app.py

import streamlit as st
import pandas as pd
import numpy as np
import math
import matplotlib.pyplot as plt
import numpy_financial as npf
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
from reportlab.lib.pagesizes import A4
from reportlab.lib.styles import getSampleStyleSheet
import io
import xlsxwriter

# ===============================
# PAGE CONFIG
# ===============================
st.set_page_config(layout="wide")
st.title("🇵🇰 Pakistan Solar Engineering & Financial Dashboard")

# ===============================
# CONFIGURATION
# ===============================

SYSTEM_LOSSES = 0.20
PANEL_COST_PER_WATT = 55
INSTALLATION_COST_PER_WATT = 35
LITHIUM_BATTERY_COST_5KWH = 95000

CITY_SUNLIGHT = {
    "Karachi": 6.2,
    "Lahore": 5.5,
    "Islamabad": 5.2,
    "Peshawar": 5.6,
    "Quetta": 6.5,
}

# Appliance Database
APPLIANCES_RESIDENTIAL = {
    "LED Bulb (12W)": 12,
    "Fan (80W)": 80,
    "Refrigerator (200W)": 200,
    "LED TV (150W)": 150,
    "Air Conditioner 1.5 Ton (1500W)": 1500,
    "Washing Machine (500W)": 500,
    "Water Pump (750W)": 750,
    "Laptop (65W)": 65,
    "Iron (1000W)": 1000,
}

APPLIANCES_COMMERCIAL = {
    "CNC Machine (2kW)": 2000,
    "Industrial AC (5kW)": 5000,
    "Lighting System (1kW)": 1000,
    "Water Pump 3HP (2.2kW)": 2200,
    "Server Rack (1.5kW)": 1500,
}

# Demo Load Profiles
DEMO_SELECTIONS = {
    "Homeowner": ["LED Bulb (12W)", "Fan (80W)", "Refrigerator (200W)", "LED TV (150W)"],
    "Solar Company": ["LED Bulb (12W)", "Fan (80W)", "CNC Machine (2kW)", "Industrial AC (5kW)"],
    "Industrial Investor": ["CNC Machine (2kW)", "Industrial AC (5kW)", "Water Pump 3HP (2.2kW)", "Server Rack (1.5kW)"]
}

# Tariffs
RESIDENTIAL_TARIFF = [
    (100, 22),
    (100, 32),
    (100, 38),
    (100, 42),
    (100, 48),
    (np.inf, 65),
]

COMMERCIAL_TARIFF = 72

# ===============================
# CALCULATION FUNCTIONS
# ===============================

def calculate_residential_bill(units):
    remaining = units
    bill = 0
    for slab_units, rate in RESIDENTIAL_TARIFF:
        if remaining > slab_units:
            bill += slab_units * rate
            remaining -= slab_units
        else:
            bill += remaining * rate
            break
    return bill

def calculate_commercial_bill(units):
    return units * COMMERCIAL_TARIFF

def calculate_system(load_watts, hours, sunlight):
    daily_kwh = (load_watts * hours) / 1000
    adjusted_kwh = daily_kwh / (1 - SYSTEM_LOSSES)
    required_kw = adjusted_kwh / sunlight
    return daily_kwh, round(required_kw, 2)

def calculate_battery(daily_kwh, backup_hours):
    backup_kwh = (daily_kwh / 24) * backup_hours
    return math.ceil(backup_kwh / 5)

def calculate_cost(system_kw, batteries, system_type):
    base_cost = system_kw * 1000 * (PANEL_COST_PER_WATT + INSTALLATION_COST_PER_WATT)
    battery_cost = batteries * LITHIUM_BATTERY_COST_5KWH

    if system_type == "On-Grid":
        return base_cost
    elif system_type == "Off-Grid":
        return base_cost + battery_cost
    else:
        return base_cost * 1.1 + battery_cost

def emi_calculator(principal, annual_rate, years):
    r = annual_rate / 100 / 12
    n = years * 12
    return round(principal * r * (1 + r)**n / ((1 + r)**n - 1))

def financial_projection(total_cost, daily_kwh, mode, years=25):
    monthly_units = daily_kwh * 30
    cashflows = []

    for year in range(1, years + 1):
        price_increase = (1 + 0.07) ** (year - 1)

        if mode == "Homeowner":
            monthly_bill = calculate_residential_bill(monthly_units * price_increase)
        else:
            monthly_bill = calculate_commercial_bill(monthly_units * price_increase)

        cashflows.append(monthly_bill * 12)

    npv = npf.npv(0.05, [-total_cost] + cashflows)
    irr = npf.irr([-total_cost] + cashflows)
    payback_year = next((i for i, cf in enumerate(np.cumsum(cashflows), 1) if cf >= total_cost), None)

    return cashflows, round(npv, 2), round(irr * 100, 2), payback_year, np.cumsum(cashflows)

