Central heating thermostat settings and timing: building demographics

Abstract

Crucial empirical data (currently absent in building energy models) on central heating demand temperatures and durations are presented. This data is derived from the first national survey of energy use in English homes and includes monitored temperatures in living rooms, central heating settings reported by participants, along with building, technical and behavioural data.The results are compared to model assumptions with respect to thermostat settings and heating durations. Contrary to assumptions, the use of controls did not reduce average maximum living room temperatures or duration of operation. Regulations, policies and programs may need to revise their assumptions that adding controls will reduce energy use.Alternative forms of heating control should be developed and tested to ascertain whether their use saves energy in real-world settings. Given the finding that detached houses are heated for longer, these dwellings should be particularly targeted in energy efficiency retrofit programs.Furthermore, social marketing programs could use the wide variation in thermostat settings as the foundation of a 'social norm' program aimed at reducing temperatures in 'overheated' homes. Finally, building energy models that inform energy policies require firmer foundations in real world data to improve policy effectiveness. Greater coordination of data collection and management would make more data available for this purpose.

Smart metering: what potential for householder engagement?

“…Programmed heating controls do not necessarily do what they are designed to do: result in lower maximum temperatures or shorter heating periods (e.g. Williams et al, 1985;Shipworth et al, 2010). Taking control away from the customer cannot be relied upon to improve the situation: it may actually entrench and legitimize highdemand practices, disengaging customers from any need to consider and question them (Strengers, 2008).…”

The shape of warmth: temperature profiles in living rooms

“…The data analysed in this paper are taken from the Carbon Reduction in Buildings Home Energy Survey (CaRB HES), the first national survey exclusively focused on energy use in English homes 1 that commenced in early 2007 (for details, see Shipworth et al, 2010). Households were selected by stratified random sample drawn from the postcode address file.…”

“…Average estimated heating duration was 8.2 hours for weekdays and 8.4 hours for weekends. Importantly, the analysis of Shipworth et al (2010) revealed large variability in the data, in particular regarding heating demand temperature (standard deviation (SD) of 2.58C). For heating duration estimates the SD was 1.5 hours.…”

“…In a small Danish sample of low-energy homes, Isaksson and Karlsson (2006) also found internal temperature differences related to type of housing. Shipworth et al (2010) used measured internal temperature to estimate thermostat settings and heating duration patterns. They found average maximum internal temperature for three winter months, used as a proxy for the thermostat setting, was 21.18C, in line with the heating demand temperatures as assumed by BREDEM-based models.…”

Thermostat Interface and Usability: A Survey

“…One of the reasons for this decision is that several recent field studies have shown no significant savings in households using PTs compared to households using non-programmable thermostats. (Cross & Judd, 1997;Haiad, et al, 2004;Nevius & Pigg, 2000;Shipworth, et al, 2010) Some of these studies have been summarized in a document by Shiller in Table 4. A few argue that homes relying on programmable thermostats consumed more energy than those where the occupants set the thermostats manually (Sachs, 2004), especially with heat pumps (Bouchelle, Parker, & Anello, 2000).…”