read electricity data locally

draw.py

@@ -35,7 +35,6 @@ def draw_results(results, filename, title_benefit, annot_benefit=False, figure_s
     new_Data = pd.DataFrame(index=[df.index[-1] + 1], columns=df.columns)
     for i in df.columns:
         new_Data[i] = df[i].iloc[-1]
-    # print(new_Data)
     df = pd.concat([df, new_Data])
 
     X, Y = np.meshgrid(np.arange(df.shape[1]), np.arange(df.shape[0]))
@@ -68,7 +67,6 @@ def draw_cost(costs, filename, title_cost, annot_cost=False, figure_size=(10, 10
     new_Data = pd.DataFrame(index=[df.index[-1] + 1], columns=df.columns)
     for i in df.columns:
         new_Data[i] = df[i].iloc[-1]
-    # print(new_Data)
     df = pd.concat([df, new_Data])
     X, Y = np.meshgrid(np.arange(df.shape[1]), np.arange(df.shape[0]))
 
@@ -98,7 +96,6 @@ def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure
     df.columns = df.columns.map(int)
     min_value = df.min().min()
     max_value = df.max().max()
-    # max_scale = max(abs(min_value/1000), abs(max_value/1000))
 
 
     df[df.columns[-1] + 1] = df.iloc[:, -1] 
@@ -132,6 +129,41 @@ def draw_overload(overload_cnt, filename, title_unmet, annot_unmet=False, figure
     plt.ylabel('PV Capacity (MW)')
     plt.savefig(filename)
 
+with open('config.json', 'r') as f:
+    js_data = json.load(f)
+
+data = pd.read_csv('combined_data.csv')
+time_interval = js_data["time_interval"]["numerator"] / js_data["time_interval"]["denominator"]
+
+pv_loss = js_data["pv"]["loss"]
+pv_cost_per_kW = js_data["pv"]["cost_per_kW"]
+pv_lifetime = js_data["pv"]["lifetime"]
+
+ess_loss = js_data["ess"]["loss"]
+ess_cost_per_kW = js_data["ess"]["cost_per_kW"]
+ess_lifetime = js_data["ess"]["lifetime"]
+
+grid_loss = js_data["grid"]["loss"]
+sell_price = js_data["grid"]["sell_price"]
+grid_capacity = js_data["grid"]["capacity"]
+
+pv_begin = js_data["pv_capacities"]["begin"]
+pv_end = js_data["pv_capacities"]["end"]
+pv_groups = js_data["pv_capacities"]["groups"]
+
+ess_begin = js_data["ess_capacities"]["begin"]
+ess_end = js_data["ess_capacities"]["end"]
+ess_groups = js_data["ess_capacities"]["groups"]
+
+annot_unmet = js_data["annotated"]["unmet_prob"]
+annot_benefit = js_data["annotated"]["benefit"]
+annot_cost = js_data["annotated"]["cost"]
+
+title_unmet = js_data["plot_title"]["unmet_prob"]
+title_cost = js_data["plot_title"]["cost"]
+title_benefit = js_data["plot_title"]["benefit"]
+
+figure_size = (js_data["figure_size"]["length"], js_data["figure_size"]["height"])
 
 directory = 'data/'
 
@@ -143,9 +175,9 @@ split_files = [f.split('-') for f in file_list]
 costs_files = [f for f in split_files if f[-1].endswith('costs.json')]
 print(f'find costs files: {costs_files}')
 overload_files = [f for f in split_files if f[-1].endswith('overload_cnt.json')]
-print(f'find overload files: {overload_files}')
+print(f'find coverage/unmet files: {overload_files}')
 results_files = [f for f in split_files if f[-1].endswith('results.json')]
-print(f'find results files: {results_files}')
+print(f'find profit/benefit files: {results_files}')
 
 costs_dfs = [read_data(directory + '-'.join(f)) for f in costs_files]
 overload_dfs = [read_data(directory + '-'.join(f)) for f in overload_files]
@@ -154,17 +186,19 @@ results_dfs = [read_data(directory + '-'.join(f)) for f in results_files]
 for costs_df, overload_df, results_df in zip(costs_dfs, overload_dfs, results_dfs):
 
