TADO° thermostat
This guide will be based on importing a ready-made flow and then modify the configuration. This is an advanced flow that aim to demonstrate more than just live input.
Features
- Query API to determine configuration options.
- Live updates with dynamic down-sampling.
- Historic imports of:
- specific dates
- time range
- nightly updates
- Dynamic down-sampling of live updates.
Data read by flow
- Zone day report (historic and nightly data):
- Call for heating (enum)
- Sun status (enum)
- Humidity (percentage)
- Inside temperature (degrees Celsius)
- Outside temperature (degrees Celsius)
- Local weather (live data):
- Outside temperature (degrees Celsius)
- Sun intensity (percentage)
- Zone state (live data):
- Humidity (percentage)
- Inside temperature (degrees Celsius)
Prequisite
Before continuing this guide, you need the following.
Physical equipment:
You need to have access to compatible equipment from https://www.tado.com/ that are installed and working. The guide is tested with Tado° Smart Radiator Thermostat V3+.
Credentials:
You need to have the following credentials at hand:
- The username and password you use for tado.com, or the Tado app.
- A Clarify credentials.json file. See Clarify credentials.
Node-RED instance:
You need access to a Node-RED instance with Node version 12 or later. See Introduction to Node-RED for installation options. If you are running your own Node-RED instance through Docker, make sure you use one of the tags that include -12, e.g. latest-12.
Install dependecies
For this flow to work, you need to install the following plugins under "Mange palette" > "Install":
node-red-contrib-clarifynode-red-contrib-credentialsnode-red-contrib-tado-client
Be sure to install node-red-contrib-tado-client and not the conflicting node-red-contrib-tado.
Import flow
Copy the JSON below to your clipboard.
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times.push(time.toISOString());\n values.push(v);\n\n time.setHours(time.getHours()+gapFillHours);\n }\n });\n return {\n times: times,\n values: values,\n };\n}\n\nfunction parseDataPoints(dataPoints, valueConf) {\n const times = [];\n const values = [];\n \n dataPoints.forEach(function(point) {\n let v = getValue(point.value, valueConf)\n \n times.push(point.timestamp);\n values.push(v);\n });\n return {\n times: times,\n values: values,\n };\n}\n\nfunction parseDataState(state, valueConf) {\n return {\n times: [state.timestamp],\n values: [getValue(state, valueConf)],\n };\n}\n\n\nfunction getValue(source, valueConf) {\n let conf = valueConf || {};\n let toEnum = conf.toEnum || null;\n let v = getPath(source, conf.path);\n \n // Convert string value to numeric value.\n if (toEnum != null) {\n v = toEnum[String(v)];\n }\n \n // Apply offsett and multiplier.\n let o = valueConf.offset || 0;\n let m = valueConf.multiplier || 1;\n v = o+v*m;\n\n return v;\n}\n\n\n// Get sourcePaths 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config","props":[{"p":"payload"},{"p":"topic","vt":"str"}],"repeat":"","crontab":"","once":true,"onceDelay":0.1,"topic":"","payload":"","payloadType":"date","x":130,"y":400,"wires":[["297a0746.2f885"]]},{"id":"297a0746.2f885","type":"credentials","z":"6f9e4912.43c788","g":"aefe6eea.38e218","name":"home info","props":[{"value":"homeId","type":"msg"},{"value":"zoneId","type":"msg"}],"x":300,"y":400,"wires":[["ed3c06f6.f79f78"]]},{"id":"ed3c06f6.f79f78","type":"function","z":"6f9e4912.43c788","g":"aefe6eea.38e218","name":"flow config","func":"// Code added here will be run once\n// whenever the node is started.\nconst homeId = msg.homeId;\nconst zoneId = msg.zoneId;\n\nflow.set(\"homeId\", homeId);\nflow.set(\"zoneId\", zoneId);\n\n// FIXME: insert node annotation support is broken.