932 resultados para Turbine, expanders, organic, Rankine, cycles, ORC, Energy, systems, computational, model


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This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/K006428/1]; and the European Regional Development Fund [grant number LUPS/ERDF/2010/4/1/0164].

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First-principles electronic structure methods are used to find the rates of intravalley and intervalley n-type carrier scattering due to alloy disorder in Si1-xGex alloys. The required alloy scattering matrix elements are calculated from the energy splitting of nearly degenerate Bloch states which arises when one average host atom is replaced by a Ge or Si atom in supercells containing up to 128 atoms. Scattering parameters for all relevant Delta and L intravalley and intervalley alloy scattering are calculated. Atomic relaxation is found to have a substantial effect on the scattering parameters. f-type intervalley scattering between Delta valleys is found to be comparable to other scattering channels. The n-type carrier mobility, calculated from the scattering rate using the Boltzmann transport equation in the relaxation time approximation, is in excellent agreement with experiments on bulk, unstrained alloys.

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Power systems require a reliable supply and good power quality. The impact of power supply interruptions is well acknowledged and well quantified. However, a system may perform reliably without any interruptions but may have poor power quality. Although poor power quality has cost implications for all actors in the electrical power systems, only some users are aware of its impact. Power system operators are much attuned to the impact of low power quality on their equipment and have the appropriate monitoring systems in place. However, over recent years certain industries have come increasingly vulnerable to negative cost implications of poor power quality arising from changes in their load characteristics and load sensitivities, and therefore increasingly implement power quality monitoring and mitigation solutions. This paper reviews several historical studies which investigate the cost implications of poor power quality on industry. These surveys are largely focused on outages, whilst the impact of poor power quality such as harmonics, short interruptions, voltage dips and swells, and transients is less well studied and understood. This paper examines the difficulties in quantifying the costs of poor power quality, and uses the chi-squared method to determine the consequences for industry of power quality phenomenon using a case study of over 40 manufacturing and data centres in Ireland.

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Climate change is expected to have marked impacts on forest ecosystems. In Ontario forests, this includes changes in tree growth, stand composition and disturbance regimes, with expected impacts on many forest-dependent communities, the bioeconomy, and other environmental considerations. In response to climate change, renewable energy systems, such as forest bioenergy, are emerging as critical tools for carbon emissions reductions and climate change mitigation. However, these systems may also need to adapt to changing forest conditions. Therefore, the aim of this research was to estimate changes in forest growth and forest cover in response to anticipated climatic changes in the year 2100 in Ontario forests, to ultimately explore the sustainability of bioenergy in the future. Using the Haliburton Forest and Wildlife Reserve in Ontario as a case study, this research used a spatial climate analog approach to match modeled Haliburton temperature and precipitation (via Fourth Canadian Regional Climate Model) to regions currently exhibiting similar climate (climate analogs). From there, current forest cover and growth rates of core species in Haliburton were compared to forests plots in analog regions from the US Forest Service Forest Inventory and Analysis (FIA). This comparison used two different emission scenarios, corresponding to a high and a mid-range emission future. This research then explored how these changes in forests may influence bioenergy feasibility in the future. It examined possible volume availability and composition of bioenergy feedstock under future conditions. This research points to a potential decline of softwoods in the Haliburton region with a simultaneous expansion of pre-established hardwoods such as northern red oak and red maple, as well as a potential loss in sugar maple cover. From a bioenergy perspective, hardwood residues may be the most feasible feedstock in the future with minimal change in biomass availability for energy production; under these possible conditions, small scale combined heat and power (CHP) and residential pellet use may be the most viable and ecologically sustainable options. Ultimately, understanding the way in which forests may change is important in informing meaningful policy and management, allowing for improved forest bioenergy systems, now and in the future.

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El presente artículo plantea una definición ampliada del concepto de seguridad energética, yendo más allá del concepto clásico establecido por la Agencia Internacional de la Energía, incorporando cuestiones relativas a la eficiencia energética, la aceptabilidad del modelo energético y los retos que impone el cambio climático, pero sin perder de perspectiva las exigencias y las dinámicas competitivas económicas globales. Sobre la base de este concepto ampliado, se examina la evolución de la seguridad energética en el marco de la Unión Europea, con una atención particular a cómo se concibe la seguridad energética en la Estrategia Global de Seguridad de 2016.

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This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.

