12 resultados para Energy Supply-Demand Modeling.
em University of Queensland eSpace - Australia
Resumo:
Australia is unique in terms of its geography, population distribution, and energy sources. It has an abundance of fossil fuel in the form of coal, natural gas, coal seam methane (CSM), oil, and a variety renewable energy sources that are under development. Unfortunately, most of the natural gas is located so far away from the main centres of population that it is more economic to ship the energy as LNG to neighboring countries. Electricity generation is the largest consumer of energy in Australia and accounts for around 50% of greenhouse gas emissions as 84% of electricity is produced from coal. Unless these emissions are curbed, there is a risk of increasing temperatures throughout the country and associated climatic instability. To address this, research is underway to develop coal gasification and processes for the capture and sequestration Of CO2. Alternative transport fuels such as biodiesel are being introduced to help reduce emissions from vehicles. The future role of hydrogen is being addressed in a national study commissioned this year by the federal government. Work at the University of Queensland is also addressing full-cycle analysis of hydrogen production, transport, storage, and utilization for both stationary and transport applications. There is a modest but growing amount of university research in fuel cells in Australia, and an increasing interest from industry. Ceramic Fuel Cells Ltd. (CFCL) has a leading position in planar solid oxide fuel cells (SOFCs) technology, which is being developed for a variety of applications, and next year Perth in Western Australia is hosting a trial of buses powered by proton-exchange fuel cells. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.
Resumo:
To advance understanding of Special Interest Tourism (SIT), this paper will explore the complexities of this phenomenon in the early 21st century. First, a look at what is out there, both from a supply and demand perspective, will serve to paint a broad picture at macro-level. The paper will present a discussion of the SIT phenomenon at the macro-level within a triangular relationship of supply, demand and media. Then, a more specific look at SIT attempts to clarify the ambiguity of the term. Finally, a look at micro-level from the consumer's perspective will introduce the concepts of enduring and situational involvement, and the nature of the product. Proposed frameworks are presented to provide structure and possible directions for future research and as a means of progressing conceptual development. (c) 2004 Elsevier Ltd. All rights reserved.
Resumo:
Background: In early 2001, Australia experienced a sudden, dramatic and;sustained decrease in heroin availability that was accompanied by sharp increases in price and decreases in street level purity-the so-called heroin shortage. These unprecedented changes occurred in a context of widespread treatment availability, which made it possible for the first time to examine the impact of a sharp reduction in heroin supply in New South Wales (NSW) on entry to and adherence with treatment for heroin dependence. Given the evidence of drug substitution by some users. the current paper also examines the effects of the shortage on entry to treatment for other forms of drug dependence. Methods: Interrupted time-series analysis of the number of persons entering opioid pharmacotherapy and other treatment modalities in NSW for heroin dependence and for the treatment for other types of drug dependence. Findings: The heroin shortage was associated with a reduction in the number of younger persons entering opioid pharmacotherapy. There was a dramatic decrease in the number of persons entering heroin withdrawal or assessment only treatment episodes. There appear to have been small improvements in adherence to and retention in heroin treatment after the reduction in heroin supply. Relatively small increases were observed in numbers being treated for cocaine dependence. Conclusions: In the context of good treatment provision, a reduction in heroin supply appeared to produce modest improvements in intermediate outcomes. Supply and demand reduction measures, when both are implemented successfully, may be complementary. (c) 2005 Elsevier Ireland Ltd. All rights reserved.