422 resultados para 660000 - Energy Supply


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Organizations adopt a Supply Chain Management System (SCMS) expecting benefits to the organization and its functions. However, organizations are facing mounting challenges to realizing benefits through SCMS. Studies suggest a growing dissatisfaction among client organizations due to an increasing gap between expectations and realization of SCMS benefits. Further, reflecting the Enterprise System studies such as Seddon et al. (2010), SCMS benefits are also expected to flow to the organization throughout its lifecycle rather than being realized all at once. This research therefore proposes to derive a lifecycle-wide understanding of SCMS benefits and realization to derive a benefit expectation management framework to attain the full potential of an SCMS. The primary research question of this study is: How can client organizations better manage their benefit expectations of SCM systems? The specific research goals of the current study include: (1) to better understand the misalignment of received and expected benefits of SCM systems; (2) to identify the key factors influencing SCM system expectations and to develop a framework to manage SCMS benefits; (3) to explore how organizational satisfaction is influenced by the lack of SCMS benefit confirmation; and (4) to explore how to improve the realization of SCM system benefits. Expectation-Confirmation Theory (ECT) provides the theoretical underpinning for this study. ECT has been widely used in the consumer behavior literature to study customer satisfaction, post-purchase behavior and service marketing in general. Recently, ECT has been extended into Information Systems (IS) research focusing on individual user satisfaction and IS continuance. However, only a handful of studies have employed ECT to study organizational satisfaction on large-scale IS. The current study will enrich the research stream by extending ECT into organizational-level analysis and verifying the preliminary findings of relevant works by Staples et al. (2002), Nevo and Chan (2007) and Nevo and Wade (2007). Moreover, this study will go further trying to operationalize the constructs of ECT into the context of SCMS. The empirical findings of the study commence with a content analysis, through which 41 vendor reports and academic reports are analyzed yielding sixty expected benefits of SCMS. Then, the expected benefits are compared with the benefits realized at a case organization in the Fast Moving Consumer Goods industry sector that had implemented a SAP Supply Chain Management System seven years earlier. The study develops an SCMS Benefit Expectation Management (SCMS-BEM) Framework. The comparison of benefit expectations and confirmations highlights that, while certain benefits are realized earlier in the lifecycle, other benefits could take almost a decade to realize. Further analysis and discussion on how the developed SCMS-BEM Framework influences ECT when applied in SCMS was also conducted. It is recommended that when establishing their expectations of the SCMS, clients should remember that confirmation of these expectations will have a long lifecycle, as shown in the different time periods in the SCMS-BEM Framework. Moreover, the SCMS-BEM Framework will allow organizations to maintain high levels of satisfaction through careful mitigation and confirming expectations based on the lifecycle phase. In addition, the study reveals that different stakeholder groups have different expectations of the same SCMS. The perspective of multiple stakeholders has significant implications for the application of ECT in the SCMS context. When forming expectations of the SCMS, the collection of organizational benefits of SCMS should represent the perceptions of all stakeholder groups. The same mechanism should be employed in the measurements of received SCMS benefits. Moreover, for SCMS, there exists interdependence of the satisfaction among the various stakeholders. The satisfaction of decision-makers or the authorized staff is not only driven by their own expectation confirmation level, it is also influenced by the confirmation level of other stakeholders‘ expectations in the organization. Satisfaction from any one particular stakeholder group can not reflect the true satisfaction of the client organization. Furthermore, it is inferred from the SCMS-BEM Framework that organizations should place emphasis on the viewpoints of the operational and management staff when evaluating the benefits of SCMS in the short and middle term. At the same time, organizations should be placing more attention on the perspectives of strategic staff when evaluating the performance of the SCMS in the long term.

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Load in distribution networks is normally measured at the 11kV supply points; little or no information is known about the type of customers and their contributions to the load. This paper proposes statistical methods to decompose an unknown distribution feeder load to its customer load sector/subsector profiles. The approach used in this paper should assist electricity suppliers in economic load management, strategic planning and future network reinforcements.

