32 resultados para energy demand

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


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Thermal stability is of major importance in polymer extrusion, where product quality is dependent upon the level of melt homogeneity achieved by the extruder screw. Extrusion is an energy intensive process and optimisation of process energy usage while maintaining melt stability is necessary in order to produce good quality product at low unit cost. Optimisation of process energy usage is timely as world energy prices have increased rapidly over the last few years. In the first part of this study, a general discussion was made on the efficiency of an extruder. Then, an attempt was made to explore correlations between melt thermal stability and energy demand in polymer extrusion under different process settings and screw geometries. A commodity grade of polystyrene was extruded using a highly instrumented single screw extruder, equipped with energy consumption and melt temperature field measurement. Moreover, the melt viscosity of the experimental material was observed by using an off-line rheometer. Results showed that specific energy demand of the extruder (i.e. energy for processing of unit mass of polymer) decreased with increasing throughput whilst fluctuation in energy demand also reduced. However, the relationship between melt temperature and extruder throughput was found to be complex, with temperature varying with radial position across the melt flow. Moreover, the melt thermal stability deteriorated as throughput was increased, meaning that a greater efficiency was achieved at the detriment of melt consistency. Extruder screw design also had a significant effect on the relationship between energy consumption and melt consistency. Overall, the relationship between the process energy demand and thermal stability seemed to be negatively correlated and also it was shown to be highly complex in nature. Moreover, the level of process understanding achieved here can help to inform selection of equipment and setting of operating conditions to optimise both energy and thermal efficiencies in parallel. 

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Extrusion is one of the fundamental production methods in the polymer processing industry and is used in the production of a large number of commodities in a diverse industrial sector. Being an energy intensive production method, process energy efficiency is one of the major concerns and the selection of the most energy efficient processing conditions is a key to reducing operating costs. Usually, extruders consume energy through the drive motor, barrel heaters, cooling fans, cooling water pumps, gear pumps, etc. Typically the drive motor is the largest energy consuming device in an extruder while barrel/die heaters are responsible for the second largest energy demand. This study is focused on investigating the total energy demand of an extrusion plant under various processing conditions while identifying ways to optimise the energy efficiency. Initially, a review was carried out on the monitoring and modelling of the energy consumption in polymer extrusion. Also, the power factor, energy demand and losses of a typical extrusion plant were discussed in detail. The mass throughput, total energy consumption and power factor of an extruder were experimentally observed over different processing conditions and the total extruder energy demand was modelled empirically and also using a commercially available extrusion simulation software. The experimental results show that extruder energy demand is heavily coupled between the machine, material and process parameters. The total power predicted by the simulation software exhibits a lagging offset compared with the experimental measurements. Empirical models are in good agreement with the experimental measurements and hence these can be used in studying process energy behaviour in detail and to identify ways to optimise the process energy efficiency.

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EU Directive 2009/28/EC on Renewable Energy requires each Member State to ensure 10% of transport energy (excluding aviation and marine transport) comes from renewable sources by 2020 (10% RES-T target). In addition to the anticipated growth in biofuels, this target is expected to be met by the increased electrification of transport coupled with a growing contribution from renewable energy to electricity generation. Energy use in transport accounted for nearly half of Ireland’s total final energy demand and about a third of energy-related carbon dioxide emissions in 2007. Energy use in transport has grown by 6.3% per annum on average in the period 1990 – 2007. This high share and fast growth relative to other countries highlights the challenges Ireland faces in meeting ambitious renewable energy targets. The Irish Government has set a specific target for Electric Vehicles (EV) as part of its strategy to deliver the 10% RES-T target. By 2020, 10% of all vehicles in its transport fleet are to be powered by electricity. This paper quantifies the impacts on energy and carbon dioxide emissions of this 10% EV target by 2020. In order to do this an ‘EV Car Stock’ model was developed to analyse the historical and future make-up of the passenger car portion of the fleet to 2025. Three scenarios for possible take-up in EVs were examined and the associated energy and emissions impacts are quantified. These impacts are then compared to Ireland’s 10% RES-T target and greenhouse gas (GHG) emissions reduction targets for 2020. Two key findings of the study are that the 10% EV target contributes 1.7% to the 10% RES-T target by 2020 and 1.4% to the 20% reduction in Non-ETS emissions by 2020 relative to 2005.

