First part of Milestone 1: Forecast Error sensors scoring the thermal model against reality, forecast trajectories, Learning Progress and Last Sample sensors, rejected-sample and poll-outcome counters, plus lint and rollback-contract tests. README explains forecast accuracy, the 30-minute learning wait after a restart and where Developer Tools now lives. ROADMAP marks the items now backed by tests; AUDIT records the evaluation design and evidence. Still observation-only. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
171 lines
8.4 KiB
Markdown
171 lines
8.4 KiB
Markdown
# Changelog
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Engineering findings and test evidence behind each change are in [AUDIT.md](AUDIT.md).
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## 0.3.0 — 2026-10-26
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First part of Milestone 1: the integration now measures how accurate its thermal
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model is. Still **observation-only**; no new options. Upgrading from an earlier
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version: also read the notes of each version in between.
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### Added
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- Four sensors, **Heating MPC Forecast Error 15/30/60/120 min**: the thermal
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model's mean absolute error over the last 7 days, scored out of sample against
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what actually happened, using the relay's real ON/OFF history. Attributes show
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the bias, the error of a no-change forecast (`persistence_mae`), `skill` and
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per-room details. See README, "Forecast accuracy".
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- **Heating MPC Learning Progress** (% towards forecasts being used) and **Heating
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MPC Last Sample** (what the last poll did for learning, with English and Romanian
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state names), so learning activity is visible without opening attributes.
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- Room forecast entities: `forecast_15min` (temperature every 15 minutes over the
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horizon) and `plan_15min` (the proposed ON/OFF plan), labelled counterfactual.
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- Status: `rejected_samples` per room in `models`, `sample_results_since_start`
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counting how each poll was handled, and `sample_result: waiting_for_inputs` when
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the relay, thermostat, outdoor temperature or every room is missing.
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### Changed
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- The model is saved after each poll's forecasts are scored, with the forecast
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statistics (about 8 KB for five rooms, at most 18 KB).
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### Upgrade notes
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- Six new entities appear (four forecast-error sensors, learning progress, last
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sample). The error sensors stay unknown until forecasts can be scored: 15 minutes after
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start for the 15-minute sensor, 2 hours for the 120-minute one. Early numbers
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include the learning phase and are pessimistic.
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- Rollback to 0.2.x is safe: older versions ignore the new saved keys, and the six
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new sensors become unavailable (remove them in the entity settings if you roll back
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permanently).
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### Development
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- Bug-finding lint (ruff: pyflakes, bugbear) in the checks and CI.
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- Tests for restoring a model saved by 0.2.1 and for 0.2.1 being able to read
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today's saved model.
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- `.DS_Store` files are ignored and rejected by the package check.
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## 0.2.3 — 2026-10-26
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A stale or failed room sensor no longer pauses the whole integration. Still
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**observation-only**. Upgrading from 0.2.1 (0.2.2 was not deployed): follow the
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0.2.2 upgrade notes below as well.
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### Changed
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- A room sensor that is stale, unavailable, missing or invalid is now **left out**
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instead of pausing everything: the weighted temperature, learning and forecasts
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continue with the other rooms, whose comfort weights are re-normalized. Learning
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and forecasts pause only if no room is usable, or if the relay, thermostat or
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outdoor temperature is missing. Readiness considers only the rooms used.
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### Added
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- Checkbox **Keep using the last value of a room sensor that stopped reporting**
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(setup and Configure, default off), for sensors that report only when the value
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changes. A stale sensor's last value is then still used, for up to 24 hours
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without a report. Unavailable or invalid sensors are always left out.
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- Status attributes `excluded_rooms` and `weight_coverage` (share of the total
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comfort weight covered by the rooms used), and a per-room `used` flag in
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`input_quality`.
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- Integration icon (a radiator with a forecast curve) in **Settings → Devices &
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services**, with a dark-theme variant. Needs Home Assistant 2026.3 or newer;
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older versions show the generic placeholder.
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### Upgrade notes
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- The new checkbox appears in **Configure**; existing installations start with it
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off. If a room is often listed in `excluded_rooms` while its temperature is
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steady, either raise that room's report-age limit or turn the checkbox on.
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- Rollback to 0.2.2 or 0.2.1 is safe; older versions ignore the new setting.
