#!/usr/bin/env python3
#
# SITER Solar Analysis - NREL PVWatts Solar Production Estimator
# Copyright (C) 2026  Known Element
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.
# DEPRECATED: This script is deprecated. Use siter-solar-analysis.sh instead.
# This file is kept for reference only.

"""
NREL PVWatts Solar Production Estimator for SITER Solar Project
Location: SITER

Usage:
  python solar_estimate.py                    # Use defaults (16 panels @ 400W = 6.4kW)
  python solar_estimate.py YOUR_API_KEY       # With your NREL API key
  python solar_estimate.py --scenarios        # Run multiple system size scenarios
"""

import os
import requests
import json
import sys
from datetime import datetime

# Location coordinates for SITER
LAT = float(os.environ.get("SITER_LAT", "30.44"))  # Central Texas
LON = float(os.environ.get("SITER_LON", "-97.62"))  # Central Texas

# Default system parameters
NUM_PANELS = 16
DEFAULT_PANEL_WATTS = 400  # Modern panels are typically 350-450W
ARRAY_TYPE = 0  # 0 = Fixed - Open Rack (ground mount)
TILT = 30  # degrees - optimal for Texas latitude (~30°N)
AZIMUTH = 180  # South-facing
MODULE_TYPE = 0  # 0 = Standard
LOSSES = 14  # System losses percentage (typical)

# Financial parameters
PROJECT_COST = 4100
CURRENT_MONTHLY_BILL = 301.08
CURRENT_ANNUAL_CONSUMPTION = 23952  # kWh/year (from actual bills: ~1996 kWh/month avg)
BASE_POWER_CONSUMPTION_RATE = 0.085  # $/kWh avoided
BASE_POWER_EXPORT_RATE = 0.04  # $/kWh buyback

# API endpoint
API_URL = "https://developer.nrel.gov/api/pvwatts/v6.json"

def get_solar_estimate(api_key, system_capacity_kw):
    """Query NREL PVWatts API for solar production estimate."""
    
    params = {
        "api_key": api_key,
        "lat": LAT,
        "lon": LON,
        "system_capacity": system_capacity_kw,
        "array_type": ARRAY_TYPE,
        "tilt": TILT,
        "azimuth": AZIMUTH,
        "module_type": MODULE_TYPE,
        "losses": LOSSES,
        "timeframe": "monthly"
    }
    
    try:
        response = requests.get(API_URL, params=params, timeout=30)
        response.raise_for_status()
        return response.json()
    except requests.exceptions.RequestException as e:
        print(f"API request failed: {e}")
        return None

def calculate_financials(annual_kwh):
    """Calculate financial projections based on annual production."""
    monthly_avg = annual_kwh / 12
    
    # Estimate self-consumption vs export
    # During peak solar hours, home may not consume all production
    # Conservative estimate: 60% self-consumed, 40% exported
    self_consumed_pct = 0.60
    self_consumed = annual_kwh * self_consumed_pct
    exported = annual_kwh * (1 - self_consumed_pct)
    
    self_consumption_value = self_consumed * BASE_POWER_CONSUMPTION_RATE
    export_value = exported * BASE_POWER_EXPORT_RATE
    total_annual_value = self_consumption_value + export_value
    
    monthly_savings = total_annual_value / 12
    offset_pct = (monthly_savings / CURRENT_MONTHLY_BILL) * 100
    payback_months = PROJECT_COST / monthly_savings if monthly_savings > 0 else float('inf')
    
    return {
        "annual_kwh": annual_kwh,
        "monthly_avg_kwh": monthly_avg,
        "self_consumed_kwh": self_consumed,
        "exported_kwh": exported,
        "self_consumption_value": self_consumption_value,
        "export_value": export_value,
        "total_annual_value": total_annual_value,
        "monthly_savings": monthly_savings,
        "offset_pct": offset_pct,
        "payback_months": payback_months,
        "payback_years": payback_months / 12
    }

def format_output(data, system_capacity_kw, panel_watts):
    """Format API response into readable report."""
    if not data or data.get("errors"):
        print("Error:", data.get("errors", "Unknown error"))
        return None
    
    outputs = data.get("outputs", {})
    station = data.get("station_info", {})
    
    annual_kwh = outputs.get("ac_annual", 0)
    fin = calculate_financials(annual_kwh)
    
