Update app.py

app.py

@@ -5,7 +5,7 @@ import pulp
 import plotly.graph_objs as go
 import plotly.express as px
 import numpy as np
-import matplotlib.pyplot as plt  # 修正：matplotlibのインポートを追加
+import matplotlib.pyplot as plt
 
 # Renewable energy data fetch function
 def get_renewable_energy_data(city_code):
@@ -29,7 +29,7 @@ def get_renewable_energy_data(city_code):
     return result_df, None
 
 # Optimize energy system and use MGA
-def optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wind_cost, river_cost, battery_cost, yearly_demand, solar_range, wind_range, river_range, offshore_wind_range, thresholds):
+def optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wind_cost, river_cost, battery_cost, yearly_demand, solar_range, wind_range, river_range, offshore_wind_range, thresholds, selected_tech):
     data, error = get_renewable_energy_data(city_code)
     if error:
         st.error(error)
@@ -104,12 +104,12 @@ def optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wi
     model.solve()
     optimal_cost = pulp.value(model.objective)
 
-    # MGA: Generate alternative solutions
+    # MGA: Generate alternative solutions for selected technologies only
     mga_models = []
     alternative_solutions = []
     for threshold in thresholds:
         relaxed_cost = optimal_cost * (1 + threshold)
-        for tech in technologies:
+        for tech in selected_tech:  # 選択された技術のみ実行
             # Minimize capacity of each technology
             alt_model_min = pulp.LpProblem(f"AlternativeModel_Min_{tech}_{threshold}", pulp.LpMinimize)
             alt_model_min += pulp.lpSum([renewable_capacity[(r, g)] * renewable_capacity_cost[g]
@@ -174,9 +174,12 @@ with st.sidebar:
     river_range = st.slider("River Capacity Range (MW)", 0, 10000, (0, 10000))
     thresholds = st.multiselect("Select MGA Cost Deviation Thresholds (%)", [0.5, 1, 2, 3, 5, 7.5, 10], default=[0.5, 1, 5])
 
+    # 技術の選択オプション
+    selected_technologies = st.multiselect("Select Technologies to Optimize", ['solar', 'onshore_wind', 'offshore_wind', 'river'], default=['solar', 'onshore_wind', 'offshore_wind', 'river'])
+
 if st.button("Run MGA Optimization"):
     # 実行して alternative_solutions を取得
-    alternative_solutions = optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wind_cost, river_cost, battery_cost, yearly_demand, solar_range, wind_range, river_range, offshore_wind_range, [t / 100 for t in thresholds])
+    alternative_solutions = optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wind_cost, river_cost, battery_cost, yearly_demand, solar_range, wind_range, river_range, offshore_wind_range, [t / 100 for t in thresholds], selected_technologies)
     
     if alternative_solutions:
         # 各しきい値ごとの最小と最大のバッテリー容量を収集