A better central heating control system
Update: The following blog describes my “ideal” central heating system; the idea being that I’d build this myself if I got the time. It looks like I won’t get the time to build this any time soon so I’ve started looking at off-the-shelf solutions. My research on off-the-shelf solutions is detailed here.
I find it remarkable that, in 2011, the average domestic central heating controller is still so simple and un-user friendly. Domestic heating accounts for a substantial proportion of the nation’s CO2 output, not to mention domestic energy bills. There are a few companies making “smart” heating controllers (e.g. PassivSystems, microWatt, HeatingSave) but the prices are, in my humble opinion, way too high for kit which is, in technological terms, not especially advanced. Many “off-the-shelf” smart heating control systems are installed by a contractor (not DIY) which substantially bumps up the price.
It seems that it should be possible to build, for a few hundred quid, a system which will significantly decrease the chances of heating an empty room (or house), whilst still ensuring the house is comfortable for the occupants. As such, the system would pay for itself within a few years and would also make the building more comfortable: a win-win which would hopefully make the system popular.
I’ll quickly describe my perspective: I live in a Victorian house with gas central heating and thermostatic radiator valves (TRVs) on each radiator and I recently refurbished our living room (lots of structural & damp correction work plus internal wall insulation, floor insulation, wet underfloor heating, lots of attention to airtightness, single-room MVHR, loads of 1-wire temperature sensors embedded all over the place). I want a control system which’ll cheaply allow us to gain far better control over our radiators, UFH and boiler. I was planning to use an off-the-shelf FS20 system without any PC control or modification but it’s starting to look like the FS20 system wont talk to my underfloor heating easily, which is what got me thinking about creating my own control system. (Some (slightly outdated) details of my pondering regarding FS20 are here)
Folks like Ken Boak and Paul Tanner are making great progress with open-hardware heating controllers.
This page is a wish-list of features for my “ideal” heating controller.
(key: the number after each item indicates its priority: 1=high priority; 3=nice but not essential).
Main features
- Room-by-room control of radiators (using radio-controlled motorised TRV heads so easy to install) - 1
- Room-by-room temperature monitoring and scheduling - 1
- Boiler doesn’t have a “CH schedule”. Instead each room has a schedule. Boiler only fires if 1 or more rooms calls for heat. - 1
- Gas consumption metering (historical data storage so the user can compare, say, November’s consumption for the past 10 years. This is useful to see the effect of insulation.) - 3
- Weather compensation (including looking at forecasts to decide whether to bother putting the heating on in the morning) - 2
- Optimise the schedule to maximise the length of time the boiler spends in condensing mode. - 2
- The system should learn the thermal properties of the building (e.g. if the user wants to living room to be at 20℃ by 8pm and the external temperature is 5℃ then should the system start heating the room at 7:30pm or 7pm?) - 2
- The system should have a (user-configurable) degree of “intelligence”. For example, the system could attempt to learn when particular rooms are occupied and the target temperature of preference for each occupant. Occupancy information could come from a variety of sources including: smart phone GPS, smart electricity meter disaggregation (if the TV is on then someone is probably in the living room), security system movement detectors, on-line calendar etc.
- the system must be resilient to communication failures (or a complete lack of internet connectivity; for example my gran doesn’t have ADSL and I’d want my gran to be able to use the software. Wireless communication is error-prone and the system must adapt as gracefully as possible) - 1
- So easy to use that your grandma could pick it up without needing a manual. Make it as easy as possible for the user. E.g. the user just tells the system “I’ll be in from x to y” and the system knows their temperature preferences (from learning when the individual complained rooms were too hot / too cold) and also knows their room-to-room movement patterns. e.g. the system knows I’m usually home at 8pm and that I spend an hour in the kitchen, an hour in the office, an hour in the livingroom and then go to bed.
