Commit graph

6 commits

Author SHA1 Message Date
Julian Pawlowski
3a9ba55dd3 feat(sensors): improve price trend sensors with temporal context
Enhanced current_price_trend and next_price_trend_change sensors with
consistent temporal information and fixed trend calculation logic.

Changes:
- Fixed trend calculation order: Calculate final trend state (momentum +
  future outlook) BEFORE scanning for next change, ensuring consistency
  between current_price_trend state and next_price_trend_change from_direction
- Added TIME_SENSITIVE_ENTITY_KEYS registration for both trend sensors
  to enable automatic 15-minute boundary updates (Timer #2)
- Removed redundant timestamp field from _trend_change_attributes (was
  duplicate of sensor state)
- Added timestamp attribute (current interval) to both sensors as first
  attribute for temporal reference
- Implemented _find_trend_start_time() to scan backward and determine
  when current trend began
- Added trend_duration_minutes to current_price_trend showing how long
  current trend has been active
- Added from_direction to current_price_trend showing previous trend
  state (enables detection of valleys/plateaus)
- Added minutes_until_change to next_price_trend_change showing time
  until trend changes
- Removed redundant attributes: valid_until, duration_hours,
  duration_minutes from current_price_trend (can be derived from
  next_price_trend_change sensor)
- Removed redundant next_direction from current_price_trend (available
  in next_price_trend_change sensor)

current_price_trend attributes:
- timestamp: Current interval (calculation basis)
- from_direction: Previous trend state (e.g., "stable" → "falling" = starting decline)
- trend_duration_minutes: How long current trend has been active

next_price_trend_change attributes:
- timestamp: Current interval (calculation basis)
- from_direction: Current trend state (should match current_price_trend state)
- direction: Target trend state
- minutes_until_change: Time until change occurs
- current_price_now, price_at_change, avg_after_change, trend_diff_%

Impact: Users can now detect important transitions (valleys: falling→stable,
plateaus: rising→stable) and understand trend context. Both sensors update
automatically every 15 minutes with consistent information.
2025-11-16 17:09:16 +00:00
Julian Pawlowski
76dc488bb5 feat(sensors): add momentum-based trend detection with two new sensors
Added intelligent price trend analysis combining historical momentum
(weighted 1h lookback) with future outlook for more accurate trend
recognition. Introduced two complementary sensors for comprehensive
trend monitoring.

New sensors:
- current_price_trend: Shows active trend direction with duration
- next_price_trend_change: Predicts when trend will reverse

Momentum analysis (historical perspective):
- Weighted 1h lookback (4 × 15-min intervals)
- Linear weight progression [0.5, 0.75, 1.0, 1.25]
- ±3% threshold for momentum classification
- Recognizes ongoing trends earlier than future-only analysis

Two-phase trend calculation:
- Phase 1: Calculate momentum from weighted trailing average
- Phase 2: Validate with volatility-adaptive future comparison
- Combines both for final trend determination (rising/falling/stable)
- Centralized in _calculate_trend_info() with 60s cache

Volatility-adaptive thresholds:
- Existing trend sensors (1h-12h) now use adaptive thresholds
- calculate_price_trend() adjusted by market volatility:
  * LOW volatility (<15% CV): factor 0.6 → more sensitive (e.g., 3%→1.8%)
  * MODERATE volatility (15-30%): factor 1.0 → baseline (3%)
  * HIGH volatility (≥30%): factor 1.4 → less sensitive (e.g., 3%→4.2%)
- Uses same coefficient of variation as volatility sensors
- Ensures mathematical consistency across integration

Default threshold reduction:
- Rising/falling thresholds: 5% → 3% (more responsive)
- Momentum-based detection enables lower thresholds without noise
- Adaptive adjustment compensates during high volatility

Architectural improvements:
- Centralized calculation: Single source of truth for both sensors
- Eliminates Henne-Ei problem (duplicate calculations)
- 60-second cache per coordinator update
- Shared helper methods: _calculate_momentum(), _combine_momentum_with_future()

Translation updates (all 5 languages):
- Documented momentum feature in custom_translations (de/en/nb/nl/sv)
- Explained "recognizes ongoing trends earlier" advantage
- Added sensor names and state options to standard translations
- Updated volatility threshold descriptions (clarify usage by trend sensors)