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Structural health monitoring (SHM) refers to the procedure used to assess the condition of structures so that their performance can be monitored and any damage can be detected early. Early detection of damage and appropriate retrofitting will aid in preventing failure of the structure and save money spent on maintenance or replacement and ensure the structure operates safely and efficiently during its whole intended life. Though visual inspection and other techniques such as vibration based ones are available for SHM of structures such as bridges, the use of acoustic emission (AE) technique is an attractive option and is increasing in use. AE waves are high frequency stress waves generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. AE technique involves recording these waves by means of sensors attached on the surface and then analysing the signals to extract information about the nature of the source. High sensitivity to crack growth, ability to locate source, passive nature (no need to supply energy from outside, but energy from damage source itself is utilised) and possibility to perform real time monitoring (detecting crack as it occurs or grows) are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications, especially in the area of analysis of recorded AE data, as large volumes of data are usually generated during monitoring. The need for effective data analysis can be linked with three main aims of monitoring: (a) accurately locating the source of damage; (b) identifying and discriminating signals from different sources of acoustic emission and (c) quantifying the level of damage of AE source for severity assessment. In AE technique, the location of the emission source is usually calculated using the times of arrival and velocities of the AE signals recorded by a number of sensors. But complications arise as AE waves can travel in a structure in a number of different modes that have different velocities and frequencies. Hence, to accurately locate a source it is necessary to identify the modes recorded by the sensors. This study has proposed and tested the use of time-frequency analysis tools such as short time Fourier transform to identify the modes and the use of the velocities of these modes to achieve very accurate results. Further, this study has explored the possibility of reducing the number of sensors needed for data capture by using the velocities of modes captured by a single sensor for source localization. A major problem in practical use of AE technique is the presence of sources of AE other than crack related, such as rubbing and impacts between different components of a structure. These spurious AE signals often mask the signals from the crack activity; hence discrimination of signals to identify the sources is very important. This work developed a model that uses different signal processing tools such as cross-correlation, magnitude squared coherence and energy distribution in different frequency bands as well as modal analysis (comparing amplitudes of identified modes) for accurately differentiating signals from different simulated AE sources. Quantification tools to assess the severity of the damage sources are highly desirable in practical applications. Though different damage quantification methods have been proposed in AE technique, not all have achieved universal approval or have been approved as suitable for all situations. The b-value analysis, which involves the study of distribution of amplitudes of AE signals, and its modified form (known as improved b-value analysis), was investigated for suitability for damage quantification purposes in ductile materials such as steel. This was found to give encouraging results for analysis of data from laboratory, thereby extending the possibility of its use for real life structures. By addressing these primary issues, it is believed that this thesis has helped improve the effectiveness of AE technique for structural health monitoring of civil infrastructures such as bridges.

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Australia requires decisive action on climate change and issues of sustainability. The Urban Informatics Research Lab has been funded by the Queensland State Government to conduct a three year study (2009 – 2011) exploring ways to support Queensland residents in making more sustainable consumer and lifestyle choices. We conduct user-centred design research that inform the development of real-time, mobile, locational, networked information interfaces, feedback mechanisms and persuasive and motivational approaches that in turn assist in-situ decision making and environmental awareness in everyday settings. The study aims to deliver usable and useful prototypes offering individual and collective visualisations of ecological impact and opportunities for engagement and collaboration in order to foster a participatory and sustainable culture of life in Australia. Raising people’s awareness with environmental data and educational information does not necessarily trigger sufficient motivation to change their habits towards a more environmentally friendly and sustainable lifestyle. Our research seeks to develop a better understanding how to go beyond just informing and into motivating and encouraging action and change. Drawing on participatory culture, ubiquitous computing, and real-time information, the study delivers research that leads to viable new design approaches and information interfaces which will strengthen Australia’s position to meet the targets of the Clean Energy Future strategy, and contribute to the sustainability of a low-carbon future in Australia. As part of this program of research, the Urban Informatics Research Lab has been invited to partner with GV Community Energy Pty Ltd on a project funded by the Victorian Government Sustainability Fund. This feasibility report specifically looks at the challenges and opportunities of energy monitoring in households in Victoria that include a PV solar installation. The report is structured into two parts: In Part 1, we first review a range of energy monitoring solutions, both stand-alone and internet-enabled. This section primarily focusses on the technical capacilities. However, in order to understand this information and make an informed decision, it is crucial to understand the basic principles and limitations of energy monitoring as well as the opportunities and challenges of a networked approach towards energy monitoring which are discussed in Section 2.

