62 resultados para Scenarios for generation and demand


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The reaction mechanism of CO and Fe2O3 in a chemical-looping combustion (CLC) was studied based on density functional theory (DFT) at B3LYP level in this paper. The structures of all reactants, intermediate, transition structures and products of this reaction had been optimized and characterized. The reaction path was validated by means of the intrinsic reaction coordinate (IRC) approach. The result showed that the reaction was divided into two steps, the adsorbed CO molecule on Fe 2O3 surface formed a medium state with one broken Fe-O bond in step1, and in step2, O atom broken here oxidized a subsequent CO molecule in the fuel reactor. Thus, Fe2O3 molecule transport O from air to oxide CO continually in the CLC process. The activation energy and rate coefficients of the two steps were also obtained.

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Climate change during the last five decades has impacted significantly on natural ecosystems and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed ‘modellable’ within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions.

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The acceleration of intense proton and ion beams by ultra-intense lasers has matured to a point where applications in basic research and technology are being developed. Crucial for harvesting the unmatched beam parameters driven by the relativistic electron sheath is the precise control of the beam. We report on recent experiments using the PHELIX laser at GSI, the VULCAN laser at RAL and the TRIDENT laser at LANL to control and use laser accelerated proton beams for applications in high energy density research. We demonstrate efficient collimation of the proton beam using high field pulsed solenoid magnets, a prerequisite to capture and transport the beam for applications. Furthermore we report on two campaigns to use intense, short proton bunches to isochorically heat solid targets up to the warm dense matter state. The temporal profile of the proton beam allows for rapid heating of the target, much faster than the hydrodynamic response time thereby creating a strongly coupled plasma at solid density. The target parameters are then probed by X-ray Thomson scattering (XRTS) to reveal the density and temperature of the heated volume. This combination of two powerful techniques developed during the past few years allows for the generation and investigation of macroscopic samples of matter in states present in giant planets or the interior of the earth.

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Grid operators and electricity retailers in Ireland manage peak demand, power system balancing and grid congestion by offering relevant incentives to consumers to reduce or shift their load. The need for active consumers in the home using smart appliances has never been greater, due to increased variable renewable generation and grid constraints. In this paper an aggregated model of a single compressor fridge-freezer population is developed. A price control strategy is examined to quantify and value demand response savings during a representative winter and summer week for Ireland in 2020. The results show an average reduction in fridge-freezer operating cost of 8.2% during winter and significantly lower during summer in Ireland. A peak reduction of at least 68% of the average winter refrigeration load is achieved consistently during the week analysed using a staggering control mode. An analysis of the current ancillary service payments confirms that these are insufficient to ensure widespread uptake by the small consumer, and new mechanisms need to be developed to make becoming an active consumer attractive. Demand response is proposed as a new ancillary service called ramping capability, as the need for this service will increase with more renewable energy penetration on the power system.

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Gas fired generation currently plays an integral support role ensuring security of supply in power systems with high wind power penetrations due to its technical and economic attributes. However, the increase in variable wind power has affected the gas generation output profile and is pushing the boundaries of the design and operating envelope of gas infrastructure. This paper investigates the mutual dependence and interaction between electricity generation and gas systems through the first comprehensive joined-up, multi-vector energy system analysis for Ireland. Key findings reveal the high vulnerability of the Irish power system to outages on the Irish gas system. It has been shown that the economic operation of the power system can be severely impacted by gas infrastructure outages, resulting in an average system marginal price of up to €167/MWh from €67/MWh in the base case. It has also been shown that gas infrastructure outages pose problems for the location of power system reserve provision, with a 150% increase in provision across a power system transmission bottleneck. Wind forecast error was shown to be a significant cause for concern, resulting in large swings in gas demand requiring key gas infrastructure to operate at close to 100% capacity. These findings are thought to increase in prominence as the installation of wind capacity increases towards 2020, placing further stress on both power and gas systems to maintain security of supply.

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The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

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We describe a protocol for the generation and validation of bacteria microarrays and their application to the study of specific features of the pathogen's surface and interactions with host receptors. Bacteria were directly printed on nitrocellulose-coated glass slides, using either manual or robotic arrayers, and printing quality, immobilization efficiency and stability of the arrays were rigorously controlled by incorporating a fluorescent dye into the bacteria. A panel of wild type and mutant strains of the human pathogen Klebsiella pneumoniae, responsible for nosocomial and community-acquired infections, was selected as model bacteria, and SYTO-13 was used as dye. Fluorescence signals of the printed bacteria were found to exhibit a linear concentration-dependence in the range of 1 x 10(8) to 1 x 10(9) bacteria per ml. Similar results were obtained with Pseudomonas aeruginosa and Acinetobacter baumannii, two other human pathogens. Successful validation of the quality and applicability of the established microarrays was accomplished by testing the capacity of the bacteria array to detect recognition by anti-Klebsiella antibodies and by the complement subcomponent C1q, which binds K. pneumoniae in an antibody-independent manner. The biotin/AlexaFluor-647-streptavidin system was used for monitoring binding, yielding strain-and dose-dependent signals, distinctive for each protein. Furthermore, the potential of the bacteria microarray for investigating specific features, e.g. glycosylation patterns, of the cell surface was confirmed by examining the binding behaviour of a panel of plant lectins with diverse carbohydrate-binding specificities. This and other possible applications of the newly developed arrays, as e.g. screening/evaluation of compounds to identify inhibitors of host-pathogen interactions, make bacteria microarrays a useful and sensitive tool for both basic and applied research in microbiology, biomedicine and biotechnology.