     draw_cost(costs_df, 
-              f'plots/costs-{int(costs_df.columns[-1])}-pv-{int(costs_df.index[-1])}.png', 
-              f'Costs for ESS-{int(costs_df.columns[-1])}-pv-{int(costs_df.index[-1])}MWh', annot_cost=False)
+              f'plots/costs-ess-{int(costs_df.columns[0])}-{int(costs_df.columns[-1])}-pv-{int(costs_df.index[0])}-{int(costs_df.index[-1])}.png', 
+              title_cost=title_cost, 
+              annot_cost=annot_cost)
 
     draw_overload(overload_df, 
-                  f'plots/overload-ess-{overload_df.columns[-1]}-pv-{overload_df.index[-1]}.png', 
-                  f'Overload for ess-{overload_df.columns[-1]}MW pv-{overload_df.index[-1]}MWh', 
+                  f'plots/overload-ess-{overload_df.columns[0]}-{overload_df.columns[-1]}-pv-{overload_df.index[0]}-{overload_df.index[-1]}.png', 
+                  title_unmet=title_unmet, 
                   annot_unmet=False)
 
     draw_results(results_df, 
-                 f'plots/results-{results_df.columns[-1]}-pv-{results_df.index[-1]}.png', 
-                 f'Results for ess-{results_df.columns[-1]}MW pv-{results_df.index[-1]}MWh', annot_benefit=False)
+                 f'plots/results-ess-{results_df.columns[0]}-{results_df.columns[-1]}-pv-{results_df.index[0]}-{results_df.index[-1]}.png', 
+                 title_benefit=title_benefit,
+                 annot_benefit=False)
 
 
 

main.py

@@ -111,7 +111,7 @@ def cal_profit(es: EnergySystem, saved_money):
 for ess_capacity in ess_capacities:
     print(f"ess_capacity:{ess_capacity}")
     for pv_capacity in pv_capacities:
-        print(f"pv_capacity:{ess_capacity}")
+        print(f"pv_capacity:{pv_capacity}")
         pv = pv_config(capacity=pv_capacity, 
                         cost_per_kW=pv_cost_per_kW,
                         lifetime=pv_lifetime, 

read_data.py

@@ -4,6 +4,7 @@ import csv
 
 sunlight_file_name = 'lightintensity.xlsx'
 factory_demand_file_name = 'factory_power1.xlsx'
+electricity_price_data = 'electricity_price_data.csv'
 
 df_sunlight = pd.read_excel(sunlight_file_name, header=None, names=['SunlightIntensity'])
 
@@ -25,20 +26,31 @@ print(df_power.head())
 
 df_combined = df_sunlight_resampled.join(df_power)
 
+
 df_combined.to_csv('combined_data.csv', index=True, index_label='Time')
 
-price_data = np.random.uniform(0.3, 0.3, len(times))
+def read_csv(file_path):
+    return pd.read_csv(file_path, index_col='Time', usecols=['Time', 'ElectricityPrice'])
+
+# price_data = np.random.uniform(0.3, 0.3, len(times))
 
 # 创建DataFrame
-price_df = pd.DataFrame(data={'Time': times, 'ElectricityPrice': price_data})
+price_df = read_csv(electricity_price_data)
+price_df.index = pd.to_datetime(price_df.index)
+price_df = price_df.reindex(df_combined.index)
 
-price_df.set_index('Time', inplace=True)
+# price_df.set_index('Time', inplace=True)
 
 # 保存到CSV文件
-price_df.to_csv('electricity_price_data.csv', index=True)
-print(price_df.head())
+# price_df.to_csv('electricity_price_data.csv', index=True)
+print("price____")
+print(price_df.index)
+print("df_combined____")
+print(df_combined.index)
+
 print("Electricity price data generated and saved.")
 
+
 df_combined2 = df_combined.join(price_df)
 print(df_combined2.head())
 # 保存结果