                etrago,
+                network_area.buses,
+                network_area.lines,
+                weight_area,
+                args["cluster_interest_area"],
+            )
+
+            medoid_idx_area.index = (
+                medoid_idx_area.index.astype(int) + busmap.apply(int).max() + 1
+            )
+            busmap_area = (
+                busmap_area.astype(int) + busmap.apply(int).max() + 1
+            ).apply(str)
+            medoid_idx = pd.concat([medoid_idx, medoid_idx_area])
+
+        busmap = pd.concat([busmap, busmap_area])
+
+        return busmap, medoid_idx
+
+
 def run_spatial_clustering(self):
     """
     Main method for running spatial clustering on the electrical network.
@@ -1091,17 +1134,11 @@ def run_spatial_clustering(self):
                 busmap_elec = kmean_clustering(
                     self, elec_network, weight, n_clusters
                 )
-                busmap_area = kmean_clustering(
-                    self,
-                    network_area,
-                    weight_area,
-                    self.args["network_clustering"]["cluster_exclusion_area"],
-                )
-                busmap_area = (
-                    busmap_area.astype(int) + busmap_elec.apply(int).max() + 1
-                ).apply(str)
-                busmap = pd.concat([busmap_elec, busmap_area])
                 medoid_idx = pd.Series(dtype=str)
+                busmap, medoid_idx = include_busmap_area(
+                    self, busmap_elec, medoid_idx, network_area, weight_area
+                )
+
             else:
                 busmap = pd.Series(dtype=str)
                 medoid_idx = pd.Series(dtype=str)
@@ -1110,32 +1147,17 @@ def run_spatial_clustering(self):
             if not self.args["network_clustering"]["k_elec_busmap"]:
                 logger.info("Start k-medoids Dijkstra Clustering")
 
-                busmap_elec, medoid_idx_elec = kmedoids_dijkstra_clustering(
+                busmap_elec, medoid_idx = kmedoids_dijkstra_clustering(
                     self,
                     elec_network.buses,
                     elec_network.lines,
                     weight,
                     n_clusters,
                 )
 
-                busmap_area, medoid_idx_area = kmedoids_dijkstra_clustering(
-                    self,
-                    network_area.buses,
-                    network_area.lines,
-                    weight_area,
-                    self.args["network_clustering"]["cluster_exclusion_area"],
-                )
-
-                medoid_idx_area.index = (
-                    medoid_idx_area.index.astype(int)
-                    + busmap_elec.apply(int).max()
-                    + 1
+                busmap, medoid_idx = include_busmap_area(
+                    self, busmap_elec, medoid_idx, network_area, weight_area
                 )
-                busmap_area = (
-                    busmap_area.astype(int) + busmap_elec.apply(int).max() + 1
-                ).apply(str)
-                busmap = pd.concat([busmap_elec, busmap_area])
-                medoid_idx = pd.concat([medoid_idx_elec, medoid_idx_area])
 
             else:
                 busmap = pd.Series(dtype=str)

etrago/cluster/spatial.py

@@ -779,20 +779,20 @@ def find_buses_area(etrago, carrier):
     """
     settings = etrago.args["network_clustering"]
 
-    if settings["exclusion_area"]:
-        if isinstance(settings["exclusion_area"], list):
+    if settings["interest_area"]:
+        if isinstance(settings["interest_area"], list):
             con = etrago.engine
             query = "SELECT gen, geometry FROM boundaries.vg250_krs"
 
             de_areas = gpd.read_postgis(query, con, geom_col="geometry")
             de_areas = de_areas[
-                de_areas["gen"].isin(settings["exclusion_area"])
+                de_areas["gen"].isin(settings["interest_area"])
             ]
-        elif isinstance(settings["exclusion_area"], str):
-            de_areas = gpd.read_file(settings["exclusion_area"])
+        elif isinstance(settings["interest_area"], str):
+            de_areas = gpd.read_file(settings["interest_area"])
         else:
             raise Exception(
-                "not supported format supplied to 'exclusion_area' argument"
+                "not supported format supplied to 'interest_area' argument"
             )
 
         try: