Working notes on developing ETV scheme. DHD20151109 onwards Initial performance claim: * 30% energy savings when using OpenTRV valves: industry-standard kWh/HDD (energy per Heating Degree Day) and reduced kgCO2 footprint per dwelling per winter for equivalent winters. * 50% energy savings when using OpenTRV valves + boiler units: industry-standard kWh/HDD (energy per Heating Degree Day) reduced kgCO2 footprint per dwelling per winter for equivalent winters. Relevant alternative: household with a boiler used to heat water for space heating, a single thermostat to control the boiler and individual mechanical TRVs attached to all radiators, except a single bypass radiator. Discussion of use of kWh/HDD metric and related methods: http://www.energylens.com/articles/degree-days https://www.energydeck.com/blog/article/degree-days-energydeck-introduction-martin-bromley/ http://www.eevs.co.uk/ipmvp.html http://www.nrel.gov/docs/fy02osti/31505.pdf Operational constraints: This device is being tested in/for the following deployment as matching its core features of energy saving from soft zoning and occupancy detection in fast-response radiator-based (hydronic) domestic space heating, typically gas-fired central heating: 1) Deployment in a multi-room UK dwelling, size 50m^2 to 500m^2, 2 to 8 heated rooms, fitted with radiators for heating with gas-fired (or similar fast-response boiler), no existing zoning in place. 2) The (rd)SAP rating of the test dwelling shall be below (worse than) EPC (Energy Performance Certificate as applied in the UK at 2015) band B, since the gains to be made from the OpenTRV technology will be much reduced in an already-efficient house. 3) The existing heating system must be in good order. 4) The dwelling must not go unheated due to lack of funds or unexpected vacancy of more than a few days. 5) The occupancy and pattern of use of the household should not change significantly during the testing. 6) The dwelling should not make use of any significant secondary heating systems, such as electric fan heaters, wood burning stoves, or air-conditioning, for example. Claims may have to be weaker for dwellings with secondary heating. 7) It must be possible to take at least 4 weekly data points for kWh and HDD (preferably at least 6 or 8) before and after the introduction/enabling of the OpenTRV ‘smart’ features. 8) If the dwelling uses the same fuel for other purposes than heating, eg DHW or cooking, this should be recorded and a baseline for that usage verified where possible with past bills or similar, and such baseline usage should be excluded from the efficiency calculations explicitly or implicitly. 9) There must be a nearby reliable weather station in a similar microclimate for daily HDD data. Typically airport weather stations are preferred. 10) A baseline temperature for kWh/HDD of 15.5C will be used by default in line with standard UK practice, but this may be reviewed by area or even by dwelling to better reflect microclimate and usage. This can be done by attempting to find the best fit with base temperatures bear this default baseline temperature; values far from this default may require the dwelling to be excluded from the test, eg Passivhaus or hospital would be outliers. 11) Radiators must have suitable valve tails to accept the OpenTRV device including suitable Danfoss M30x1.5 fitting and suitable pin travel. It is notionally possible to replace the tails though that may be too invasive for these tests, and may actually alter heating system performance, eg by forcing a drain-down and recharge. 12) OpenTRV must be deployed to all radiators that will be regularly used for the duration of the trial, with exceptions allowed if only accounting for a small portion of space heat, or if being used as bypass radiators, or in very humid areas such as bathrooms where the humidity might affect correct functioning of the device. 13) Dwellings using radiator valve tails with vertical pins to control flow are preferred as the initial design target. Method: Where possible following IPMVP principles, eg see: http://www.eevs.co.uk/ipmvp.html Apply standard linear regression analysis (http://www.degreedays.net/regression-analysis) to energy consumption vs local weather heating degree days to quantify change in heating efficiency and implied change in carbon footprint (slope kWh/HDD, plus robustness from r-squared). Inputs: 1) Heating Degree Days (daily and weekly) based on measurements from local weather station or similar suitable source (see operational constraints). 2) Weekly (or more frequent) regular space-heating fuel energy consumption measurements, eg from gas meter, over an absolute minimum of 4 weeks and 8 measurement points (eg weekly for 8 weeks or twice-weekly for 4 weeks), before and after installation/enabling OpenTRV tech. 3) Record of available details of heating system such as overall system design if possible, boiler name, model, age, SEDBUK or similar efficiency measures, maintenance schedule, number and sizes of radiators and valve types (TRV or not) and typical reported usage patterns. 4) Before and after surveys of occupants of: heating comfort/satisfaction, reported usage patterns (by time, level of interaction with heating system, frugal/other, etc). Also understand any supplementary heating systems used, eg fan-heaters in addition to gas central heating. 5) If available: previous energy readings, eg from bills. 6) If available: house construction and age, rdSAP for building from public record, boiler type and SEDBUK or equivalent rating. 7) Energy intensity of heating fuel in kgCO2/kWh. 8) Record any supplementary heating systems used, such as open fires, portable fan heaters, and even dehumidifiers. Outputs: 1) Change in kWh/HDD (and gross heat energy use) before and after OpenTRV installed/enabled. (Standard method computing slope and intercept automatically largely excludes typical baseline usage, eg for domestic hot water on same boiler as central heating.) 2) Change in r-squared 'fit' before and after. A secondary sign of improved heating controls is an r-squared value that more closely approaches 1 (from below). 3) Change in user satisfaction/comfort/interaction as far as reasonably possible, probably mainly qualitative rather than quantitative, and other user comments. Anonymised results or extracts may be published.