Tado CE Features Guide

Complete guide to all Tado CE exclusive features, configurations, and usage scenarios.

Entity ID note: All automation examples use v2.3.1 entity_ids (preserved for migrated users). Fresh v3.0.0 installs get different entity_ids — see ENTITIES.md for the mapping.

📑 Table of Contents

Multi-Home Support
API Management
Smart Polling
Thermal Analytics
Smart Comfort Analytics
Enhanced Mold Risk Assessment
Heating Cycle Detection
Enhanced Controls
Bridge API Integration
Weather Compensation
Optional Features
Per-Zone Configuration
Zone Features Toggles
Configuration Scenarios
Actionable Insights
Troubleshooting

🏠 Multi-Home Support

Available: v3.0.0 | Requirement: Multiple Tado homes/accounts | Automatic

Run multiple Tado accounts or homes in a single Home Assistant instance with full data isolation.

Overview

Each config entry is completely isolated — its own coordinator, API client, data loader, and cleanup. All per-entry state uses ConfigEntry.runtime_data instead of shared global state. A line-by-line audit across all 60 source files confirmed zero data isolation issues.

How It Works

Add a second Tado CE integration via Settings → Devices & Services → Add Integration → Tado CE
Authenticate with a different Tado account (or same account, different home)
Each home gets its own set of entities, data files, and polling schedule

Data Isolation

All data files include {home_id} suffix:

zones_{home_id}.json, ratelimit_{home_id}.json, config_{home_id}.json, etc.
Entity unique IDs include {home_id} prefix for collision avoidance
Each home has independent API quota tracking and adaptive polling

Migration from Single-Home

If upgrading from v2.3.1 (single home), migration runs automatically:

Entity unique IDs updated to include {home_id} prefix (idempotent)
Refresh token copied from config.json to entry.data
Existing automations continue to work unchanged

📊 API Management

Available: v1.0.0+ | Requirement: None | Always Enabled

Real-time tracking of your Tado API usage, helping you avoid rate limiting and understand consumption patterns.

Overview

Tado enforces API rate limits (100–20,000 calls/day depending on your plan). The official HA integration doesn't expose usage data. Tado CE solves this by:

Reading rate limit data from Tado API response headers
Auto-detecting your daily limit (100/1000/20000)
Tracking reset time, call history, and per-endpoint breakdown
Providing Test Mode to simulate low-quota scenarios

Sensors

Sensor	Friendly Name	Unit	Description
`sensor.tado_ce_api_usage`	API Usage	calls	API calls used today
`sensor.tado_ce_api_limit`	API Limit	calls	Daily API call limit
`sensor.tado_ce_api_reset`	API Reset	timestamp	When your limit resets
`sensor.tado_ce_api_status`	API Status	text	API connection status
`sensor.tado_ce_token_status`	Token Status	text	Auth token health
`sensor.tado_ce_next_sync`	Next Sync	timestamp	Next scheduled API sync
`sensor.tado_ce_polling_interval`	Polling Interval	minutes	Current polling interval
`sensor.tado_ce_call_history`	Call History	count	API call history with statistics
`sensor.tado_ce_api_call_breakdown`	API Breakdown	text	Call breakdown by endpoint type

API Status States

State	Meaning	When
`ok`	All good	Quota usage < 80%
`warning`	High usage	Quota usage > 80%
`rate_limited`	Quota exhausted	Remaining = 0
`error`	Connection issue	Failed to read rate limit data
`unavailable`	Sensor not ready	During HA restart/reload

Configuration

API History Retention:

Go to Settings → Devices & Services → Tado CE → Configure
Set "API History Retention" (0–365 days, default: 14)
Set to 0 for unlimited retention

Test Mode (v2.0.2+):

Enable "Enable Test Mode" in Configure
Integration simulates a 100 call/day API tier
Each API call increments a simulated counter (capped at 100)
All API sensors show test_mode: true attribute
Quota Reserve, Bootstrap Reserve, and Adaptive Polling all use simulated values
When real API reset is detected, simulated counter resets to 0

Usage Scenarios

Scenario 1: Monitor API Usage to Avoid Rate Limiting

automation:
  - alias: "Alert: API Usage High"
    trigger:
      - platform: state
        entity_id: sensor.tado_ce_api_status
        to: "warning"
    action:
      - service: notify.mobile_app
        data:
          title: "⚠️ Tado API Usage High"
          message: >
            API status: {{ states('sensor.tado_ce_api_status') }}.
            Usage: {{ states('sensor.tado_ce_api_usage') }} / {{ states('sensor.tado_ce_api_limit') }}.
            Resets at {{ states('sensor.tado_ce_api_reset') }}.

Scenario 2: Dashboard Card

type: entities
entities:
  - entity: sensor.tado_ce_api_usage
    name: "Calls Used Today"
  - entity: sensor.tado_ce_api_limit
    name: "Daily Limit"
  - entity: sensor.tado_ce_api_status
    name: "API Status"
  - entity: sensor.tado_ce_api_reset
    name: "Resets At"

🔄 Smart Polling

Available: v1.0.0+ | Requirement: None | Always Enabled

Automatically adjusts API polling frequency based on time of day, remaining quota, and configuration.

Overview

Smart Polling includes multiple strategies:

Day/Night Polling — more frequent during day, less at night
Adaptive Polling — auto-adjusts based on remaining quota (minimum 5 min, max 120 min)
Quota Reserve Protection — pauses polling when quota critically low (≤5%), auto-resumes after reset
Bootstrap Reserve — hard limit of 3 API calls never used, reserved for auto-recovery after reset
Custom Intervals — override with fixed intervals (1–1440 min)

Configuration

Day/Night Schedule:

Option	Default	Description
Day Start Hour	7	When "day" period starts (0–23)
Night Start Hour	23	When "night" period starts (0–23)
Custom Day Interval	Empty	Fixed interval during day (1–1440 min)
Custom Night Interval	Empty	Fixed interval during night (1–1440 min)

Optional Sensors (affect API usage):

Option	Default	API Calls Saved
Enable Weather Sensors	Off	1 call per sync
Enable Mobile Device Tracking	Off	1 call per full sync (every 6h)
Enable Home State Sync	Off	Required for Away Mode

How It Works

Adaptive Polling Formula:

Interval = (Time Until Reset / Remaining Calls) / 0.90
Clamped to: 5 min (floor) – 120 min (ceiling)

Day/Night Aware (v2.0.1):

Night period: Fixed 120 min interval to conserve quota
Day period: Adaptive based on remaining quota after reserving night calls
If Day Start == Night Start: always uses adaptive polling (24/7 mode)

Quota Reserve (v2.0.0):

Pauses polling when remaining ≤5% or ≤5 calls
Reserves quota for manual operations (set temperature, change mode)
Auto-resumes when API reset time passes

Bootstrap Reserve (v2.0.1):

Hard limit of 3 API calls never used, even for manual actions
When triggered: persistent notification "API limit reached. Use the Tado app for emergency changes."
Auto-dismisses when API reset detected

Usage Scenarios

Scenario 1: Low Quota (100 calls/day) Day/Night Setup

Day Start: 7, Night Start: 23
Custom Day Interval: 30 min, Custom Night Interval: 120 min
Weather: Off, Mobile Tracking: Off

Expected: Day 32 syncs × 2 = 64, Night 4 × 2 = 8, Full sync 4 × 2 = 8 → ~80 calls/day

Scenario 2: High Quota (1000+) Adaptive

Leave custom intervals empty. Adaptive polling uses 5-minute minimum. Enable all optional sensors. Adaptive will override if quota drops critically low.

