Update app.py

app.py

@@ -1,175 +1,109 @@
-# import streamlit as st
-# import pandas as pd
-# import plotly.express as px
-# from app_backend import fetch_weather, generate_synthetic_data, optimize_load
-
-# # Constants
-# API_KEY = "84e26811a314599e940f343b4d5894a7"
-# LOCATION = "Pakistan"
-
-# # Sidebar
-# st.sidebar.title("Smart Grid Dashboard")
-# location = st.sidebar.text_input("Enter Location", LOCATION)
-
-# # Fetch and display weather data
-# weather = fetch_weather(API_KEY, location)
-# if weather:
-#     st.sidebar.write(f"Temperature: {weather['temperature']} °C")
-#     st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
-#     st.sidebar.write(f"Weather: {weather['weather']}")
-
-# # Main dashboard with tabs
-# tabs = st.tabs(["Home", "Storage", "Trading"])
-
-# with tabs[0]:
-#     st.title("Real-Time Smart Grid Dashboard")
-
-#     # Generate synthetic data
-#     data = generate_synthetic_data()
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+from app_backend import fetch_weather, generate_synthetic_data, optimize_load
 
-#     # Plot total consumption, grid generation, and storage usage
-#     fig = px.line(data, x="timestamp", y=["total_consumption_kwh", "grid_generation_kwh", "storage_usage_kwh"],
-#                   title="Energy Consumption, Generation, and Storage Usage Over Time",
-#                   labels={"value": "Energy (kWh)", "variable": "Energy Source"})
-#     st.plotly_chart(fig)
+# Constants
+API_KEY = "84e26811a314599e940f343b4d5894a7"
+LOCATION = "Pakistan"
 
-#     # Grid health overview
-#     st.subheader("Grid Health Overview")
-#     grid_health_counts = data["grid_health"].value_counts()
-#     st.bar_chart(grid_health_counts)
+# Sidebar
+st.sidebar.title("Smart Grid Dashboard")
+location = st.sidebar.text_input("Enter Location", LOCATION)
 
-#     # Optimization recommendations
-#     current_demand = data["total_consumption_kwh"].iloc[-1]
-#     current_solar = data["solar_output_kw"].iloc[-1]
-#     current_wind = data["wind_output_kw"].iloc[-1]
-#     recommendation = optimize_load(current_demand, current_solar, current_wind)
+# Fetch and display weather data
+weather = fetch_weather(API_KEY, location)
+if weather:
+    st.sidebar.write(f"Temperature: {weather['temperature']} °C")
+    st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
+    st.sidebar.write(f"Weather: {weather['weather']}")
 
-#     st.subheader("Recommendations")
-#     st.write(f"Current Load Demand: {current_demand} kWh")
-#     st.write(f"Solar Output: {current_solar} kW")
-#     st.write(f"Wind Output: {current_wind} kW")
-#     st.write(f"Recommendation: {recommendation}")
+# Main dashboard with tabs
+tabs = st.tabs(["Home", "Storage", "Trading"])
 
-# with tabs[1]:
-#     st.title("Energy Storage Overview")
+with tabs[0]:
+    st.title("Real-Time Smart Grid Dashboard")
 
-#     # Total energy stored
-#     total_storage = 500  # Example of total energy storage
-#     st.subheader(f"Total Energy Stored: {total_storage} kWh")
+    # Generate synthetic data
+    data = generate_synthetic_data()
 
-#     # Energy storage contribution from different sources
-#     st.subheader("Energy Storage Contributions")
-#     energy_sources = pd.DataFrame({
-#         "Source": ["Wind", "Solar", "Turbine"],
-#         "Energy (kW/min)": [5, 7, 10]
-#     })
-#     st.bar_chart(energy_sources.set_index("Source"))
+    # Plot total consumption, grid generation, and storage usage
+    fig = px.line(data, x="timestamp", y=["total_consumption_kwh", "grid_generation_kwh", "storage_usage_kwh"],
+                  title="Energy Consumption, Generation, and Storage Usage Over Time",
+                  labels={"value": "Energy (kWh)", "variable": "Energy Source"})
+    st.plotly_chart(fig)
 
-#     # Show energy storage status with a rounded circle
-#     st.subheader("Energy Storage Circle")
-#     st.markdown("Energy storage is a combination of contributions from different renewable sources.")
+    # Grid health overview
+    st.subheader("Grid Health Overview")
+    grid_health_counts = data["grid_health"].value_counts()
+    st.bar_chart(grid_health_counts)
 
-#     # Visualization of energy storage circle using Plotly
-#     storage_data = {
-#         "Source": ["Wind", "Solar", "Turbine"],
-#         "Energy": [5, 7, 10],
-#     }
-#     storage_df = pd.DataFrame(storage_data)
-#     fig = px.pie(storage_df, names="Source", values="Energy", title="Energy Storage Sources")
-#     st.plotly_chart(fig)
+    # Optimization recommendations
+    current_demand = data["total_consumption_kwh"].iloc[-1]
+    current_solar = data["solar_output_kw"].iloc[-1]
+    current_wind = data["wind_output_kw"].iloc[-1]
+    recommendation = optimize_load(current_demand, current_solar, current_wind)
 
-# with tabs[2]:
-#     st.title("Energy Trading Overview")
+    st.subheader("Recommendations")
+    st.write(f"Current Load Demand: {current_demand} kWh")
+    st.write(f"Solar Output: {current_solar} kW")
+    st.write(f"Wind Output: {current_wind} kW")
+    st.write(f"Recommendation: {recommendation}")
 
