Household Energy Use in New Zealand: the Changing Role of Televisions

<p>Energy efficiency plays a major role in policies to mitigate climate change and to secure future energy supply. Understanding energy use behaviour and appliance energy use is vital to policy design. The drivers of energy use in household sector are complex. Households use energy for comfort, health and entertainment in contrast to, the uses of energy for making a profit in industrial and commercial sectors. As a part of this study a model was developed identifying the major drivers of household energy use. Household income and behaviour, house size, appliance technology and appliance energy efficiency are few factors that can influence household energy consumption patterns. Many OECD countries have managed to restrain traditional household energy end-uses such as space and water heating. However, IEA studies have indicated energy used by information, communication and entertainment appliances continue to increase. Television energy use was chosen for this study because it is widely used and operates together with many other associated appliances. This analysis draws from the New Zealand Television Energy Usage and Purchasing Survey to understand the current trends and patterns of television usage. The survey suggests television and associated appliance ownership and usage is increasing. Analysis draws from the survey to quantify TV energy use in New Zealand. This study illustrates how household behaviour, technology and size affects household energy use. The survey also demonstrate how households associate energy use with environmental impact. Some OECD data on household energy was used to analyse and contrast New Zealand’s patterns in a wider context.</p>

Household Energy Use in New Zealand: the Changing Role of Televisions

<p>Energy efficiency plays a major role in policies to mitigate climate change and to secure future energy supply. Understanding energy use behaviour and appliance energy use is vital to policy design. The drivers of energy use in household sector are complex. Households use energy for comfort, health and entertainment in contrast to, the uses of energy for making a profit in industrial and commercial sectors. As a part of this study a model was developed identifying the major drivers of household energy use. Household income and behaviour, house size, appliance technology and appliance energy efficiency are few factors that can influence household energy consumption patterns. Many OECD countries have managed to restrain traditional household energy end-uses such as space and water heating. However, IEA studies have indicated energy used by information, communication and entertainment appliances continue to increase. Television energy use was chosen for this study because it is widely used and operates together with many other associated appliances. This analysis draws from the New Zealand Television Energy Usage and Purchasing Survey to understand the current trends and patterns of television usage. The survey suggests television and associated appliance ownership and usage is increasing. Analysis draws from the survey to quantify TV energy use in New Zealand. This study illustrates how household behaviour, technology and size affects household energy use. The survey also demonstrate how households associate energy use with environmental impact. Some OECD data on household energy was used to analyse and contrast New Zealand’s patterns in a wider context.</p>

The Transition in Household Energy Use for Cooking in India: Evidence from a Longitudinal Survey

This article seeks to assess the transition in household energy use for cooking in India based on data from two rounds of the India Human Development Survey in 2004–2005 and 2011–2012. In this study, we have used the multinomial logistic regression and Multiple Classification Analysis conversion model to assess the transition in household energy use according to the socio-economic characteristics of households. Our findings suggest that although the transition from solid fuel to clean fuel is universal across households, it is greater among the socio-economically better-off households than their poorer counterparts. The use of solid fuel for cooking was more prevalent among the socio-economically disadvantaged households than among their socio-economically better-off counterparts in both 2004–2005 and 2011–2012. Convergence in clean cooking fuel use across the households can be possible only when socio-economically disadvantaged households progress faster than their already better-off counterparts. JEL Codes: B5, C23, D31, I3, Q5

Survey And Articifical Neural Network Analysis On Occupant's Household Energy Use In A High-Rise Multi-Unit Residential Building In Toronto, Canada

Examining occupant's household energy use is a crucial step in achieving significant reductions in energy consumption. The purpose of this thesis is to collect information on ownership of appliances and electronics to evaluate their use, energy consumption, and behaviour with respect to energy in a Toronto high-rise multi-unit residential building (MURB). In this thesis, a survey was developed and implemented in a Toronto high-rise MURB. The survey data, energy consumption data from October 2010 to September 2012, and weather conditions were analyzed and used to develop an artificial neural network (ANN) model. The detailed analysis of survey data resulted in the development of relationships between occupant's demographics and energy consumption. By creating an ANN model, results showed that the implementation of the survey may have reduced occupant's energy consumption in the high-rise MURB.

Survey And Articifical Neural Network Analysis On Occupant's Household Energy Use In A High-Rise Multi-Unit Residential Building In Toronto, Canada

Examining occupant's household energy use is a crucial step in achieving significant reductions in energy consumption. The purpose of this thesis is to collect information on ownership of appliances and electronics to evaluate their use, energy consumption, and behaviour with respect to energy in a Toronto high-rise multi-unit residential building (MURB). In this thesis, a survey was developed and implemented in a Toronto high-rise MURB. The survey data, energy consumption data from October 2010 to September 2012, and weather conditions were analyzed and used to develop an artificial neural network (ANN) model. The detailed analysis of survey data resulted in the development of relationships between occupant's demographics and energy consumption. By creating an ANN model, results showed that the implementation of the survey may have reduced occupant's energy consumption in the high-rise MURB.