Scenario 3: Disable Optional Sensors to Save Calls

Weather off: saves ~144 calls/day (at 10 min intervals)
Mobile tracking off: saves ~4 calls/day
Home State Sync off: saves 1 call/sync

🔥 Thermal Analytics

Available: v2.0.0+ | Requirement: Zones with heatingPower data (TRV or Smart Thermostat) | Always Enabled

Real-time analysis of heating system thermal performance based on complete heating cycles.

Sensors

Sensor	Friendly Name	Unit	Description
`sensor.{zone}_thermal_inertia`	Thermal Inertia	minutes	Time constant for temperature changes
`sensor.{zone}_avg_heating_rate`	Heating Rate	°C/h	Average heating rate when heating ON
`sensor.{zone}_preheat_time`	Preheat Time	minutes	Estimated time to reach target
`sensor.{zone}_analysis_confidence`	Confidence	%	Confidence score for analysis
`sensor.{zone}_heating_acceleration`	Heat Accel	°C/h²	Rate of change of heating rate
`sensor.{zone}_approach_factor`	Approach Factor	%/hour	How quickly zone approaches target

Sensor Interpretation

Thermal Inertia:

Low (10–30 min): Room heats/cools quickly — may indicate poor insulation or small room
Medium (30–60 min): Typical for most rooms
High (60+ min): Good insulation or large thermal mass

Heating Rate:

Slow (<0.6°C/h): Possible radiator, boiler, or insulation issues
Normal (0.6–1.8°C/h): Typical
Fast (>1.8°C/h): Small room or oversized radiator

Analysis Confidence:

<50%: Not enough data yet
50–80%: Reasonable confidence
80%: High confidence, reliable estimates

Approach Factor:

<50%/h: Slow approach, multiple hours to target
50–100%/h: Normal, 1–2 hours
100%/h: Fast approach, less than 1 hour

Configuration

Global Toggle: Options → Tado CE Exclusive → Thermal Analytics

Per-Zone Control (v2.1.0+): Options → Tado CE Exclusive → Thermal Analytics Zones

Default: All zones with heatingPower data enabled
Deselect zones that never call for heat (passive heating) to keep UI clean

Supported Devices (v2.0.1+): TRV (VA01, VA02, RU01, RU02), Smart Thermostat (SU02)

Usage Scenarios

Scenario 1: Optimize Preheat Timing

automation:
  - alias: "Bedroom Preheat"
    trigger:
      - platform: time
        at: "17:30:00"
    condition:
      - condition: numeric_state
        entity_id: sensor.bedroom_preheat_time
        above: 20
    action:
      - service: climate.set_temperature
        target:
          entity_id: climate.bedroom
        data:
          temperature: 21

Wait for _analysis_confidence > 80% before trusting preheat estimates.

Scenario 2: Detect Insulation Issues

Indicators:

Low thermal inertia (<20 min) — heat escapes quickly
Low heating rate (<0.6°C/h) — struggling to heat
High approach factor (>150%/h) — temperature fluctuates rapidly

Action: Check for drafts, verify radiator valve, check boiler flow temperature.

Scenario 3: Compare Room Performance

Room	Thermal Inertia	Heating Rate	Confidence	Status
Living Room	45 min	1.2°C/h	95%	✅ Normal
Bedroom	35 min	1.5°C/h	90%	✅ Good
Bathroom	15 min	0.6°C/h	85%	⚠️ Poor insulation
Kitchen	60 min	0.8°C/h	80%	✅ High thermal mass

Scenario 4: Detect Radiator/Boiler Problems

Watch for sudden drops in heating rate or increases in preheat time. Check radiator valve, bleed radiators, check boiler flow temperature, verify TRV battery.

🧠 Smart Comfort Analytics

Available: v1.9.0+ | Requirement: None | Opt-in Configuration

Learns from heating patterns and provides predictive insights.

Sensors

Sensor	Friendly Name	Unit	Description
`sensor.{zone}_historical_deviation`	Schedule Deviation	°C	Difference from 7-day average at same time
`sensor.{zone}_next_schedule_time`	Next Schedule	timestamp	When next schedule change occurs
`sensor.{zone}_next_schedule_temp`	Next Sched Temp	°C	Target for next schedule block
`sensor.{zone}_preheat_advisor`	Preheat Advisor	minutes	Recommended preheat start time
`sensor.{zone}_smart_comfort_target`	Comfort Target	°C	AI-recommended target temperature

Preheat Cooling Rate Prediction (v3.0.0)

The Preheat Advisor now considers cooling trends when the room is above the target temperature. Previously, if current_temp >= target_temp, it simply showed "Ready" — now it estimates when the temperature will drop below target and calculates a proactive preheat start time.

How it works:

estimate_cooling_crossover() calculates hours until temperature crosses below target using the current cooling rate
If a crossover is predicted, the advisor calculates when to start preheating to prevent undershoot
Heating rate data (from thermal analytics) is used to determine how long preheat needs

Preheat Advisor attributes (when cooling prediction active):

Attribute	Description
`cooling_rate`	Current cooling rate in °C/h (negative value)
`predicted_crossover_time`	Estimated time when temp will drop below target
`is_cooling_prediction`	`true` when cooling prediction is active
`summary`	Human-readable explanation of the prediction

Adaptive Preheat Passive Mode (v3.3.0+)

Preheat now has three modes per zone, configured via Options Flow → Zone Configuration:

Mode	Behavior
Off	Preheat disabled for this zone
Active	Always triggers preheat before the next schedule change
Passive	Only triggers when the zone is following its schedule — skips preheat if you've set a manual override from HomeKit, the Tado app, etc.

Existing users with preheat enabled are automatically migrated to Active mode. Passive mode is useful if you frequently override temperatures manually and don't want preheat fighting your changes.

