873 resultados para Energy Efficient Algorithms
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This chapter aims at contributing to the trade and energy debate by focusing on the specific issue of export restrictions. It starts from the premise that a balanced and efficient regulation of export barriers in the energy sector would contribute to tackle emerging energy concerns such as energy security and the elimination of fossil fuel subsidies in light of the challenge of climate change mitigation. It assesses the adequacy of existing WTO rules on export restrictions and accordingly identifies the main gaps and inconsistencies inherent in the current disciplines from an energy-specific perspective. Finally, it discusses the merits of an energy-specific approach to advance existing disciplines in the most deficient area of export duties based on the systematisation of the Russian ‘model’. Such approach could raise the overall level of commitments in the energy sector while still allowing for the systemic applicability of GATT environmental exceptions in a manner consistent with the principle of sustainable development recognised in the Preamble of the WTO Agreement.
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Background Energy Policy is one of the main drivers of Transport Policy. A number of strategies to reduce current energy consumption trends in the transport sector have been designed over the last decades. They include fuel taxes, more efficient technologies and changing travel behavior through demand regulation. But energy market has a high degree of uncertainty and the effectiveness of those policy options should be assessed. Methods A scenario based assessment methodology has been developed in the frame of the EU project STEPS. It provides an integrated view of Energy efficiency, environment, social and competitiveness impacts of the different strategies. It has been applied at European level and to five specific Regions. Concluding remarks The results are quite site specific dependent. However they show that regulation measures appear to be more effective than new technology investments. Higher energy prices could produce on their turn a deterioration of competitiveness and a threat for social goals.
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Predictions about electric energy needs, based on current electric energy models, forecast that the global energy consumption on Earth for 2050 will double present rates. Using distributed procedures for control and integration, the expected needs can be halved. Therefore implementation of Smart Grids is necessary. Interaction between final consumers and utilities is a key factor of future Smart Grids. This interaction is aimed to reach efficient and responsible energy consumption. Energy Residential Gateways (ERG) are new in-building devices that will govern the communication between user and utility and will control electric loads. Utilities will offer new services empowering residential customers to lower their electric bill. Some of these services are Smart Metering, Demand Response and Dynamic Pricing. This paper presents a practical development of an ERG for residential buildings.
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During recent years, wind energy has moved from an emerging technology to a nearly competitive technology. This fact, coupled with an increasing global focus on environmental concern and a political desire of a certain level of diversification in the energy supply, ensures wind energy an important role in the future electricity market. For this challenge to be met in a cost-efficient way, a substantial part of new wind turbine installations is foreseen to be erected in big onshore or offshore wind farms. This fact makes the production, loading and reliability of turbines operating under such conditions of particular interest.
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The intermediate band solar cell [1] has been proposed as a concept able to substantially enhance the efficiency limit of an ordinary single junction solar cell. If a band permitted for electrons is inserted within the forbidden band of a semiconductor then a novel path for photo generation is open: electron hole pairs may be formed by the successive absorption of two sub band gap photons using the intermediate band (IB) as a stepping stone. While the increase of the photovoltaic (PV) current is not a big achievement —it suffices to reduce the band gap— the achievement of this extra current at high voltage is the key of the IB concept. In ordinary cells the voltage is limited by the band gap so that reducing it would also reduce the band gap. In the intermediate band solar cell the high voltage is produced when the IB is permitted to have a Quasi Fermi Level (QFL) different from those of the Conduction Band (CB) and the Valence Band (VB). For it the cell must be properly isolated from the external contacts, which is achieved by putting the IB material between two n- and p-type ordinary semiconductors [2]. Efficiency thermodynamic limit of 63% is obtained for the IB solar cell1 vs. the 40% obtained [3] for ordinary single junction solar cells. Detailed information about the IB solar cells can be found elsewhere [4].