-#     # Energy cubes
-#     st.subheader("Energy Cubes Stored")
-#     energy_cubes = pd.DataFrame({
-#         "Country": ["China", "Sri Lanka", "Bangladesh"],
-#         "Energy (kWh)": [100, 200, 300],
-#         "Shareable": [True, True, False]
-#     })
+with tabs[1]:
+    st.title("Energy Storage Overview")
 
-#     # Displaying the energy cubes in a grid
-#     st.write("Stored energy can be shared with other countries.")
-#     st.dataframe(energy_cubes)
+    # Total energy stored
+    total_storage = 500  # Example of total energy storage
+    st.subheader(f"Total Energy Stored: {total_storage} kWh")
 
-#     # Visualization of energy that can be shared
-#     st.subheader("Energy Trading Visualization")
-#     st.markdown("The following energy amounts are available for sharing with different countries.")
-#     trading_fig = px.bar(energy_cubes, x="Country", y="Energy (kWh)", color="Shareable", title="Energy Trading")
-#     st.plotly_chart(trading_fig)
+    # Energy storage contribution from different sources
+    st.subheader("Energy Storage Contributions")
+    energy_sources = pd.DataFrame({
+        "Source": ["Wind", "Solar", "Turbine"],
+        "Energy (kW/min)": [5, 7, 10]
+    })
+    st.bar_chart(energy_sources.set_index("Source"))
 
+    # Show energy storage status with a rounded circle
+    st.subheader("Energy Storage Circle")
+    st.markdown("Energy storage is a combination of contributions from different renewable sources.")
 
+    # Visualization of energy storage circle using Plotly
+    storage_data = {
+        "Source": ["Wind", "Solar", "Turbine"],
+        "Energy": [5, 7, 10],
+    }
+    storage_df = pd.DataFrame(storage_data)
+    fig = px.pie(storage_df, names="Source", values="Energy", title="Energy Storage Sources")
+    st.plotly_chart(fig)
 
+with tabs[2]:
+    st.title("Energy Trading Overview")
 
+    # Energy cubes
+    st.subheader("Energy Cubes Stored")
+    energy_cubes = pd.DataFrame({
+        "Country": ["China", "Sri Lanka", "Bangladesh"],
+        "Energy (kWh)": [100, 200, 300],
+        "Shareable": [True, True, False]
+    })
 
+    # Displaying the energy cubes in a grid
+    st.write("Stored energy can be shared with other countries.")
+    st.dataframe(energy_cubes)
 
+    # Visualization of energy that can be shared
+    st.subheader("Energy Trading Visualization")
+    st.markdown("The following energy amounts are available for sharing with different countries.")
+    trading_fig = px.bar(energy_cubes, x="Country", y="Energy (kWh)", color="Shareable", title="Energy Trading")
+    st.plotly_chart(trading_fig)
 
 
 
 
 
-import streamlit as st
-import pandas as pd
-import plotly.express as px
-from app_backend import fetch_weather, generate_synthetic_data, optimize_load
 
-# Constants
-API_KEY = "84e26811a314599e940f343b4d5894a7"
-LOCATION = "Pakistan"
 
-# Sidebar
-st.sidebar.title("Smart Grid Dashboard")
-location = st.sidebar.text_input("Enter Location", LOCATION)
 
-# Fetch and display weather data
-weather = fetch_weather(API_KEY, location)
-if weather:
-    st.sidebar.write(f"Temperature: {weather['temperature']} °C")
-    st.sidebar.write(f"Wind Speed: {weather['wind_speed']} m/s")
-    st.sidebar.write(f"Weather: {weather['weather']}")
 
-# Main dashboard
-st.title("Real-Time Smart Grid Dashboard")
-
-# Generate synthetic data
-data = generate_synthetic_data()
-
-# Plot total power consumption (load demand) in MW
-fig = px.line(data, x="timestamp", y="load_demand_mw", title="Power Consumption (MW) Over Time")
-st.plotly_chart(fig)
-
-# Plot renewable energy generation in MW (solar + wind) on the graph
-fig = px.bar(
-    data,
-    x="timestamp",
-    y=["solar_output_mw", "wind_output_mw"],
-    title="Renewable Energy Generation (MW)",
-    labels={"value": "Power (MW)", "variable": "Energy Source"}
-)
-st.plotly_chart(fig)
-
-# Show battery storage in kWh
-fig = px.line(data, x="timestamp", y="battery_storage_kwh", title="Battery Storage (kWh) Over Time")
-st.plotly_chart(fig)
-
-# Grid health
-st.subheader("Grid Health Overview")
-grid_health_counts = data["grid_health"].value_counts()
-st.bar_chart(grid_health_counts)
-
-# Optimization recommendations
-current_demand = data["load_demand_mw"].iloc[-1]  # Load demand in MW
-current_solar = data["solar_output_mw"].iloc[-1]  # Solar output in MW
-current_wind = data["wind_output_mw"].iloc[-1]  # Wind output in MW
-recommendation = optimize_load(current_demand, current_solar, current_wind)
-
-st.subheader("Recommendations")
-st.write(f"Current Load Demand: {current_demand} MW")
-st.write(f"Solar Output: {current_solar} MW")
-st.write(f"Wind Output: {current_wind} MW")
-st.write(f"Recommendation: {recommendation}")
-
-# Electricity Trade Management Tab
-st.subheader("Electricity Trade Management")
-st.write("Manage energy trading here.")