Create app.py

app.py

@@ -0,0 +1,39 @@
+import streamlit as st
+import pandas as pd
+import math
+
+def calculate_solar_requirements(load_profile, panel_rating, sunlight_hours):
+    total_load = sum(load_profile)
+    energy_needed = total_load / 0.85  # Considering 85% efficiency
+    panels_needed = math.ceil(energy_needed / (panel_rating * sunlight_hours))
+    return total_load, energy_needed, panels_needed
+
+def main():
+    st.title("Solar Power Plant Load Calculation")
+
+    st.sidebar.header("Input Parameters")
+    
+    # User inputs
+    num_devices = st.sidebar.number_input("Number of Devices", min_value=1, value=3)
+    load_profile = []
+
+    for i in range(num_devices):
+        load = st.sidebar.number_input(f"Load of device {i+1} (Watts)", min_value=1, value=100)
+        hours = st.sidebar.number_input(f"Operating hours of device {i+1} (per day)", min_value=1, value=6)
+        load_profile.append(load * hours)
+
+    panel_rating = st.sidebar.number_input("Solar Panel Rating (Watts)", min_value=50, value=400)
+    sunlight_hours = st.sidebar.number_input("Average Sunlight Hours per Day", min_value=1.0, value=5.0)
+
+    if st.sidebar.button("Calculate"):
+        total_load, energy_needed, panels_needed = calculate_solar_requirements(load_profile, panel_rating, sunlight_hours)
+
+        st.subheader("Calculation Results")
+        st.write(f"**Total Daily Load:** {total_load:.2f} Watt-hours")
+        st.write(f"**Energy Needed (with Efficiency Consideration):** {energy_needed:.2f} Watt-hours")
+        st.write(f"**Number of Solar Panels Required:** {panels_needed}")
+
+        st.subheader("Device Load Details")
+        device_data = pd.DataFrame({
+            "Device": [f"Device {i+1}" for i in range(num_devices)],
+            "Load (Watts)": [load_profile[i] // hours for i, hours in enumerate([load_profile[i] / load_profile[i] ** 0] [i **.]}