275 resultados para Electricity generation


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Simple and reliable formation of biodegradable nanoparticles formed from poly-ε-caprolactone was achieved using 1.645 MHz piston atomization of a source fluid of 0.5% w/v of the polymer dissolved in acetone; the particles were allowed to descend under gravity in air 8 cm into a 1 mM solution of sodium dodecyl sulfate. After centrifugation to remove surface agglomerations, a symmetric monodisperse distribution of particles φ 186 nm (SD=5.7, n=6) was obtained with a yield of 65.2%. © 2006 American Institute of Physics.

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The global efforts to reduce carbon emissions from power generation have favoured renewable energy resources such as wind and solar in recent years. The generation of power from the renewable energy resources has become attractive because of various incentives provided by government policies supporting green power. Among the various available renewable energy resources, the power generation from wind has seen tremendous growth in the last decade. This article discusses various advantages of the upcoming offshore wind technology and associated considerations related to their construction. The conventional configuration of the offshore wind farm is based on the alternative current internal links. With the recent advances of improved commercialised converters, voltage source converters based high voltage direct current link for offshore wind farms is gaining popularity. The planning and construction phases of offshore wind farms, including related environmental issues, are discussed here.

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This paper relates to the importance of impact of the chosen bottle-point method when conducting ion exchange equilibria experiments. As an illustration, potassium ion exchange with strong acid cation resin was investigated due to its relevance to the treatment of various industrial effluents and groundwater. The “constant mass” bottle-point method was shown to be problematic in that depending upon the resin mass used the equilibrium isotherm profiles were different. Indeed, application of common equilibrium isotherm models revealed that the optimal fit could be with either the Freundlich or Temkin equations, depending upon the conditions employed. It could be inferred that the resin surface was heterogeneous in character, but precise conclusions regarding the variation in the heat of sorption were not possible. Estimation of the maximum potassium loading was also inconsistent when employing the “constant mass” method. The “constant concentration” bottle-point method illustrated that the Freundlich model was a good representation of the exchange process. The isotherms recorded were relatively consistent when compared to the “constant mass” approach. Unification of all the equilibrium isotherm data acquired was achieved by use of the Langmuir Vageler expression. The maximum loading of potassium ions was predicted to be at least 116.5 g/kg resin.

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In this chapter, we explore methods for automatically generating game content—and games themselves—adapted to individual players in order to improve their playing experience or achieve a desired effect. This goes beyond notions of mere replayability and involves modeling player needs to maximize their enjoyment, involvement, and interest in the game being played. We identify three main aspects of this process: generation of new content and rule sets, measurement of this content and the player, and adaptation of the game to change player experience. This process forms a feedback loop of constant refinement, as games are continually improved while being played. Framed within this methodology, we present an overview of our recent and ongoing research in this area. This is illustrated by a number of case studies that demonstrate these ideas in action over a variety of game types, including 3D action games, arcade games, platformers, board games, puzzles, and open-world games. We draw together some of the lessons learned from these projects to comment on the difficulties, the benefits, and the potential for personalized gaming via adaptive game design.

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Understanding the dynamics of disease spread is essential in contexts such as estimating load on medical services, as well as risk assessment and interven- tion policies against large-scale epidemic outbreaks. However, most of the information is available after the outbreak itself, and preemptive assessment is far from trivial. Here, we report on an agent-based model developed to investigate such epidemic events in a stylised urban environment. For most diseases, infection of a new individual may occur from casual contact in crowds as well as from repeated interactions with social partners such as work colleagues or family members. Our model therefore accounts for these two phenomena. Given the scale of the system, efficient parallel computing is required. In this presentation, we focus on aspects related to paralllelisation for large networks generation and massively multi-agent simulations.

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Integrating renewable energy into public space is becoming more common as a climate change solution. However, this approach is often guided by the environmental pillar of sustainability, with less focus on the economic and social pillars. The purpose of this paper is to examine this issue in the speculative renewable energy propositions for Freshkills Park in New York City submitted for the 2012 Land Art Generator Initiative (LAGI) competition. This paper first proposes an optimal electricity distribution (OED) framework in and around public spaces based on relevant ecology and energy theory (Odum’s fourth and fifth law of thermodynamics). This framework addresses social engagement related to public interaction, and economic engagement related to the estimated quantity of electricity produced, in conjunction with environmental engagement related to the embodied energy required to construct the renewable energy infrastructure. Next, the study uses the OED framework to analyse the top twenty-five projects submitted for the LAGI 2012 competition. The findings reveal an electricity distribution imbalance and suggest a lack of in-depth understanding about sustainable electricity distribution within public space design. The paper concludes with suggestions for future research.

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Utilities worldwide are focused on supplying peak electricity demand reliably and cost effectively, requiring a thorough understanding of all the factors influencing residential electricity use at peak times. An electricity demand reduction project based on comprehensive residential consumer engagement was established within an Australian community in 2008, and by 2011, peak demand had decreased to below pre-intervention levels. This paper applied field data discovered through qualitative in-depth interviews of 22 residential households at the community to a Bayesian Network complex system model to examine whether the system model could explain successful peak demand reduction in the case study location. The knowledge and understanding acquired through insights into the major influential factors and the potential impact of changes to these factors on peak demand would underpin demand reduction intervention strategies for a wider target group.

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This work explores the potential of Australian native plants as a source of second-generation biodiesel for internal combustion engines application. Biodiesels were evaluated from a number of non-edible oil seeds which are grow naturally in Queensland, Australia. The quality of the produced biodiesels has been investigated by several experimental and numerical methods. The research methodology and numerical model developed in this study can be used for a broad range of biodiesel feedstocks and for the future development of renewable native biodiesel in Australia.

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This paper introduces the smooth transition logit (STL) model that is designed to detect and model situations in which there is structural change in the behaviour underlying the latent index from which the binary dependent variable is constructed. The maximum likelihood estimators of the parameters of the model are derived along with their asymptotic properties, together with a Lagrange multiplier test of the null hypothesis of linearity in the underlying latent index. The development of the STL model is motivated by the desire to assess the impact of deregulation in the Queensland electricity market and ascertain whether increased competition has resulted in significant changes in the behaviour of the spot price of electricity, specifically with respect to the occurrence of periodic abnormally high prices. The model allows the timing of any change to be endogenously determined and also market participants' behaviour to change gradually over time. The main results provide clear evidence in support of a structural change in the nature of price events, and the endogenously determined timing of the change is consistent with the process of deregulation in Queensland.

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Integration of small-scale electricity generators, known as distributed generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of the synchronous-type generator has potential to give DG a better chance at participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of DG as a voltage regulator and, at the same time, minimize interaction with other active devices, such as an on-load tap changing transformer and a voltage regulator. The technique has been developed based on the concept of control zone, line drop compensation, dead band, as well as the choice of controllers' parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

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This work is a MATLAB/Simulink model of a controller for a three-phase, four-wire, grid-interactive inverter. The model provides capacity for simulating the performance of power electroinic hardware, as well as code generation for an embedded controller. The implemented hardware topology is a three-leg bridge with a neutral connection to the centre-tap of the DC bus. An LQR-based current controller and MAF-based phase detector are implemented. The model is configured for code generation for a Texas Instruments TMS320F28335 Digital Signal Processor (DSP).

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Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.