56 resultados para Power to gas

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

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The European Union continues to exert a large influence on the direction of member states energy policy. The 2020 targets for renewable energy integration have had significant impact on the operation of current power systems, forcing a rapid change from fossil fuel dominated systems to those with high levels of renewable power. Additionally, the overarching aim of an internal energy market throughout Europe has and will continue to place importance on multi-jurisdictional co-operation regarding energy supply. Combining these renewable energy and multi-jurisdictional supply goals results in a complicated multi-vector energy system, where the understanding of interactions between fossil fuels, renewable energy, interconnection and economic power system operation is increasingly important. This paper provides a novel and systematic methodology to fully understand the changing dynamics of interconnected energy systems from a gas and power perspective. A fully realistic unit commitment and economic dispatch model of the 2030 power systems in Great Britain and Ireland, combined with a representative gas transmission energy flow model is developed. The importance of multi-jurisdictional integrated energy system operation in one of the most strategically important renewable energy regions is demonstrated.

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The spatial distributions of marine fauna and of pollution are both highly structured, and thus the resulting high levels of autocorrelation may invalidate conclusions based on classical statistical approaches. Here we analyse the close correlation observed between proxies for the disturbance associated with gas extraction activities and amphipod distribution patterns around four hydrocarbon platforms. We quantified the amount of variation independently accounted for by natural environmental variables, proxies for the disturbance caused by platforms, and spatial autocorrelation. This allowed us to demonstrate how each of these three factors significantly affects the community structure of amphipods. Sophisticated statistical techniques are required when taking into account spatial autocorrelation: nevertheless our data demonstrate that this approach not only enables the formulation of robust statistical inferences but also provides a much deeper understanding of the subtle interactions between human disturbance and natural factors affecting the structure of marine invertebrates communities. (C) 2012 Elsevier Ltd. All rights reserved.

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Large samples of multiplex pedigrees will probably be needed to detect susceptibility loci for schizophrenia by linkage analysis. Standardized ascertainment of such pedigrees from culturally and ethnically homogeneous populations may improve the probability of detection and replication of linkage. The Irish Study of High-Density Schizophrenia Families (ISHDSF) was formed from standardized ascertainment of multiplex schizophrenia families in 39 psychiatric facilities covering over 90% of the population in Ireland and Northern Ireland. We here describe a phenotypic sample and a subset thereof, the linkage sample. Individuals were included in the phenotypic sample if adequate diagnostic information, based on personal interview and/or hospital record, was available. Only individuals with available DNA were included in the linkage sample. Inclusion of a pedigree into the phenotypic sample required at least two first, second, or third degree relatives with non-affective psychosis (NAP), one whom had schizophrenia (S) or poor-outcome schizo-affective disorder (PO-SAD). Entry into the linkage sample required DNA samples on at least two individuals with NAP, of whom at least one had S or PO-SAD. Affection was defined by narrow, intermediate, and broad criteria. The phenotypic sample contained 277 pedigrees and 1,770 individuals and the linkage sample 265 pedigrees and 1,408 individuals. Using the intermediate definition of affection, the phenotypic sample contained 837 affected individuals and 526 affected sibling pairs. Parallel figures for the linkage sample were 700 and 420. Individuals with schizophrenia from these multiplex pedigrees resembled epidemiologically sampled cases with respect to age at onset, gender distribution, and most clinical symptoms, although they were more thought-disordered and had a poorer outcome. Power analyses based on the model of linkage heterogeneity indicated that the ISHDSF should be able to detect a major locus that influences susceptibility to schizophrenia in as few as 20% of families. Compared to first-degree relatives of epidemiologically sampled schizophrenic probands, first-degree relatives of schizophrenic members from the ISHDSF had a similar risk for schizotypal personality disorder, affective illness, alcoholism, and anxiety disorder. With sufficient resources, large-scale ascertainment of multiplex schizophrenia pedigrees is feasible, especially in countries with catchmented psychiatric care and stable populations. Although somewhat more severely ill, schizophrenic members of such pedigrees appear to clinically resemble typical schizophrenic patients. Our ascertainment process for multiplex schizophrenia families did not select for excess familial risk for affective illness or alcoholism. With its large sample ascertained in a standardized manner from a relatively homogeneous population, the ISHDSF provides considerable power to detect susceptibility loci for schizophrenia.

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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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An experimental investigation of the argon plasma behavior near the E-H transition in an inductively coupled Gaseous Electronics Conference reference cell is reported. Electron density and temperature, ion density, argon metastable density, and optical emission measurements have been made as function of input power and gas pressure. When plotted versus plasma power, applied power corrected for coil and hardware losses, no hysteresis is observed in the measured plasma parameter dependence at the E-H mode transition. This suggests that hysteresis in the E-H mode transition is due to ignoring inherent power loss, primarily in the matching system.

