Julian Pawlowski 47b0a298d4 feat(periods): add midnight-crossing periods and day volatility attributes ... Periods can now naturally cross midnight boundaries, and new diagnostic attributes help users understand price classification changes at midnight. **New Features:** 1. Midnight-Crossing Period Support (relaxation.py): - group_periods_by_day() assigns periods to ALL spanned days - Periods crossing midnight appear in both yesterday and today - Enables period formation across calendar day boundaries - Ensures min_periods checking works correctly at midnight 2. Extended Price Data Window (relaxation.py): - Period calculation now uses full 3-day data (yesterday+today+tomorrow) - Enables natural period formation without artificial midnight cutoff - Removed date filter that excluded yesterday's prices 3. Day Volatility Diagnostic Attributes (period_statistics.py, core.py): - day_volatility_%: Daily price spread as percentage (span/avg × 100) - day_price_min/max/span: Daily price range in minor currency (ct/øre) - Helps detect when midnight classification changes are economically significant - Uses period start day's reference prices for consistency **Documentation:** 4. Design Principles (period-calculation-theory.md): - Clarified per-day evaluation principle (always was the design) - Added comprehensive section on midnight boundary handling - Documented volatility threshold separation (sensor vs period filters) - Explained market context for midnight price jumps (EPEX SPOT timing) 5. User Guides (period-calculation.md, automation-examples.md): - Added \"Midnight Price Classification Changes\" troubleshooting section - Provided automation examples using volatility attributes - Explained why Best→Peak classification can change at midnight - Documented level filter volatility threshold behavior **Architecture:** - Per-day evaluation: Each interval evaluated against its OWN day's min/max/avg (not period start day) ensures mathematical correctness across midnight - Period boundaries: Periods can naturally cross midnight but may split when consecutive days differ significantly (intentional, mathematically correct) - Volatility thresholds: Sensor thresholds (user-configurable) remain separate from period filter thresholds (fixed internal) to prevent unexpected behavior Impact: Periods crossing midnight are now consistently visible before and after midnight turnover. Users can understand and handle edge cases where price classification changes at midnight on low-volatility days.		2025-11-21 23:18:46 +00:00
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tibber_prices	feat(periods): add midnight-crossing periods and day volatility attributes	2025-11-21 23:18:46 +00:00