Update app.py

app.py

@@ -1,8 +1,7 @@
 import streamlit as st
-from translate import Translator
-from pvlib import location, pvsystem
 import pandas as pd
 import numpy as np
+from translate import Translator
 
 # Translator setup
 def translate_text(text, lang_code):
@@ -29,76 +28,57 @@ lang_code = languages[selected_language]
 # App title
 st.title(translate_text("Solar System Designer", lang_code))
 
-# Solar panel selection
-solar_panel_capacity = 550  # Fixed for simplicity
-
-# Battery options
+# Battery efficiency
 battery_types = {"Lithium-Ion": 0.95, "Lead-Acid": 0.8}
 battery_choice = st.selectbox(translate_text("Select Battery Type", lang_code), options=battery_types.keys())
 battery_efficiency = battery_types[battery_choice]
 
-# Predefined appliances
-appliances = {
-    "LED Bulbs": 10,
-    "Fans": 60,
-    "LED TV": 80,
-    "Computers": 150,
-    "Refrigerator": 200,
-    "Washing Machine": 500,
-    "Water Pump": 750,
-    "Iron": 1000,
-    "Microwave Oven": 1200,
-    "Water Dispenser": 150,
-    "Geyser": 2000,
-    "Heater": 2000,
-    "Dishwasher": 1800,
-    "Inverter AC": 1500,
-    "Others": 0  # Custom power input
-}
+# Table for appliance selection
+st.subheader(translate_text("Appliances Input", lang_code))
+appliance_data = pd.DataFrame(columns=["Appliance", "Wattage (W)", "Hours per Day", "Quantity"])
+default_appliances = ["LED Bulb", "Fan", "Refrigerator", "Microwave Oven", "Water Pump", "Iron", "Inverter AC", "Others"]
 
-# Appliance selection and customization
-st.subheader(translate_text("Select Appliances", lang_code))
-selected_appliances = []
+# Appliance input table
+for appliance in default_appliances:
+    wattage = st.number_input(translate_text(f"{appliance} - Wattage:", lang_code), min_value=0, step=1, key=f"{appliance}_wattage")
+    hours = st.number_input(translate_text(f"{appliance} - Hours per Day:", lang_code), min_value=0, step=1, key=f"{appliance}_hours")
+    quantity = st.number_input(translate_text(f"{appliance} - Quantity:", lang_code), min_value=0, step=1, key=f"{appliance}_quantity")
+    if wattage > 0 and hours > 0 and quantity > 0:
+        appliance_data = pd.concat([appliance_data, pd.DataFrame([[appliance, wattage, hours, quantity]], columns=appliance_data.columns)], ignore_index=True)
 
-for appliance, power in appliances.items():
-    if appliance == "Others":
-        power = st.number_input(translate_text("Enter Power for Others (Watts):", lang_code), min_value=0)
-    hours = st.number_input(translate_text(f"Usage Hours for {appliance}:", lang_code), min_value=0, max_value=24, value=1)
-    if hours > 0:
-        selected_appliances.append({"name": appliance, "power": power, "hours": hours})
+if not appliance_data.empty:
+    st.write(translate_text("Selected Appliances", lang_code))
+    st.dataframe(appliance_data)
 
-if selected_appliances:
-    st.write(translate_text("Selected Appliances:", lang_code))
-    st.table(selected_appliances)
-
-# Calculate recommendations
+# System recommendations
 if st.button(translate_text("Calculate Recommendations", lang_code)):
-    total_load = sum(a["power"] * a["hours"] for a in selected_appliances)
-    st.write(translate_text(f"Total Load (Watts): {total_load}", lang_code))
+    total_energy_consumption = sum(appliance_data["Wattage (W)"] * appliance_data["Hours per Day"] * appliance_data["Quantity"]) / 1000  # in kWh
+    total_load = sum(appliance_data["Wattage (W)"] * appliance_data["Quantity"])  # in Watts
 
-    # Inverter requirement
-    inverter_capacity = total_load / 1000  # Convert to kW
-    st.write(translate_text(f"Inverter Required: {inverter_capacity:.2f} kW", lang_code))
+    st.write(translate_text(f"Total Load: {total_load} Watts", lang_code))
+    st.write(translate_text(f"Total Energy Consumption: {total_energy_consumption:.2f} kWh/day", lang_code))
 
-    # Solar panel calculation
+    # Calculate solar panel and battery requirements
+    solar_panel_capacity = 550  # Fixed capacity of a solar panel
     sunlight_hours = 5  # Average peak sunlight hours
-    panels_required = np.ceil(total_load / (solar_panel_capacity * sunlight_hours))
-    st.write(translate_text(f"Solar Panels Required: {int(panels_required)}", lang_code))
+    panels_required = np.ceil(total_energy_consumption / (solar_panel_capacity / 1000 * sunlight_hours))
+
+    battery_capacity_kWh = total_energy_consumption / battery_efficiency  # Battery capacity in kWh
+    battery_capacity_ah = battery_capacity_kWh * 1000 / 48  # Assuming a 48V system
+    batteries_required = np.ceil(battery_capacity_ah / 200)  # Assuming 200 Ah per battery
 
-    # Battery calculation
-    battery_capacity = np.ceil(total_load / (battery_efficiency * sunlight_hours))
-    st.write(translate_text(f"Number of Batteries Required: {int(battery_capacity)}", lang_code))
+    st.subheader(translate_text("System Recommendations", lang_code))
+    st.write(translate_text(f"Solar Panels Required: {int(panels_required)} (550W each)", lang_code))
+    st.write(translate_text(f"Batteries Required: {int(batteries_required)} (200 Ah, 48V system)", lang_code))
 
     # Suggestions
     st.subheader(translate_text("System Design Suggestions", lang_code))
     suggestions = [
         "Ensure panels are installed at the optimal tilt angle.",
-        "Consider a hybrid system for backup and grid integration.",
-        "Use high-quality MPPT charge controllers.",
-        "Plan for system expansion in the future.",
-        "Maintain batteries regularly for longevity.",
-        "Choose reliable and locally available components.",
-        "Use an energy monitoring system to track usage.",
+        "Consider a hybrid system for grid integration.",
+        "Use MPPT charge controllers for efficiency.",
+        "Plan for future system expansion.",
+        "Choose high-quality and reliable components.",
         "Consult a certified solar installer for best practices."
     ]
     for suggestion in suggestions:
@@ -113,3 +93,4 @@ if st.button(translate_text("Calculate Recommendations", lang_code)):
 
 
 
+