Update app.py

app.py

@@ -176,12 +176,15 @@ st.markdown("""
 This application is designed to help researchers and policymakers explore and optimize renewable energy systems for a specified region. By inputting cost parameters for different renewable energy sources and energy storage systems, the application determines the optimal mix of resources to meet energy demand while minimizing cost.
 The optimization problem is solved using linear programming, ensuring a balance between supply and demand, and incorporating battery energy storage to manage intermittency issues inherent in renewable energy.
 The visualizations provided help to better understand how different energy sources contribute to the overall power supply, how energy storage systems are utilized, and the impact of cost variations on energy prices.
+- Data : [Japan energy database](https://energy-sustainability.jp/)
+- Method: [An Analysis of the Effects in Allocation and Load Shifting of Data Centers in Japanese Power System](https://jglobal.jst.go.jp/detail?JGLOBAL_ID=202302220123698562)
+
 """)
 
 # Sidebar input fields for user to provide parameters
 with st.sidebar:
     st.header('Input Parameters')
-    city_code = st.text_input("Enter City Code", value="")
+    city_code = st.text_input("Enter City Code", value=999999)
     solar_cost = st.number_input("Solar Capacity Cost (¥/MW)", value=80.0, help="Estimated average cost of solar capacity per MW")
     onshore_wind_cost = st.number_input("Onshore Wind Capacity Cost (¥/MW)", value=120.0, help="Estimated average cost of onshore wind capacity per MW")
     offshore_wind_cost = st.number_input("Offshore Wind Capacity Cost (¥/MW)", value=180.0, help="Estimated average cost of offshore wind capacity per MW")