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.

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The Community Domestic Energy Model (CDEM) has been developed to explore potential routes to reduce CO 2 emissions and the model is used to predict the CO 2 emissions of the existing English housing stock. The average dwelling CO 2 emissions are estimated as 5,827 kgCO 2 per year, of which space heating accounts for 53%, water heating 20%, cooking 5% and lights and appliance 22%. Local sensitivity analysis is undertaken for dwellings of different age and type, to investigate the effect on predicted emissions of uncertainty in the model's inputs. High normalised sensitivity coefficients were calculated for parameters that affect the space heating energy use. The effects of the input uncertainties were linear and superposable, so the impact of multiple uncertainties could be easily determined. The results show that the accumulated impact on national CO 2 emissions of the underperformance of energy efficiency measures could be very large. Quality control of the complete energy system in new and refurbished dwellings is essential if national CO 2 targets are to be met. Quality control needs to prioritise detached dwellings because their emissions are both the greatest and the most sensitive to all energy efficiency measures. The work demonstrates that the uncertainty in the predictions of stock models can be large; failure to acknowledge this can lead to a false sense of their reliability.

This paper describes exploratory analysis of domestic electricity profiles recorded at a high time resolution of one minute on eight houses. It includes a detailed analysis of the effects of time averaging.For dwellings with on-site generation such as micro-CHP, a better understanding of electricity profiles is important for economic analysis of systems, and to examine the effects of widespread on-site generation on local electricity networks. Most load data is available at half-hour intervals; averaging data over periods longer than a minute is shown to under-estimate the proportions of both export and import. The frequency distribution of loads is shown to be highly skewed, with varying distributions and an average load factor of 0.1. Further work is needed to develop more general relationships for a large sample of houses, to apply in design and research.Keywords: domestic, energy, electrical, load, generation. IntroductionMost published information on electrical loads is at a time resolution of half an hour, which is the standard interval for load analysis and electricity trading in the UK industry electricity [1 * Corresponding author: telephone +44 (0) 116 2577960, fax +44 (0) 116 2577981, email awright@dmu.ac.uk.], although shorter intervals, e.g. 15 minutes, are used in some countries. A half-hour resolution is sufficient to show variations in load aggregated across many customers (for example at a transformer), and is entirely appropriate for domestic profiles used for billing [2]. However, this resolution hides high frequency variations in loads over timescales of the order of a minute in individual buildings. In dwellings particularly, loads can vary greatly over a few minutes due to the small number of appliances and patterns of usage. On-site generation is becoming more widespread for dwellings (for example photovoltaic panels, micro-CHP and micro-wind) and is considered by the UK government to have great potential to increase [3] due to improving technology, falling costs relative to fuel prices, and environmental

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