A panel model for predicting the diversity of internal temperatures from English dwellings

Using panel methods, a model for predicting daily mean internal temperature demand across a heterogeneous domestic building stock is developed. The model offers an important link that connects building stock models to human behaviour. It represents the first time a panel model has been used to estimate the dynamics of internal temperature demand from the natural daily fluctuations of external temperature combined with important behavioural, socio-demographic and building efficiency variables. The model is able to predict internal temperatures across a heterogeneous building stock to within ~0.71°C at 95% confidence and explain 45% of the variance of internal temperature between dwellings. The model confirms hypothesis from sociology and psychology that habitual behaviours are important drivers of home energy consumption. In addition, the model offers the possibility to quantify take-back (direct rebound effect) owing to increased internal temperatures from the installation of energy efficiency measures. The presence of thermostats or thermostatic radiator valves (TRV) are shown to reduce average internal temperatures, however, the use of an automatic timer is statistically insignificant. The number of occupants, household income and occupant age are all important factors that explain a proportion of internal temperature demand. Households with children or retired occupants are shown to have higher average internal temperatures than households who do not. As expected, building typology, building age, roof insulation thickness, wall U-value and the proportion of double glazing all have positive and statistically significant effects on daily mean internal temperature. In summary, the model can be used as a tool to predict internal temperatures or for making statistical inferences. However, its primary contribution offers the ability to calibrate existing building stock models to account for behaviour and socio-demographic effects making it possible to back-out more accurate predictions of domestic energy demand

Household thermal routines and their impact on space heating demand patterns

Patterns of home heating demand during the day have significant implications for the design of energy networks and will be an important consideration in the introduction of low carbon heating systems such as heat pumps. In homes in the UK it is very common to operate space heating intermittently; the heating is usually switched off when the occupants are asleep at night and when they are out during the day. The strong association between heating operation and household routines leads to a morning peak in demand which, if it persists following electrification of heating, will require significant reinforcement of electricity supply networks. This paper examines factors that underlie current UK home heating practices. A unique dataset of heating controller settings from 337 UK homes with smart heating controllers allows investigation of how patterns of heating operation in individual homes contribute to daily patterns of space heating energy consumption at the group level. A mixed method approach is followed, combining quantitative analysis of data with interviews with householders, drawing on insights from social practice theory. The peak level of space heating demand is found to be higher in the morning than the evening. The concept of thermal routines is introduced, bringing a time dimension to the consideration of domestic thermal comfort and recognising that demand for space heating is linked to patterns of practices in the home, which are themselves linked to social routines, e.g. timing of work and school. The results from this study suggest that household thermal routines around 07:00 in the morning are a particularly important consideration for a transition to future energy systems with a high proportion of low carbon heat. Factors that currently limit flexibility of heating demand in the UK are identified and the implications for a transition to low carbon heating sources are discussed

How household thermal routines shape UK home heating demand patterns

In homes in the UK, it is very common to operate space heating intermittently; the heating is usually switched off when the occupants are asleep at night and when they are out during the day. The strong association between heating operation and household routines leads to a morning peak in demand which, if it persists following electrification of heating, will require significant reinforcement of electricity supply networks. This paper examines factors that underpin how heating is used in the UK. A unique dataset of heating controller settings from 337 UK allows investigation of how patterns of heating operation in individual homes contribute to daily patterns of space heating energy consumption at the group level. A mixed method approach is followed, combining quantitative analysis of data with interviews with householders. The concept of thermal routines is introduced, bringing a time dimension to the consideration of domestic thermal comfort and recognising that demand for space heating is linked to patterns of practices in the home, which are themselves linked to social routines, e.g. timing of work and school. The results from this study suggest that household thermal routines around 07:00 in the morning are a particularly important consideration for a transition to future energy systems with a high proportion of low carbon heat. Factors that currently limit flexibility of heating demand in the UK are identified, and the implications for a transition to low carbon heating sources are discussed

Community energy groups: Can they shield consumers from the risks of using blockchain for peer-to-peer energy trading?