    # Self-consumption percentage used in calculations
    self_consumed_pct = 0.60
    
    print("=" * 70)
    print("SITER SOLAR PROJECT - NREL PVWATTS ANALYSIS")
    print("=" * 70)
    print(f"\nLocation: SITER")
    print(f"  Coordinates: {LAT}, {LON}")
    print(f"  Station: {station.get('city', 'N/A')}, {station.get('state', 'Texas')}")
    print(f"  Distance: {station.get('distance', 'N/A')}m | Elevation: {station.get('elev', 'N/A')}m")
    
    print(f"\nSystem Configuration:")
    print(f"  Panels: {NUM_PANELS} × {panel_watts}W = {system_capacity_kw} kW DC")
    print(f"  Array Type: Fixed Open Rack (Ground Mount)")
    print(f"  Orientation: {TILT}° tilt, {AZIMUTH}° azimuth (South-facing)")
    print(f"  System Losses: {LOSSES}%")
    
    print(f"\n{'='*70}")
    print("MONTHLY PRODUCTION ESTIMATE (NREL PVWatts)")
    print(f"{'='*70}")
    
    months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun", 
              "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
    
    ac_monthly = outputs.get("ac_monthly", [])
    solrad_monthly = outputs.get("solrad_monthly", [])
    
    print(f"\n{'Month':<6} {'AC Output':<14} {'Daily Avg':<12} {'Solar Rad':<15}")
    print(f"{'':6} {'(kWh)':<14} {'(kWh/day)':<12} {'(kWh/m²/day)':<15}")
    print("-" * 50)
    
    for i, month in enumerate(months):
        ac = ac_monthly[i] if i < len(ac_monthly) else 0
        daily_avg = ac / 30.5 if ac else 0
        solrad = solrad_monthly[i] if i < len(solrad_monthly) else 0
        print(f"{month:<6} {ac:>10.0f} {daily_avg:>10.0f} {solrad:>14.2f}")
    
    print("-" * 50)
    print(f"{'ANNUAL':<6} {fin['annual_kwh']:>10.0f} {fin['monthly_avg_kwh']:>10.0f}")
    
    print(f"\n{'='*70}")
    print("ANNUAL PERFORMANCE SUMMARY")
    print(f"{'='*70}")
    print(f"  Annual AC Output: {fin['annual_kwh']:,.0f} kWh")
    print(f"  Monthly Average: {fin['monthly_avg_kwh']:,.0f} kWh")
    print(f"  Daily Average: {fin['annual_kwh']/365:,.0f} kWh")
    print(f"  Capacity Factor: {outputs.get('capacity_factor', 'N/A')}%")
    print(f"  Avg Solar Radiation: {outputs.get('solrad_annual', 'N/A')} kWh/m²/day")
    
    print(f"\n{'='*70}")
    print("FINANCIAL ANALYSIS")
    print(f"{'='*70}")
    
    print(f"\n  Current Consumption: {CURRENT_ANNUAL_CONSUMPTION:,} kWh/year")
    print(f"  Solar Production: {fin['annual_kwh']:,.0f} kWh/year")
    print(f"  Self-Sufficiency: {(fin['annual_kwh']/CURRENT_ANNUAL_CONSUMPTION)*100:.1f}%")
    
    print(f"\n  Self-Consumed ({self_consumed_pct*100:.0f}%): {fin['self_consumed_kwh']:,.0f} kWh")
    print(f"    Value @ ${BASE_POWER_CONSUMPTION_RATE}/kWh: ${fin['self_consumption_value']:,.2f}/year")
    
    print(f"\n  Exported to Grid ({(1-self_consumed_pct)*100:.0f}%): {fin['exported_kwh']:,.0f} kWh")
    print(f"    Value @ ${BASE_POWER_EXPORT_RATE}/kWh: ${fin['export_value']:,.2f}/year")
    
    print(f"\n  TOTAL ANNUAL VALUE: ${fin['total_annual_value']:,.2f}")
    print(f"  MONTHLY SAVINGS: ${fin['monthly_savings']:,.2f}")
    
    print(f"\n{'='*70}")
    print("ROI ANALYSIS")
    print(f"{'='*70}")
    print(f"\n  Project Cost: ${PROJECT_COST:,.2f}")
    print(f"  Current Monthly Bill: ${CURRENT_MONTHLY_BILL:,.2f}")
    print(f"  Projected Monthly Savings: ${fin['monthly_savings']:,.2f}")
    print(f"  Bill Offset: {fin['offset_pct']:.1f}%")
    print(f"\n  PAYBACK PERIOD: {fin['payback_months']:.1f} months ({fin['payback_years']:.1f} years)")
    