Configuration

Settings → Devices & Services → Tado CE → Configure
Enable "Smart Comfort Analytics"
Configure Smart Comfort Mode: None / Light / Moderate / Aggressive
Set Temperature History days (1–30)
Optionally set Outdoor Temperature Entity for weather compensation

Usage Scenarios

Scenario 1: Detect Unusual Patterns

automation:
  - alias: "Alert: Room Colder Than Usual"
    trigger:
      - platform: numeric_state
        entity_id: sensor.bedroom_historical_deviation
        below: -2.0
    action:
      - service: notify.mobile_app
        data:
          message: "Bedroom is 2°C colder than usual — check for open windows"

Scenario 2: Automatic Preheat

automation:
  - alias: "Smart Preheat Before Schedule"
    trigger:
      - platform: template
        value_template: >
          {{ now().timestamp() >= 
             (state_attr('sensor.bedroom_next_schedule_time', 'timestamp') - 
              (states('sensor.bedroom_preheat_advisor') | int * 60)) }}
    action:
      - service: climate.set_temperature
        target:
          entity_id: climate.bedroom
        data:
          temperature: "{{ states('sensor.bedroom_next_schedule_temp') }}"

Scenario 3: Energy Optimization

automation:
  - alias: "Reduce Heating When Warmer Than Usual"
    trigger:
      - platform: numeric_state
        entity_id: sensor.living_room_historical_deviation
        above: 1.0
    condition:
      - condition: state
        entity_id: climate.living_room
        state: "heat"
    action:
      - service: climate.set_temperature
        target:
          entity_id: climate.living_room
        data:
          temperature: >
            {{ state_attr('climate.living_room', 'temperature') - 0.5 }}

💧 Enhanced Mold Risk Assessment

Available: v2.0.0+ | Requirement: Outdoor temperature sensor | Always Enabled

Uses surface temperature calculation to accurately detect cold spots where mold can grow.

Sensors

Sensor	Friendly Name	Description
`sensor.{zone}_mold_risk`	Mold Risk	Risk level: Low / Medium / High / Critical
`sensor.{zone}_mold_risk_percentage`	Mold Risk %	Numeric risk percentage
`sensor.{zone}_condensation_risk`	Condensation	Condensation risk (AC zones)
`sensor.{zone}_surface_temperature`	Surface Temp	Calculated surface temperature
`sensor.{zone}_dew_point`	Dew Point	Dew point temperature
`sensor.{zone}_comfort_level`	Comfort Level	Overall comfort assessment

Heat Index & Heat Risk (v3.3.0+)

The Comfort Level sensor now includes "feels like" temperature when it's warm (above 26.7°C), factoring in humidity using the NOAA/NWS Rothfusz regression. Risk levels appear in the sensor attributes and in comfort recommendations.

Comfort Level extra attributes (when heat index is active):

Attribute	Description
`heat_index`	Calculated "feels like" temperature (°C)
`heat_risk_level`	NOAA risk level (see table below)

Heat Risk Levels:

Risk Level	Heat Index	Guidance
None	Below 26.7°C	No heat risk
Caution	26.7–32°C	Fatigue possible with prolonged exposure
Extreme Caution	32–39°C	Heat cramps and exhaustion possible
Danger	39–51°C	Heat cramps/exhaustion likely, heatstroke possible
Extreme Danger	Above 51°C	Heatstroke highly likely

When heat index is active, the comfort level calculation uses the "feels like" temperature instead of the raw air temperature for deviation and recommendation logic.

Window Type Settings

Window Type	U-Value (W/m²K)	Mold Risk
Single Pane	5.0	⚠️ High
Double Pane	2.7	⚠️ Medium
Triple Pane	1.0	✅ Low
Passive House	0.8	✅ Very Low

Mold Risk Thresholds

Risk Level	Surface RH	Action
Low	<60%	None — safe
Medium	60–70%	Monitor, increase ventilation
High	70–80%	Action needed, increase heating
Critical	>80%	Urgent — mold growth likely

Configuration

Settings → Devices & Services → Tado CE → Configure
Select "Window Type" (default: Double Pane)
Set "Outdoor Temperature Entity" (e.g., weather.home)

Per-Zone Window Type (v2.1.0+): Use Zone Config entity select.{zone}_window_type to set different window types per zone.

Usage Scenarios

Scenario 1: Prevent Mold Growth

automation:
  - alias: "Alert: High Mold Risk"
    trigger:
      - platform: numeric_state
        entity_id: sensor.bedroom_mold_risk_percentage
        above: 70
        for:
          minutes: 30
    action:
      - service: notify.mobile_app
        data:
          title: "⚠️ High Mold Risk in Bedroom"
          message: >
            Mold risk: {{ states('sensor.bedroom_mold_risk_percentage') }}%
            Surface temp: {{ state_attr('sensor.bedroom_mold_risk', 'surface_temperature') }}°C
            Action: Increase heating or ventilate

Scenario 2: Window Upgrade ROI

Scenario	Indoor	Outdoor	Single Pane	Double Pane	Triple Pane
Winter	20°C	0°C	12.0°C (⚠️ 85% RH)	15.4°C (⚠️ 72% RH)	17.8°C (✅ 58% RH)
Cold Day	20°C	5°C	14.5°C (⚠️ 78% RH)	16.7°C (⚠️ 65% RH)	18.5°C (✅ 55% RH)
Mild Day	20°C	10°C	16.5°C (⚠️ 68% RH)	17.8°C (✅ 58% RH)	19.0°C (✅ 52% RH)

Passive Window Detection (v3.3.0+)

Detects open windows even when your heating or AC is off. Combines temperature drop speed, humidity changes, and indoor-outdoor temperature difference to tell the difference between a natural cooldown and an open window. Adjusts for your window type and is stricter in winter.

How it differs from active detection:

Mode	When It Works	How It Detects
Active	Only when heating/cooling is running	Rapid temperature drop while HVAC is active
Passive	Anytime, even when HVAC is off	Temperature drop speed + humidity + outdoor differential

Window Detection Mode Per Zone (v3.3.0+)

Choose how each zone detects open windows. Configured via Options Flow → Zone Configuration.

Mode	Behavior
Active	Only detects when heating/cooling is running (original behavior)
Passive	Detects anytime, including when HVAC is off
Auto	Picks the best method automatically — uses active when HVAC is running, passive when it's off

Sensitivity presets (per zone):

Sensitivity	Min Readings	Temp Rate Threshold	Best For
Low	4 readings	0.4°C/min	Reducing false alarms in drafty rooms
Medium	3 readings	0.25°C/min	Most rooms (default)
High	2 readings	0.15°C/min	Rooms where you want fast detection

Window Detection Events (v3.3.0+)

HA events fire when a window is detected or cleared — useful for building your own automations:

Event	When
`tado_ce_window_predicted`	Window open detected
`tado_ce_window_predicted_cleared`	Detection cleared

The Window Predicted sensor also tracks when the last detection happened, how many times today, and which detection mode was used. Daily count resets at midnight.

Smoother Detection (v3.3.0+)

The Window Predicted sensor no longer flickers on/off rapidly. It waits for several stable readings before clearing a detection (3 readings on Low sensitivity, 2 on Medium, 1 on High).

🔄 Heating Cycle Detection

Available: v2.0.0+ | Requirement: Zones with heatingPower data | Always Enabled

Identifies complete heating cycles (heating ON → target reached → heating OFF) for accurate thermal analysis.

Automatically detects complete heating cycles
Minimum cycle: 10 minutes, maximum: 4 hours
No configuration needed

Monitor cycle health via sensor.{zone}_thermal_inertia attributes:

cycle_count: Total cycles analyzed
timeout_count: Cycles that timed out
Success rate >90% = heating system working well

⚡ Enhanced Controls

Available: v1.0.0+ | Requirement: None | Always Enabled

Improved responsiveness and convenience features for climate control.

