927 resultados para fuel and power generation


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Bornite, Cu5FeS4, is a naturally-occuring mineral with an ultralow thermal conductivity and potential for thermoelectric power generation. We describe here a new, easy and scalable route to synthesise bornite, together with the thermoelectric behaviour of manganese-substituted derivatives, Cu5Fe1-xMnxS4 (0 ≤ x ≤ 0.10). The electrical and thermal transport properties of Cu5Fe1-xMnxS4 (0 ≤ x ≤ 0.10), which are p-type semiconductors, were measured from room temperature to 573 K. The stability of bornite was investigated by thermogravimetric analysis under inert and oxidising atmospheres. Repeated measurements of the electrical transport properties confirm that bornite is stable up to 580 K under an inert atmosphere, while heating to 890 K results in rapid degradation. Ball milling leads to a substantial improvement in the thermoelectric figure of merit of unsusbtituted bornite (ZT = 0.55 at 543 K), when compared to bornite prepared by conventional high-temperature synthesis (ZT < 0.3 at 543 K). Manganese-substituted samples have a ZT comparable to that of unsubstituted bornite.

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Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

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The diffusion of Concentrating Solar Power Systems (CSP) systems is currently taking place at a much slower pace than photovoltaic (PV) power systems. This is mainly because of the higher present cost of the solar thermal power plants, but also for the time that is needed in order to build them. Though economic attractiveness of different Concentrating technologies varies, still PV power dominates the market. The price of CSP is expected to drop significantly in the near future and wide spread installation of them will follow. The main aim of this project is the creation of different relevant case studies on solar thermal power generation and a comparison betwwen them. The purpose of this detailed comparison is the techno-economic appraisal of a number of CSP systems and the understanding of their behaviour under various boundary conditions. The CSP technologies which will be examined are the Parabolic Trough, the Molten Salt Power Tower, the Linear Fresnel Mirrors and the Dish Stirling. These systems will be appropriatly sized and simulated. All of the simulations aim in the optimization of the particular system. This includes two main issues. The first is the achievement of the lowest possible levelized cost of electricity and the second is the maximization of the annual energy output (kWh). The project also aims in the specification of these factors which affect more the results and more specifically, in what they contribute to the cost reduction or the power generation. Also, photovoltaic systems will be simulated under same boundary conditions to facolitate a comparison between the PV and the CSP systems. Last but not leats, there will be a determination of the system which performs better in each case study.

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The gradual changes in the world development have brought energy issues back into high profile. An ongoing challenge for countries around the world is to balance the development gains against its effects on the environment. The energy management is the key factor of any sustainable development program. All the aspects of development in agriculture, power generation, social welfare and industry in Iran are crucially related to the energy and its revenue. Forecasting end-use natural gas consumption is an important Factor for efficient system operation and a basis for planning decisions. In this thesis, particle swarm optimization (PSO) used to forecast long run natural gas consumption in Iran. Gas consumption data in Iran for the previous 34 years is used to predict the consumption for the coming years. Four linear and nonlinear models proposed and six factors such as Gross Domestic Product (GDP), Population, National Income (NI), Temperature, Consumer Price Index (CPI) and yearly Natural Gas (NG) demand investigated.

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The research aims to gain a deeper understanding of direct buyer-supplier relationships within the Australian fresh produce industry. Specifically, dependence and power within the buyer-supplier relationship are considered in terms of their antecedents and their relationships their-in. In-depth interviews with buyers and suppliers provided the means by which to expose perceptions with regard to the relative importance of dependence and power within the relationship. The research reveals that relationship antecedents (trading offer: price and quality) impact power and dependence and are, in tum, impacted by them.

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The electrical data of two quay cranes, one has a DC drive system and the other has an AC drive system, in actual working conditions at a container terminal are measured and presented in this paper. Peak demand, energy usage, power factor and power quality are examined and compared.

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Although the thermodynamic advantages of using solar energy to replace the bled off steam in the regeneration system of Rankine cycle coal fired power stations has been proven theoretically, the practical techno/economic feasibility of the concept has yet to be confirmed relative to real power station applications. To investigate this concept further, computer modelling software “THERMSOLV” was specifically developed for this project at Deakin University, together with the support of the Victorian power industry and Australian Research Council (ARC). This newly developed software simulates the steam cycle to assess the techno/economic merit of the solar aided concept for various power station structures, locations and local electricity market conditions. Two case studies, one in Victoria Australia and one in Yunnan Province, China, have been carried out with the software. Chapter one of this thesis defines the aims and scope of this study. Chapter two details the literature search in the related areas for this study. The thermodynamic concept of solar aid power generation technology has been described in chapter three. In addition, thermodynamic analysis i.e. exergy/availability has been described in this chapter. The “Thermosolv” software developed in this study is detailed in chapter four with its structure, functions and operation manual included. In chapter five the outcomes of two case studies using the “Thermosolv” software are presented, with discussions and conclusions about the study in chapters 6 and 7 respectfully. The relevant recommendations are then made in chapter eight.

