eGauge Energy Analysis Toolkit

Analyze energy consumption and costs from your eGauge energy monitor with Time-of-Use (TOU) pricing optimization and circuit-level analysis.

Features

• TOU Cost Analysis: Calculate costs based on Peak, Part-Peak, and Off-Peak periods
• Circuit-Level Breakdown: Analyze individual CT registers/circuits
• Historical Trend Analysis: Week-over-week comparisons and 30-day averages
• Data Persistence: Store historical data locally for long-term tracking
• Visualization: Generate charts (requires matplotlib)
• Email Notifications: Automated report delivery (optional)
• Device-Specific Analysis: Specialized scripts for furnace, kegerator, etc.

Quick Start

1. Configure Credentials

Copy the example environment file and add your credentials:

cp .env.example .env
nano .env  # Edit with your eGauge credentials

2. Install Dependencies

pip install -r requirements.txt

3. Run Your First Report

python3 egauge_weekly_analysis.py

Scripts

Main Analysis Script

egauge_weekly_analysis.py - Comprehensive energy analysis

# Analyze last 7 days
python3 egauge_weekly_analysis.py

# Analyze last 30 days
python3 egauge_weekly_analysis.py --days 30

# Save report to file
python3 egauge_weekly_analysis.py --output report.txt

# Generate charts
python3 egauge_weekly_analysis.py --charts

# Send email report
python3 egauge_weekly_analysis.py --email

# All options combined
python3 egauge_weekly_analysis.py --days 7 --output report.txt --charts --email

Output includes:

• Summary table ranked by total cost
• Week-over-week trend comparison
• 30-day historical average comparison
• Detailed breakdown by TOU period for each register
• Alerts for high usage
• Time-shifting recommendations

Quick Status Check

quick_check.sh - Real-time power usage check

./quick_check.sh

Shows current power consumption, TOU period, and top active loads.

Weekly Automation

weekly_cron.sh - Automated weekly reports

Set up automatic weekly reports via cron:

# Make executable
chmod +x weekly_cron.sh

# Add to crontab (runs every Monday at 6am)
crontab -e
# Add this line:
0 6 * * 1 /path/to/egauge/weekly_cron.sh

Device-Specific Analysis

furnace_savings_analysis.py - Analyze furnace efficiency

python3 furnace_savings_analysis.py
python3 furnace_savings_analysis.py --days 14

kegerator_analysis.py - Analyze kegerator/mini-fridge usage

python3 kegerator_analysis.py

mattress_pad_analysis.py - Before/after comparison for equipment changes

# Analyze usage before/after a change
python3 mattress_pad_analysis.py --change-date 2026-01-25 --overnight-only

# Customize for other circuits
python3 mattress_pad_analysis.py --register "CT 8 - Laundry [kWh]" --change-date 2026-01-20

Configuration

All configuration is managed through environment variables in .env:

# eGauge Device Credentials (Required)
EGAUGE_URL=https://your-egauge.egaug.es
EGAUGE_USER=owner
EGAUGE_PASSWORD=your_password

# Email Notifications (Optional)
EMAIL_ENABLED=true
EMAIL_TO=your@email.com
SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
SMTP_USER=your@gmail.com
SMTP_PASSWORD=your_app_password
SMTP_USE_TLS=true

Rate configuration and thresholds are in config.py.

File Structure

egauge/
├── .env                    # Your credentials (git-ignored)
├── .env.example            # Template for .env
├── config.py               # Centralized configuration
├── egauge_weekly_analysis.py   # Main analysis script
├── quick_check.sh          # Quick status check
├── weekly_cron.sh          # Cron automation script
├── data_store.py           # Data persistence layer
├── visualization.py        # Chart generation
├── email_notify.py         # Email notifications
├── device_analysis.py      # Device-specific utilities
├── furnace_savings_analysis.py
├── kegerator_analysis.py
├── mattress_pad_analysis.py
├── data/                   # Historical data (git-ignored)
├── reports/                # Generated reports (git-ignored)
└── charts/                 # Generated charts (git-ignored)

TOU Period Definitions

Based on PG&E EV2-A schedule:

• Peak: 4:00 PM - 9:00 PM (highest rates)
• Part-Peak: 3:00 PM - 4:00 PM and 9:00 PM - 12:00 AM (medium rates)
• Off-Peak: 12:00 AM - 3:00 PM (lowest rates)

Rate Information

Current rates for SJCE (San Jose Clean Energy) on PG&E EV2-A:

Season	Peak	Part-Peak	Off-Peak
Winter (Oct-May)	$0.51928	$0.49193	$0.29780
Summer (Jun-Sep)	$0.64639	$0.52525	$0.29780

Update rates in config.py when they change.

Requirements

• Python 3.8+
• curl (for fetching data from eGauge)
• python-dotenv (for environment variable loading)
• matplotlib (optional, for charts)

Troubleshooting

"eGauge credentials not configured"

• Create a .env file from .env.example and add your credentials

"Authentication required" errors

• Check eGauge credentials in .env
• Verify the eGauge domain is accessible

No data returned

• Check that eGauge is online and accessible
• Try accessing your eGauge URL in a browser

Charts not generating

• Install matplotlib: pip install matplotlib

Email not sending

• Set EMAIL_ENABLED=true in .env
• Configure SMTP settings for your email provider
• For Gmail, use an App Password (not your regular password)