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## 0.2.2 — 2026-10-26 (not deployed)
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Reliability release (Milestone 0). Still **observation-only**: the integration never
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calls the relay, the thermostat or any other service. No new options or UI text;
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entity IDs and settings carry over. Tested in a Home Assistant Core test harness
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with HA 2025.12.0 and 2026.2.3; not yet tested on HAOS or with real devices.
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### Upgrade notes
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- Back up Home Assistant, replace `custom_components/heating_mpc`, restart Core.
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- Saved models load, but coefficients learned by 0.2.1 were fitted with a broken
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radiator-lag estimate (see Fixed). Either let them re-converge over a few days of
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heating, or reset the model: disable the integration, delete
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`/config/.storage/heating_mpc.<entry_id>`, restart Core, enable it again. Deleting
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the file while the integration runs does not work; it saves the model again.
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Deleting and re-adding the integration also resets it, but loses the settings.
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- After each HA restart, learning pauses for about 30 minutes
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(`sample_result: lag_uncertain`) because the radiator state is unknown.
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Forecasts continue.
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- After a day of running, compare each sensor's `max_age_seconds_24h` in Status
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with the freshness limits in Configure (see README, "Choosing freshness limits").
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- Rollback: restore the previous folder (or the backup) and restart. 0.2.1 reads
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models saved by 0.2.2 and ignores the new keys.
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### Fixed
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- The radiator-lag estimate jumped to fully hot or fully cold at every relay
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change. In simulation this learned the heating gain about a third too low, and
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forecasts made just after a boiler cycle started from the wrong state.
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- The learner's covariance grew without limit during long OFF periods (for
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example a summer), which could destabilize learning when heating resumed and
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eventually make a restart discard the saved model.
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- Optional weather sources could not be removed in Configure.
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- A finished forecast was discarded, making proposed heat unavailable for five
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minutes, when only a diagnostic weather sensor or the thermostat's current
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temperature changed during the calculation.
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- Config entries from 0.1 were not migrated.
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- Forecast entities of removed rooms stayed in the entity registry.
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- Malformed or physically implausible saved models could crash setup or be used.
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- ON/OFF readiness counts included rejected samples and other rooms' history.
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- Polls 4–7 minutes apart, or containing a relay change, were learned as normal
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5-minute samples.
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- Thermostat targets were read as Celsius on Fahrenheit installations.
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- Invalid room weights or optimizer settings could cause crashes.
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- 30/45-minute horizons reported their end point as a 60-minute forecast.
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### Added
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- Room and weather report-age limits in setup and Configure (5–1440 minutes,
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defaults 30 and 120). Stale outdoor sources fall back to the next one; a stale
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room pauses learning and forecasts until it reports again.
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- A read-only listener on the relay, so all relay changes between polls are
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timestamped and integrated.
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- Models of rooms removed in Configure are kept (up to 24) and restored if the
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room is added back.
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- Status attributes: `input_quality` (per-source state and report age, including
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`max_age_seconds_24h`), `heat_lag`, `heat_lag_uncertainty`, `sample_result`,
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`retired_room_models`, and per-room accepted ON/OFF counts in `models`.
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- Statuses `invalid_weights` and `inputs_changed`.
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### Changed
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- Readiness now also requires 30 accepted ON and 30 accepted OFF samples per room.
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- Learning skips intervals with a relay change, an outdoor-source switch or an
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uncertain lag estimate, and polls not 270–330 seconds apart.
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- `input_quality` and `weather_comparison` are no longer written to the Recorder;
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they change every poll. Other attributes are still recorded.
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### Persisted data
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- Model payload `schema_version` 2 (0.2.1 wrote no version). Optional keys:
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per-room `on_count`/`off_count` and `retired_learners`. Older readers ignore them.
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### Development
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- Home Assistant Core test harness for HA 2025.12.0 and 2026.2.3, a Gitea Actions
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matrix over both, package and translation validation, and a static test that
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fails if actuator service calls are added.
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## 0.2.1
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- Corrects the manifest classification from `helper` to `service`. Existing config
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entries move from Helpers to **Settings → Devices & services → Integrations**
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after replacing the files and restarting Home Assistant Core.
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- Deleting the config entry removes its entities and the learned model
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(`.storage/heating_mpc.<entry_id>`). The component folder stays until removed
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manually.
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- MPC behavior otherwise unchanged; read-only / shadow-only.
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