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We have developed a new projector model specifically tailored for fast list-mode tomographic reconstructions in Positron emission tomography (PET) scanners with parallel planar detectors. The model provides an accurate estimation of the probability distribution of coincidence events defined by pairs of scintillating crystals. This distribution is parameterized with 2D elliptical Gaussian functions defined in planes perpendicular to the main axis of the tube of response (TOR). The parameters of these Gaussian functions have been obtained by fitting Monte Carlo simulations that include positron range, acolinearity of gamma rays, as well as detector attenuation and scatter effects. The proposed model has been applied efficiently to list-mode reconstruction algorithms. Evaluation with Monte Carlo simulations over a rotating high resolution PET scanner indicates that this model allows to obtain better recovery to noise ratio in OSEM (ordered-subsets, expectation-maximization) reconstruction, if compared to list-mode reconstruction with symmetric circular Gaussian TOR model, and histogram-based OSEM with precalculated system matrix using Monte Carlo simulated models and symmetries.
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A novel time integration scheme is presented for the numerical solution of the dynamics of discrete systems consisting of point masses and thermo-visco-elastic springs. Even considering fully coupled constitutive laws for the elements, the obtained solutions strictly preserve the two laws of thermo dynamics and the symmetries of the continuum evolution equations. Moreover, the unconditional control over the energy and the entropy growth have the effect of stabilizing the numerical solution, allowing the use of larger time steps than those suitable for comparable implicit algorithms. Proofs for these claims are provided in the article as well as numerical examples that illustrate the performance of the method.
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The improvement of energy efficiency in existing buildings is always a challenge due to their particular, and sometimes protected, constructive solutions. New constructive regulations in Spain leave a big undefined gap when a restoration is considered because they were developed for new buildings. However, rehabilitation is considered as an opportunity for many properties because it allows owners to obtain benefits from the use of the buildings. The current financial and housing crisis has turned society point of view to existing buildings and making them more efficient is one of the Spanish government’s aims. The economic viability of a rehabilitation action should take all factors into account: both construction costs and the future operative costs of the building must be considered. Nevertheless, the application of these regulations in Spain is left to the designer’s opinion and always under a subjective point of view. With the research work described in this paper and with the help of some case-studies, the cost of adapting an existing building to the new constructive regulations will be studied and Energetic Efficiency will be evaluated depending on how the investment is recovered. The interest of the research is based on showing how new constructive solutions can achieve higher levels of efficiency in terms of energy, construction and economy and it will demonstrate that Life Cycle Costing analysis can be a mechanism to find the advantages and disadvantages of using these new constructive solutions. Therefore, this paper has the following objectives: analysing constructive solutions in existing buildings - to establish a process for assessing total life cycle costs (LCC) during the planning stages with consideration of future operating costs - to select the most advantageous operating system – To determine the return on investment in terms of construction costs based on new techniques, the achieved energy savings and investment payback periods.
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Multijunction solar cells present a certain reflectivity on its surface that lowers its light absorption. This reflectivity produces a loss in electrical efficiency and thus a loss in global energy production for CPV systems. We present here an optical design for recovering this portion of reflected light, and thus leading to a system efficiency increase. This new design is based on an external confinement cavity, an optical element able to redirect the light reflected by the cell towards its surface again. We have proven the excellent performance of these cavities integrated in CPV modules offering outstanding results: 33.2% module electrical efficiency @Tcell = 25 °C and relative efficiency and Isc gains of over 6%
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Energy management has always been recognized as a challenge in mobile systems, especially in modern OS-based mobile systems where multi-functioning are widely supported. Nowadays, it is common for a mobile system user to run multiple applications simultaneously while having a target battery lifetime in mind for a specific application. Traditional OS-level power management (PM) policies make their best effort to save energy under performance constraint, but fail to guarantee a target lifetime, leaving the painful trading off between the total performance of applications and the target lifetime to the user itself. This thesis provides a new way to deal with the problem. It is advocated that a strong energy-aware PM scheme should first guarantee a user-specified battery lifetime to a target application by restricting the average power of those less important applications, and in addition to that, maximize the