Update app.py

app.py

@@ -210,10 +210,54 @@ def optimize_energy_system(city_code, solar_cost, onshore_wind_cost, offshore_wi
         yaxis=dict(showgrid=True, gridwidth=0.5, gridcolor='lightgray')
     )
 
-    # Perform sensitivity analysis immediately after optimization
-    fig_sensitivity = analyze_cost_sensitivity(renewable_capacity_cost, technologies, renewable_capacity)
+    return fig_energy, heatmaps, curtailment_values, SOC_normalized, fig_capacity_ranges, renewable_capacity
+
+# 資源コストの感度解析を行う関数
+def analyze_cost_sensitivity(renewable_capacity_cost, technologies, renewable_capacity):
+    # コストの変動範囲（0.5倍から1.5倍）
+    cost_multipliers = np.linspace(0.5, 1.5, 11)
+
+    # 結果を格納する辞書
+    sensitivity_results = {}
+
+    for tech in technologies:
+        # 各技術ごとのコスト変動に対する総コストの変化を計算
+        original_cost = renewable_capacity_cost[tech]
+        total_costs = []
+
+        for multiplier in cost_multipliers:
+            # コストを変更
+            modified_cost = original_cost * multiplier
+            # 総コスト = 変更後のコスト * 設備容量
+            total_cost = modified_cost * renewable_capacity[('region1', tech)].varValue
+            total_costs.append(total_cost)
+
+        # 技術ごとに結果を保存
+        sensitivity_results[tech] = total_costs
+
+    # 可視化
+    fig = go.Figure()
+
+    for tech, total_costs in sensitivity_results.items():
+        fig.add_trace(go.Scatter(
+            x=cost_multipliers,
+            y=total_costs,
+            mode='lines+markers',
+            name=f'{tech} Cost Sensitivity'
+        ))
+
+    # グラフのレイアウト
+    fig.update_layout(
+        title='Cost Sensitivity Analysis: Impact of Cost Changes on Total System Cost',
+        xaxis_title='Cost Multiplier (0.5x to 1.5x)',
+        yaxis_title='Total System Cost (￥)',
+        hovermode='x unified',
+        plot_bgcolor='white',
+        xaxis=dict(showgrid=True, gridwidth=0.5, gridcolor='lightgray'),
+        yaxis=dict(showgrid=True, gridwidth=0.5, gridcolor='lightgray')
+    )
 
-    return fig_energy, heatmaps, curtailment_values, SOC_normalized, fig_capacity_ranges, renewable_capacity, fig_sensitivity
+    return fig
 
 # Streamlit UI setup
 st.set_page_config(page_title='Renewable Energy System Optimization', layout='wide')
@@ -248,8 +292,10 @@ with st.sidebar:
     offshore_wind_range = st.slider("Offshore Wind Capacity Range (MW)", 0, 10000, (0, 10000))
     river_range = st.slider("River Capacity Range (MW)", 0, 10000, (0, 10000))
 
+calculated_optimal_energy_mix = False
+
 if st.button('Calculate Optimal Energy Mix'):
-    fig_energy, heatmaps, curtailment_values, soc_per_hour, fig_capacity_ranges, renewable_capacity, fig_sensitivity = optimize_energy_system(
+    fig_energy, heatmaps, curtailment_values, soc_per_hour, fig_capacity_ranges, renewable_capacity = 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
     )
     
@@ -277,6 +323,17 @@ if st.button('Calculate Optimal Energy Mix'):
         # Plot optimized capacity vs. capacity ranges
         st.plotly_chart(fig_capacity_ranges, use_container_width=True, height=800)
 
-        # Plot cost sensitivity analysis
-        st.markdown("### Cost Sensitivity Analysis")
-        st.plotly_chart(fig_sensitivity, use_container_width=True, height=800)
+        calculated_optimal_energy_mix = True
+
+# Streamlit UIに感度解析ボタンを追加
+if st.button('Analyze Cost Sensitivity'):
+    if calculated_optimal_energy_mix:
+        fig_sensitivity = analyze_cost_sensitivity({
+            'solar': solar_cost,
+            'onshore_wind': onshore_wind_cost,
+            'offshore_wind': offshore_wind_cost,
+            'river': river_cost
+        }, ['solar', 'onshore_wind', 'offshore_wind', 'river'], renewable_capacity)
+        st.plotly_chart(fig_sensitivity, use_container_width=True, height=800)
+    else:
+        st.error("Please calculate the optimal energy mix first before running the cost sensitivity analysis.")