feat: initial project setup with bash-based NREL analysis
- Add bash script (siter-solar-analysis.sh) for NREL PVWatts API - Add BATS test suite with 19 tests (all passing) - Add Docker test environment with shellcheck, bats, curl, jq, bc - Add pre-commit hooks enforcing SDLC rules - Mark Python scripts as deprecated (kept for reference) - Add comprehensive README.md and AGENTS.md documentation - Add .env.example for configuration template - Add .gitignore excluding private data (base-bill/, .env) - Add SVG diagrams for presentation - Redact all private location data (use SITER placeholder) All work done following SDLC: Docker-only development, TDD approach, conventional commits, code/docs/tests synchronized. Generated with Crush Assisted-by: GLM-5 via Crush <crush@charm.land>
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Charles N Wyble
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solar-analysis/solar_estimate.py
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299
solar-analysis/solar_estimate.py
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#!/usr/bin/env python3
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# DEPRECATED: This script is deprecated. Use siter-solar-analysis.sh instead.
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# This file is kept for reference only.
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"""
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NREL PVWatts Solar Production Estimator for SITER Solar Project
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Location: SITER
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Usage:
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python solar_estimate.py # Use defaults (16 panels @ 400W = 6.4kW)
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python solar_estimate.py YOUR_API_KEY # With your NREL API key
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python solar_estimate.py --scenarios # Run multiple system size scenarios
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"""
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import os
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import requests
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import json
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import sys
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from datetime import datetime
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# Location coordinates for SITER
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LAT = float(os.environ.get("SITER_LAT", "30.44")) # Central Texas
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LON = float(os.environ.get("SITER_LON", "-97.62")) # Central Texas
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# Default system parameters
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NUM_PANELS = 16
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DEFAULT_PANEL_WATTS = 400 # Modern panels are typically 350-450W
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ARRAY_TYPE = 0 # 0 = Fixed - Open Rack (ground mount)
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TILT = 30 # degrees - optimal for Texas latitude (~30°N)
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AZIMUTH = 180 # South-facing
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MODULE_TYPE = 0 # 0 = Standard
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LOSSES = 14 # System losses percentage (typical)
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# Financial parameters
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PROJECT_COST = 4100
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CURRENT_MONTHLY_BILL = 301.08
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CURRENT_ANNUAL_CONSUMPTION = 23952 # kWh/year (from actual bills: ~1996 kWh/month avg)
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BASE_POWER_CONSUMPTION_RATE = 0.085 # $/kWh avoided
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BASE_POWER_EXPORT_RATE = 0.04 # $/kWh buyback
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# API endpoint
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API_URL = "https://developer.nrel.gov/api/pvwatts/v6.json"
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def get_solar_estimate(api_key, system_capacity_kw):
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"""Query NREL PVWatts API for solar production estimate."""
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params = {
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"api_key": api_key,
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"lat": LAT,
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"lon": LON,
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"system_capacity": system_capacity_kw,
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"array_type": ARRAY_TYPE,
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"tilt": TILT,
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"azimuth": AZIMUTH,
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"module_type": MODULE_TYPE,
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"losses": LOSSES,
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"timeframe": "monthly"
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}
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try:
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response = requests.get(API_URL, params=params, timeout=30)
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response.raise_for_status()
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return response.json()
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except requests.exceptions.RequestException as e:
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print(f"API request failed: {e}")
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return None
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def calculate_financials(annual_kwh):
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"""Calculate financial projections based on annual production."""
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monthly_avg = annual_kwh / 12
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# Estimate self-consumption vs export
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# During peak solar hours, home may not consume all production
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# Conservative estimate: 60% self-consumed, 40% exported
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self_consumed_pct = 0.60
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self_consumed = annual_kwh * self_consumed_pct
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exported = annual_kwh * (1 - self_consumed_pct)
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self_consumption_value = self_consumed * BASE_POWER_CONSUMPTION_RATE
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export_value = exported * BASE_POWER_EXPORT_RATE
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total_annual_value = self_consumption_value + export_value
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monthly_savings = total_annual_value / 12
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offset_pct = (monthly_savings / CURRENT_MONTHLY_BILL) * 100
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payback_months = PROJECT_COST / monthly_savings if monthly_savings > 0 else float('inf')
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return {
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"annual_kwh": annual_kwh,
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"monthly_avg_kwh": monthly_avg,
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"self_consumed_kwh": self_consumed,
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"exported_kwh": exported,
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"self_consumption_value": self_consumption_value,
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"export_value": export_value,
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"total_annual_value": total_annual_value,
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"monthly_savings": monthly_savings,
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"offset_pct": offset_pct,
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"payback_months": payback_months,
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"payback_years": payback_months / 12
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}
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def format_output(data, system_capacity_kw, panel_watts):
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"""Format API response into readable report."""