    # 5-year projection
    print(f"\n{'='*70}")
    print("5-YEAR FINANCIAL PROJECTION")
    print(f"{'='*70}")
    print(f"\n  {'Year':<6} {'Cumulative Savings':<20} {'Net Position':<15}")
    print(f"  {'-'*40}")
    for year in range(6):
        cum_savings = fin['total_annual_value'] * year
        net = cum_savings - PROJECT_COST
        print(f"  {year:<6} ${cum_savings:>17,.2f} ${net:>12,.2f}")
    
    print(f"\n{'='*70}")
    
    return fin

def run_scenarios(api_key):
    """Run analysis for multiple system configurations."""
    print("=" * 70)
    print("SITER SOLAR - SYSTEM SIZE SCENARIOS")
    print("=" * 70)
    print(f"\nLocation: SITER")
    print(f"Current Annual Consumption: {CURRENT_ANNUAL_CONSUMPTION:,} kWh")
    print(f"Current Monthly Bill: ${CURRENT_MONTHLY_BILL:,.2f}")
    print()
    
    scenarios = [
        # (panels, watts_per_panel, description)
        (16, 250, "16 × 250W (older panels)"),
        (16, 300, "16 × 300W"),
        (16, 350, "16 × 350W"),
        (16, 400, "16 × 400W (modern standard)"),
        (16, 450, "16 × 450W (high efficiency)"),
        (20, 400, "20 × 400W (expanded)"),
        (24, 400, "24 × 400W (full offset target)"),
    ]
    
    results = []
    
    print(f"{'System':<25} {'kW':>6} {'kWh/yr':>8} {'$/mo':>8} {'Offset':>8} {'Payback':>10}")
    print("-" * 70)
    
    for panels, watts, desc in scenarios:
        capacity_kw = (panels * watts) / 1000
        data = get_solar_estimate(api_key, capacity_kw)
        
        if data and not data.get("errors"):
            annual_kwh = data.get("outputs", {}).get("ac_annual", 0)
            fin = calculate_financials(annual_kwh)
            
            results.append({
                "description": desc,
                "panels": panels,
                "watts": watts,
                "capacity_kw": capacity_kw,
                **fin
            })
            
            print(f"{desc:<25} {capacity_kw:>6.1f} {fin['annual_kwh']:>8,.0f} "
                  f"${fin['monthly_savings']:>6.2f} {fin['offset_pct']:>6.1f}% "
                  f"{fin['payback_years']:>8.1f} yrs")
    
    print("-" * 70)
    
    # Find system size for ~100% offset
    target_monthly_savings = CURRENT_MONTHLY_BILL
    target_annual_value = target_monthly_savings * 12
    
    # Back-calculate required production
    # annual_value = (production * 0.60 * 0.085) + (production * 0.40 * 0.04)
    # annual_value = production * (0.051 + 0.016) = production * 0.067
    required_production = target_annual_value / 0.067  # ~$4,016 annual value needed
    required_kw = required_production / 1500  # Rough: 1kW produces ~1500 kWh/year in Texas
    
    print(f"\nTo achieve 100% bill offset, estimated system size needed:")
    print(f"  ~{required_kw:.0f} kW ({int(required_kw/0.4)} panels @ 400W each)")
    
    return results

def main():
    global NUM_PANELS
    api_key = os.environ.get("NREL_API_KEY", "DEMO_KEY")
    run_scenarios_mode = False
    panel_watts = DEFAULT_PANEL_WATTS
    
    for arg in sys.argv[1:]:
        if arg == "--scenarios":
            run_scenarios_mode = True
        elif arg.startswith("--panels="):
            NUM_PANELS = int(arg.split("=")[1])
        elif arg.startswith("--watts="):
            panel_watts = int(arg.split("=")[1])
        elif not arg.startswith("--"):
            api_key = arg
    
    system_capacity_kw = (NUM_PANELS * panel_watts) / 1000
    
    if run_scenarios_mode:
        run_scenarios(api_key)
    else:
        print(f"Querying NREL PVWatts API (system: {system_capacity_kw} kW)...")
        data = get_solar_estimate(api_key, system_capacity_kw)
        
        if data:
            result = format_output(data, system_capacity_kw, panel_watts)
            
            # Save JSON for further analysis
            with open("nrel_solar_data.json", "w") as f:
                json.dump(data, f, indent=2)
            print(f"\nRaw data saved to nrel_solar_data.json")

if __name__ == "__main__":
    main()