Features

1. Immediate Refresh

Dashboard updates immediately after climate control actions. Configurable debounce delay (default: 15s, range: 1–60s).

2. Boost & Smart Boost

Button	Friendly Name	Description
`button.{zone}_boost`	Boost	Quick boost: 25°C for 30 min (replicates Tado app feature)
`button.{zone}_smart_boost`	Smart Boost	Intelligent duration based on thermal analytics

⬆ Boost replicates the Tado app's boost feature. HA official doesn't expose this. Smart Boost is CE exclusive — calculates optimal duration from thermal data.

3. Climate Timer Service

# Timer mode — boost for specific duration
service: tado_ce.set_climate_timer
target:
  entity_id: climate.living_room
data:
  temperature: 22
  time_period: 60

# Overlay mode (v2.3.0+) — until next schedule change
service: tado_ce.set_climate_timer
target:
  entity_id: climate.living_room
data:
  temperature: 22
  overlay: next_time_block

# Overlay mode — indefinite
service: tado_ce.set_climate_timer
target:
  entity_id: climate.living_room
data:
  temperature: 22
  overlay: manual

v2.3.0: time_period is optional when overlay is specified. Supported: next_time_block, manual. Both Heating and AC zones.

4. Enhanced Hot Water Timer

Control hot water with AUTO/HEAT/OFF modes. Timer duration configurable (1–1440 min, default: 60).

service: tado_ce.set_water_heater_timer
target:
  entity_id: water_heater.hot_water
data:
  time_period: 60

5. Temperature Offset

Calibrate device temperature readings (range: -10°C to +10°C).

service: tado_ce.set_climate_temperature_offset
target:
  entity_id: climate.bedroom
data:
  offset: -0.5

Enable "Temperature Offset" in Configure to add offset_celsius attribute to climate entities.

6. Climate Group Support (v2.2.3+)

Target climate groups with Tado CE custom services. Groups defined in configuration.yaml are automatically expanded.

# Define group
group:
  tado_group:
    name: Tado TVR
    entities:
      - climate.bedroom
      - climate.living_room

# Use with Tado CE services
service: tado_ce.set_climate_timer
data:
  entity_id: group.tado_group
  temperature: 22
  time_period: "01:30:00"

# Resume schedule for all zones
service: tado_ce.resume_schedule
data:
  entity_id: group.tado_group

Supported services: set_climate_timer, set_water_heater_timer, resume_schedule.

7. Open Window Services (v3.1.0+)

Three services for open window management, each serving a different purpose:

Service	Purpose	When to Use
`tado_ce.activate_open_window`	Confirm Tado's own detection	Auto-Assist replacement — Tado has already detected an open window
`tado_ce.deactivate_open_window`	Cancel open window mode	Resume normal heating after window is closed
`tado_ce.set_open_window_mode`	Trigger from external sensors	Zigbee/Z-Wave contact sensors — no Tado detection needed

Set Open Window Mode is the most useful for automations. It sets the zone to frost protection (5°C) with a timer:

# Basic — uses zone's Open Window Detection timeout, or 15 min default
service: tado_ce.set_open_window_mode
target:
  entity_id: climate.bedroom

# Custom duration (seconds)
service: tado_ce.set_open_window_mode
target:
  entity_id: climate.bedroom
data:
  duration: 1800  # 30 minutes

# Indefinite — stays until manually resumed (v3.2.1+)
service: tado_ce.set_open_window_mode
target:
  entity_id: climate.bedroom
data:
  duration: 0

Duration priority: user-provided duration > zone's openWindowDetection.timeoutInSeconds > 15 min default.

Automation example — contact sensor triggers open window mode:

automation:
  - alias: "Open Window — Bedroom"
    trigger:
      - platform: state
        entity_id: binary_sensor.bedroom_window_contact
        to: "on"
    action:
      - service: tado_ce.set_open_window_mode
        target:
          entity_id: climate.bedroom
        data:
          duration: 0  # indefinite until window closes

  - alias: "Close Window — Bedroom"
    trigger:
      - platform: state
        entity_id: binary_sensor.bedroom_window_contact
        to: "off"
    action:
      - service: tado_ce.deactivate_open_window
        target:
          entity_id: climate.bedroom

8. Restore Previous State (v3.3.0+)

Puts a zone back to whatever it was doing before the last change. Works with heating, AC, and hot water.

State is saved automatically before any overlay action (timers, temperature changes, open window mode, preheat). If nothing was saved, it falls back to resuming the schedule. Saved state survives HA restarts and clears when you arrive home.

# Restore a single zone
service: tado_ce.restore_previous_state
target:
  entity_id: climate.bedroom

# Restore multiple zones
service: tado_ce.restore_previous_state
target:
  entity_id:
    - climate.bedroom
    - climate.living_room

Pairs well with open window mode:

automation:
  - alias: "Close Window — Restore State"
    trigger:
      - platform: state
        entity_id: binary_sensor.bedroom_window_contact
        to: "off"
    action:
      - service: tado_ce.restore_previous_state
        target:
          entity_id: climate.bedroom

🌉 Bridge API Integration

Available: v3.2.0+ | Requirement: Tado Internet Bridge with serial + auth key | Opt-in Configuration

Direct communication with your Tado Internet Bridge for boiler flow temperature monitoring and control. Independent from the cloud API — errors never affect main polling.

Overview

The Bridge API uses the serial number and auth key printed on the bottom of your Internet Bridge to authenticate directly with my.tado.com/api/v2/homeByBridge/{serial}/. This is separate from the OAuth-based cloud API used for zone data.

Entities

Entity	Friendly Name	Type	Description
`binary_sensor.tado_ce_{home_id}_bridge_connected`	Bridge Connected	Binary Sensor	Whether the Internet Bridge is reachable
`sensor.tado_ce_{home_id}_boiler_wiring_state`	Boiler Wiring State	Sensor	Bridge installation status (Ready / Installing / Failed)
`sensor.tado_ce_{home_id}_boiler_output_temperature`	Boiler Output Temperature	Sensor	Real-time boiler output temperature (°C)
`number.tado_ce_{home_id}_boiler_max_output_temperature`	Boiler Max Output Temperature	Number	Control max flow temperature (25–80°C, 0.5°C step)

Bridge Connected Sensor (v3.3.0+)

The Bridge Connected binary sensor shows whether your Internet Bridge is reachable. It tolerates brief hiccups — the bridge is only marked as disconnected after 3 consecutive failures, so a single timeout won't trigger a false alarm.

