feat: 优化回路数计算逻辑，提升报表准确性

.vscode/launch.json

@@ -0,0 +1,16 @@
+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Python Debugger: Current File with Arguments",
+      "type": "debugpy",
+      "request": "launch",
+      "program": "main.py",
+      "console": "integratedTerminal",
+      "args": "--excel abc.xlsx"
+    },
+  ]
+}

gui.py

@@ -781,8 +781,12 @@ def index():
                     total_length_m = sum(d["length"] for d in res["eval"]["details"])
                     total_length_km = total_length_m / 1000
 
+                    # 获取回路数 (通过统计从升压站发出的连接)
+                    n_circuits = sum(1 for d in res["eval"]["details"] if d["source"] == "substation" or d["target"] == "substation")
+
                     row_dict = {
                         "name": name_display,
+                        "n_circuits": n_circuits,
                         "cost_wan": f"{res['cost'] / 10000:.2f}",
                         "loss_kw": f"{res['loss']:.2f}",
                         "total_length": f"{total_length_km:.2f}",
@@ -938,6 +942,12 @@ def index():
                             "required": True,
                             "align": "left",
                         },
+                        {
+                            "name": "n_circuits",
+                            "label": "回路数",
+                            "field": "n_circuits",
+                            "sortable": True,
+                        },
                         {
                             "name": "cost_wan",
                             "label": "总投资 (万元)",

main.py

@@ -655,38 +655,20 @@ def design_with_rotational_sweep(
     return final_connections, turbines
 
 
-def get_max_cable_capacity_mw(
+# 4. 获取电缆最大容量(MW)
-    cable_specs=None, voltage=VOLTAGE_LEVEL, power_factor=POWER_FACTOR
+def get_max_cable_capacity_mw(cable_specs, voltage=VOLTAGE_LEVEL, power_factor=POWER_FACTOR):
-):
     """
-    计算给定电缆规格中能够承载的最大功率 (单位: MW)。
+    根据电缆规格计算最大承载功率
-
+    :param cable_specs: 电缆规格列表 list of tuples，或者直接是最大功率数值(MW)
-    基于提供的电缆规格列表，选取最大载流量，结合系统电压和功率因数计算理论最大传输功率。
-
-    参数:
-        cable_specs (list, optional): 电缆规格列表。每个元素应包含 (截面积, 额定电流, 单价, 损耗系数)。
-        voltage (float): 系统电压 (V), 默认 66000
-        power_factor (float): 功率因数, 默认 0.95
-
-    返回:
-        float: 最大功率承载能力 (MW)。
-
-    异常:
-        Exception: 当未提供 cable_specs 时抛出，提示截面不满足。
     """
-    if cable_specs is None:
+    # 如果传入的已经是数值，直接返回
-        # Default cable specs if not provided (same as in evaluate_design)
+    if isinstance(cable_specs, (int, float, np.number)):
-        cable_specs = [
+        return float(cable_specs)
-            (35, 150, 0.524, 80),
+
-            (70, 215, 0.268, 120),
+    # 兼容性检查：如果列表为空
-            (95, 260, 0.193, 150),
+    if not cable_specs:
-            (120, 295, 0.153, 180),
+        print("Warning: 没有可用的电缆规格，使用默认最大容量 100MW")
-            (150, 330, 0.124, 220),
+        return 100.0
-            (185, 370, 0.0991, 270),
-            (240, 425, 0.0754, 350),
-            (300, 500, 0.0601, 450),
-            (400, 580, 0.0470, 600),
-        ]
 
     # 从所有电缆规格中找到最大的额定电流容量
     max_current_capacity = max(spec[1] for spec in cable_specs)
@@ -1009,10 +991,12 @@ def export_to_excel(connections_details, filename):
     df = pd.DataFrame(data)
 
     # 汇总统计
+    n_circuits = sum(1 for conn in connections_details if conn["source"] == "substation" or conn["target"] == "substation")
     summary = {
         "Total Cost (¥)": df["Cost (¥)"].sum(),
         "Total Effective Length (m)": df["Effective Length (m)"].sum(),
         "Total Vertical Length (m)": df["Vertical Length (m)"].sum(),
+        "Number of Circuits": n_circuits,
     }
     summary_df = pd.DataFrame([summary])
 
@@ -1038,15 +1022,14 @@ def export_all_scenarios_to_excel(results, filename):
             # 1. 总览 Sheet
             summary_data = []
             for res in results:
-                # 获取回路数
+                # 获取回路数 (通过统计从升压站发出的连接)
-                n_circuits = 0
+                n_circuits = sum(1 for conn in res["eval"]["details"] if conn["source"] == "substation" or conn["target"] == "substation")
-                if "turbines" in res and "cluster" in res["turbines"].columns:
-                    n_circuits = res["turbines"]["cluster"].nunique()
 
                 summary_data.append(
                     {
                         "Scenario": res["name"],
                         "Total Cost (¥)": res["cost"],
+                        "总费用(万元)": res.get("total_cost_npv", res["cost"]) / 10000,
                         "Total Loss (kW)": res["loss"],
                         "Num Circuits": n_circuits,
                         # 计算电缆统计
@@ -1413,14 +1396,10 @@ def compare_design_methods(
 
         print(f"  最大电缆容量: {max_cable_mw:.2f} MW")
 