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In an age of depleting oil reserves and increasing energy demand, humanity faces a stalemate between environmentalism and politics, where crude oil is traded at record highs yet the spotlight on being ‘green’ and sustainable is stronger than ever. A key theme on today’s political agenda is energy independence from foreign nations, and the United Kingdom is bracing itself for nuclear renaissance which is hoped will feed the rapacious centralised system that the UK is structured upon. But what if this centralised system was dissembled, and in its place stood dozens of cities which grow and monopolise from their own energy? Rather than one dominant network, would a series of autonomous city-based energy systems not offer a mutually profitable alternative? Bio-Port is a utopian vision of a ‘Free Energy City’ set in Liverpool, where the old dockyards, redundant space, and the Mersey Estuary have been transformed into bio-productive algae farms. Bio-Port Free Energy City is a utopian ideal, where energy is superfluous; in fact so abundant that meters are obsolete. The city functions as an energy generator and thrives from its own product with minimal impact upon the planet it inhabits. Algaculture is the fundamental energy source, where a matrix of algae reactors swamp the abandoned dockyards; which themselves have been further expanded and reclaimed from the River Mersey. Each year, the algae farm is capable of producing over 200 million gallons of bio-fuel, which in-turn can produce enough electricity to power almost 2 million homes. The metabolism of Free-Energy City is circular and holistic, where the waste products of one process are simply the inputs of a new one. Livestock farming – once traditionally a high-carbon countryside exercise has become urbanised. Cattle are located alongside the algae matrix, and waste gases emitted by farmyards and livestock are largely sequestered by algal blooms or anaerobically converted to natural gas. Bio-Port Free Energy City mitigates the imbalances between ecology and urbanity, and exemplifies an environment where nature and the human machine can function productively and in harmony with one another. According to James Lovelock, our population has grown in number to the point where our presence is perceptibly disabling the planet, but in order to reverse the effects of our humanist flaws, it is vital that new eco-urban utopias are realised.

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Seasonal and day-to-day variations in travel behaviour and performance of private passenger vehicles can be partially explained by changes in weather conditions. Likewise, in the electricity sector, weather affects energy demand. The impact of weather conditions on private passenger vehicle performance, usership statistics and travel behaviour has been studied for conventional, internal combustion engine, vehicles. Similarly, weather-driven variability in electricity demand and generation has been investigated widely. The aim of these analyses in both sectors is to improve energy efficiency, reduce consumption in peak hours and reduce greenhouse gas emissions. However, the potential effects of seasonal weather variations on electric vehicle usage have not yet been investigated. In Ireland the government has set a target requiring 10% of all vehicles in the transport fleet to be powered by electricity by 2020 to meet part of its European Union obligations to reduce greenhouse gas emissions and increase energy efficiency. This paper fills this knowledge gap by compiling some of the published information available for internal combustion engine vehicles and applying the lessons learned and results to electric vehicles with an analysis of historical weather data in Ireland and electricity market data in a number of what-if scenarios. Areas particularly impacted by weather conditions are battery performance, energy consumption and choice of transportation mode by private individuals.

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Dissolved Air Flotation (DAF) is a well-known coagulation-flotation system applied at large scale for microalgae harvesting. Compared to conventional harvesting technologies DAF allows high cell recovery at lower energy demand. By replacing microbubbles with microspheres, the innovative Ballasted Dissolved Air Flotation (BDAF) technique has been reported to achieve the same algae cell removal efficiency, while saving up to 80% of the energy required for the conventional DAF unit. Using three different algae cultures (Scenedesmus obliquus, Chlorella vulgaris and Arthrospira maxima), the present work investigated the practical, economic and environmental advantages of the BDAF system compared to the DAF system. 99% cells separation was achieved with both systems, nevertheless, the BDAF technology allowed up to 95% coagulant reduction depending on the algae species and the pH conditions adopted. In terms of floc structure and strength, the inclusion of microspheres in the algae floc generated a looser aggregate, showing a more compact structure within single cell alga, than large and filamentous cells. Overall, BDAF appeared to be a more reliable and sustainable harvesting system than DAF, as it allowed equal cells recovery reducing energy inputs, coagulant demand and carbon emissions. © 2014 Elsevier Ltd.

