With housing in the UK responsible for over a quarter of all building related carbon dioxide (CO2) emissions, it is becoming increasingly difficult to ignore the impact of occupant behaviour on such emissions. One area where occupant behaviour contributes largely towards emissions is space heating within domestic buildings. Despite technological improvements in the efficiency of heating systems, controls have become increasingly complex. Hence, there is a need to enable people to use their heating controls effectively in order to help reduce the associated CO2 emissions. This research found that significant numbers of people were excluded from using digital programmable thermostats, in particular people over 50 years old. The first study examined the scale of exclusion relating to digital programmable thermostats installed at a specific housing development. A second study explored in detail the reasons for exclusion from successfully programming a range of digital programmable thermostats. This was an in-depth usability study of heating controls that focused on the usability issues experienced by older people and was published in the Journal of Engineering Design. Based upon the outcomes of the first two studies a more inclusive heating control interface prototype was developed. The prototype demonstrated a reduction in both cognitive demands and associated user exclusion. Task success rates increased by 56.3% amongst older participants, and detailed energy modelling indicated that energy savings of 14.5-15.6% annually could be achievable. This work suggests that a more inclusive heating control interface could enable energy savings in the region of 15% through reducing the cognitive demands. Furthermore, this research challenges the existing paradigm and shows that inclusive design research may contribute to sustainable development in an environmental, as well as social, capacity.

Energy consumption in the home depends on appliance ownership and use, space heating systems, control set-points and hot water use. It represents a significant proportion of national demand in the UK. The factors that drive the level of consumption are a complex and interrelated mix of the numbers of people in the home, the building and system characteristics as well as the preferences for the internal environment and service choices of occupants. Reducing the energy demand in the domestic sector is critical to achieving the national 2050 carbon targets, as upward of 60% reduction in demand is assumed by many energy system scenarios and technology pathways. The uptake of reduction measures has been demonstrated to be quite ad hoc and intervention studies have demonstrated considerable variation in the results. Additionally, a limitation of many studies is that they only consider one intervention, whereas a more holistic approach to the assessment of the potential of reduction measures in specific homes may yield a better understanding of the likely impact of measures on the whole house consumption and indeed would shed light on the appropriateness of the assumptions that underpin the decisions that need to be made regarding the future energy supply system and demand strategies. This work presents a systematic approach to modelling potential reductions for a set of seven family homes, feeding back this information to householders and then evaluating the likely reduction potential based on their responses. Carried out through a combination of monitoring and semi-structured interviews, the approach develops a methodology to model energy reduction in specific homes using monitoring data and steady-state heat balance principles to determine ventilation heat loss, improving the assumptions within the energy model regarding those variables affected by human behaviour. The findings suggest that the anticipated reductions in end use energy demand in the domestic sector are possible, but that there is no `one size fits all' solution. A combination of retrofitting and lifestyle change is needed in most homes and smart home technology may potentially be useful in assisting the home owner to achieve reductions where they are attempting to strike a balance between energy efficiency, service and comfort.

Yes / This paper presents a method of generating realistic electricity load profile data for the UK domestic buildings. The domestic space heating and domestic hot water have been excluded in this study. The information and results of previous investigations and works that is available in public reports and statistics have been used as input data when modeling of domestic energy consumption. A questionnaire survey was conducted to find out what occupants do in different times of the day in order to get probabilistic estimates of usage of electrical household. The daily energy demand load profile of each appliance can be predicted using this method. A measured data set is also applied for comparison, and verification. Our analysis shows that the generated load profiles have a good agreement with real data. The daily load profile from individual dwelling to community can be predicted using this method.