182 resultados para Electricity -- Costs -- Ontario.


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Climate change is leading to an increased frequency and severity of heat waves. Spells of several consecutive days of unusually high temperatures have led to increased mortality rates for the more vulnerable in the community. The problem is compounded by the escalating energy costs and increasing peak electrical demand as people become more reliant on air conditioning. Domestic air conditioning is the primary determinant of peak power demand which has been a major driver of higher electricity costs. This report presents the findings of multidisciplinary research which develops a national framework to evaluate the potential impacts of heat waves. It presents a technical, social and economic approach to adapt Australian residential buildings to ameliorate the impact of heat waves in the community and reduce the risk of its adverse outcomes. Through the development of a methodology for estimating the impact of global warming on key weather parameters in 2030 and 2050, it is possible to re-evaluate the size and anticipated energy consumption of air conditioners in future years for various climate zones in Australia. Over the coming decades it is likely that mainland Australia will require more cooling than heating. While in some parts the total electricity usage for heating and cooling may remain unchanged, there is an overall significant increase in peak electricity demand, likely to further drive electricity prices. Through monitoring groups of households in South Australia, New South Wales and Queensland, the impact of heat waves on both thermal comfort sensation and energy consumption for air conditioning has been evaluated. The results show that households are likely to be able to tolerate slightly increased temperature levels indoors during periods of high outside temperatures. The research identified that household electricity costs are likely to rise above what is currently projected due to the impact of climate change. Through a number of regulatory changes to both household design and air conditioners, this impact can be minimised. A number of proposed retrofit and design measures are provided, which can readily reduce electricity usage for cooling at minimal cost to the household. Using a number of social research instruments, it is evident that households are willing to change behaviour rather than to spend money. Those on lower income and elderly individuals are the least able to afford the use of air conditioning and should be a priority for interventions and assistance. Increasing community awareness of cost effective strategies to manage comfort and health during heat waves is a high priority recommended action. Overall, the research showed that a combined approach including behaviour change, dwelling modification and improved air conditioner selection can readily adapt Australian households to the impact of heat waves, reducing the risk of heat related deaths and household energy costs.

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This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.

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Farmers' exposure to pesticides is high in developing countries. As a result many farmers suffer from ill-health, both short and long term. Deaths are not uncommon. This paper addresses this issue. Field survey data from Sri Lanka are used to estimate farmers' expenditure on defensive behavior (DE) and to determine factors that influence DE. The avertive behavior approach is used to estimate costs. Tobit regression analysis is used to determine factors that influence DE. Field survey data show that farmers' expenditures on DE are low. This is inversely related to high incidence of ill health among farmers using pesticides.

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Housing affordability is gaining increasing prominence in the Australian socioeconomic landscape, despite strong economic growth and prosperity. It is a major consideration for any new development. However, it is multi-dimensional, has many facets, is complex and interwoven. One factor widely held to impact housing affordability is holding costs. Although it is only one contributor, the nature and extent of its impact requires clarification. It is certainly more multifarious than simple calculation of the interest or opportunity cost of land holding. For example, preliminary analysis suggests that even small shifts in the regulatory assessment period can significantly affect housing affordability. Other costs associated with “holding” also impact housing affordability, however these costs cannot always be easily identified. Nevertheless it can be said that ultimately the real impact is felt by those whom can least afford it - new home buyers whom can be relatively easily pushed into the realms of un-affordability.

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This report presents the results of research projects conducted by The Australian Cooperative Research Centre for Construction Innovation, Queensland University of Technology, RMIT University, Queensland Government Department of Main Roads and Queensland Department of Public Works. The research projects aimed at developing a methodology for assessing variation and risk in investment in road network, including the application of the method in assessing road network performance and maintenance and rehabilitation costs for short- and long-term future investment.

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Realistic estimates of short- and long-term (strategic) budgets for maintenance and rehabilitation of road assessment management should consider the stochastic characteristics of asset conditions of the road networks so that the overall variability of road asset data conditions is taken into account. The probability theory has been used for assessing life-cycle costs for bridge infrastructures by Kong and Frangopol (2003), Zayed et.al. (2002), Kong and Frangopol (2003), Liu and Frangopol (2004), Noortwijk and Frangopol (2004), Novick (1993). Salem 2003 cited the importance of the collection and analysis of existing data on total costs for all life-cycle phases of existing infrastructure, including bridges, road etc., and the use of realistic methods for calculating the probable useful life of these infrastructures (Salem et. al. 2003). Zayed et. al. (2002) reported conflicting results in life-cycle cost analysis using deterministic and stochastic methods. Frangopol et. al. 2001 suggested that additional research was required to develop better life-cycle models and tools to quantify risks, and benefits associated with infrastructures. It is evident from the review of the literature that there is very limited information on the methodology that uses the stochastic characteristics of asset condition data for assessing budgets/costs for road maintenance and rehabilitation (Abaza 2002, Salem et. al. 2003, Zhao, et. al. 2004). Due to this limited information in the research literature, this report will describe and summarise the methodologies presented by each publication and also suggest a methodology for the current research project funded under the Cooperative Research Centre for Construction Innovation CRC CI project no 2003-029-C.