# ===============================
# PDF REPORT
# ===============================

def generate_pdf(report_data):
    file_path = "solar_report.pdf"
    doc = SimpleDocTemplate(file_path, pagesize=A4)
    elements = []
    styles = getSampleStyleSheet()

    elements.append(Paragraph("Pakistan Solar Feasibility Report", styles['Title']))
    elements.append(Spacer(1, 12))

    for k, v in report_data.items():
        elements.append(Paragraph(f"{k}: {v}", styles['Normal']))
        elements.append(Spacer(1, 6))

    doc.build(elements)
    return file_path

# ===============================
# STREAMLIT UI
# ===============================

audience = st.selectbox("Select Audience", ["Homeowner", "Solar Company", "Industrial Investor"])
city = st.selectbox("Select City", list(CITY_SUNLIGHT.keys()))
sunlight = CITY_SUNLIGHT[city]

# Demo Settings Buttons
if st.button("🎯 Load Demo Appliances"):
    if audience in DEMO_SELECTIONS:
        st.session_state["demo_appliances"] = DEMO_SELECTIONS[audience]
        st.success("Demo appliances loaded!")

if "demo_appliances" in st.session_state:
    default_selection = st.session_state["demo_appliances"]
else:
    default_selection = []

# Appliance Selection
if audience == "Homeowner":
    appliances = st.multiselect("Select Appliances", list(APPLIANCES_RESIDENTIAL.keys()),
                                default=default_selection)

elif audience == "Solar Company":
    appliances = st.multiselect("Select Appliances", 
                                list(APPLIANCES_RESIDENTIAL.keys()) + list(APPLIANCES_COMMERCIAL.keys()),
                                default=default_selection)

else:
    appliances = st.multiselect("Select Industrial Equipment",
                                list(APPLIANCES_COMMERCIAL.keys()),
                                default=default_selection)

# Demo Settings Button
if st.button("🎯 Load Demo City & Settings"):
    city = "Karachi"
    sunlight = CITY_SUNLIGHT[city]
    hours = 8
    backup_hours = 4
    st.success("Demo settings loaded!")

hours = st.slider("Usage Hours per Day", 1, 24, 8)
system_type = st.radio("System Type", ["On-Grid", "Off-Grid", "Hybrid"])
backup_hours = st.slider("Battery Backup Hours", 0, 24, 4)

# Calculation Trigger
if st.button("⚡ Calculate Solar System"):

    if not appliances:
        st.error("Please select appliances")
    else:

        total_load = sum(APPLIANCES_RESIDENTIAL.get(a, 0) + APPLIANCES_COMMERCIAL.get(a, 0) for a in appliances)

        daily_kwh, system_kw = calculate_system(total_load, hours, sunlight)

        batteries = calculate_battery(daily_kwh, backup_hours)

        total_cost = calculate_cost(system_kw, batteries, system_type)

        interest = st.slider("Bank Interest Rate (%)", 5, 25, 15)
        years_loan = st.slider("Loan Duration (Years)", 1, 10, 5)

        emi = emi_calculator(total_cost, interest, years_loan)

        cashflows, npv, irr, payback_year, cumulative_savings = financial_projection(total_cost, daily_kwh, audience)

        # Results
        st.subheader("System Results")
        st.write(f"Total Load: {total_load} W")
        st.write(f"Daily Energy: {round(daily_kwh,2)} kWh")
        st.write(f"System Size: {system_kw} kW")
        st.write(f"Battery Units: {batteries}")
        st.write(f"Total Cost: PKR {round(total_cost):,}")
        st.write(f"EMI: PKR {emi:,}")
        st.write(f"NPV: PKR {npv:,}")
        st.write(f"IRR: {irr}%")
        st.write(f"Payback Year: {payback_year}")

        # Charts
        st.subheader("Savings Growth")
        plt.figure(figsize=(10,4))
        plt.plot(range(1,26), cumulative_savings)
        plt.axhline(total_cost, linestyle="--")
        st.pyplot(plt)

        # PDF + Excel
        report_data = {
            "Audience": audience,
            "City": city,
            "System Size (kW)": system_kw,
            "Total Cost": total_cost,
            "IRR": irr,
            "NPV": npv,
            "Payback Year": payback_year
        }

        pdf_file = generate_pdf(report_data)

        with open(pdf_file, "rb") as f:
            st.download_button("Download PDF Report", f, file_name="Solar_Report.pdf")