Files changed:
- custom_components/tibber_prices/sensor/core.py (930 lines added)
  * New: _calculate_momentum(), _combine_momentum_with_future()
  * New: _calculate_trend_info() (centralized with cache)
  * New: _get_current_trend_value(), _get_next_trend_change_value()
  * Modified: _get_price_trend_value() (volatility-adaptive thresholds)
- custom_components/tibber_prices/sensor/definitions.py
  * Added: current_price_trend (ENUM sensor)
  * Added: next_price_trend_change (TIMESTAMP sensor)
- custom_components/tibber_prices/sensor/attributes.py
  * New: _add_cached_trend_attributes() helper
  * Support for current_trend_attributes, trend_change_attributes
- custom_components/tibber_prices/price_utils.py (178 lines added)
  * New: _calculate_lookahead_volatility_factor()
  * Modified: calculate_price_trend() with volatility adjustment
  * Added: VOLATILITY_FACTOR_* constants (0.6/1.0/1.4)
- custom_components/tibber_prices/entity_utils/icons.py
  * Added: Dynamic icon handling for next_price_trend_change
- custom_components/tibber_prices/const.py
  * Changed: DEFAULT_PRICE_TREND_THRESHOLD_RISING/FALLING (5→3%)
- custom_components/tibber_prices/translations/*.json (5 files)
  * Added: Sensor names, state options, descriptions
- custom_components/tibber_prices/custom_translations/*.json (5 files)
  * Added: Long descriptions with momentum feature explanation

Impact: Users get significantly more accurate trend detection that
understands they're ALREADY in a trend, not just predicting future
changes. Momentum-based approach recognizes ongoing movements 15-60
minutes earlier. Adaptive thresholds prevent false signals during
volatile periods. Two complementary sensors enable both status display
(current trend) and event-based automation (when will it change).
Perfect for use cases like "charge EV when next trend change shows
falling prices" or dashboard badges showing "Rising for 2.5h".
2025-11-16 12:49:43 +00:00
Julian Pawlowski
decca432df feat(sensors): add timing sensors for best_price and peak_price periods
Added 10 new timing sensors (5 for best_price, 5 for peak_price) to track
period timing and progress:

Timestamp sensors (quarter-hour updates):
- best_price_end_time / peak_price_end_time
  Shows when current/next period ends (always useful reference time)
- best_price_next_start_time / peak_price_next_start_time
  Shows when next period starts (even during active periods)

Countdown sensors (minute updates):
- best_price_remaining_minutes / peak_price_remaining_minutes
  Minutes left in current period (0 when inactive)
- best_price_next_in_minutes / peak_price_next_in_minutes
  Minutes until next period starts
- best_price_progress / peak_price_progress
  Progress percentage through current period (0-100%)

Smart fallback behavior:
- Sensors always show useful values (no 'Unknown' during normal operation)
- Timestamp sensors show current OR next period end/start times
- Countdown sensors return 0 when no period is active
- Grace period: Progress stays at 100% for 60 seconds after period ends

Dynamic visual feedback:
- Progress icons differentiate 3 states at 0%:
  * No data: mdi:help-circle-outline (gray)
  * Waiting for next period: mdi:timer-pause-outline
  * Period just started: mdi:circle-outline
- Progress 1-99%: mdi:circle-slice-1 to mdi:circle-slice-8 (pie chart)
- Timer icons based on urgency (alert/timer/timer-sand/timer-outline)
- Dynamic colors: green (best_price), orange/red (peak_price), gray (disabled)
- icon_color attribute for UI styling

Implementation details:
- Dual update mechanism: quarter-hour (timestamps) + minute (countdowns)
- Period state callbacks: Check if period is currently active
- IconContext dataclass: Reduced function parameters from 6 to 3
- Unit constants: UnitOfTime.MINUTES, PERCENTAGE from homeassistant.const
- Complete translations for 5 languages (de, en, nb, nl, sv)

Impact: Users can now build sophisticated automations based on period timing
('start dishwasher if remaining_minutes > 60'), display countdowns in
dashboards, and get clear visual feedback about period states. All sensors
provide meaningful values at all times, making automation logic simpler.
2025-11-15 17:12:55 +00:00
Julian Pawlowski
22165d038d feat(sensors): add timestamp attributes and enhance icon system
Added timestamp attributes to all sensors and enhanced the dynamic icon
system for comprehensive price sensor coverage with rolling hour support.

