© 2014 The Authors. With smart metering initiatives gaining increasing global popularity, the present paper seeks to challenge the increasingly entrenched view that providing householders with feedback about their energy usage, via an in-home-display, will lead them to substantially reduce their energy consumption. Specifically, we draw on existing quantitative and qualitative evidence to outline three key problems with feedback, namely: (a) the limited evidence of efficacy, (b) the need for user engagement, and (c) the potential for unintended consequences. We conclude by noting that, in their current form, existing in-home-displays may not induce the desired energy-reduction response anticipated by smart metering initiatives. Instead, if smart metering is to effectively reduce energy consumption there is a clear need to develop and test innovative new feedback devices that have been designed with user engagement in mind

To date, a multitude of studies have examined the empirical effect of feedback on energy consumption yet very few have examined how feedback might work and the processes it involves. Moreover, it remains to be seen if the theoretical claims made concerning how feedback works can be substantiated using empirical data. To start to address this knowledge gap, the present research used qualitative data analysis to examine how consumers use and respond to energy monitors. The findings suggest feedback may increase both the physical and conscious visibility of consumption as well as knowledge about consumption. Accordingly, support was evident for the theoretical assertions that feedback transforms energy from invisible to visible, prompts motivated users to learn about their energy habits, and helps address information deficits about energy usage. We conclude by evaluating the feasibility of feedback to substantially reduce consumption and discuss ways in which feedback could be improved to aid its effectiveness in the long term before discussing the implication our findings may have for government policy. © 2014 The Authors

This paper assesses the feasibility of determining key household characteristics based on temporal load profiles of household electricity demand. It is known that household characteristics, behaviours and routines drive a number of features of household electricity loads in ways which are currently not fully understood. The roll out of domestic smart meters in the UK and elsewhere could enable better understanding through the collection of high temporal resolution electricity monitoring data at the household level. Such data affords tremendous potential to invert the established relationship between household characteristics and temporal load profiles. Rather than use household characteristics as a predictor of loads, observed electricity load profiles, or indicators based on them, could instead be used to impute household characteristics. These micro level imputed characteristics could then be aggregated at the small area level to produce ‘census-like’ small area indicators. This work briefly reviews the nature of current and future census taking in the UK before outlining the household characteristics that are to be found in the UK census and which are also known to influence electricity load profiles. It then presents descriptive analysis of a large scale smart meter-like dataset of half-hourly domestic electricity consumption before reviewing the correlation between household attributes and electricity load profiles. The paper then reports the results of multilevel model-based analysis of these relationships. The work concludes that a number of household characteristics of the kind to be found in UK census-derived small area statistics may be predicted from particular load profile indicators. A discussion of the steps required to test and validate this approach and the wider implications for census taking is also provided

Climate change, socio-demographic change and changing patterns of ordinary consumption are creating new and unpredictable pressures on urban water resources in the UK. While demand management is currently offered as a first option for managing supply/demand deficit, the uncertainties around demand and its’ potential trajectories are problematic for water resources research, planning and policy. In this article we review the ways in which particular branches of social science come together to offer a model of ‘distributed demand’ that helps explain these current and future uncertainties. We also identify potential strategies for tracking where the drivers of change for demand may lie. Rather than suggest an alternative ‘demand forecasting’ technique, we propose methodological approaches that ‘stretch out’ and ‘scale up’ proxy measures of demand to inform water resources planning and policy. These proxy measurements could act as ‘indictors of change’ to water demand at a population level that could then be used to inform research and policy strategies. We conclude by arguing for the need to recognise the co-production of demand futures and supply trajectories.

The uneven temporal distribution of domestic energy demand is a well-known phenomenon that is increasingly troublesome for energy infrastructures and sustainable or low carbon energy systems. People tend to demand energy, and especially electricity, at specific times of the day and they do not necessarily do so when the sun is shining or the wind is blowing. The potential value of demand response as a solution rests on understanding the nature of temporal energy demand and the timing of the interconnected domestic activities that drive it. The paper uses current and historical time-use diary data to explore the temporal change in laundry practices in the United Kingdom over the last 20 years. ‘Doing the laundry’ is frequently cited as a potentially ‘flexible demand’ and yet very little is known about when people do the laundry, who does it at particular times, how this has changed and what implications this might have for the flexibility of demand. Through this analysis of laundry, the paper starts to unpack some of the ‘doings’ that contribute to current known energy demand and considers the extent to which they may or may not enable flexibility in the context of consumer demand response