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The solubility of carbon dioxide in five tetraalkylphosphonium superbase ionic liquids, namely the trihexyltetradecylphoshonium phenoxide, trihexyltetradecylphoshonium benzotriazolide, trihexyltetradecylphoshonium benzimidazolide, trihexyltetradecylphoshonium 1,2,3-triazolide, and trihexyltetradecylphoshonium 1,2,4-triazolide was studied experimentally under dry and wet conditions at 22 A degrees C and at atmospheric pressure, using a gravimetric saturation technique. The effects of anion structure and of the presence or absence of water in the solution on the carbon dioxide solubility were then deduced from the data. H-1 and C-13-NMR spectroscopy and ab initio calculations were also conducted to probe the interactions in these solutions, as carbon dioxide and water can compete in the ionic liquid structure during the absorption process. Additionally, the viscosity of selected superbase ionic liquids was measured under dry and wet conditions, in the presence or absence of CO2, to evaluate their practical application in carbon dioxide capture processes. Finally, the recyclability of the trihexyltetradecylphoshonium 1,2,4-triazolide under dry and wet conditions was determined to probe the ability of selected solvents to solubilize chemically a high concentration of carbon dioxide and then release it in a low energy demand process.

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This paper presents a new methodology for characterising the energy performance of buildings suitable for city-scale, top-down energy modelling. Building properties that have the greatest impact on simulated energy performance were identified via a review of sensitivity analysis studies. The methodology greatly simplifies the description of a building to decrease labour and simulation processing overheads. The methodology will be used in the EU FP7 INDICATE project which aims to create a master-planning tool that uses dynamic simulation to facilitate the design of sustainable, energy efficient smart cities.

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The penetration of the electric vehicle (EV) has increased rapidly in recent years mainly as a consequence of advances in transport technology and power electronics and in response to global pressure to reduce carbon emissions and limit fossil fuel consumption. It is widely acknowledged that inappropriate provision and dispatch of EV charging can lead to negative impacts on power system infrastructure. This paper considers EV requirements and proposes a module which uses owner participation, through mobile phone apps and on-board diagnostics II (OBD-II), for scheduled vehicle charging. A multi-EV reference and single-EV real-time response (MRS2R) online algorithm is proposed to calculate the maximum and minimum adjustable limits of necessary capacity, which forms part of decision-making support in power system dispatch. The proposed EV dispatch module is evaluated in a case study and the influence of the mobile app, EV dispatch trending and commercial impact is explored.

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Recent cold winters and prolonged periods of low wind speeds have prompted concerns about the increasing penetration of wind generation in the Irish and other northern European power systems. On the combined Republic of Ireland and Northern Ireland system there was in excess of 1.5 GW of installed wind power in January 2010. As the penetration of these variable, non-dispatchable generators increases, power systems are becoming more sensitive to weather events on the supply side as well as on the demand side. In the temperate climate of Ireland, sensitivity of supply to weather is mainly due to wind variability while demand sensitivity is driven by space heating or cooling loads. The interplay of these two weather-driven effects is of particular concern if demand spikes driven by low temperatures coincide with periods of low winds. In December 2009 and January 2010 Ireland experienced a prolonged spell of unusually cold conditions. During much of this time, wind generation output was low due to low wind speeds. The impacts of this event are presented as a case study of the effects of weather extremes on power systems with high penetrations of variable renewable generation.

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Dwindling fossil fuel resources and pressures to reduce greenhouse gas (GHG) emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is that supply instantaneously meets demand and that robust operating standards are maintained to ensure a consistent supply of high quality electricity to end-users. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management (DSM) with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating (EWH) has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper, a continuous Direct Load Control (DLC) EWH algorithm is applied in a liberalized market environment using actual historical electricity system and market data to examine the potential energy savings, cost reductions and electricity system operational improvements.

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In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize or address two major issues. The first is that, when fitting dynamic panel models, the lagged consumption term in the right-hand side of the demand equation is endogenous. This has resulted in potentially inconsistent estimates of the long-run price elasticity of demand. The second is that energy price is likely mismeasured.