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Purpose: Despite the significant interest in molecular hydrogen as an antioxidant in the last eight years, its quantitative metabolic parameters in vivo are still lacking, as is an appropriate method for determination of hydrogen effectivity in the mammalian organism under various conditions.

Basic Procedures: Intraperitoneally-applied deuterium gas was used as a metabolic tracer and deuterium enrichment was determined in the body water pool. Also, in vitro experiments were performed using bovine heart submitochondrial particles to evaluate superoxide formation in Complex I of the respiratory chain.

Main Findings: A significant oxidation of about 10% of the applied dose was found under physiological conditions in rats, proving its antioxidant properties. Hypoxia or endotoxin application did not exert any effect, whilst pure oxygen inhalation reduced deuterium oxidation. During in vitro experiments, a significant reduction of superoxide formation by Complex I of the respiratory chain was found under the influence of hydrogen. The possible molecular mechanisms of the beneficial effects of hydrogen are discussed, with an emphasis on the role of iron sulphur clusters in reactive oxygen species generation and on iron species-dihydrogen interaction.

Principal Conclusions: According to our findings, hydrogen may be an efficient, non-toxic, highly bioavailable and low-cost antioxidant supplement for patients with pathological conditions involving ROS-induced oxidative stress.

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Clean and renewable energy generation and supply has drawn much attention worldwide in recent years, the proton exchange membrane (PEM) fuel cells and solar cells are among the most popular technologies. Accurately modeling the PEM fuel cells as well as solar cells is critical in their applications, and this involves the identification and optimization of model parameters. This is however challenging due to the highly nonlinear and complex nature of the models. In particular for PEM fuel cells, the model has to be optimized under different operation conditions, thus making the solution space extremely complex. In this paper, an improved and simplified teaching-learning based optimization algorithm (STLBO) is proposed to identify and optimize parameters for these two types of cell models. This is achieved by introducing an elite strategy to improve the quality of population and a local search is employed to further enhance the performance of the global best solution. To improve the diversity of the local search a chaotic map is also introduced. Compared with the basic TLBO, the structure of the proposed algorithm is much simplified and the searching ability is significantly enhanced. The performance of the proposed STLBO is firstly tested and verified on two low dimension decomposable problems and twelve large scale benchmark functions, then on the parameter identification of PEM fuel cell as well as solar cell models. Intensive experimental simulations show that the proposed STLBO exhibits excellent performance in terms of the accuracy and speed, in comparison with those reported in the literature.

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Quasi-phase matching (QPM) can be used to increase the conversion efficiency of the high harmonic generation (HHG) process. We observed QPM with an improved dual-gas foil target with a 1 kHz, 10 mJ, 30 fs laser system. Phase tuning and enhancement were possible within a spectral range from 17 nm to 30 nm. Furthermore analytical calculations and numerical simulations were carried out to distinguish QPM from other effects, such as the influence of adjacent jets on each other or the laser gas interaction. The simulations were performed with a 3 dimensional code to investigate the phase matching of the short and long trajectories individually over a large spectral range.

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This paper introduces a novel load sharing algorithm to enable island synchronization. The system model used for development is based on an actual system for which historical measurement and fault data is available and is used to refine and test the algorithms performance and validity. The electrical system modelled is selected due to its high-level of hydroelectric generation and its history of islanding events. The process of developing the load sharing algorithm includes a number of steps. Firstly, the development of a simulation model to represent the case study accurately - this is validated by way of matching system behavior based on data from historical island events. Next, a generic island simulation is used to develop the load sharing algorithm. The algorithm is then tested against the validated simulation model representing the case study area selected. Finally, a laboratory setup is described which is used as validation method for the novel load sharing algorithm.

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The results in this paper are based on a data set containing system demand, wind generation and CO2 emission between Jan 2010 and Sep 2013. The data was recorded at 15 minute intervals and reflects the macroscopic operation of the Republic of Ireland's electrical grid. The data was analyzed by investigating how daily wind generation effected daily CO2 emission across multiple days with equivalent daily demand. A figure for wind turbine efficiency was determined by dividing the CO2 mitigation potential of wind power by the CO2 intensity of the grid; both in units of Tonnes of CO2 per MWh. The yearly wind power efficiency appears to have increased by 5.6% per year, now standing around 90%. Over the four years significant regularity was observed in the profiles of wind turbine efficiency against daily demand. It appears that the efficiency profile has moved in recent years so that maximum efficiency coincides with most frequent demand.

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Attempts to record, understand and respond to variations in child welfare and protection reporting, service patterns and outcomes are international, numerous and longstanding. Reframing such variations as an issue of inequity between children and between families opens the way to a new approach to explaining the profound difference in intervention rates between and within countries and administrative districts. Recent accounts of variation have frequently been based on the idea that there is a binary division between bias and risk (or need). Here we propose seeing supply (bias) and demand (risk) factors as two aspects of a single system, both framed, in part, by social structures. A recent finding from a study of intervention rates in England, the 'inverse intervention law', is used to illustrate the complex ways in which a range of factors interact to produce intervention rates. In turn, this analysis raises profound moral, policy, practice and research questions about current child welfare and child protection services.