Attributes:

Attribute	Description
`response_time`	Last successful response time
`failure_count`	Consecutive failure count
`last_successful_connection`	Timestamp of last successful connection

Wiring State Attributes

The Boiler Wiring State sensor includes extra state attributes from the Bridge API response:

Attribute	Description
`bridge_connected`	Whether the bridge is online
`hot_water_zone_present`	Whether hot water zone is detected
`device_type`	Device wired to boiler (e.g. RU02)
`device_serial`	Serial number of the wired device
`therm_interface_type`	Connection type (OPENTHERM, eBUS, relay)
`device_connected`	Whether the wired device is connected

Configuration

Go to Settings → Devices & Services → Tado CE → Configure → Global Settings → Flow Temperature Control
Enable the Internet Bridge toggle
Enter your Bridge Serial Number (starts with IB, printed on the bottom of your Internet Bridge)
Enter your Bridge Auth Key (also printed on the bottom)
Save — credentials are validated automatically against the Bridge API

Turning off the Internet Bridge toggle automatically cleans up all bridge-related entities. V2 bridges (GW serial) aren't supported by the Bridge API.

How It Works

Bridge data is fetched during each coordinator update cycle alongside cloud API data
Bridge API errors are isolated — they never affect cloud data or trigger reauth
The boiler.outputTemperature.celsius field in the wiring state response provides real-time boiler output temperature
Max output temperature control PUTs to boilerMaxOutputTemperature endpoint

Bridge API vs Cloud API Boiler Sensors

Sensor	Source	Requires
Boiler Flow Temp	Cloud API (`activityDataPoints.boilerFlowTemperature`)	OpenTherm-connected boiler
Boiler Output Temperature	Bridge API (`boiler.outputTemperature.celsius`)	Bridge credentials
Boiler Max Output Temperature	Bridge API (`boilerMaxOutputTemperature`)	Bridge credentials

Both can coexist — they read from different data sources.

Usage Scenarios

Scenario 1: Monitor Boiler Output Temperature

type: entities
entities:
  - entity: sensor.tado_ce_{home_id}_boiler_output_temperature
    name: "Boiler Output Temp"
  - entity: sensor.tado_ce_{home_id}_boiler_wiring_state
    name: "Bridge Status"
  - entity: number.tado_ce_{home_id}_boiler_max_output_temperature
    name: "Max Flow Temp"

Scenario 2: Weather-Compensated Flow Temperature

automation:
  - alias: "Lower Flow Temp When Mild"
    trigger:
      - platform: numeric_state
        entity_id: sensor.tado_ce_hub_outside_temp
        above: 12
        for:
          hours: 2
    action:
      - service: number.set_value
        target:
          entity_id: number.tado_ce_{home_id}_boiler_max_output_temperature
        data:
          value: 45

  - alias: "Raise Flow Temp When Cold"
    trigger:
      - platform: numeric_state
        entity_id: sensor.tado_ce_hub_outside_temp
        below: 2
        for:
          hours: 1
    action:
      - service: number.set_value
        target:
          entity_id: number.tado_ce_{home_id}_boiler_max_output_temperature
        data:
          value: 65

🌡️ Weather Compensation

Available: v3.3.0+ | Requirement: Bridge API configured OR cloud outdoor temperature | Opt-in Configuration

Automatically adjusts your boiler's flow temperature based on outdoor temperature, so your heating runs more efficiently in mild weather and ramps up when it's cold.

Overview

Weather compensation uses a heating curve to map outdoor temperature to a target boiler flow temperature. When it's mild outside, the boiler runs at a lower flow temperature (saving energy). When it's cold, the flow temperature increases to maintain comfort.

The engine runs every coordinator update cycle. A 10-minute hold between adjustments prevents oscillation, and outdoor temperature is smoothed (EMA or rolling average) to avoid reacting to brief fluctuations.

Heating System Presets

Preset	Max Flow Temp	Description
Radiators Standard	65°C	Traditional radiators
Radiators Low Temp	55°C	Modern low-temperature radiators
Underfloor	45°C	Underfloor heating systems
Custom	User-defined	Full control over all parameters

Presets automatically calculate the slope from your min/max flow and design/shutoff temperatures, so the heating curve spans the full outdoor range without flat zones. Custom preset gives you full manual control over the slope.

Configuration

Go to Settings → Tado CE → Configure → Global Settings → Flow Temperature Control
Enable the Internet Bridge toggle (or use cloud outdoor temperature)
Enable Weather Compensation
Select a Heating System Preset (or choose Custom for full control)
Save — the engine starts adjusting on the next update cycle

Custom parameters (when preset = Custom):

Parameter	Default	Range	Description
Slope	1.5	0.1–3.0	Heating curve steepness
Design Outdoor Temp	-5°C	-30 to 10°C	Coldest expected outdoor temperature
Max Flow Temp	65°C	25–80°C	Maximum boiler flow temperature
Min Flow Temp	25°C	20–50°C	Minimum boiler flow temperature
Shutoff Temp	18°C	5–25°C	Outdoor temp above which heating stops
Smoothing Method	EMA	EMA / Rolling Avg	How outdoor temperature is smoothed
Smoothing Window	60 min	15–240 min	Smoothing time window
Room Compensation	Off	On/Off	Adjust flow temp based on room temperature
Room Compensation Factor	3.0	1.0–5.0	How strongly room temp affects flow temp
Step Size	1.0°C	0.5–5.0°C	Minimum change between adjustments
Hysteresis	1.0°C	0.5–5.0°C	Deadband to prevent oscillation

Sensors

Entity	Name	Description
`sensor.tado_ce_hub_ce_wc_target_flow_temp`	WC Target Flow Temp	Calculated target flow temperature
`sensor.tado_ce_hub_ce_wc_status`	WC Status	Engine status: active / paused / disabled

WC Target Flow Temp attributes:

Attribute	Description
`outdoor_temperature`	Smoothed outdoor temperature
`outdoor_temperature_raw`	Raw outdoor temperature reading
`heating_system_preset`	Active preset name
`room_compensation_offset`	Room feedback adjustment (°C)
`smoothing_method`	EMA or rolling_avg
`smoothing_window`	Smoothing window in minutes

How the Heating Curve Works

Target Flow Temp = Max Flow Temp - Slope × (Outdoor Temp - Design Outdoor Temp)

For presets, the slope is automatically calculated:

Auto Slope = (Max Flow - Min Flow) / (Shutoff Temp - Design Outdoor Temp)

This ensures the curve reaches exactly min_flow_temp at the shutoff temperature — no flat zones where outdoor changes have no effect.

Example with Radiators Standard (max 65°C, min 25°C, design -5°C, shutoff 18°C → auto-slope 1.74):

Outdoor -5°C → Flow 65°C (full power)
Outdoor 5°C → Flow 47.6°C
Outdoor 10°C → Flow 38.9°C
Outdoor 18°C+ → Heating off (shutoff)

Usage Scenarios

Scenario 1: Standard Radiator Setup

Select "Radiators Standard" preset. The default curve works well for most homes with traditional radiators. Monitor wc_target_flow_temp for a few days to verify the curve matches your comfort needs.

Scenario 2: Underfloor Heating

Select "Underfloor" preset. The gentler slope (0.8) and lower max flow temp (45°C) protect UFH systems from overheating. If your floors feel cold in very cold weather, increase the slope slightly using Custom mode.