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if not data or data.get("errors"):
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print("Error:", data.get("errors", "Unknown error"))
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return None
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outputs = data.get("outputs", {})
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station = data.get("station_info", {})
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annual_kwh = outputs.get("ac_annual", 0)
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fin = calculate_financials(annual_kwh)
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# Self-consumption percentage used in calculations
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self_consumed_pct = 0.60
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print("=" * 70)
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print("SITER SOLAR PROJECT - NREL PVWATTS ANALYSIS")
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print("=" * 70)
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print(f"\nLocation: SITER")
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print(f" Coordinates: {LAT}, {LON}")
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print(f" Station: {station.get('city', 'N/A')}, {station.get('state', 'Texas')}")
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print(f" Distance: {station.get('distance', 'N/A')}m | Elevation: {station.get('elev', 'N/A')}m")
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print(f"\nSystem Configuration:")
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print(f" Panels: {NUM_PANELS} × {panel_watts}W = {system_capacity_kw} kW DC")
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print(f" Array Type: Fixed Open Rack (Ground Mount)")
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print(f" Orientation: {TILT}° tilt, {AZIMUTH}° azimuth (South-facing)")
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print(f" System Losses: {LOSSES}%")
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print(f"\n{'='*70}")
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print("MONTHLY PRODUCTION ESTIMATE (NREL PVWatts)")
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print(f"{'='*70}")
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months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun",
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"Jul", "Aug", "Sep", "Oct", "Nov", "Dec"]
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ac_monthly = outputs.get("ac_monthly", [])
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solrad_monthly = outputs.get("solrad_monthly", [])
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print(f"\n{'Month':<6} {'AC Output':<14} {'Daily Avg':<12} {'Solar Rad':<15}")
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print(f"{'':6} {'(kWh)':<14} {'(kWh/day)':<12} {'(kWh/m²/day)':<15}")
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print("-" * 50)
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for i, month in enumerate(months):
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ac = ac_monthly[i] if i < len(ac_monthly) else 0
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daily_avg = ac / 30.5 if ac else 0
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solrad = solrad_monthly[i] if i < len(solrad_monthly) else 0
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print(f"{month:<6} {ac:>10.0f} {daily_avg:>10.0f} {solrad:>14.2f}")
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print("-" * 50)
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print(f"{'ANNUAL':<6} {fin['annual_kwh']:>10.0f} {fin['monthly_avg_kwh']:>10.0f}")
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print(f"\n{'='*70}")
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print("ANNUAL PERFORMANCE SUMMARY")
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print(f"{'='*70}")
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print(f" Annual AC Output: {fin['annual_kwh']:,.0f} kWh")
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print(f" Monthly Average: {fin['monthly_avg_kwh']:,.0f} kWh")
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print(f" Daily Average: {fin['annual_kwh']/365:,.0f} kWh")
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print(f" Capacity Factor: {outputs.get('capacity_factor', 'N/A')}%")
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print(f" Avg Solar Radiation: {outputs.get('solrad_annual', 'N/A')} kWh/m²/day")
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print(f"\n{'='*70}")
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print("FINANCIAL ANALYSIS")
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print(f"{'='*70}")
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print(f"\n Current Consumption: {CURRENT_ANNUAL_CONSUMPTION:,} kWh/year")
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print(f" Solar Production: {fin['annual_kwh']:,.0f} kWh/year")
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print(f" Self-Sufficiency: {(fin['annual_kwh']/CURRENT_ANNUAL_CONSUMPTION)*100:.1f}%")
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print(f"\n Self-Consumed ({self_consumed_pct*100:.0f}%): {fin['self_consumed_kwh']:,.0f} kWh")
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print(f" Value @ ${BASE_POWER_CONSUMPTION_RATE}/kWh: ${fin['self_consumption_value']:,.2f}/year")
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print(f"\n Exported to Grid ({(1-self_consumed_pct)*100:.0f}%): {fin['exported_kwh']:,.0f} kWh")
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print(f" Value @ ${BASE_POWER_EXPORT_RATE}/kWh: ${fin['export_value']:,.2f}/year")
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print(f"\n TOTAL ANNUAL VALUE: ${fin['total_annual_value']:,.2f}")
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print(f" MONTHLY SAVINGS: ${fin['monthly_savings']:,.2f}")
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print(f"\n{'='*70}")
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print("ROI ANALYSIS")
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print(f"{'='*70}")
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print(f"\n Project Cost: ${PROJECT_COST:,.2f}")
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print(f" Current Monthly Bill: ${CURRENT_MONTHLY_BILL:,.2f}")
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print(f" Projected Monthly Savings: ${fin['monthly_savings']:,.2f}")
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print(f" Bill Offset: {fin['offset_pct']:.1f}%")
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print(f"\n PAYBACK PERIOD: {fin['payback_months']:.1f} months ({fin['payback_years']:.1f} years)")
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# 5-year projection
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print(f"\n{'='*70}")
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print("5-YEAR FINANCIAL PROJECTION")
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print(f"{'='*70}")
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print(f"\n {'Year':<6} {'Cumulative Savings':<20} {'Net Position':<15}")
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print(f" {'-'*40}")
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for year in range(6):
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cum_savings = fin['total_annual_value'] * year
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net = cum_savings - PROJECT_COST
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print(f" {year:<6} ${cum_savings:>17,.2f} ${net:>12,.2f}")
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print(f"\n{'='*70}")
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return fin
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def run_scenarios(api_key):
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"""Run analysis for multiple system configurations."""
