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Major improvements to period calculation with smarter defaults and simplified configuration: **Adaptive Defaults:** - ENABLE_MIN_PERIODS: true (was false) - Always try to find periods - MIN_PERIODS target: 2 periods/day (ensures coverage) - BEST_PRICE_MAX_LEVEL: "cheap" (was "any") - Prefer genuinely cheap - PEAK_PRICE_MIN_LEVEL: "expensive" (was "any") - Prefer genuinely expensive - GAP_TOLERANCE: 1 (was 0) - Allow 1-level deviations in sequences - MIN_DISTANCE_FROM_AVG: 5% (was 2%) - Ensure significance - PEAK_PRICE_MIN_PERIOD_LENGTH: 30min (was 60min) - More responsive - PEAK_PRICE_FLEX: -20% (was -15%) - Better peak detection **Volatility Filter Removal:** - Removed CONF_BEST_PRICE_MIN_VOLATILITY from const.py - Removed CONF_PEAK_PRICE_MIN_VOLATILITY from const.py - Removed volatility filter UI controls from config_flow.py - Removed filter_periods_by_volatility() calls from coordinator.py - Updated all 5 translations (de, en, nb, nl, sv) **Period Calculation Logic:** - Level filter now integrated into _build_periods() (applied during interval qualification, not as post-filter) - Gap tolerance implemented via _check_level_with_gap_tolerance() - Short periods (<1.5h) use strict filtering (no gap tolerance) - Relaxation now passes level_filter + gap_count directly to PeriodConfig - show_periods check skipped when relaxation enabled (relaxation tries "any" as fallback) **Documentation:** - Complete rewrite of docs/user/period-calculation.md: * Visual examples with timelines * Step-by-step explanation of 4-step process * Configuration scenarios (5 common use cases) * Troubleshooting section with specific fixes * Advanced topics (per-day independence, early stop, etc.) - Updated README.md: "volatility" → "distance from average" Impact: Periods now reliably appear on most days with meaningful quality filters. Users get warned about expensive periods and notified about cheap opportunities without manual tuning. Relaxation ensures coverage while keeping filters as strict as possible. Breaking change: Volatility filter removed (was never a critical feature, often confused users). Existing configs continue to work (removed keys are simply ignored). |
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| automation-examples.md | ||
| configuration.md | ||
| installation.md | ||
| period-calculation.md | ||
| README.md | ||
| sensors.md | ||
| services.md | ||
| troubleshooting.md | ||
User Documentation
Welcome to Tibber Prices! This integration provides enhanced electricity price data from Tibber with quarter-hourly precision, statistical analysis, and intelligent ratings.
📚 Documentation
- Installation - How to install via HACS and configure the integration
- Configuration - Setting up your Tibber API token and price thresholds
- Period Calculation - How Best/Peak Price periods are calculated and configured
- Sensors - Available sensors, their states, and attributes
- Services - Custom services and how to use them
- Automation Examples - Ready-to-use automation recipes
- Troubleshooting - Common issues and solutions
🚀 Quick Start
- Install via HACS (add as custom repository)
- Add Integration in Home Assistant → Settings → Devices & Services
- Enter Tibber API Token (get yours at developer.tibber.com)
- Configure Price Thresholds (optional, defaults work for most users)
- Start Using Sensors in automations, dashboards, and scripts!
✨ Key Features
- Quarter-hourly precision - 15-minute intervals for accurate price tracking
- Statistical analysis - Trailing/leading 24h averages for context
- Price ratings - LOW/NORMAL/HIGH classification based on your thresholds
- Best/Peak hour detection - Automatic detection of cheapest/peak periods with configurable filters (learn how)
- ApexCharts integration - Custom services for beautiful price charts
- Multi-currency support - EUR, NOK, SEK with proper minor units (ct, øre, öre)
🔗 Useful Links
🤝 Need Help?
- Check the Troubleshooting Guide
- Search existing issues
- Open a new issue if needed
Note: These guides are for end users. If you want to contribute to development, see the Developer Documentation.