Scenario 3: Fine-Tuning with Room Compensation

Enable Room Compensation to let the engine adjust flow temperature based on actual room temperatures. If rooms are consistently too warm, the engine reduces flow temp. If rooms are cold, it increases. The compensation factor controls how aggressively it responds.

Scenario 4: Dashboard Card

type: entities
entities:
  - entity: sensor.tado_ce_hub_ce_wc_target_flow_temp
    name: "Target Flow Temp"
  - entity: sensor.tado_ce_hub_ce_wc_status
    name: "WC Status"
  - entity: number.tado_ce_{home_id}_boiler_max_output_temperature
    name: "Current Max Flow Temp"

🔧 Optional Features

Available: Various versions | Requirement: Varies | Opt-in Configuration

Schedule Calendar

Shows heating schedules as calendar events. Enable in Configure → "Schedule Calendar".

Entity	Friendly Name
`calendar.{zone}`	Schedule

Boiler Flow Temperature

Monitors OpenTherm boiler flow temperature. Auto-detected if available.

Entity	Friendly Name
`sensor.tado_ce_boiler_flow_temperature`	Boiler Flow Temp

Device Tracking

Tracks mobile device presence (home/away). Enable "Mobile Device Tracking" in Configure.

Entity	Friendly Name
`device_tracker.tado_ce_{device_name}`	{device_name}

API usage: 1 call per full sync (every 6h). Enable "Sync Mobile Frequently" for every-poll updates.

Home State Sync & Presence Mode

Syncs home/away presence state. Enable "Home/Away State Sync" in Configure.

Entity	Friendly Name	Description
`select.tado_ce_presence_mode`	Presence Mode	Control: auto / home / away
`binary_sensor.tado_ce_home`	Home	Read-only home/away status

Overlay Mode (v2.0.2)

Controls how long manual temperature changes last.

Entity	Friendly Name
`select.tado_ce_overlay_mode`	Overlay Mode
`select.tado_ce_overlay_timer_duration`	Overlay Timer

Options:

Option	Description
Tado Mode	Follows per-device "Manual Control" settings in Tado app (default)
Next Time Block	Override lasts until next scheduled change
Manual	Infinite override until manually changed

Understanding Geofencing vs Presence Mode

Geofencing is a Tado account-level setting configured in the Tado app, not in this integration.

Scenario	"Auto" Mode Behavior
Geofencing enabled	Tado auto-switches Home/Away based on mobile locations
Geofencing disabled	Stays in current state — no automatic switching

How Presence Lock Works:

"home" or "away": Creates a presence lock that overrides geofencing
"auto": Deletes the presence lock. If geofencing enabled, Tado resumes automatic control. If disabled, state stays as-is.

Multi-Language (v3.0.0)

Config flow and options UI available in 7 languages:

Language	Code
English	`en`
German	`de`
Spanish	`es`
French	`fr`
Italian	`it`
Dutch	`nl`
Portuguese	`pt`

HA automatically selects the language based on your system locale. No configuration needed.

Common Misconception (geofencing OFF):

Home → Away → Auto = Back to Home?  ❌ WRONG
Home → Away → Auto = Stays Away     ✅ CORRECT

When geofencing is disabled, "Auto" just removes the lock — it doesn't change state. Use "Home"/"Away" directly, or use HA automations with other presence detection.

🏠 Per-Zone Configuration

Available: v2.1.0+ | Requirement: None | Opt-in via Zone Features Toggle

Customize settings for each individual zone instead of using global defaults.

Configuration Entities

Heating Zones:

Entity	Friendly Name	Type	Description
`select.{zone}_heating_type`	Heat Emitter	Select	Radiator or Underfloor Heating
`number.{zone}_ufh_buffer`	UFH Buffer	Number	Extra preheat buffer for UFH (0–60 min)

All Climate Zones:

Entity	Friendly Name	Type	Description
`switch.{zone}_adaptive_preheat`	Adaptive Preheat	Switch	Enable adaptive preheat
`select.{zone}_smart_comfort_mode`	Smart Comfort	Select	Weather compensation level
`select.{zone}_window_type`	Window Type	Select	Window insulation for mold risk
`select.{zone}_overlay_mode`	Overlay Mode	Select	How temperature changes behave
`select.{zone}_overlay_timer_duration`	Overlay Timer	Select	Timer duration
`number.{zone}_min_temp`	Min Temp	Number	Minimum temperature (5–25°C)
`number.{zone}_max_temp`	Max Temp	Number	Maximum temperature (15–30°C)
`number.{zone}_temp_offset`	Temp Offset	Number	Temperature calibration (-3.0 to +3.0°C)
`number.{zone}_surface_temp_offset`	Surface Offset	Number	Surface temp calibration

Zone Overlay Mode Options

Option	Behavior
Tado Mode	Inherit from global setting (default)
Next Time Block	Revert at next schedule change
Timer	Revert after timer duration
Manual	Stay until manually changed

Use Cases

# Living room: Manual control (stays until changed)
select.living_room_overlay_mode: Manual

# Bedroom: Timer (reverts after 30 min)
select.bedroom_overlay_mode: Timer

# Mark bathroom as UFH with 15 min buffer
select.bathroom_heating_type: Underfloor Heating
number.bathroom_ufh_buffer: 15

# Child's room: Limit max temp
number.childs_room_max_temp: 22

Migration from Global Settings

When upgrading to v2.1.0:

ufh_zones → per-zone heating_type = UFH
ufh_buffer_minutes → per-zone ufh_buffer
adaptive_preheat_zones → per-zone adaptive_preheat = ON
Global overlay_mode remains as default; zones inherit unless overridden

🎛️ Zone Features Toggles

Available: v2.1.0+ | Requirement: None | Options Flow Configuration

Control which entity types are created, reducing clutter for users who don't need all features.

Available Toggles

Toggle	Entities Controlled	Default (New)	Default (Upgrade)
Zone Diagnostics	Battery, connection, heating power sensors	OFF	ON
Device Controls	Child lock, early start switches	OFF	ON
Boost Buttons	Boost, Smart Boost buttons	OFF	ON
Environment Sensors	Mold risk, comfort level, condensation risk	OFF	ON
Thermal Analytics	Thermal inertia, heating rate, preheat time	OFF	ON
Zone Configuration	Per-zone config entities	OFF	ON

New installs: All toggles OFF for minimal setup. Enable what you need. Upgrades: All toggles ON to preserve existing entities and automations.

Configure: Settings → Devices & Services → Tado CE → Configure → "Zone Features" section.