Peer-to-peer (P2P) energy trading is emerging as a new mechanism for settling the ex-change of energy between renewable energy generators and consumers. P2P provides a mechanism for local balancing when it is facilitated through distributed ledgers (‘blockchains’). Energy communities across Europe have uncovered the potential of this technology and are currently running pi-lots to test its applicability in P2P energy trading. The aim of this paper is to assess, using legal literature and legislation, whether the legal forms available to energy communities in the United Kingdom (UK) can help resolve some of the uncertainties around the individual use of blockchain for P2P energy trading. This includes the legal recognition of ‘prosumers’, the protection of their personal data, as well as the validity of ‘smart contracts’ programmed to trade energy on the block-chain network. The analysis has shown that legal entities, such as Limited Liability Partnerships and Co-operative Societies, can play a crucial role in providing the necessary framework to protect consumers engaging in these transactions. This is particularly the case for co-operatives, given that they can hold members liable for not respecting the rules set out in their (compulsory) governing document. These findings are relevant to other European countries, where the energy co-operative model is also used

Behaviour, practice – whatever? A theory-agnostic framework for describing and informing demand-side response

Different theoretical perspectives present diverse interpretations for why and how people may (or may not) be able to vary their electricity consumption patterns, and often propose different approaches to facilitating demand-side response (DSR). The framework set out here is suggested as a way of matching and marrying these various approaches with the goal of exploring how to achieve the maximum possible demand response which people are happy and able to provide. The framework is based around ‘electricity-relevant dimensions’, or factors which may be considered to be associated in some way with a person or people’s electricity use – activities engaged in, location, room temperature, and so on. Within each dimension, any at instant in time, certain states (such as ‘walking’ or ‘watching TV’ for activity) are more or less possible/acceptable than others for a variety of reasons. Effective DSR is understood as involving influencing adoption of those states with lower (or higher, as necessary) electricity outcomes at certain times, from a ‘phase space’ of possible options. This paper describes how the framework can be used to consider the role of DSR interventions with their roots in different theoretical positions, such as changes in material conditions or competencies (associated with social practice theory), or in the framing of messages to activate loss-aversion (behavioural economics). It is intended to prompt consideration of how such approaches (and their proponents) could work together to optimize the potential of DSR programmes and policies, and is illustrated throughout with real and hypothetical examples

Generating empirical probabilities of metabolic rate and clothing insulation values in field studies using wearable sensors

This research introduces a mixed-method framework to estimate metabolic rate and clothing insulation as objective and quantitative variables. Methods included automated visual diaries and both environmental and wearable sensors. Applying this framework in an exploratory study, during the winters of 2012 and 2013, allowed empirical probabilities of metabolic rate and clothing insulation values to be generated. The results indicate that current standards overestimate winter clothing insulation by 22% but underestimate residential metabolic activity by 9%. Beyond reviewing the standards thresholds, these probability distributions may be used as input to building energy simulation (BES) programs

All about size? – The potential of downsizing in reducing energy demand

Residential energy consumption is one of the main contributors to CO2 emissions in the UK. One strategy aimed at reducing emissions is to increase retrofitting rates of buildings. In this paper, an alternative approach is discussed and its potential impact on energy use assessed, that of downsizing (moving to smaller homes). Reviews of previous research show that a wide range of what can be termed psychological barriers exist to downsizing, such as the loss of ownership and independence, concern about what to do with possessions, not having enough space for visitors, and attachment to one’s home. Benefits of downsizing from a personal perspective are economic, with lower bills and/or rent, release of capital, lower maintenance costs, and also potential lifestyle improvements including living in easier-to-maintain and more age-appropriate housing. Wider societal benefits include the potential to significantly reduce energy consumption, and mitigating the housing crisis in cities where not enough properties are available. Empirical analysis on a nationally representative sample in England showed that building size alone accounts for 24% of the variability in energy consumption (compared to 11% of household size). If single-person households with more than two bedrooms downsized by one bedroom, energy-savings of 8% could be achieved, and if single-person households occupied only one bedroom, savings of 27%. Data also showed a significant amount of underoccupation, with almost two-thirds of households having more bedrooms than considered necessary compared to the bedroom-standard. However, analysis also revealed a structural barrier to downsizing, namely the lack of available alternative, smaller houses. The evidence would suggest that downsizing could realize significant energy savings, and address a range of other social benefits. However, against this stand significant personal interests, inadequate alternative housing and other infrastructure issues. Promoting downsizing as a means to achieve energy policy goals is therefore a potentially significant but socially challenging policy option

