Understanding Australian household water-related energy use and identifying physical and human characteristics of major end uses

Abstract

Residential resource use efficiency and management is a subject of interest to a number of fields spanning the physical and social sciences. Energy use for residential water heating in Australia is some five to eleven times more than the energy required to deliver urban water services. However, little is known about which activities within households contribute most significantly to water-related energy use (WRE). This work quantifies WRE use in individual households, and identifies household characteristics which contribute significantly to variation. Empirical data were collected through in-home audits, interviews and high-resolution end-use water flow meters for five households in Melbourne, and two in Brisbane, Australia. This was used to characterise 139 parameters describing household occupancy characteristics, behaviours, technologies, and structural and environmental aspects of influence. Mathematical material flow analysis (MMFA) modelling was conducted for individual water and energy use subsystems within each household. WRE use ranged from 7 to 21 kWh hh-1 d-1 (13-24% of total household energy use in Melbourne and 76-79% in Brisbane). Detailed end use analysis of the five Melbourne households showed that shower use (11-61% WRE), hot water system efficiency losses (8-31% WRE) and clothes washer usage (4-17% WRE) contributed most to differences in WRE between households. Findings highlighted shower use as a consistent influence on WRE across households, and suggest further investigation of shower programs as a potentially effective demand management measure for both water and energy in households. The work highlights the importance of consistent messaging for both water and energy efficiency, and suggests that a focus on both human and technical characteristics of households is needed for effective management of combined water and energy use.

Household analysis identifies water-related energy efficiency opportunities

“…Litres (L)/cycle, temperature/cycle, minutes/cycle for clothes-washing machines) or from similar manuals available from suppliers, (v) confirming by inspection the plumbing of clothes-washers and dishwashers to either the cold or both hot and cold water supplies, and finally (vi) estimating from literature the relatively small number of parameters that could not be measured directly. Binks et al (2016) describe the data collection methodology in detail including fieldwork.…”

“…The present work builds on work in a larger project (Binks et al (2016), Kenway et al ref) with additional data collected specifically for shower systems and community water use to inform realistic parameter variation (Steps 2.2 and 2.3 in Figure 1). The principle innovations, and foci of this paper include (i) systematic sensitivity analysis (ii) normalisation of sensitivity analysis to enable comparison of sensitivities across households (iii) variation of individual key parameters to understand the scope for influencing water-related energy, (ivi) variation of key parameters in combination to improve understanding of interaction effects.…”

“…The objective of the sensitivity analysis was to systematically quantify the effects of small changes to all input parameters and to identify key parameters. This uses the validated MMFA model (Binks et al 2016) of each individual household, fully characterised for all parameters, by progressively changing each individual parameter (from P1 to P139) and determining the associated change for each ResWE output variable. The "relative sensitivity" of i X with respect to parameter j p is defined as: As an example of Equation 1, a 10% increase in adult occupancy for a household with 3.0 persons would increase by 0.3 "adults" per day (as an average over a year), i.e.…”

“…This research has been undertaken as a component of a larger collaborative industry-government-university project, we build on the baseline characterisation of seven households (Binks et al 2016). We build on this work here to (i) systematically identify key sensitivities across all seven households using Material Flow Analysis, (ii) use additional data for 5,399 shower events from 94 households in the community and 491 new shower temperature records to (iii) undertake single parameter variation to understand scope for changing water-related energy.…”

A Case Study of Success in Phasing out Policy of Instantaneous Water Heater in Australia and Feasibility in Thailand

“…The Australian research showed that the household water-energy system factor of Australian can be described in term of "human" (occupancy and behavioral) and "Physical" (technological, structural and environmental) attributes [13]. The Australian residential was distinguished into 3 types; 83% class 1, 16% class 2 and 1% other types.…”