-        # --- Run 1: Base Algorithm (Capacitated Sweep) ---
+        # --- Run 1: Base Sector Sweep ---
         base_name = f"{name} (Base)"
         conns_base, turbines_base = design_with_capacitated_sweep(
-            turbines.copy(),
+            turbines.copy(), substation, max_cable_mw, voltage=voltage
-            substation,
-            cable_specs=current_specs,
-            voltage=voltage,
-            power_factor=power_factor,
         )
         eval_base = evaluate_design(
             turbines,
@@ -1432,7 +1411,7 @@ def compare_design_methods(
             voltage=voltage,
             power_factor=power_factor,
         )
-
+        n_circuits_base = sum(1 for d in eval_base["details"] if d["source"] == "substation" or d["target"] == "substation")
         comparison_results.append(
             {
                 "name": base_name,
@@ -1444,17 +1423,13 @@ def compare_design_methods(
             }
         )
         print(
-            f"  [Base]       Cost: ¥{eval_base['total_cost']:,.2f} | Loss: {eval_base['total_loss']:.2f} kW"
+            f"  [Base] Cost: ¥{eval_base['total_cost']:,.2f} | Loss: {eval_base['total_loss']:.2f} kW | Circuits: {n_circuits_base}"
         )
 
-        # --- Run 2: Rotational Algorithm (Optimization) ---
+        # --- Run 2: Rotational Sweep (Optimization) ---
         rot_name = f"{name} (Rotational)"
         conns_rot, turbines_rot = design_with_rotational_sweep(
-            turbines.copy(),
+            turbines.copy(), substation, max_cable_mw, voltage=voltage
-            substation,
-            cable_specs=current_specs,
-            voltage=voltage,
-            power_factor=power_factor,
         )
         eval_rot = evaluate_design(
             turbines,
@@ -1466,7 +1441,7 @@ def compare_design_methods(
             voltage=voltage,
             power_factor=power_factor,
         )
-
+        n_circuits_rot = sum(1 for d in eval_rot["details"] if d["source"] == "substation" or d["target"] == "substation")
         comparison_results.append(
             {
                 "name": rot_name,
@@ -1478,7 +1453,7 @@ def compare_design_methods(
             }
         )
         print(
-            f"  [Rotational] Cost: ¥{eval_rot['total_cost']:,.2f} | Loss: {eval_rot['total_loss']:.2f} kW"
+            f"  [Rotational] Cost: ¥{eval_rot['total_cost']:,.2f} | Loss: {eval_rot['total_loss']:.2f} kW | Circuits: {n_circuits_rot}"
         )
 
         # --- Run 3: Esau-Williams Algorithm ---
@@ -1496,7 +1471,7 @@ def compare_design_methods(
             voltage=voltage,
             power_factor=power_factor,
         )
-
+        n_circuits_ew = sum(1 for d in eval_ew["details"] if d["source"] == "substation" or d["target"] == "substation")
         comparison_results.append(
             {
                 "name": ew_name,
@@ -1508,7 +1483,7 @@ def compare_design_methods(
             }
         )
         print(
-            f"  [Esau-Williams] Cost: ¥{eval_ew['total_cost']:,.2f} | Loss: {eval_ew['total_loss']:.2f} kW"
+            f"  [Esau-Williams] Cost: ¥{eval_ew['total_cost']:,.2f} | Loss: {eval_ew['total_loss']:.2f} kW | Circuits: {n_circuits_ew}"
         )
 
         # 记录最佳
@@ -1525,7 +1500,7 @@ def compare_design_methods(
         # 可视化 (只画 Base 版本)
         ax_idx = i + 1
         if plot_results and ax_idx < 4:
-            n_circuits = turbines_base["cluster"].nunique()
+            n_circuits = sum(1 for d in eval_base["details"] if d["source"] == "substation" or d["target"] == "substation")
             title = f"{base_name} ({n_circuits} circuits)\nCost: ¥{eval_base['total_cost'] / 10000:.2f}万"
             visualize_design(
                 turbines_base, substation, eval_base["details"], title, ax=axes[ax_idx]
@@ -1565,7 +1540,11 @@ def compare_design_methods(
         for i, res in enumerate(comparison_results):
             if res["cost"] < comparison_results[best_idx]["cost"]:
                 best_idx = i
-            print(f"  {i + 1}. {res['name']} - Cost: ¥{res['cost']:,.2f}")
+            
+            # 获取回路数 (通过统计从升压站发出的连接)
+            n_circuits = sum(1 for conn in res["eval"]["details"] if conn["source"] == "substation" or conn["target"] == "substation")
+            
+            print(f"  {i + 1}. {res['name']} - Cost: ¥{res['cost']:,.2f} | Circuits: {n_circuits}")
 
         print(f"推荐方案: {comparison_results[best_idx]['name']} (默认)")