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This paper presents an approach to modelling the resilience of a generic (potable) water supply system. The system is contextualized as a meta-system consisting of three subsystems to represent the natural catchment, the water treatment plant and the water distribution infrastructure for urban use. An abstract mathematical model of the meta-system is disaggregated progressively to form a cascade of equations forming a relational matrix of models. This allows the investigation of commonly implicit relationships between various operational components within the meta system, the in-depth understanding of specific system components and influential factors and the incorporation of explicit disturbances to explore system behaviour. Consequently, this will facilitate long-term decision making to achieve sustainable solutions for issues such as, meeting a growing demand or managing supply-side influences in the meta-system under diverse water availability regimes. This approach is based on the hypothesis that the means to achieve resilient supply of water may be better managed by modelling the effects of changes at specific levels that have a direct or in some cases indirect impact on higher-order outcomes. Additionally, the proposed strategy allows the definition of approaches to combine disparate data sets to synthesise previously missing or incomplete higher-order information, a scientifically robust means to define and carry out meta-analyses using knowledge from diverse yet relatable disciplines relevant to different levels of the system and for enhancing the understanding of dependencies and inter-dependencies of variable factors at various levels across the meta-system. The proposed concept introduces an approach for modelling a complex infrastructure system as a meta system which consists of a combination of bio-ecological, technical and socio-technical subsystems.

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This paper addresses the snap of renewable energy and the need for effective progress strategies linked with sustainable energy development along with prospect of renewable energy in Bangladesh. Our country is gifted with vast renewable energy resources such as biomass and solar. Approximately 73% of total energy demand of the country is supplied by local biomass based fuels. Bangladesh is endowed with abundant supplies of solar energy. Annually about 1.9 MWh energy is received per square meter of horizontal area in Bangladesh. Besides, hydro and wind as well as geothermal power can be considered as potential renewable energy resources. Karnafuli Hydro Station is the merely hydro energy power generation plant of the country that generates 230 MW. The annual wind speed at a height of 25m at some coastal locations is above 5 m/s and much higher in the pre-monsoon and monsoon periods.

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The most suitable temperature range for domestic purposes is about 200C to 260C .Besides, both cold and hot water appear to be essential frequently for industrial purposes. In summer bringing down the water temperature at a comfortable range causes significant energy consumption. This project aims at saving energy to control water temperature by making water tank insulated .Therefore applying better insulation system which would reduce the disparity between the desired temperature and the actual temperature and hence saving energy significantly. Following the investigation, this project used cotton jacket to insulate the tank and the tank was placed under a paddy straw shade with a view to attaining the maximum energy saving. Finally, it has been found that reduction in energy consumption is to be about 50-60% which is quite satisfactory. Since comfortable temperature range varies from person to person this project thus combines insulating effect with automatic water heater.

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The conversion of tamarind seeds into pyrolytic oil by fixed bed fire-tube heating reactor has been taken into consideration in this study. The major components of the system were fixed bed fire-tube heating reactor, liquid condenser and collectors. The raw and crushed tamarind seed in particle form was pyrolized in an electrically heated 10 cm diameter and 27 cm high fixed bed reactor. The products are oil, char and gases. The parameters varied were reactor bed temperature, running time, gas flow rate and feed particle size. The parameters were found to influence the product yields significantly. The maximum liquid yield was 45 wt% at 4000C for a feed size of 1.07cm3 at a gas flow rate of 6 liter/min with a running time of 30 minute. The pyrolysis oil was obtained at these optimum process conditions were analyzed for physical and chemical properties to be used as an alternative fuel.