Efficient energy research for effective energy policy: strategy, design and methods

The energy policy sector is awash with research focused either on technical engineering or economics/modelling (Sovacool, 2014). A growing recognition of the need for more social science in this area has given rise to an increasing literature from disciplines in that area. Yet, despite recognition that energy systems are socio-technical systems, and the need to understand the technical in direct relation to the social, very little research is actually socio-technical (Love and Cooper, 2015). Doing socio-technical research in energy for policy demands complex, expensive and novel data collection – and to do this requires strategic thinking to make best use of research resources. Socio-technical research is pivotal for ensuring that energy policy works well with people and technology, so developing this area is critical for success. In the UK, recent work (Cooper, Shipworth and Humphreys, 2014) has focused on developing a large-scale (N = >10,000) socio-technical longitudinal panel of homes. Such a panel – if designed well – could serve as a central spine in a strategic programme that can makes sense of, and add value to the wider range of research activity. Small scale technical or qualitative social studies can be situated in relation to what is known about the wider population. A key challenge in making socio-technical research work is the generation of new research methods that support integration across domains. These issues collectively give rise to the need to consider how strategy, research design and methods are all implicated in the generation of efficient energy research for effective energy policy

Observational evidence of the seasonal and demographic variation in experienced temperature from 77,743 UK Biobank participants

Background: Exposure to cold is known to be associated with severe health impacts. The primary epidemiological evidence for this is the seasonal variation in mortality. However, there is a paucity of directly measured data for personal cold temperature exposure. This paper develops the concept of experienced temperature, and reports how it varies with season, demographics and housing factors. / Methods: This study uses data from 77 743 UK Biobank participants. A novel method to directly measure participant’s exposure to low temperatures using a thermistor in a wrist-worn activity monitor is described. These readings are combined with demographic and housing factor variables in a multiple regression model to understand underlying relationships. / Results: The study reveals a significant difference in experienced temperature of ~1.8°C between the periods of coldest and hottest external temperature. A number of demographic differences were also observed—such as people of Chinese ethnic background experiencing 0.65°C lower temperatures than other groups. / Conclusions: This paper presents primary evidence for a seasonal variation in experienced temperature. This variation likely contributes to cold related mortality and morbidity. It is hypothesized that this relationship would be less strong in countries which suffer fewer impacts of cold winter temperatures

What motivates retrofitting? Results of a nationally representative sample in Great Britain

Energy use in buildings is one of the largest contributors to total energy consumption. The UK Government established the goal of reducing carbon emissions from homes by 29% by 2020, with energy efficiency improvements forming a central part of the plans. However, the recent ‘Green Deal’ policy to promote energy-efficiency measures in homes through financial incentives had very little uptake. In a nationally representative survey, we assessed framing effects on the hypothetical uptake of free home insulation provided by the energy supplier. The frames tested were: (1) monetary savings, (2) a warmer home, (3) carbon savings, (4) health benefits, and (5) social norms. The option emphasizing monetary savings was associated with significantly higher likeliness to take up the offer than any of the other options, which all received similar mean ratings. Higher trust in the energy supplier was associated with higher likeliness to participate in the scheme. Financial benefits seem to be the greatest incentive for retrofit measures, supporting policy based on them. In this context we critically discuss the apparent failure of the Green Deal, and suggest how the importance of trust in the energy supplier could be used in the future