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The transport sector is considered to be one of the most dependent sectors on fossil fuels. Meeting ecological, social and economic demands throughout the sector has got increasingly important in recent times. A passenger vehicle with a more environmentally friendly propulsion system is the hybrid electric vehicle. Combining an internal combustion engine and an electric motor offers the potential to reduce carbon dioxide emissions. The overall objective of this research is to provide an appraisal of the use of a micro gas turbine as the range extender in a plug-in hybrid electric vehicle. In this application, the gas turbine can always operate at its most efficient operating point as its only requirement is to recharge the battery. For this reason, it is highly suitable for this purpose. Gas turbines offer many benefits over traditional internal combustion engines which are traditionally used in this application. They offer a high power-to-weight ratio, multi-fuel capability and relatively low emission levels due to continuous combustion.

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Context. The ESA Rosetta spacecraft, currently orbiting around comet 67P/Churyumov-Gerasimenko, has already provided in situ measurements of the dust grain properties from several instruments,particularly OSIRIS and GIADA. We propose adding value to those measurements by combining them with ground-based observations of the dust tail to monitor the overall, time-dependent dust-production rate and size distribution.
Aims. To constrain the dust grain properties, we take Rosetta OSIRIS and GIADA results into account, and combine OSIRIS data during the approach phase (from late April to early June 2014) with a large data set of ground-based images that were acquired with the ESO Very Large Telescope (VLT) from February to November 2014.
Methods. A Monte Carlo dust tail code, which has already been used to characterise the dust environments of several comets and active asteroids, has been applied to retrieve the dust parameters. Key properties of the grains (density, velocity, and size distribution) were obtained from Rosetta observations: these parameters were used as input of the code to considerably reduce the number of free parameters. In this way, the overall dust mass-loss rate and its dependence on the heliocentric distance could be obtained accurately.
Results. The dust parameters derived from the inner coma measurements by OSIRIS and GIADA and from distant imaging using VLT data are consistent, except for the power index of the size-distribution function, which is α = −3, instead of α = −2, for grains smaller than 1 mm. This is possibly linked to the presence of fluffy aggregates in the coma. The onset of cometary activity occurs at approximately 4.3 AU, with a dust production rate of 0.5 kg/s, increasing up to 15 kg/s at 2.9 AU. This implies a dust-to-gas mass ratio varying between 3.8 and 6.5 for the best-fit model when combined with water-production rates from the MIRO experiment.

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We investigate entanglement properties of a recently introduced class of macroscopic quantum superpositions in two-mode mixed states. One of the tools we use in order to infer the entanglement in this non-Gaussian class of states is the power to entangle a qubit system. Our study reveals features which are hidden in a standard approach to entanglement investigation based on the uncertainty principle of the quadrature variables. We briefly describe the experimental setup corresponding to our theoretical scenario and a suitable modification of the protocol which makes our proposal realizable within the current experimental capabilities.

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Reproducible modulations in low-pressure, inductively coupled discharges operating in chlorine and argon-chlorine mixtures have been observed and studied. Changes in the light output, floating potential, negative ion fraction, and charged particle densities were observed. Here we report two types of unstable operational modes in an inductively coupled discharge. On the one hand, when the discharge was matched, to minimize reflected power, instabilities were observed in argon-chlorine plasmas over limited operating conditions of input power and gas pressure. The instability window decreased with increasing chlorine content and was observed for chlorine concentrations between 30% and 60% only. However, when operating at pressures below 5 mTorr and the discharge circuit detuned to increase the reflected power, modulations were observed in a pure chlorine discharge. These modulations varied in nature from a series of sharp bursts to a very periodic behavior and can be controlled, by variation of the matching conditions, to produce an apparent pulsed plasma environment. (C) 2005 American Institute of Physics.

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This paper reports the findings from a discrete-choice experiment designed to estimate the economic benefits associated with rural landscape improvements in Ireland. Using a mixed logit model, the panel nature of the dataset is exploited to retrieve willingness-to-pay values for every individual in the sample. This departs from customary approaches in which the willingness-to-pay estimates are normally expressed as measures of central tendency of an a priori distribution. Random-effects models for panel data are subsequently used to identify the determinants of the individual-specific willingness-to-pay estimates. In comparison with the standard methods used to incorporate individual-specific variables into the analysis of discrete-choice experiments, the analytical approach outlined in this paper is shown to add considerable explanatory power to the welfare estimates.

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Background: Several lines of evidence suggest that the clinical heterogeneity of schizophrenia is due to genetic heterogeneity. Genetic heterogeneity may decrease the signal-to-noise ratio in linkage and association studies. Therefore, linkage studies of clinically homogeneous classes of psychotic illness may result in greater power to detect at least some loci.

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Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised. (C) 2011 Elsevier Ltd. All rights reserved.

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A gas chromatographic/mass spectrometric method is described for the detection of clenbuterol residues in liver, muscle, urine and retina. Tissue samples are first digested using protease and any clenbuterol present is extracted using a simple liquid/liquid extraction procedure. The dried extracts are then derivatized using methylboronic acid and the derivatives are subjected to gas chromatography/mass spectrometry on a magnetic sector instrument. The detection limit of the assay is 0.05 ng g-1 clenbuterol in liver, muscle or urine using a 10 g sample size, and 4 ng g-1 in retina using a 0.5 g sample size. The assay is made very specific by using selected ion monitoring of three ions at a resolution of 3500 and by ion ratio measurements. The precision and reproducibility of the assay are enhanced by the use of a deuterated internal standard, with a typical coefficient of variation of 3%.