An integrated approach to modelling end-use energy and water consumption of Australian households

Abstract To predict both end-use energy and water consumption of households, an integrated approach was developed by adding water module into the AusZEH design tool, which was a physically-based model to simulate energy consumption of residential buildings considering building envelop, appliance characteristics, local climate and occupant behaviour. Water and its associated energy consumption includes indoor and outdoor water systems considering actual operation of the water systems. Monte Carlo approach was applied to simulate both energy and water use patterns of appliances considering uncertainties. The comparisons between simulation and actual data show the model can track both energy and water consumption and usage patterns.

[1]  M. Newborough,et al.  Dynamic energy-consumption indicators for domestic appliances: environment, behaviour and design , 2003 .

[2]  K. Steemers,et al.  A method of formulating energy load profile for domestic buildings in the UK , 2005 .

[3]  Zhengen Ren,et al.  Assessment of end-use electricity consumption and peak demand by Townsville's housing stock , 2013 .

[4]  Stephen Cook,et al.  Energy use in the provision and consumption of urban water in Australia: an update , 2012 .

[5]  Dong Chen,et al.  A model for predicting household end-use energy consumption and greenhouse gas emissions in Australia , 2013 .

[6]  Rodney Anthony Stewart,et al.  Residential water heaters in Brisbane, Australia: thinking beyond technology selection to enhance energy efficiency and level of service , 2014 .

[7]  Evan Mills.  Inter-comparison of North American residential energy analysis tools , 2004 .

[8]  S. Kenway,et al.  Energy use in the provision and consumption of urban water in Australia and New Zealand , 2008 .

[9]  Claudia Copeland,et al.  Energy-Water Nexus: The Water Sector’s Energy Use , 2014 .

[10]  David Infield,et al.  Domestic electricity use: A high-resolution energy demand model , 2010 .

[11]  Regina Lamedica,et al.  A bottom-up approach to residential load modeling , 1994 .

[12]  Ryan Cahill,et al.  Household water use and conservation models using Monte Carlo techniques for the East Bay municipal utilities district , 2013 .

[13]  Peter W. Newton,et al.  Pathways to decarbonizing the housing sector: a scenario analysis , 2011 .

[14]  Nando de Freitas,et al.  Sequential Monte Carlo Methods in Practice , 2001, Statistics for Engineering and Information Science.

[15]  Zhengen Ren,et al.  A local-community-level, physically-based model of end-use energy consumption by Australian housing stock , 2012 .