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Stormwater management has long been a critical societal and environmental challenge for communities. An increasing number of municipalities are turning to novel approaches such as green infrastructure to develop more sustainable stormwater management systems. However, there is a need to better understand the technological decision-making processes that lead to specific outcomes within urban stormwater governance systems. We used the social-ecological system (SES) framework to build a classification system for identifying significant variables that influence urban stormwater governance decisions related to green infrastructure adoption. To adapt the framework, we relied on findings from observations at national stormwater meetings in combination with a systematic literature review on influential factors related to green infrastructure adoption. We discuss our revisions to the framework that helped us understand the decision by municipal governments to adopt green infrastructure. Remaining research needs and challenges are discussed regarding the development of an urban stormwater SES framework as a classification tool for knowledge accumulation and synthesis.

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This paper proposes a novel demand response model using a fuzzy subtractive cluster approach. The model development provides support to domestic consumer decisions on controllable loads management, considering consumers' consumption needs and the appropriate load shape or rescheduling in order to achieve possible economic benefits. The model based on fuzzy subtractive clustering method considers clusters of domestic consumption covering an adequate consumption range. Analysis of different scenarios is presented considering available electric power and electric energy prices. Simulation results are presented and conclusions of the proposed demand response model are discussed. (C) 2016 Elsevier Ltd. All rights reserved.

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O presente relatório de projeto explicita as etapas da elaboração e os resultados obtidos através da realização de um projeto de reabilitação energética de um complexo de piscinas interiores. Esta reabilitação energética tem por objetivo a redução dos custos energéticos através da subtração de consumos supérfluos de energia ou da melhoria da eficiência energética dos equipamentos. Para alcançar estes objetivos recorreu-se à simulação dinâmica do edifício de modo a estimar múltiplas variáveis energéticas e identificar quais os setores e equipamentos que maior influência têm no consumo energético do complexo em estudo. Para a realização da simulação, recorreu-se a um software desenvolvido pelo DOE dos Estados Unidos da América, o Energy Plus, com o auxílio do Design Builder, que permite a criação e edição do modelo de forma mais fácil e acessível. Os valores retirados da simulação foram posteriormente comparados com valores reais. Com o complexo caraterizado e os principais consumidores identificados foi possível iniciar o estudo das medidas de melhoria da eficiência energética. As principais medidas estudadas incidiram na instalação de coberturas isotérmicas nas piscinas para reduzir a perda de energia através da evaporação e da radiação, a introdução de fontes de energia renovável como alternativa energética, substituição de elementos do sistema de iluminação e o aproveitamento de energia dissipada em equipamentos. Com este estudo, a entidade gestora do complexo encontra-se mais informada e pronta a tomar decisões que influenciem de forma significativa o consumo de energia no complexo, podendo optar pela instalação de alguma das medidas propostas.

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Os oceanos representam um dos maiores recursos naturais, possuindo expressivo potencial energético, podendo suprir parte da demanda energética mundial. Nas últimas décadas, alguns dispositivos destinados à conversão da energia das ondas dos oceanos em energia elétrica têm sido estudados. No presente trabalho, o princípio de funcionamento do conversor do tipo Coluna de Água Oscilante, do inglês Oscillating Water Colum, (OWC) foi analisado numericamente. As ondas incidentes na câmara hidro-pneumática da OWC, causam um movimento alternado da coluna de água no interior da câmara, o qual produz um fluxo alternado de ar que passa pela chaminé. O ar passa e aciona uma turbina a qual transmite energia para um gerador elétrico. O objetivo do presente estudo foi investigar a influência de diferentes formas geométricas da câmara sobre o fluxo resultante de ar que passa pela turbina, que influencia no desempenho do dispositivo. Para isso, geometrias diferentes para o conversor foram analisadas empregando modelos computacionais 2D e 3D. Um modelo computacional desenvolvido nos softwares GAMBIT e FLUENT foi utilizado, em que o conversor OWC foi acoplado a um tanque de ondas. O método Volume of Fluid (VOF) e a teoria de 2ª ordem Stokes foram utilizados para gerar ondas regulares, permitindo uma interação mais realista entre o conversor, água, ar e OWC. O Método dos Volumes Finitos (MVF) foi utilizado para a discretização das equações governantes. Neste trabalho o Contructal Design (baseado na Teoria Constructal) foi aplicado pela primeira vez em estudos numéricos tridimensionais de OWC para fim de encontrar uma geometria que mais favorece o desempenho do dispositivo. A função objetivo foi a maximização da vazão mássica de ar que passa através da chaminé do dispositivo OWC, analisado através do método mínimos quadrados, do inglês Root Mean Square (RMS). Os resultados indicaram que a forma geométrica da câmara influencia na transformação da energia das ondas em energia elétrica. As geometrias das câmaras analisadas que apresentaram maior área da face de incidência das ondas (sendo altura constante), apresentaram também maior desempenho do conversor OWC. A melhor geometria, entre os casos desse estudo, ofereceu um ganho no desempenho do dispositivo em torno de 30% maior.