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The central concern of this study is to identify the role of power and politics in systems implementation. The current literature on systems implementation is typically divided into two areas, process modelling and factor based studies. Process modelling classifies the implementation into a linear process, whereas factor based studies have argued that in order to ‘successfully’ implement a system, particular critical factors are required. This literature misses the complexities involved in systems implementation through the human factors and political nature of systems implementation and is simplistic in its nature and essentially de-contextualises the implementation process. Literature has investigated some aspects of human factors in systems implementation. However, it is believed that these studies have taken a simplistic view of power and politics. It is argued in this thesis that human factors in systems implementation are constantly changing and essentially operating in a dynamic relationship affecting the implementation process. The concept of power relations, as proposed by Foucault (1976, 1977, 1978, 1980, 1982), have been utilised in order to identify the dynamic nature of power and politics. Foucault (1978) argued that power is a dynamic set of relationships constantly changing from one point in time to the next. It is this recognition that is lacking from information systems. Furthermore, these power relations are created through the use of discourse. Discourse represents meaning and social relationships, forming both subjectivity and power relations. Discourses are also the practices of talk, text and argument that continuously form that which actors speak. A post-structuralist view of power as both an obvious and hidden concept has provided the researcher a lens through which the selection and implementation of an enterprise-wide learning management system can be observed. The framework aimed to identify the obvious process of system selection implementation, and then deconstruct that process to expose the hegemonic nature of policy, the reproduction of organisational culture, the emancipation within discourse, and the nature of resistance and power relations. A critical case study of the selection and implementation of an enterprise-wide learning management system at the University of Australia was presented providing an in-depth investigation of the implementation of an enterprise-wide learning management system, spanning five years. This critical case study was analysed using social dramas to distinguish between the front stage issues of power and the hidden discourses underpinning the front stage dramas. The enterprise-wide learning management system implemented in the University of Australia in 2003 is a system which enables academic staff to manage learners, the students, by keeping track of their progress and performance across all types of training activities. Through telling the story of the selection and implementation of an enterprise-wide learning management system at the University of Australia discourses emerged. The key findings from this study have indicated that the system selection and implementation works at two levels. The low level is the selection and implementation process, which operates for the period of the project. The high level is the arena of power and politics, which runs simultaneously to the selection and implementation process. Challenges for power are acted out in the front stage, or public forums between various actors. The social dramas, as they have been described here, are superfluous to the discourse underpinning the front stage. It is the discourse that remains the same throughout the system selection and implementation process, but it is through various social dramas that reflect those discourses. Furthermore, the enactment of policy legitimises power and establishes the discourse, limiting resistance. Additionally, this research has identified the role of the ‘State’ and its influence at the organisational level, which had been previously suggested in education literature (Ball, 1990).

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Objective : To compare the energy expenditure of adolescents when playing sedentary and new generation active computer games.

Design : Cross sectional comparison of four computer games.

Setting : Research laboratories.

Participants : Six boys and five girls aged 13-15 years.

Procedure : Participants were fitted with a monitoring device validated to predict energy expenditure. They played four computer games for 15 minutes each. One of the games was sedentary (XBOX 360) and the other three were active (Wii Sports).

Main outcome measure : Predicted energy expenditure, compared using repeated measures analysis of variance.

Results : Mean (standard deviation) predicted energy expenditure when playing Wii Sports bowling (190.6 (22.2) kJ/kg/min), tennis (202.5 (31.5) kJ/kg/min), and boxing (198.1 (33.9) kJ/kg/min) was significantly greater than when playing sedentary games (125.5 (13.7) kJ/kg/min) (P<0.001). Predicted energy expenditure was at least 65.1 (95% confidence interval 47.3 to 82.9) kJ/kg/min greater when playing active rather than sedentary games.