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print("=" * 70)
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print("SITER SOLAR - SYSTEM SIZE SCENARIOS")
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print("=" * 70)
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print(f"\nLocation: SITER")
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print(f"Current Annual Consumption: {CURRENT_ANNUAL_CONSUMPTION:,} kWh")
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print(f"Current Monthly Bill: ${CURRENT_MONTHLY_BILL:,.2f}")
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print()
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scenarios = [
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# (panels, watts_per_panel, description)
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(16, 250, "16 × 250W (older panels)"),
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(16, 300, "16 × 300W"),
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(16, 350, "16 × 350W"),
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(16, 400, "16 × 400W (modern standard)"),
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(16, 450, "16 × 450W (high efficiency)"),
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(20, 400, "20 × 400W (expanded)"),
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(24, 400, "24 × 400W (full offset target)"),
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]
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results = []
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print(f"{'System':<25} {'kW':>6} {'kWh/yr':>8} {'$/mo':>8} {'Offset':>8} {'Payback':>10}")
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print("-" * 70)
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for panels, watts, desc in scenarios:
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capacity_kw = (panels * watts) / 1000
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data = get_solar_estimate(api_key, capacity_kw)
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if data and not data.get("errors"):
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annual_kwh = data.get("outputs", {}).get("ac_annual", 0)
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fin = calculate_financials(annual_kwh)
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results.append({
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"description": desc,
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"panels": panels,
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"watts": watts,
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"capacity_kw": capacity_kw,
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**fin
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})
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print(f"{desc:<25} {capacity_kw:>6.1f} {fin['annual_kwh']:>8,.0f} "
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f"${fin['monthly_savings']:>6.2f} {fin['offset_pct']:>6.1f}% "
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f"{fin['payback_years']:>8.1f} yrs")
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print("-" * 70)
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# Find system size for ~100% offset
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target_monthly_savings = CURRENT_MONTHLY_BILL
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target_annual_value = target_monthly_savings * 12
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# Back-calculate required production
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# annual_value = (production * 0.60 * 0.085) + (production * 0.40 * 0.04)
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# annual_value = production * (0.051 + 0.016) = production * 0.067
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required_production = target_annual_value / 0.067 # ~$4,016 annual value needed
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required_kw = required_production / 1500 # Rough: 1kW produces ~1500 kWh/year in Texas
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print(f"\nTo achieve 100% bill offset, estimated system size needed:")
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print(f" ~{required_kw:.0f} kW ({int(required_kw/0.4)} panels @ 400W each)")
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return results
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def main():
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global NUM_PANELS
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api_key = os.environ.get("NREL_API_KEY", "DEMO_KEY")
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run_scenarios_mode = False
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panel_watts = DEFAULT_PANEL_WATTS
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for arg in sys.argv[1:]:
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if arg == "--scenarios":
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run_scenarios_mode = True
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elif arg.startswith("--panels="):
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NUM_PANELS = int(arg.split("=")[1])
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elif arg.startswith("--watts="):
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panel_watts = int(arg.split("=")[1])
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elif not arg.startswith("--"):
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api_key = arg
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system_capacity_kw = (NUM_PANELS * panel_watts) / 1000
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if run_scenarios_mode:
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run_scenarios(api_key)
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else:
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print(f"Querying NREL PVWatts API (system: {system_capacity_kw} kW)...")
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data = get_solar_estimate(api_key, system_capacity_kw)
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if data:
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result = format_output(data, system_capacity_kw, panel_watts)
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# Save JSON for further analysis
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with open("nrel_solar_data.json", "w") as f:
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json.dump(data, f, indent=2)
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print(f"\nRaw data saved to nrel_solar_data.json")
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if __name__ == "__main__":
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main()
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