Upload app.py

app.py

@@ -599,7 +599,7 @@ def page_model(): #, write_pickle_from_standard_excel, color_dict):
         df_production = plot_production(m, i_with_capacity, dt, color_dict, colb2, df)
         # df_price = plot_electricity_prices(m, dt, colb2, df)
         df_curtailment = plot_curtailment(m, iRes, color_dict, colb1, df)
-        df_residual_load_duration = plot_residual_load_duration(m, dt, colb1, df, D_t, i_with_capacity, iRes, color_dict, df_curtailment)
+        df_residual_load_duration = plot_residual_load_duration(m, dt, colb1, df, D_t, i_with_capacity, iRes, color_dict, df_curtailment, iConv)
         df_price = plot_electricity_prices(m, dt, colb2, df, df_residual_load_duration)
          
         df_contr_marg = plot_contribution_margin(m, dt, i_with_capacity, color_dict, colb1, df)
@@ -897,7 +897,7 @@ def plot_electricity_prices(m, dt, col, df, df_residual_load_duration):
     
     return df_price
 
-def plot_residual_load_duration(m, dt, col, df, D_t, i_with_capacity, iRes, color_dict, df_curtailment):
+def plot_residual_load_duration(m, dt, col, df, D_t, i_with_capacity, iRes, color_dict, df_curtailment, iConv):
     """
     Plots the residual load and corresponding production as a stacked area chart.
     Supports both German and English labels for the plot titles and axis labels.
@@ -961,9 +961,19 @@ def plot_residual_load_duration(m, dt, col, df, D_t, i_with_capacity, iRes, colo
 
     # Plotting with Plotly - Creating stacked area chart
     fig = go.Figure()
+    
+    # Sort technology_columns based on the highest index in df_sorted (only for iConv); others are placed at the end
+    sorted_technology_columns = sorted(
+        technology_columns,
+        key=lambda tech: (
+            tech not in iConv,  # Place non-iConv technologies at the end
+            -df_sorted[df_sorted[tech] != 0].index.max() if tech in iConv and not df_sorted[df_sorted[tech] != 0].empty else float('inf')
+        )
+    )
+
 
     # Add stacked area traces for each production technology with consistent colors and language-specific names
-    for tech in technology_columns:
+    for tech in sorted_technology_columns:
         tech_name = tech_mapping_en_to_de.get(tech, tech)  # Get the translated name or fallback to the original
         fig.add_trace(go.Scatter(
             x=df_sorted.index,