Conclusions :
Playing new generation active computer games uses significantly more energy than playing sedentary computer games but not as much energy as playing the sport itself. The energy used when playing active Wii Sports games was not of high enough intensity to contribute towards the recommended daily amount of exercise in children.

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It is anticipated that the current workforce of teachers in Victoria, Australia will retire within the next 5-15 years. The paradox for teachers at the career entry point is that while they are expected to quickly assume responsibility for education in this state, beginning teachers are reporting dissatisfaction with teaching and describing it as an ‘unprofessional’ profession. Drawing from recently commissioned research for the Victorian Institute of Teaching, a study of sixty beginning teachers and a micro study of the ‘internship’ experience of teacher educators, this paper explores the consequences of what counts as professional knowledge. By problematising identity issues for beginning teachers it is hoped that greater understanding of the complexities of their realities is revealed. The aspirations for the (re) generation of a profession are entangled in discordant displacement of meanings of what it is to become a teacher. What do ‘othering’ and power(less) positions of beginning teachers mean for the immediate future of the profession? What then are the implications for school contexts, colleague support and pre-service teacher education?

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Previous research suggests that there is a relationship between social contexts (e.g., economic growth, engagement in wars) and motives within populations. In particular, high achievement motive is associated with subsequent economic growth, which in turn increases power motive. Increased national achievement and power motives have been argued to precede social changes that lead to decreased affiliation motives, and engagement in wars. The present study aimed to examine differences in achievement, power, and affiliation motives between 266 college students in China (a nation with sustained high economic growth) and 255 college students in the USA (a nation with previously strong but now slowing economic growth, and engaged in war). Analysis of personal strivings suggested that Chinese college students showed significantly higher levels of achievement motive than the American college students, but American college students showed significantly higher levels of affiliation motive than Chinese college students. Overall, males exhibited higher achievement motivation than females. No significant interaction effects were found for gender by location for any of the three motives. The findings are discussed in relation to previous research.

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Data analysis using intelligent systems is a key solution to many industrial problems. In this paper, a mutation-based evolving artificial neural network, which is based on an integration of the Fuzzy ARTMAP (FAM) neural network and evolutionary programming (EP), is proposed. The proposed FAMEP model is applied to detect and classify possible faults from a number of sensory signals of a circulating water system in a power generation plant. The efficiency of FAM-EP is assessed and compared with that of the original FAM network in terms of classification accuracy as well as network complexity. In addition, the bootstrap method is used to quantify the performance statistically. The results positively demonstrate the usefulness of FAM-EP in tackling data classification problems.

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This paper describes the application of an adaptive neural network, called Fuzzy ARTMAP (FAM), to handle fault prediction and condition monitoring problems in a power generation station. The FAM network, which is supplemented with a pruning algorithm, is used as a classifier to predict different machine conditions, in an off-line learning mode. The process under scrutiny in the power plant is the Circulating Water (CW) system, with prime attention to monitoring the heat transfer efficiency of the condensers. Several phases of experiments were conducted to investigate the `optimum' setting of a set of parameters of the FAM classifier for monitoring heat transfer conditions in the power plant.

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Positive Unit commitment and economic dispatch are two important decisions in thermal power generation scheduling. The tasks involve determination and allocation of power generation to thermal units that minimize the total power generation cost and satisfy the production constraints.This paper presents a cascade Genetic Algorithm and Particle Swarm Optimization (GA-PSO) approach for solving thermal power generation scheduling based on a layered matrix encoding structure.The proposed hybrid method is compared to layered matrix encoding GA using the thermal power generation problem given in Williams [1] to demonstrate its effectiveness in generating an optimal, cost-effective power generation schedule.The results showed that cascade GA-PSO outperformed the layered matrix encoding GA in minimizing the total power production cost for unit commitment and power dispatch problems.

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A hybrid network, based on the integration of Fuzzy ARTMAP (FAM) and the Rectangular Basis Function Network (RecBFN), is proposed for rule learning and extraction problems. The underlying idea for such integration is that FAM operates as a classifier to cluster data samples based on similarity, while the RecBFN acts as a “compressor” to extract and refine knowledge learned by the trained FAM network. The hybrid network is capable of classifying data samples incrementally as well as of acquiring rules directly from data samples for explaining its predictions. To evaluate the effectiveness of the hybrid network, it is applied to a fault detection and diagnosis task by using a set of real sensor data collected from a Circulating Water (CW) system in a power generation plant. The rules extracted from the network are analyzed and discussed, and are found to be in agreement with experts’ opinions used in maintaining the CW system.