TIMESTAMP ATTRIBUTES:

Core Changes:
- sensor/attributes.py:
  * Enhanced add_average_price_attributes() to track extreme intervals
    for min/max sensors and add appropriate timestamps
  * Added _update_extreme_interval() helper to reduce complexity
  * Extended add_volatility_type_attributes() with timestamp logic for
    all 4 volatility types (today/tomorrow/today_tomorrow/next_24h)
  * Fixed current_interval_price timestamp assignment (use interval_data)

Timestamp Logic:
- Interval-based sensors: Use startsAt of specific 15-minute interval
- Min/Max sensors: Use startsAt of interval with extreme price
- Average sensors: Use startsAt of first interval in window
- Volatility sensors: Use midnight (00:00) for calendar day sensors,
  current time for rolling 24h window
- Daily sensors: Already used fallback to midnight (verified)

ICON SYSTEM ENHANCEMENTS:

Major Extensions:
- entity_utils/icons.py:
  * Created get_rolling_hour_price_level_for_icon() implementing
    5-interval window aggregation matching sensor calculation logic
  * Extended get_price_sensor_icon() coverage from 1 to 4 sensors:
    - current_interval_price (existing)
    - next_interval_price (NEW - dynamic instead of static)
    - current_hour_average_price (NEW - uses rolling hour aggregation)
    - next_hour_average_price (NEW - uses rolling hour aggregation)
  * Added imports for aggregate_level_data and find_rolling_hour_center_index

Documentation:
- sensor/definitions.py:
  * Updated 30+ sensor descriptions with detailed icon behavior comments
  * Changed next_interval_price from static to dynamic icon
  * Documented dynamic vs static icons for all sensor types
  * Added clear icon mapping source documentation

SENSOR KEY RENAMING:

Renamed for clarity (current_hour_average → current_hour_average_price):
- sensor/core.py: Updated value getters and cached data lookup
- sensor/definitions.py: Updated entity descriptions
- sensor/attributes.py: Updated key references in attribute builders
- coordinator.py: Updated TIME_SENSITIVE_ENTITY_KEYS set
- const.py: Updated comment documentation

Translation Updates:
- custom_translations/*.json (5 files): Updated sensor keys
- translations/*.json (5 files): Updated sensor keys

Impact:
- All sensors now have timestamp attribute showing applicable time/interval
- Icon system provides richer visual feedback for more sensor types
- Consistent sensor naming improves code readability
- Users get temporal context for all sensor values
- Dynamic icons adapt to price conditions across more sensors
2025-11-15 15:31:43 +00:00
Julian Pawlowski
e18d653233 feat(sensors): add daily aggregated price level and rating sensors
Added 6 new sensors for yesterday/today/tomorrow aggregated price
levels and ratings, following the same calculation logic as existing
current/next interval sensors.

New sensors:
- yesterday_price_level, today_price_level, tomorrow_price_level
- yesterday_price_rating, today_price_rating, tomorrow_price_rating

Implementation details:
- Added DAILY_LEVEL_SENSORS and DAILY_RATING_SENSORS in sensor/definitions.py
- Implemented _get_daily_aggregated_value() in sensor/core.py using
  existing aggregate_level_data() and aggregate_rating_data() helpers
- Extended icon support in entity_utils/icons.py for dynamic icons
- Added icon_color attributes in sensor/attributes.py with helper
  functions _get_day_key_from_sensor_key() and _add_fallback_timestamp()
- Complete translations in all 5 languages (de, en, nb, nl, sv):
  * Standard translations: sensor names
  * Custom translations: description, long_description, usage_tips

Impact: Users can now see aggregated daily price levels and ratings
for yesterday, today, and tomorrow at a glance, making it easier to
compare overall price situations across days and plan energy consumption
accordingly. Sensors use same aggregation logic as hourly sensors for
consistency.
2025-11-15 13:31:44 +00:00
Julian Pawlowski
fa40c00f67 refactor(sensors): Transform sensor platform into package 2025-11-15 11:46:54 +00:00