Merge pull request #900 from scud-soptim/generic_branch_examples

Generic branch examples

Author: TonyXiang8787

docs/examples/Generic Branch Example.ipynb

@@ -175,24 +175,24 @@
     "\"\"\"\n",
     "\n",
     "\n",
-    "# Spannungsebenen des Transformators\n",
+    "# Voltage levels of the transformer\n",
     "u_rated = {\"HV\": 200e3, \"MV\": 150e3, \"LV\": 30.2e3, \"AUX\": 200e3, \"Station1\": 150e3, \"Source\": 200e3}\n",
     "\n",
-    "# Eingespeiste Leistung (200 kV) auf der 380 kV Seite\n",
+    "# Injected power (200 kV) on the 380 kV side\n",
     "source_voltage = u_rated[\"Source\"]  # 200 kV\n",
     "source_power = 1e40  # hohe  Kurzschlussleistung -> v_pu = 1.0\n",
     "\n",
-    "# Lasten\n",
+    "# Loads\n",
     "load_MV = {\"P\": 30e6, \"Q\": 5e6}\n",
     "load_LV = {\"P\": 1.5e6, \"Q\": 0.15e6}  # Eigenbedarf\n",
     "\n",
-    "# Zuweisung der Knotennummern\n",
+    "# Assignment of node numbers\n",
     "nodes = {\"HV\": 1, \"MV\": 2, \"LV\": 3, \"AUX\": 4, \"Station1\": 11, \"Source\": 14}\n",
     "non = len(nodes)  # number of nodes\n",
     "# tap-changer\n",
     "v_tap = 6.0e3\n",
     "\n",
-    "# Generiere Knoten\n",
+    "# generated nodes\n",
     "node_data = initialize_array(DatasetType.input, ComponentType.node, non)\n",
     "node_data[\"id\"] = list(nodes.values())\n",
     "node_data[\"u_rated\"] = list(u_rated.values())\n",
@@ -202,15 +202,15 @@
     "\n",
     "# node_data[\"u_rated\"] = [u_rated['HV'], u_rated['MV'], u_rated['LV'], u_rated['AUX'],u_rated['Station1'] ]\n",
     "\n",
-    "# Quelle auf der 380kV-Seite (Slack)\n",
+    "# Slack\n",
     "source_data = initialize_array(DatasetType.input, ComponentType.source, 1)\n",
     "source_data[\"id\"] = [5]\n",
     "source_data[\"node\"] = [nodes[\"Source\"]]\n",
     "source_data[\"status\"] = [1]\n",
     "source_data[\"u_ref\"] = [1.0]\n",
     "source_data[\"sk\"] = [source_power]\n",
     "\n",
-    "# Last auf der 110kV-Seite\n",
+    "# Loads 110kV\n",
     "load_data = initialize_array(DatasetType.input, ComponentType.sym_load, 2)\n",
     "load_data[\"id\"] = [6, 7]\n",
     "load_data[\"type\"] = [LoadGenType.const_power, LoadGenType.const_power]\n",
@@ -222,10 +222,10 @@
     "node_name = [\"HV\", \"MV\", \"LV\", \"AUX\", \"Station1\", \"Source\"]\n",
     "branch_name = [\"BHV\", \"BMV\", \"BLV\", \"BLine2\", \"BLine1\"]\n",
     "\n",
-    "# Generic Branch für jeden der zwei Wickler\n",
+    "\n",
     "branch_data = initialize_array(DatasetType.input, ComponentType.generic_branch, 5)\n",
     "\n",
-    "# Verbindungen der zwei Wickler\n",
+    "\n",
     "branch_data[\"id\"] = [8, 9, 10, 12, 13]\n",
     "branch_data[\"from_node\"] = [nodes[\"HV\"], nodes[\"AUX\"], nodes[\"AUX\"], nodes[\"MV\"], nodes[\"Source\"]]\n",
     "branch_data[\"to_node\"] = [nodes[\"AUX\"], nodes[\"MV\"], nodes[\"LV\"], nodes[\"Station1\"], nodes[\"HV\"]]\n",
@@ -241,18 +241,17 @@
     "branch_data[\"theta\"] = [0.0, 0.0, 0.0, 0.0, 0.0]\n",
     "branch_data[\"sn\"] = [450e6, 450e6, 100e6, 100e6, 450e6]\n",
     "\n",
-    "# Input-Daten sammeln\n",
     "input_data = {\n",
     "    ComponentType.node: node_data,\n",
     "    ComponentType.source: source_data,\n",
     "    ComponentType.sym_load: load_data,\n",
     "    ComponentType.generic_branch: branch_data,\n",
     "}\n",
     "\n",
-    "# Überprüfung der Eingabedaten\n",
+    "\n",
     "assert_valid_input_data(input_data=input_data, calculation_type=CalculationType.power_flow)\n",
     "\n",
-    "# Power-Flow Modell erstellen und Berechnungen durchführen\n",
+    "\n",
     "model = PowerGridModel(input_data)\n",
     "output_data = model.calculate_power_flow(\n",
     "    symmetric=True, error_tolerance=1e-8, max_iterations=20, calculation_method=CalculationMethod.newton_raphson\n",
@@ -370,11 +369,10 @@
     "    genb_out = output_data[ComponentType.generic_branch]\n",
     "    df = pd.DataFrame(genb_out)\n",
     "\n",
-    "    # Summiere die aktive und reaktive Leistung über alle Branches hinweg\n",
+    "    # Sum up the active and reactive performance across all branches\n",
     "    P_total = e6(df[\"p_from\"].sum()) + e6(df[\"p_to\"].sum())\n",
     "    Q_total = e6(df[\"q_from\"].sum()) + e6(df[\"q_to\"].sum())\n",
     "\n",
-    "    # Ausgabe der Gesamtsummen\n",
     "    print(\"\\nTotal Power for all Branches\")\n",
     "    print(\"----------------------------\")\n",
     "    print(f\"Total Active Power (P_total): {P_total:.2f} MW\")\n",
@@ -394,8 +392,6 @@
     "print_load_input(input_data)\n",
     "print_source_input(input_data)\n",
     "\n",
-    "\n",
-    "# Ausgabe der Spannungen und Ströme\n",
     "print(\"========================================\")\n",
     "print(\"   Output Data\")\n",
     "print(\"========================================\")\n",
@@ -754,11 +750,10 @@
     "    genb_out = output_data[ComponentType.generic_branch]\n",
     "    df = pd.DataFrame(genb_out)\n",
     "\n",
-    "    # Summiere die aktive und reaktive Leistung über alle Branches hinweg\n",
+    "    #  Sum up the active and reactive performance across all branches\n",
     "    P_total = e6(df[\"p_from\"].sum()) + e6(df[\"p_to\"].sum())\n",
     "    Q_total = e6(df[\"q_from\"].sum()) + e6(df[\"q_to\"].sum())\n",
     "\n",
-    "    # Ausgabe der Gesamtsummen\n",
     "    print(\"\\nTotal Power for all Branches\")\n",
     "    print(\"----------------------------\")\n",
     "    print(f\"Total Active Power (P_total): {P_total:.2f} MW\")\n",

docs/index.md

@@ -93,6 +93,7 @@ examples/Validation Examples.ipynb
 examples/Make Test Dataset.ipynb
 examples/Asymmetric Calculation Example.ipynb
 examples/Transformer Examples.ipynb
+examples/Generic Branch Example.ipynb
 ```
 
 ```{toctree}