- …but also makes it easy for 3rd party developers / hackers to add functionality - 1
- Use as much off-the-shelf hardware as possible; allowing users to mix-and-match if technically possible - 1
- Use as many open-standards as possible - 1
- multi-user (most houses have more than one person living in them! each will have different preferences and schedules) - 3
- Open source, hosted on GitHub (or similar), with high quality wikified documentation for both users and developers; including a one-page “quick-start” guide showing end-users where to get the kit, how to install themselves, how to setup. Use standard tech. E.g. use oAuth to authorise apps (if appropriate)
- Interface:
- System hardware user interfaces in each room - 2
- Web interface (using Dynamic DNS) - must be secure
- iPhone, Android etc apps
- Allow the user to easily see how much energy they’re using and how much it’s costing them and break the data down into easily digested chunks (e.g. “with the external temp at 5C, it costs you 50p per night to heat your livingroom for 3 hours”). Perhaps use “game mechanics” / smiling/frowning faces to provide quite, gutteral feedback
- Google TV / Apple TV / Myth TV / XBMC etc apps
- Hardware
- back end should be able to run on a tiny machine - possibly even an arduino?
- needs to be responsive
- needs to run in the absence on an internet connection
- needs to be able to talk to:
- boiler (with OpenTherm?)
- UFH pump and valves
- room thermostats
- zone valves / rad valves
- light switches
- electric heaters
- MVHR
- gas / electricity / water meters
- Room occupancy:
- assign a probabilityOccupied value to each room
- The system must “miss” as infrequently as possible. People hate cold rooms. Perhaps, for room occupancy probabilities above a certain threashold (say 70%), translate the probability that a room will be occupied into a target temperature. E.g. if the user’s target temp is 18C, the current (unheated) temp is 15C and there’s a 75% chance that they’ll be in the room at a particular time then bring it up to 17C. (Caswell’s idea)
- probabilityOccupied can be informed by:
- at the most basic: a manually entered schedule
- user using smart phone / tablet / laptop to say “I’m here now”
- static computers (Desktops / HTPCs / laptops which live in one room) on the network could report to the heating control to say “I’m on and the user last interacted with me X minutes ago”; or the heating system could just ping the PCs (although there are lots of reasons why a PC might be on even though the user is elsewhere)
- Smart meters with NILM could tell the heating control “the toaster has just come on” / “the upstairs TV has just come on” etc. The user could manually specify which device is in which room; or the system could correlate devices with other room occupancy data. But the system would have to be trained to know which appliances lived in which rooms and so it may be necessary to spend a week or two with a low power keyfob as Ken suggest
- Alarm sensors (PIR, window, door etc) (if present) or Arduino-based wireless motion sensors like JeeLabs’
- If we were to build our own TRV-head actuators then perhaps the actuators could have built-in ultrasonic movement detectors?
- One challenge is that none is the room occupancy data will be 100% reliable so an algorithm would be required to sift through the live sensor data and also use prior experience to assign a probability that each room is (or will soon be) occupied. There’s lots of noisy room occupancy data; finding signal in the noise will be challenging
- House occupancy:
- manually entered schedule
- pull in iCal / Google Calendar feeds (configurable: could assume that any empty entries or entries with “home” as the location mean you’ll be at home). Elegantly handle events marked as “TBC” in calendar.
- Track the geo location of occupants:
- It looks at how far you are away. If you’re <100 miles then it calculates how long it’ll take to drive (perhaps using OSM / Google Maps) and/or learns from past experience e.g. “The fastest he’s ever gotten from South Ken to home is 45 minutes”.
- Foursquare / FaceBook places / Google Latitude
- Have an option in the smart phone app to send location whenever the app is used / automatically
- Have an option on the web interface to send location
- allow functionality to post updates to twitter / facebook etc if the user wants / make it easy for users to compare with their friends (talk to Ed E about his ideas about socialising this)
Existing kit
I did a bit of Googling this morning to see if anyone has successfully hacked the FS20 wireless protocol used by the Conrad Wireless TRV Actuators and Room Thermostats… and… much to my delight… it looks like good old JeeLabs have made a good start on communicating with FS20 using their wireless module: http://jeelabs.org/?s=FS20 I’m very tempted to buy a Conrad Wireless TRV Actuator and Room Thermostat and JeeLabs wireless module and make a start.
The idea I’m thinking of is something like this: use Conrad Wireless TRVs, Room Thermostats and Boiler Control for basic heating control. Then use a Nanode+JeeLabsWireless to add an open-source “Internet gateway” to the FS20 system to allow for remote control and monitoring of the heating system. One of the nice properties of this system is that, when we move house (which may be in only a few year’s time), I can remove the DIY components from the system (i.e. the Nanode) and the core FS20 system will continue to work.