Upload app.py

app.py

@@ -24,10 +24,25 @@ import streamlit as st
 
 # %%
 
-url_excel = r'Input_Jahr_2021.xlsx'
+#url_excel = r'Input_Jahr_2021.xlsx'
 url_excel = st.file_uploader(label = 'Excel Upload')
+if url_excel == None:
+    url_excel = r'Input_Jahr_2021.xlsx'
 
+# # %%
+# # Slider for gas price [€/MWh_th]
+price_gas = st.slider(value=10, min_value=0, max_value=400, label="Natural gas price [€/MWh]", step=10)
 
+# Slider for CO2 price [€/t]
+price_co2 = st.slider(value=80, min_value=0, max_value=400, label="CO2 price [€/t CO2eq]", step=10)
+
+# Slider for CO2 limit [mio. t]
+limit_co2 = st.slider(value=400, min_value=0, max_value=750, label="CO2 limit [mio. t]", step=50)
+
+# Slider for H2 price / usevalue [€/MWH_th]
+price_h2 = st.slider(value=100, min_value=0, max_value=300, label="Hydrogen price [€/MWh]", step=10)
+
+# %%
 
 # %% [markdown]
 #  Read Sets
@@ -62,8 +77,8 @@ iHyRes = pd.Index(df_excel.iloc[0:1,10], name = 'iHyRes')
 # %%
 ### Parameters
 # CO2 limit (from slider)
-l_co2 = limit_co2.value
-p_co2 = price_co2.value
+l_co2 = limit_co2
+p_co2 = price_co2
 
 # length of timesteps
 dt = 1
@@ -94,8 +109,8 @@ df_excel = df_excel.fillna(0)
 df_excel = df_excel.set_index('i')
 c_fuel_i = df_excel.iloc[:,0].to_xarray()
 # Apply slider value
-c_fuel_i.loc[dict(i = 'Fossil Gas')]  = price_gas.value
-c_fuel_i.loc[dict(i = 'H2')]  = price_h2.value
+c_fuel_i.loc[dict(i = 'Fossil Gas')]  = price_gas
+c_fuel_i.loc[dict(i = 'H2')]  = price_h2
 
 # Other var. costs
 df_excel = pd.read_excel(url_excel, sheet_name = 'OtherVarCosts')
@@ -186,7 +201,7 @@ m.add_objective(C_tot)
 
 ## Costs terms for objective function
 # Operational costs minus revenue for produced hydrogen
-C_op_sum = m.add_constraints((y * c_var_i * dt).sum() - ((y_ch.sel(i = iPtG) / eff_i.sel(i = iPtG)) * price_h2.value * dt).sum() == C_op, name = 'C_op_sum')
+C_op_sum = m.add_constraints((y * c_var_i * dt).sum() - ((y_ch.sel(i = iPtG) / eff_i.sel(i = iPtG)) * price_h2 * dt).sum() == C_op, name = 'C_op_sum')
 
 # Investment costs
 C_inv_sum = m.add_constraints((K * c_inv_i).sum() == C_inv, name = 'C_inv_sum')
@@ -222,18 +237,6 @@ m.solve(solver_name = 'highs')
 
 
 
-# %% [markdown]
-#  Results
-
-# %%
-
-# %%
-
-m.solve(solver_name = 'highs',presolve = 'off',run_crossover = 'off',solver = 'ipm')
-
-# %%
-#m.solve(solver_name = 'highs', solver = 'ipm', log_file = 'solverlog.txt',run_crossover = 'off' )
-
 # %%
 # Read Objective from solution
 m.objective_value
@@ -247,7 +250,7 @@ df
 
 # %%
 # Read values
-Productionlevels = m.solution['y'].sel(r = 'DE').to_dataframe().reset_index()
+Productionlevels = m.solution['y'].to_dataframe().reset_index()
 
 df = Productionlevels
 df
@@ -259,8 +262,3 @@ fig = px.line(df, x=df['t'], y=df['y'], color = df['i'])
 fig
 
 # %%
-
-
-
-
-#Productionlevels