Abstract
Effective low carbon heating products, services and policies are critical if the UK is to meet its climate change commitments. However, these are normally developed for the hypothetical or ‘modelled’ household. The activities, behaviours and needs of ‘real’ households cannot be anticipated based on their income or makeup, nor do they remain static for any length of time. Drawing from a mixed methods approach, this paper discusses the range of needs which affect how households use the heating in their homes. These needs are grouped into 4 categories (wellbeing, resources, ease of use and relational dynamics), and 8 subcategories (health, comfort, cost, waste, control, convenience, harmony and hospitality). The paper discusses the individual and changing nature of these needs through a ‘continuum of priority’ and the factors affecting decision making. This categorisation aims to educate technologists and policy developers of the scale of flexibility required for impactful change. Low carbon policies, products and services will be more successful if they enable consumers to meet all of these needs. The challenge is to develop tools that enable designers and developers to recognise what needs each household has and how their needs change over time.
Highlights
20% of carbon emissions come from the way people use heat and hot water in the home [1], and less than 5% of energy used for heating homes comes from low-carbon sources [2]
Examples of variations include: the difference between living room and other room mean temperatures, which is often less than predicted by models; the difference between weekday and weekend mean temperatures, which whilst assumed by RDSAP, does not exist in monitored data; and the length of monitored heating seasons, which are shorter than the 8 month period predicted by SAP [8]
This paper reports findings from research conducted by the Energy Technologies Institute as part of the Smart Systems and Heat Programme
Summary
20% of carbon emissions come from the way people use heat and hot water in the home [1], and less than 5% of energy used for heating homes comes from low-carbon sources [2]. The commonly used Energy Performance Certificate (EPC) [5] or RDSAP [6] use these standardised assumptions, where either all rooms are heated consistently [7] or where all homes are heated and used in the same way. Stazi et al [11] attempted to categorise the different factors that influence occupants’ behaviour in buildings as: environmental, time-related, contextual, physiological, psychological, social, and random. Wei et al [12] identified 27 different factors from existing studies which influence space-heating behaviours. These ranged from dwelling type to thermal sensation, only a few of these factors were found to be represented in building performance simulation
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