Updated the translations for various price phase sensors in the sensor reference documentation to ensure consistency and accuracy across multiple languages.
Impact: Users will see improved clarity in the documentation for price phase sensors in their preferred language.
automation-examples.md:
- Add info callout blocks with "Blueprint available" badges and
one-click import links for each appliance section (dishwasher,
washing machine, dryer, EV charging, pipeline)
- Update YAML examples to reflect current service API (remove
relaxation_applied template, fix indentation)
sensor-reference.md:
- Remove stale data-refs attributes from current_price_trend,
next_price_trend_change, and today_volatility anchors
examples/:
- Add examples/scripts/ directory with placeholder for
tibber_notify_residents.yaml script example
User-Impact: none
Introduce additional sensors for current price phase, phase duration, and upcoming phase timings to enhance user visibility of pricing dynamics.
Impact: Users can now monitor current price phases and their durations, improving decision-making based on real-time pricing information.
Revised the descriptions and names for the previous interval price rank entities across multiple language translation files to enhance clarity and consistency.
Impact: Users will see improved terminology in the interface, making it clearer that the ranks refer to the previous interval's prices.
Updated the sensor reference documentation to remove obsolete price phase sensors, ensuring clarity and relevance for users.
Impact: Users will see a cleaner and more accurate list of available sensors.
Introduced comprehensive documentation for price phase sensors, detailing their functionality and usage. Updated links in existing documentation for clarity.
Impact: Users can now understand and utilize price phase sensors effectively in their configurations.
Rename the three existing price rank sensors from price_rank_* to
current_interval_price_rank_* to clarify they rank the current
quarter-hour interval's price, not a daily aggregate — consistent with
current_interval_price_level / current_interval_price_rating naming.
Add 8 new rank sensors covering additional subjects and reference windows:
- next_interval_price_rank_{today,today_tomorrow}
- previous_interval_price_rank_{today,today_tomorrow}
- current_hour_price_rank_{today,today_tomorrow} (5-interval rolling avg)
- next_hour_price_rank_{today,today_tomorrow} (5-interval rolling avg)
All new sensors are disabled by default. The volatility calculator gains a
subject parameter (_get_subject_price / _get_subject_price_attr_key /
_get_rolling_hour_avg_price) to select which price to rank. Sensor key
routing in value_getters.py and attributes/__init__.py updated accordingly.
No migration entries needed — the original price_rank_* sensors were never
released to users.
All 5 translation files updated. sensor-reference.md regenerated (129 entities).
Impact: Users can now track price rank for the next interval (look-ahead),
the previous interval (logging), and rolling hourly averages — for both
same-day and two-day reference windows.
Update sensors-volatility.md to cover the three new price rank sensors and the
IQR-based volatility attributes (typical price band / price spike count).
Section headers include technical terms in parentheses for experts:
"Typical Price Band Statistics (IQR)" and "Price Rank Sensors (Percentile Rank)".
Attribute tables list Tukey fence formulas and plain-language explanations
side-by-side.
Regenerate sensor-reference.md to include price_rank_today,
price_rank_tomorrow, and price_rank_today_tomorrow with translations for all
five supported languages.
Impact: Users have full documentation for the new sensors including examples,
formulas, and a multi-language lookup table.
Introduces a new day_pattern.py module that analyses the 15-min price curve
for each calendar day (yesterday/today/tomorrow) and classifies its shape.
New sensors:
day_pattern_yesterday / day_pattern_today / day_pattern_tomorrow
EntityCategory.DIAGNOSTIC, SensorDeviceClass.ENUM
Patterns: valley, peak, double_valley, double_peak, flat, rising, falling, mixed
The detector uses centred-rolling smoothing, prominence-filtered extrema,
Kneedle-based knee detection, and monotone segment building.
Coordinator populates transformed_data["dayPatterns"] after priceInfo enrichment.
Impact: Users can trigger automations based on the shape of the day's price
curve, e.g. pre-heat when tomorrow is a valley day.
Add a comprehensive entity reference system that helps users find
entities across all 5 supported languages (EN, DE, NO, NL, SV).
Core components:
- Generator script (scripts/docs/generate-sensor-reference) that
builds sensor-reference.md from translation files with --check
mode for CI validation
- EntityRef component for compact inline entity annotations with
tooltip and version-aware linking to the reference table
- EntitySearch component with live filtering, clickable results,
keyboard navigation, "/" shortcut to focus, category filter chips,
match highlighting, copy-entity-ID button per row, back-links to
documentation pages, persistent row highlights, hash-based deep
linking, and mobile-responsive layout
- MDXComponents theme override for global component registration
Documentation updates:
- New sensor-reference.md page (115 entities x 5 languages)
- EntityRef annotations across 10 documentation pages
- Sidebar entry for quick navigation
- CI integration (docusaurus.yml + scripts/check)
- Ruff per-file-ignores for scripts/ (T201, INP001)
Impact: Users can now find any entity by its localized display name
regardless of their UI language. Inline EntityRef annotations link
directly to the multi-language lookup table with version-aware URLs.