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The growing demand of air-conditioning is one of the largest contributors to Australia’s overall electricity consumption. This has started to create peak load supply problems for some electricity utilities particularly in Queensland. This research aimed to develop consumer demand side response model to assist electricity consumers to mitigate peak demand on the electrical network. The model developed demand side response model to allow consumers to manage and control air conditioning for every period, it is called intelligent control. This research investigates optimal response of end-user toward electricity price for several cases in the near future, such as: no spike, spike and probability spike price cases. The results indicate the potential of the scheme to achieve energy savings, reducing electricity bills (costs) to the consumer and targeting best economic performance for electrical generation distribution and transmission.

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Road safety barriers are used to minimise the severity of road accidents and protect lives and property. There are several types of barrier in use today. This paper reports the initial phase of research carried out to study the impact response of portable water-filled barrier (PWFB) which has the potential to absorb impact energy and hence provide crash mitigation under low to moderate speeds. Current research on the impact and energy absorption capacity of water-filled road safety barriers is limited due to the complexity of fluid-structure interaction under dynamic impact. In this paper, a novel fluid-structure interaction method is developed based on the combination of Smooth Particle Hydrodynamics (SPH) and Finite Element Method (FEM). The sloshing phenomenon of water inside a PWFB is investigated to explore the energy absorption capacity of water under dynamic impact. It was found that water plays an important role in energy absorption. The coupling analysis developed in this paper will provide a platform to further the research in optimising the behaviour of the PWFB. The effect of the amount of water on its energy absorption capacity is investigated and the results have practical applications in the design of PWFBs.

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Improving energy efficiency has become increasingly important in data centers in recent years to reduce the rapidly growing tremendous amounts of electricity consumption. The power dissipation of the physical servers is the root cause of power usage of other systems, such as cooling systems. Many efforts have been made to make data centers more energy efficient. One of them is to minimize the total power consumption of these servers in a data center through virtual machine consolidation, which is implemented by virtual machine placement. The placement problem is often modeled as a bin packing problem. Due to the NP-hard nature of the problem, heuristic solutions such as First Fit and Best Fit algorithms have been often used and have generally good results. However, their performance leaves room for further improvement. In this paper we propose a Simulated Annealing based algorithm, which aims at further improvement from any feasible placement. This is the first published attempt of using SA to solve the VM placement problem to optimize the power consumption. Experimental results show that this SA algorithm can generate better results, saving up to 25 percentage more energy than First Fit Decreasing in an acceptable time frame.

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Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.

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Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

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The Midwest Independent Transmission System Operator (MISO) has experienced significant amounts of wind power development within the last decade. The MISO footprint spans the majority of the upper Midwest region of the country, from the Dakotas to Indiana and as far east as Michigan. These areas have a rich wind energy resource. States in the MISO footprint have passed laws or set goals that require load serving entities to supply a portion of their load using renewable energy. In order to meet these requirements, significant investments are needed to build the transmission infrastructure necessary to deliver the power from these often remote wind energy resources to the load centers. This paper presents some of the transmission planning related work done at MISO which was largely influenced by current and future needs for increased wind power generation in the footprint. Specifically, topics covered are generator interconnection, long-term planning coordination, and cost-allocation for new transmission lines.

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Australia is rich in renewable energy resources such as wind, solar and geothermal. Geographical diversity of these renewable resources combined with developing climate change policies poses a great challenge for the long term interconnection planning. Intermittency of wind and solar potentially driving the development of new transmission lines bring additional complexity to power system operations and planning. This paper provides an overview of generation and transmission planning studies in Australia to meet 20% renewable energy target by 2020. Appraisal of the effectiveness of dispersed energy storage, non schedulable peaking plants, wide area controls and demand management techniques to aid the penetration of renewables is presented in this paper