🎯 Configuration Scenarios

Scenario 1: Small Apartment (1–2 rooms, 100 calls/day)

Adaptive Polling: Enabled (default)
Smart Comfort: Disabled (save quota)
Weather Sensors: Disabled
Mold Risk: Enabled (important for small spaces)
Window Type: Double Pane

Expected: ~80–120 calls/day, polling ~15–20 min

Scenario 2: Large House (5+ rooms, 1000+ calls/day)

Adaptive Polling: Enabled
Smart Comfort: Enabled
Weather Sensors: Enabled
Mold Risk: Enabled
Window Type: Per-zone (mix of double/triple)
Outdoor Temp: Weather integration

Expected: ~300–800 calls/day, polling ~5–10 min

Scenario 3: Energy Optimization Focus

Smart Comfort: Enabled (for preheat advisor)
Thermal Analytics: Monitor closely
Key sensors: _preheat_time, _historical_deviation, _avg_heating_rate
Automations: Preheat before schedule, reduce when warmer than usual

Scenario 4: Mold Prevention Focus

Mold Risk: Enabled
Window Type: Accurate setting per zone
Outdoor Temp: Required
Key sensors: _mold_risk, surface_temperature (attribute), _comfort_level
Automations: Alert when mold risk >70%, auto-ventilation

Scenario 5: Low Quota (100 calls/day) Detailed

Day Start: 7, Night Start: 23
Custom Day Interval: 30 min
Custom Night Interval: 120 min
Weather: Off, Mobile Tracking: Off, Home State Sync: Off
Smart Comfort: Off, Schedule Calendar: Off

Day (16h): 32 syncs × 2 = 64 calls
Night (8h): 4 syncs × 2 = 8 calls
Full sync (6h): 4 × 2 = 8 calls
Total: ~80 calls/day (20% buffer)

Scenario 6: High Quota (1000+) All Features

Custom Intervals: Empty (use adaptive)
All features: On
Sync Mobile Frequently: On
Smart Comfort Mode: Moderate
History Days: 30

Expected: ~576 calls/day at ~5 min intervals

Scenario 7: Mixed Zone Types (Heating + AC)

Feature	Heating Zones	AC Zones
Thermal Analytics	✅ Available	❌ No heatingPower data
Smart Comfort	✅ Heating patterns	✅ Cooling patterns
Condensation Risk	❌ N/A	✅ AC-specific
Weather Impact	Moderate	High (solar gain)

Scenario 8: OpenTherm Boiler

Auto-detected via sensor.tado_ce_boiler_flow_temperature. Monitor flow temp alongside zone heating rates to detect boiler issues.

automation:
  - alias: "Alert: Low Boiler Flow Temperature"
    trigger:
      - platform: numeric_state
        entity_id: sensor.tado_ce_boiler_flow_temperature
        below: 45
        for:
          minutes: 30
    condition:
      - condition: template
        value_template: "{{ states('climate.living_room') == 'heat' }}"
    action:
      - service: notify.mobile_app
        data:
          title: "⚠️ Low Boiler Flow Temperature"
          message: "Flow temp: {{ states('sensor.tado_ce_boiler_flow_temperature') }}°C"

💡 Actionable Insights

Available: v2.2.0+ | Requirement: None | Always Enabled

Intelligent, context-aware recommendations across all zones for comfort, mold prevention, and energy optimization.

v3.0.0 Insight Enhancements

Smarter Summary

Home insights sensor now produces action-based summaries instead of generic counts:

Before: "3 actions needed across 2 zones"
After: "Replace batteries: Guest, Lounge — Mold risk: Bedroom"

Top-priority insight drives summary text. Actions grouped by type across zones.

Correlation / Deduplication

Related insights within a zone are automatically merged into a single action:

Mold risk + humidity trend + condensation → single "humidity problem" action
Configurable correlation groups in CORRELATION_GROUPS
Cross-zone insights excluded from correlation

History & Trending

Persistent tracking of insight appearance/disappearance (survives HA restarts):

Stored in .storage/tado_ce/insight_history_{home_id}.json
Duration-aware messages appended to recommendations ("persisting for 3 days")
Weekly digest attribute with most frequent insight types and 7-day rolling window
Auto-pruning of entries older than 30 days

Priority Escalation

Auto-escalation rules based on persistence duration:

Battery low > 7 days → high, > 14 days → critical
Mold risk > 3 days → high, > 7 days → critical
Monotonic escalation (never downgrades). Capped at CRITICAL.
Configurable via ESCALATION_RULES

Health Score

Numeric 0-100 score reflecting overall home health:

Based on active insight count and severity
Exposed as insight_health_score attribute on Home Insights sensor
100 = no active insights, lower = more/worse issues

Home Insights Sensor

sensor.tado_ce_home_insights — hub-level aggregation:

State: Total number of active insights (integer)
Attributes: critical_count, high_count, medium_count, low_count, top_priority, top_recommendation, zones_with_issues, cross_zone_insights

Zone Insights Sensor

sensor.{zone}_insights — per-zone insights:

State: Number of active insights for this zone
Attributes: top_priority, top_recommendation, insight_types, recommendations
Dynamic icon: Changes based on highest priority

Insight Types

Zone-level insights:

Insight	Priority	Trigger
Mold Risk	Critical/High/Medium	Dew point margin < 7°C
Comfort Level	High/Medium	Temperature outside 18–24°C
Window Predicted	High	Rapid temperature drop
Battery Low	Critical/Low	Device battery LOW/CRITICAL
Device Offline	High	Connection lost
Preheat Timing	Medium	Preheat time exceeds schedule gap
Schedule Deviation	Medium	Consistent deviation from schedule
Heating Anomaly	High	Power ≥80% but temp change <0.5°C for 60+ min
Condensation Risk	Medium/High/Critical	AC zone condensation detected
Overlay Duration	Medium/High	Manual override active too long
Frequent Override	Medium	Multiple manual overrides recently
Heating Off Cold Room	High	Heating off but room below comfort
Early Start Disabled	Low	Preheat feature not enabled
Poor Thermal Efficiency	Medium/High	Below expected threshold
Schedule Gap	Medium	Large gap leaving zone unheated
Boiler Flow Anomaly	High	Flow temp outside expected range
Humidity Trend	Medium	Sustained rising humidity
Device Limitation	Low	Hardware limitations affecting features

Home-level insights (in sensor.tado_ce_home_insights only):

Insight	Priority	Trigger
Cross-Zone Mold	High	3+ zones with Medium+ mold risk
Cross-Zone Windows	High	2+ zones with window predicted open
Cross-Zone Condensation	High	Multiple zones with condensation
Cross-Zone Efficiency	Medium	Significant efficiency variation
Temperature Imbalance	Medium	Large temp difference between zones
Humidity Imbalance	Medium	Large humidity difference
Away Heating Active	High	Away mode but heating still active
Home All Off	Low	Everyone home but all heating off
Solar Gain	Low	Solar gain detected
Solar AC Load	Medium	Strong solar increasing AC load
Frost Risk	Critical	Outdoor temp near freezing
Heating Season Advisory	Low	Seasonal guidance
Geofencing Offline	High	Mobile device for geofencing offline
API Usage Spike	Medium/High	Unusual API call rate spike
API Quota Planning	Medium/High	Projected exhaustion <6h before reset
Weather Impact	Medium	Outdoor temp >5°C below 7-day average

Recommendation Attributes

These sensors include a recommendation attribute with actionable guidance:

sensor.{zone}_mold_risk — specific humidity/temperature changes needed
sensor.{zone}_comfort_level — context-aware (considers if HVAC is active)
sensor.{zone}_condensation_risk — AC-specific prevention
sensor.{zone}_battery — battery replacement reminders
sensor.{zone}_connection — device troubleshooting
sensor.tado_ce_api_status — quota management suggestions

Empty string when no action needed.

