update comment

main.py

@@ -1,21 +1,71 @@
-import matplotlib
+import matplotlib.pyplot as plt
+import seaborn as sns
+import numpy as np
 import pandas as pd
 from EnergySystem import EnergySystem
 from config import pv_config, grid_config, ess_config
 
 
 if __name__ == '__main__':
-    price_schedule = pd.read_csv('price_schedule.csv')
-    data = pd.read_csv('simulation_data.csv')
-
-
-    pv = pv_config(capacity=100000,cost_per_kW=200,lifetime=25,loss=0.95)
-    ess = ess_config(capacity=100000,cost_per_kW=300,lifetime=25,loss=0.95,charge_power=100000,discharge_power=100000)
-    grid = grid_config(price_schedule=price_schedule, capacity=5000, grid_loss=0.95, sell_price=0.4)
-
-    energy_system = EnergySystem(pv_type=pv, ess_type=ess, grid_type=grid)
-
+    data = pd.read_csv('combined_data.csv')
     time_interval = 15 / 60
-    benefit = energy_system.simulate(data=data, time_interval=time_interval)
 
-    print(benefit)
+    pv_loss = 0.95
+    pv_cost_per_kW = 200
+    pv_base = 50000
+    pv_lifetime = 25
+
+    ess_loss = 0.95
+    ess_cost_per_kW = 300
+    ess_base = 50000
+    ess_lifetime = 25
+
+    grid_loss = 0.95
+    sell_price = 0.4 #kWh
+    grid_capacity = 5000 #kWh
+
+
+    pv_step=10000
+    ess_step=10000
+
+    pv_capacities = np.linspace(50000, 150000, 11)
+    ess_capacities = np.linspace(50000, 150000, 11)
+    results = pd.DataFrame(index=pv_capacities, columns = ess_capacities)
+    for pv_capacity in pv_capacities:
+        print(f"pv_capacity:{pv_capacity}")
+        for ess_capacity in ess_capacities:
+            print(f"ess_capacity:{ess_capacity}")
+            pv = pv_config(capacity=pv_capacity, 
+                           cost_per_kW=pv_cost_per_kW,
+                           lifetime=pv_lifetime, 
+                           loss=pv_loss)
+            ess = ess_config(capacity=ess_capacity, 
+                             cost_per_kW=ess_cost_per_kW, 
+                             lifetime=ess_lifetime, 
+                             loss=ess_loss,
+                             charge_power=ess_capacity,
+                             discharge_power=ess_capacity)
+            grid = grid_config(capacity=grid_capacity, 
+                               grid_loss=grid_loss,
+                               sell_price= sell_price)
+            energySystem = EnergySystem(pv_type=pv, 
+                                        ess_type=ess, 
+                                        grid_type= grid)
+            benefit = energySystem.simulate(data, time_interval)
+            results.loc[pv_capacity,ess_capacity] = benefit
+    results = results.astype(float)
+
+    plt.figure(figsize=(10, 8))  # 设置图形大小
+    sns.heatmap(results, annot=True, fmt=".1f", cmap='viridis')
+    plt.title('Benefit Heatmap Based on PV and ESS Capacities')
+    plt.xlabel('ESS Capacity (kWh)')
+    plt.ylabel('PV Capacity (kW)')
+    plt.show()
+
+    # pv = pv_config(capacity=100000,cost_per_kW=200,lifetime=25,loss=0.95)
+    # ess = ess_config(capacity=100000,cost_per_kW=300,lifetime=25,loss=0.95,charge_power=100000,discharge_power=100000)
+    # grid = grid_config(price_schedule=price_schedule, capacity=5000, grid_loss=0.95, sell_price=0.4)
+    # grid = grid_config(capacity=50000, grid_loss=0.95, sell_price=0.4)
+
+
+    # print(benefit)