Upload app.py

app.py

@@ -61,7 +61,7 @@ def timstep_aggregate(time_steps_aggregate, xr ):
 #sets_dict, params_dict= load_data_from_excel(url_excel, load_from_pickle_flag = False)
 
 
-dt = 6
+#dt = 6
 # Unpack sets_dict into the workspace
 t = sets_dict['t']
 i = sets_dict['i']
@@ -75,17 +75,14 @@ iHyRes = sets_dict['iHyRes']
 l_co2 = params_dict['l_co2']
 p_co2 = params_dict['p_co2']
 
-D_t = timstep_aggregate(dt,params_dict['D_t'])
 eff_i = params_dict['eff_i']
 c_fuel_i = params_dict['c_fuel_i']
 c_other_i = params_dict['c_other_i']
 c_inv_i = params_dict['c_inv_i']
 co2_factor_i = params_dict['co2_factor_i']
 #c_var_i = params_dict['c_var_i']
-s_t_r_iRes = timstep_aggregate(dt,params_dict['s_t_r_iRes'])
 K_0_i = params_dict['K_0_i']
 e2p_iSto = params_dict['e2p_iSto']
-h_t = timstep_aggregate(dt,params_dict['h_t'])
 
 t = D_t.get_index('t')
 partial_year_factor = (8760/len(t))/dt
@@ -106,6 +103,13 @@ with col2:
             if i_idx in ['Lignite']:
                 c_fuel_i.loc[i_idx] = st.slider(value=int(c_fuel_i.loc[i_idx]), min_value=0, max_value=300, label=i_idx + ' Price' , step=10)
 
+    dt = st.number_input(label="Insert length of timesteps", value=6, placeholder="Type an integer number...")
+
+# Aggregate time series
+D_t = timstep_aggregate(dt,params_dict['D_t'])
+s_t_r_iRes = timstep_aggregate(dt,params_dict['s_t_r_iRes'])
+h_t = timstep_aggregate(dt,params_dict['h_t'])
+
 with col3:
     # Slider for CO2 limit [mio. t]
     for i_idx in c_fuel_i.get_index('i'):