Usage Scenarios

Scenario 1: Dashboard Overview

type: entities
entities:
  - entity: sensor.tado_ce_home_insights
    name: "Active Insights"
  - type: attribute
    entity: sensor.tado_ce_home_insights
    attribute: top_priority
    name: "Top Priority"
  - type: attribute
    entity: sensor.tado_ce_home_insights
    attribute: top_recommendation
    name: "Top Action"

Scenario 2: Alert on Critical Insights

automation:
  - alias: "Alert: Critical Home Insight"
    trigger:
      - platform: state
        entity_id: sensor.tado_ce_home_insights
        attribute: top_priority
        to: "critical"
    action:
      - service: notify.mobile_app
        data:
          title: "🚨 Critical Home Issue"
          message: >
            {{ state_attr('sensor.tado_ce_home_insights', 'top_recommendation') }}

🔧 Troubleshooting

Thermal Analytics Shows "Unknown"

Causes: Zone doesn't report heatingPower, not enough cycles (need 3–5), heating always on (no complete cycles).

Solution: Check sensor.{zone}_heating exists, wait 2–3 days, verify cycle_count attribute > 0, ensure heating turns on/off regularly.

Inaccurate Thermal Analytics Values

Causes: Low confidence (<50%), recent room changes, external heat sources.

Solution: Wait for confidence >80% (5–10 heating cycles). Avoid room changes during data collection.

Heating Efficiency >200%

Normal! Means free heat from solar gain, cooking, appliances, or people. No action needed — consider reducing target to save energy.

Mold Risk Always Shows "Room Temperature"

Causes: Outdoor temperature entity not configured, sensor unavailable, window type not set.

Solution: Configure outdoor temp entity, verify sensor works, set window type. Check temperature_source attribute — should show "surface_estimation".

Adaptive Polling Too Slow

Causes: Low remaining quota, custom interval too high, many zones consuming quota.

Solution: Check sensor.tado_ce_api_usage, disable custom interval for pure adaptive, disable optional features, check if Test Mode is enabled.

Smart Comfort Sensors Not Appearing

Causes: Not enabled, integration not restarted, not enough historical data.

Solution: Enable "Smart Comfort Analytics" in Configure, restart HA, wait 24–48 hours.

API Rate Limit Exceeded

Causes: Too many manual actions, polling too short, too many optional features, multiple HA instances.

Solution: Increase polling intervals, disable optional features (Weather, Mobile Tracking), wait for reset (sensor.tado_ce_api_reset), ensure single HA instance.

Schedule Calendar Not Showing Events

Causes: Not enabled, no schedules in Tado app, calendar integration not loaded.

Solution: Enable "Schedule Calendar", restart HA, verify schedules exist in Tado app.

Boiler Flow Temperature Not Detected

Causes: Boiler not OpenTherm-compatible, Tado system doesn't support OpenTherm.

Solution: Verify boiler supports OpenTherm, check Tado app for flow temp data.

Bridge API Sensors Showing "Unknown"

Causes: Wrong data path (fixed in v3.2.2), bridge credentials invalid, bridge offline.

Solution: Update to v3.2.2+, verify credentials in Configure → Bridge Configuration, check bridge is online. Enable debug logging:

logger:
  default: info
  logs:
    custom_components.tado_ce.bridge_api: debug
    custom_components.tado_ce.sensor_bridge: debug
    custom_components.tado_ce.coordinator: debug

Look for Bridge API full response in logs to verify the API is returning data.

Device Tracking Not Working

Causes: Not enabled, geo-tracking not enabled in Tado app, no mobile devices registered.

Solution: Enable "Mobile Device Tracking", enable geo-tracking in Tado app, wait for next full sync (6h).

Temperature Offset Not Applying

Causes: Offset attribute not enabled, value out of range, service call failed.

Solution: Enable "Temperature Offset" in Configure, verify offset within range (-10 to +10°C), check HA logs.

Preheat Advisor Shows 0 Minutes

Causes: Already at target, heating rate unknown, next schedule temp same as current.

Solution: Check current vs next schedule temp, wait for thermal analytics data (3–5 cycles), verify _avg_heating_rate has valid value.

📚 Related Documentation

ENTITIES.md — Complete entity reference (86 entities)
README.md — Installation and setup
API_REFERENCE.md — Technical API details
ROADMAP.md — Planned features and ideas

Last Updated: v3.3.0 (2026-03-21)

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Tado CE Features Guide

📑 Table of Contents

🏠 Multi-Home Support

Overview

How It Works

Data Isolation

Migration from Single-Home

📊 API Management

Overview

Sensors

API Status States

Configuration

Usage Scenarios

Scenario 1: Monitor API Usage to Avoid Rate Limiting

Scenario 2: Dashboard Card

🔄 Smart Polling

Overview

Configuration

How It Works

Usage Scenarios

Scenario 1: Low Quota (100 calls/day) Day/Night Setup

Scenario 2: High Quota (1000+) Adaptive

Scenario 3: Disable Optional Sensors to Save Calls

🔥 Thermal Analytics

Sensors

Sensor Interpretation

Configuration

Usage Scenarios

Scenario 1: Optimize Preheat Timing

Scenario 2: Detect Insulation Issues

Scenario 3: Compare Room Performance

Scenario 4: Detect Radiator/Boiler Problems

🧠 Smart Comfort Analytics

Sensors

Preheat Cooling Rate Prediction (v3.0.0)

Adaptive Preheat Passive Mode (v3.3.0+)

Configuration

Usage Scenarios

Scenario 1: Detect Unusual Patterns

Scenario 2: Automatic Preheat

Scenario 3: Energy Optimization

💧 Enhanced Mold Risk Assessment

Sensors

Heat Index & Heat Risk (v3.3.0+)

Window Type Settings

Mold Risk Thresholds

Configuration

Usage Scenarios

Scenario 1: Prevent Mold Growth

Scenario 2: Window Upgrade ROI

Passive Window Detection (v3.3.0+)

Window Detection Mode Per Zone (v3.3.0+)

Window Detection Events (v3.3.0+)

Smoother Detection (v3.3.0+)

🔄 Heating Cycle Detection

⚡ Enhanced Controls

Features

1. Immediate Refresh

2. Boost & Smart Boost

3. Climate Timer Service

4. Enhanced Hot Water Timer

5. Temperature Offset

6. Climate Group Support (v2.2.3+)

7. Open Window Services (v3.1.0+)

8. Restore Previous State (v3.3.0+)

🌉 Bridge API Integration

Overview

Entities

Bridge Connected Sensor (v3.3.0+)

Wiring State Attributes

Configuration

How It Works

Bridge API vs Cloud API Boiler Sensors

Usage Scenarios