total performance of applications without harming the lifetime guarantee. As a support, energy, instead of CPU or transmission bandwidth, should be globally managed as the first-class resource by the OS. As the first-stage work of a complete PM scheme, this thesis presents the energy-based fair queuing scheduling, a novel class of energy-aware scheduling algorithms which, in combination with a mechanism of battery discharge rate restricting, systematically manage energy as the first-class resource with the objective of guaranteeing a user-specified battery lifetime for a target application in OS-based mobile systems. Energy-based fair queuing is a cross-application of the traditional fair queuing in the energy management domain. It assigns a power share to each task, and manages energy by proportionally serving energy to tasks according to their assigned power shares. The proportional energy use establishes proportional share of the system power among tasks, which guarantees a minimum power for each task and thus, avoids energy starvation on any task. Energy-based fair queuing treats all tasks equally as one type and supports periodical time-sensitive tasks by allocating each of them a share of system power that is adequate to meet the highest energy demand in all periods. However, an overly conservative power share is usually required to guarantee the meeting of all time constraints. To provide more effective and flexible support for various types of time-sensitive tasks in general purpose operating systems, an extra real-time friendly mechanism is introduced to combine priority-based scheduling into the energy-based fair queuing. Since a method is available to control the maximum time one time-sensitive task can run with priority, the power control and time-constraint meeting can be flexibly traded off. A SystemC-based test-bench is designed to assess the algorithms. Simulation results show the success of the energy-based fair queuing in achieving proportional energy use, time-constraint meeting, and a proper trading off between them. La gestión de energía en los sistema móviles está considerada hoy en día como un reto fundamental, notándose, especialmente, en aquellos terminales que utilizando un sistema operativo implementan múltiples funciones. Es común en los sistemas móviles actuales ejecutar simultaneamente diferentes aplicaciones y tener, para una de ellas, un objetivo de tiempo de uso de la batería. Tradicionalmente, las políticas de gestión de consumo de potencia de los sistemas operativos hacen lo que está en sus manos para ahorrar energía y satisfacer sus requisitos de prestaciones, pero no son capaces de proporcionar un objetivo de tiempo de utilización del sistema, dejando al usuario la difícil tarea de buscar un compromiso entre prestaciones y tiempo de utilización del sistema. Esta tesis, como contribución, proporciona una nueva manera de afrontar el problema. En ella se establece que un esquema de gestión de consumo de energía debería, en primer lugar, garantizar, para una aplicación dada, un tiempo mínimo de utilización de la batería que estuviera especificado por el usuario, restringiendo la potencia media consumida por las aplicaciones que se puedan considerar menos importantes y, en segundo lugar, maximizar las prestaciones globales sin comprometer la garantía de utilización de la batería. Como soporte de lo anterior, la energía, en lugar del tiempo de CPU o el ancho de banda, debería gestionarse globalmente por el sistema operativo como recurso de primera clase. Como primera fase en el desarrollo completo de un esquema de gestión de consumo, esta tesis presenta un algoritmo de planificación de encolado equitativo (fair queueing) basado en el consumo de energía, es decir, una nueva clase de algoritmos de planificación que, en combinación con mecanismos que restrinjan la tasa de descarga de una batería, gestionen de forma sistemática la energía como recurso de primera clase, con el objetivo de garantizar, para una aplicación dada, un tiempo de uso de la batería, definido por el usuario, en sistemas móviles empotrados. El encolado equitativo de energía es una extensión al dominio de la energía del encolado equitativo tradicional. Esta clase de algoritmos asigna una reserva de potencia a cada tarea y gestiona la energía sirviéndola de manera proporcional a su reserva. Este uso proporcional de la energía garantiza que cada tarea reciba una porción de potencia y evita que haya tareas que se vean privadas de recibir energía por otras con un comportamiento más ambicioso. Esta clase de algoritmos trata a todas las tareas por igual y puede planificar tareas periódicas en tiempo real asignando a cada una de ellas una reserva de potencia que es adecuada para proporcionar la mayor de las cantidades de energía demandadas por período. Sin embargo, es posible demostrar que sólo se consigue cumplir con los requisitos impuestos por todos los plazos temporales con reservas de potencia extremadamente conservadoras. En esta tesis, para proporcionar un soporte más flexible y eficiente para diferentes tipos de tareas de tiempo real junto con el resto de tareas, se combina un mecanismo de planificación basado en prioridades con el encolado equitativo basado en energía. En esta clase de algoritmos, gracias al método introducido, que controla el tiempo que se ejecuta con prioridad una tarea de tiempo real, se puede establecer un compromiso entre el cumplimiento de los requisitos de tiempo real y el consumo de potencia. Para evaluar los algoritmos, se ha diseñado en SystemC un banco de pruebas. Los resultados muestran que el algoritmo de encolado equitativo basado en el consumo de energía consigue el balance entre el uso proporcional a la energía reservada y el cumplimiento de los requisitos de tiempo real.