\nconst commonAnnotations = {\n \"tado-com/collection-method\": `${msg.topic}`,\n \"tado-com/home-id\": `${homeId}`,\n \"tado-com/zone-id\": `${zoneId}`,\n}\n\nconst zoneLabels = {\n \"data-source\": [\"Tado°\"],\n \"location\": [\"My Home\", \"Living Room\"],\n};\nconst homeLabels = {\n \"data-source\": [\"Tado°\"],\n \"location\": [\"My Home\"],\n};\n\n// zoneDayReportPaths lists a series of paths to extract\n// information from from getZoneDayReport responses.\nconst zoneDayReportPaths = [\n {\n path: [\"measuredData\", \"insideTemperature\"],\n value: {\n path: [\"celsius\"],\n },\n topic: `${homeId}-${zoneId}-zr-temp`,\n signal: {\n name: \"Inside temperature\",\n type: \"numeric\",\n engUnit: \"°C\",\n gapDetection: \"PT1H\",\n labels: zoneLabels,\n },\n },\n {\n path: [\"measuredData\", \"humidity\"],\n value: {\n multiplier: 100,\n },\n topic: `${homeId}-${zoneId}-zr-humidity`,\n signal: {\n name: \"Relative humidity\",\n type: \"numeric\",\n engUnit: \"%\",\n gapDetection: \"PT1H\",\n labels: zoneLabels,\n },\n },\n {\n path: [\"weather\", \"condition\"],\n value: {\n path: [\"temperature\", \"celsius\"],\n gapFillHours: 4,\n },\n topic: `${homeId}-r-out-temp`,\n signal: {\n name: \"Outside temperature\",\n engUnit: \"°C\",\n gapDetection: \"PT4H1S\",\n sourceType: \"aggregation\",\n labels: homeLabels,\n },\n },\n {\n path: [\"callForHeat\"],\n value: {\n toEnum: {\n \"NONE\": 0,\n \"LOW\": 2,\n \"MEDIUM\": 3,\n \"HIGH\": 4,\n },\n gapFillHours: 6,\n },\n topic: `${homeId}-${zoneId}-zr-heat-call`,\n signal: {\n name: \"Call for heating\",\n type: \"enum\",\n sourceType: \"aggregation\",\n enumValues: {\n \"0\": \"Off\",\n \"2\": \"Low\",\n \"3\": \"Medium\",\n \"4\": \"High\",\n },\n gapDetection: \"PT6H1S\",\n labels: zoneLabels,\n },\n },\n {\n path: [\"weather\", \"sunny\"],\n value: {\n toEnum: {\n \"false\": 0,\n \"true\": 1,\n },\n gapFillHours: 12,\n },\n topic:`${homeId}-zr-sun`,\n signal: {\n name: \"Sun\",\n gapDetection: \"PT12H1S\",\n sourceType: \"aggregation\",\n type: \"enum\",\n enumValues: {\n \"0\": \"Not sunny\",\n \"1\": \"Sunny\",\n },\n labels: homeLabels,\n },\n },\n];\n\n// zoneDayReportPaths lists a series of paths to extract\n// information from from getZoneSate responses.\nconst zoneStatePaths = [\n {\n path: [\"activityDataPoints\", \"heatingPower\"],\n value: {\n path: [\"percentage\"],\n },\n topic: `${homeId}-${zoneId}-zs-heat-pw`,\n signal: {\n name: \"Heating power (live)\",\n engUnit: \"%\",\n samplingInterval: \"PT15M\",\n gapDetection: \"PT1H10M\",\n labels: zoneLabels,\n },\n },\n {\n path: [\"sensorDataPoints\", \"insideTemperature\"],\n value: {\n path: [\"celsius\"],\n },\n topic: `${homeId}-${zoneId}-zs-temp`,\n signal: {\n name: \"Inside temperature (live)\",\n engUnit: \"%\",\n samplingInterval: \"PT15M\",\n gapDetection: \"PT1H10M\",\n labels: zoneLabels,\n },\n },\n {\n path: [\"sensorDataPoints\", \"humidity\"],\n value: {\n path: [\"percentage\"],\n },\n topic: `${homeId}-${zoneId}-zs-humidity`,\n signal: {\n name: \"Relative humidity (live)\",\n engUnit: \"%\",\n samplingInterval: \"PT15M\",\n gapDetection: \"PT1H10M\",\n labels: zoneLabels,\n },\n },\n];\n\n// zoneDayReportPaths lists a series of paths to extract\n// information from from getZoneSate responses.\nconst weatherPaths = [\n {\n path: [\"outsideTemperature\"],\n value: {\n path: [\"celsius\"],\n },\n topic: `${homeId}-w-out-temp`,\n signal: {\n name: \"Outside temperature (live)\",\n engUnit: \"°C\",\n samplingInterval: \"PT1H\",\n gapDetection: \"PT4H\",\n sourceType: \"prediction\",\n labels: homeLabels,\n },\n },\n {\n path: [\"solarIntensity\"],\n value: {\n path: [\"percentage\"],\n },\n topic: `${homeId}-w-sun`,\n signal: {\n name: \"Solar intensity (live)\",\n engUnit: \"%\",\n samplingInterval: \"PT1H\",\n gapDetection: \"PT4H\",\n sourceType: \"prediction\",\n labels: homeLabels,\n },\n },\n];\n\nflow.set(\"zoneDayReportPaths\", zoneDayReportPaths);\nflow.set(\"zoneStatePaths\", zoneStatePaths);\nflow.set(\"weatherPaths\", weatherPaths);","outputs":0,"noerr":0,"initialize":"","finalize":"","libs":[],"x":470,"y":400,"wires":[]},{"id":"5e165e0b.41e558","type":"change","z":"6f9e4912.43c788","g":"4a776c34.35efe4","name":"Set home info","rules":[{"t":"set","p":"homeId","pt":"msg","to":"homeId","tot":"flow"},{"t":"set","p":"zoneId","pt":"msg","to":"zoneId","tot":"flow"}],"action":"","property":"","from":"","to":"","reg":false,"x":560,"y":580,"wires":[["81f8d515.73b35"]]},{"id":"efa5ae6c.196b7","type":"rbe","z":"6f9e4912.43c788","g":"d93c633f.b27eb","name":"time change >= 1h","func":"deadbandEq","gap":"3600000","start":"","inout":"out","septopics":true,"property":"payload.time","x":350,"y":960,"wires":[["19e936a7.0ac509"]]},{"id":"9ba5bda2.221a88","type":"clarify_api","name":"Node-RED"},{"id":"5d86a70.fc3e658","type":"tado-config","name":"Tado"}]
Select Import in Node-RED, and paste the content there.
Configure credentials
Before you can use the new flow, you need to configure credentials for all the Tado and Clarify nodes. Double-click each of the nodes to configure relevant credentials.
Note that once you have configured the first Tado node, you should configure all the other nodes to use the same credentials. By default, we have provided a global configuration node for Clarify and Tado that you can configure with the correct credentials. You can choose to keep these nodes, rename them, or configure your own.
Configure Home info
The next thing we should do is to get the homeId and zoneId to use for our data import. To make these values easy to find, we provide a helper flow (in green) that you can run to extract the relevant information.
Trigger the log home info flow. If you only have one home and one zone, then you can get the homeId and zoneId to use from looking at the node status as shown below. If you however have multiple homes or multiple zones, you should check the debug log to determine which information you want to use.
Multi zone imports?
The imported flow is assuming that you only want to import data from a single homeId and single zoneId. If you want to import data from multiple zones or homes at once in the same flow, you need to find a way to modify the "flow config" and/or "home info" nodes.
Hint: You should think about which zones to log for each home, and if you want to log the same information (including weather data) for each of these zones.
Test live data flows
Deploy your system and test that your live data import is working. The recurring nodes will trigger after 1 second. The Clarify node will group incoming data for another 5 seconds, before sending the data to Clarify.
Once your flow has completed, you should go to your integration in Clarify, and check that signals are have been created. You can now publish them, and drag them into a (new) timeline. Did you receive any data?
Import historic data
Test with one date first
When doing historic imports, test with one date first. This allows you to test if the flow is correctly configured, and works for your device configuration.
Now you should be ready to trigger a historic import of your data. I would recommend testing with one date before importing a longer data period. To do this, you can first edit the Manual dates block to contain a date when your equipment was installed and active.
Hit Deploy, and manually trigger the Manual dates flow. If this works well, you can move on to configuring Date range, Deploy again, and manually trigger it. If everything went well, you should now see your historic Tado data in Clarify.
If you found any errors, ambiguities or have any suggestions on how to make this guide better, please contact us via chat or send an email to hello@clarify.io 🙌
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