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The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.

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The share of variable renewable energy in electricity generation has seen exponential growth during the recent decades, and due to the heightened pursuit of environmental targets, the trend is to continue with increased pace. The two most important resources, wind and insolation both bear the burden of intermittency, creating a need for regulation and posing a threat to grid stability. One possibility to deal with the imbalance between demand and generation is to store electricity temporarily, which was addressed in this thesis by implementing a dynamic model of adiabatic compressed air energy storage (CAES) with Apros dynamic simulation software. Based on literature review, the existing models due to their simplifications were found insufficient for studying transient situations, and despite of its importance, the investigation of part load operation has not yet been possible with satisfactory precision. As a key result of the thesis, the cycle efficiency at design point was simulated to be 58.7%, which correlated well with literature information, and was validated through analytical calculations. The performance at part load was validated against models shown in literature, showing good correlation. By introducing wind resource and electricity demand data to the model, grid operation of CAES was studied. In order to enable the dynamic operation, start-up and shutdown sequences were approximated in dynamic environment, as far as is known, the first time, and a user component for compressor variable guide vanes (VGV) was implemented. Even in the current state, the modularly designed model offers a framework for numerous studies. The validity of the model is limited by the accuracy of VGV correlations at part load, and in addition the implementation of heat losses to the thermal energy storage is necessary to enable longer simulations. More extended use of forecasts is one of the important targets of development, if the system operation is to be optimised in future.

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The ongoing depletion of fossil fuels and the severe consequences of the greenhouse effect make the development of alternative energy systems crucially important. While hydrogen is, in principle, a promising alternative, releasing nothing but energy and pure water. Hydrogen storage is complicated and no completely viable technique has been proposed so far. This work is concerned with the study of one potential alternative to pure hydrogen: ammonia, and more specifically its storage in solids. Ammonia, NH3, can be regarded as a chemical hydrogen carrier with the advantages of strongly reduced flammability and explosiveness as compared to hydrogen. Furthermore, ammine metal salts presented here as promising ammonia stores easily store up to 50 wt.-% ammonia, giving them a volumetric energy density comparable to natural gas. The model system NiX2–NH3 ( X = Cl, Br, I) is studied thoroughly with respect to ammine salt formation, thermal decomposition, air stability and structural effects. The system CuX2–NH3 ( X = Cl, Br) has an adverse thermal decomposition behaviour, making it impractical for use as an ammonia store. This system is, however, most interesting from a structural point of view and some work concerning the study of the structural behaviour of this system is presented. Finally, close chemical relatives to the metal ammine halides, the metal ammine nitrates are studied. They exhibit interesting anion arrangements, which is an impressive showcase for the combination of diffraction and spectroscopic information. The characterisation techniques in this thesis range from powder diffraction over single crystal diffraction, spectroscopy, computational modelling, thermal analyses to gravimetric uptake experiments. Further highlights are the structure solutions and refinements from powder data of (NH4)2[NiCl4(H2O)(NH3)] and Ni(NH3)2(NO3)2, the combination of crystallographic and chemical information for the elucidation of the (NH4)2[NiCl4(H2O)(NH3)] formation reaction and the growth of single crystals under ammonia flow, a technique allowing the first documented successful growth and single crystal diffraction measurement for [Cu(NH3)6]Cl2.

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Common building energy modeling approaches do not account for the influence of surrounding neighborhood on the energy consumption patterns. This thesis develops a framework to quantify the neighborhood impact on a building energy consumption based on the local wind flow. The airflow in the neighborhood is predicted using Computational Fluid Dynamics (CFD) in eight principal wind directions. The developed framework in this study benefits from wind multipliers to adjust the wind velocity encountering the target building. The input weather data transfers the adjusted wind velocities to the building energy model. In a case study, the CFD method is validated by comparing with on-site temperature measurements, and the building energy model is calibrated using utilities data. A comparison between using the adjusted and original weather data shows that the building energy consumption and air system heat gain decreased by 5% and 37%, respectively, while the cooling gain increased by 4% annually.