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Abstract interpretation has been widely used for the analysis of object-oriented languages and, in particular, Java source and bytecode. However, while most existing work deals with the problem of flnding expressive abstract domains that track accurately the characteristics of a particular concrete property, the underlying flxpoint algorithms have received comparatively less attention. In fact, many existing (abstract interpretation based—) flxpoint algorithms rely on relatively inefHcient techniques for solving inter-procedural caligraphs or are speciflc and tied to particular analyses. We also argüe that the design of an efficient fixpoint algorithm is pivotal to supporting the analysis of large programs. In this paper we introduce a novel algorithm for analysis of Java bytecode which includes a number of optimizations in order to reduce the number of iterations. The algorithm is parametric -in the sense that it is independent of the abstract domain used and it can be applied to different domains as "plug-ins"-, multivariant, and flow-sensitive. Also, is based on a program transformation, prior to the analysis, that results in a highly uniform representation of all the features in the language and therefore simplifies analysis. Detailed descriptions of decompilation solutions are given and discussed with an example. We also provide some performance data from a preliminary implementation of the analysis.
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Abstract interpretation has been widely used for the analysis of object-oriented languages and, more precisely, Java source and bytecode. However, while most of the existing work deals with the problem of finding expressive abstract domains that track accurately the characteristics of a particular concrete property, the underlying fixpoint algorithms have received comparatively less attention. In fact, many existing (abstract interpretation based) fixpoint algorithms rely on relatively inefficient techniques to solve inter-procedural call graphs or are specific and tied to particular analyses. We argue that the design of an efficient fixpoint algorithm is pivotal to support the analysis of large programs. In this paper we introduce a novel algorithm for analysis of Java bytecode which includes a number of optimizations in order to reduce the number of iterations. Also, the algorithm is parametric in the sense that it is independent of the abstract domain used and it can be applied to different domains as "plug-ins". It is also incremental in the sense that, if desired, analysis data can be saved so that only a reduced amount of reanalysis is needed after a small program change, which can be instrumental for large programs. The algorithm is also multivariant and flowsensitive. Finally, another interesting characteristic of the algorithm is that it is based on a program transformation, prior to the analysis, that results in a highly uniform representation of all the features in the language and therefore simplifies analysis. Detailed descriptions of decompilation solutions are provided and discussed with an example.
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This paper explores the water-energy nexus of Spain and offers calculations for both the energy used in the water sector and the water required to run the energy sector. The article takes a prospective approach, offering evaluations of policy objectives for biofuels and expected renewable energy sources. Approximately 5.8% of total electricity demand in Spain is due to the water sector. Irrigated agriculture is one of the Spanish water sectors that show the largest growth in energy requirements. Searches for more efficient modes of farm water use, urban waste water treatment, and the use of desalinated water must henceforth include the energy component. Furthermore, biofuel production, to the levels targeted for 2020, would have an unbearable impact on the already stressed water resources in Spain. However, growing usage of renewable energy sources is not threatened by water scarcity, but legislative measures in water allocation and water markets will be required to meet the requirements of using these sources. Some of these measures, which are pushed by regional governments, are discussed in concluding sections.
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In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.
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Renewable energy hybrid systems and mini-grids for electrification of rural areas are known to be reliable and more cost efficient than grid extension or only-diesel based systems. However, there is still some uncertainty in some areas, for example, which is the most efficient way of coupling hybrid systems: AC, DC or AC-DC? With the use of Matlab/Simulink a mini-grid that connects a school, a small hospital and an ecotourism hostel has been modelled. This same mini grid has been coupled in the different possible ways and the system’s efficiency has been studied. In addition, while keeping the consumption constant, the generation sources and the consumption profile have been modified and the effect on the efficiency under each configuration has also been analysed. Finally different weather profiles have been introduced and, again, the effect on the efficiency of each system has been observed.