Warm house, Cold house: a review of thermal comfort measures used in Get Bill Smart

Warm house, Cold house: a review of thermal comfort measures used in Get Bill Smart

Authors:

Dr Phillipa Watson and Dr Steve Watson

Organisation of Presenter:

University of Tasmania and RED Sustainability Consultants, Australia

Abstract:

In both hot and cold climates, maintaining thermal comfort in homes requires consumption of energy [1,2,3]. For low income households, who commonly live in thermally poor housing stock, maintaining comfort can be costly relative to household income. Trade-offs are often made between thermal comfort levels and energy costs. Managing thermal comfort is established as a critical influence on energy use in homes [4,5]. Comfort as a concept has been explored from many vantages, including as a cultural construct [6], an energy efficiency standard [7], a physiological need [8,9], as a building design parameter [4] and as a parameter for healthy housing [10]. Despite this extensive exploration, there is little data available that provides detailed insight into thermal comfort levels of occupants in existing housing stock and the impact of intervention/support program on household thermal comfort.

This paper reviews thermal comfort measures used in a project, Get Bill Smart (GBS), to identify change to indoor thermal comfort levels in low income households in Tasmania, Australia. Get Bill Smart was an applied research project, funded as part of the Commonwealth Government’s Low Income Energy Efficiency Program (LIEEP). Thermal comfort indicators were explored in conjunction with changes to energy use and energy efficiency in participant homes. The nature, size and budget of GBS meant that thermal comfort data collection had to be pragmatic and fit in with a number of other data collection needs. Thermal comfort responses were collected using logged temperature, humidity and energy data, housing observations and longitudinal interviews. This data was collected in 51 participating households, which were a sub-set of 510 overall participating households, for a period of 15 months. Analysis of the households used a defined comfort zone of 18-24 degrees, which alongside other logged data and interview data, helped to identify whether occupants were living in thermally comfortable or thermally stressed conditions. Thermal comfort data is examined in this paper in conjunction with logged energy data to help understand why and how we may use thermal comfort indicators in future projects. With the help of thermal indicators the GBS project team found, in many cases, that householders were either living significantly below the identified comfort zone (in danger of ill health) or were using significant amounts of energy to avoid cold, unhealthy indoor environments and that multi-method approaches do help to develop thermal comfort understanding. Suggestions are made for the refinement of measures discussed for use in future research into occupant health, thermal comfort and energy efficiency.