21 resultados para Energy scenario

em Universidad Politécnica de Madrid


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The advantages of fast-spectrum reactors consist not only of an efficient use of fuel through the breeding of fissile material and the use of natural or depleted uranium, but also of the potential reduction of the amount of actinides such as americium and neptunium contained in the irradiated fuel. The first aspect means a guaranteed future nuclear fuel supply. The second fact is key for high-level radioactive waste management, because these elements are the main responsible for the radioactivity of the irradiated fuel in the long term. The present study aims to analyze the hypothetical deployment of a Gen-IV Sodium Fast Reactor (SFR) fleet in Spain. A nuclear fleet of fast reactors would enable a fuel cycle strategy different than the open cycle, currently adopted by most of the countries with nuclear power. A transition from the current Gen-II to Gen-IV fleet is envisaged through an intermediate deployment of Gen-III reactors. Fuel reprocessing from the Gen-II and Gen-III Light Water Reactors (LWR) has been considered. In the so-called advanced fuel cycle, the reprocessed fuel used to produce energy will breed new fissile fuel and transmute minor actinides at the same time. A reference case scenario has been postulated and further sensitivity studies have been performed to analyze the impact of the different parameters on the required reactor fleet. The potential capability of Spain to supply the required fleet for the reference scenario using national resources has been verified. Finally, some consequences on irradiated final fuel inventory are assessed. Calculations are performed with the Monte Carlo transport-coupled depletion code SERPENT together with post-processing tools.

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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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The change towards a sustainable economic system represents a big challenge for the present as well as next generations. Such a process requires important long-term changes in technologies, lifestyle, infrastructures and institutions. In this scenario the innovation process is a crucial element for fostering sustainability as well as an egalitarian development in developing countries. For those reasons the concept of Eco-Innovation System is introduced and further considerations are provided for the case of less-developed countries. The paper illustrates that sustainable development is possible by exploiting local potential and traditional knowledge in order to achieve at the same time economic growth, social equality and environmental sustainability. In order to prove such an assumption a specific case study is described: The renewable energy sector in Bolivia. The case study summarizes many important dimensions of the innovation process in developing countries such as technological transfer, diffusion and adaptation, social dimension and development issues.

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In the present uncertain global context of reaching an equal social stability and steady thriving economy, power demand expected to grow and global electricity generation could nearly double from 2005 to 2030. Fossil fuels will remain a significant contribution on this energy mix up to 2050, with an expected part of around 70% of global and ca. 60% of European electricity generation. Coal will remain a key player. Hence, a direct effect on the considered CO2 emissions business-as-usual scenario is expected, forecasting three times the present CO2 concentration values up to 1,200ppm by the end of this century. Kyoto protocol was the first approach to take global responsibility onto CO2 emissions monitoring and cap targets by 2012 with reference to 1990. Some of principal CO2emitters did not ratify the reduction targets. Although USA and China spur are taking its own actions and parallel reduction measures. More efficient combustion processes comprising less fuel consuming, a significant contribution from the electricity generation sector to a CO2 dwindling concentration levels, might not be sufficient. Carbon Capture and Storage (CCS) technologies have started to gain more importance from the beginning of the decade, with research and funds coming out to drive its come in useful. After first researching projects and initial scale testing, three principal capture processes came out available today with first figures showing up to 90% CO2 removal by its standard applications in coal fired power stations. Regarding last part of CO2 reduction chain, two options could be considered worthy, reusing (EOR & EGR) and storage. The study evaluates the state of the CO2 capture technology development, availability and investment cost of the different technologies, with few operation cost analysis possible at the time. Main findings and the abatement potential for coal applications are presented. DOE, NETL, MIT, European universities and research institutions, key technology enterprises and utilities, and key technology suppliers are the main sources of this study. A vision of the technology deployment is presented.

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(Matsukawa and Habeck, 2007) analyse the main instruments for risk mitigation in infrastructure financing with Multilateral Financial Institutions (MFIs). Their review coincided with the global financial crisis of 2007-08, and is highly relevant in current times considering the sovereign debt crisis, the lack of available capital and the increases in bank regulation in Western economies. The current macroeconomic environment has seen a slowdown in the level of finance for infrastructure projects, as they pose a higher credit risk given their requirements for long term investments. The rationale for this work is to look for innovative solutions that are focused on the credit risk mitigation of infrastructure and energy projects whilst optimizing the economic capital allocation for commercial banks. This objective is achieved through risk-sharing with MFIs and looking for capital relief in project finance transactions. This research finds out the answer to the main question: "What is the impact of risk-sharing with MFIs on project finance transactions to increase their efficiency and viability?", and is developed from the perspective of a commercial bank assessing the economic capital used and analysing the relevant variables for it: Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). An overview of project finance for the infrastructure and energy sectors in terms of the volume of transactions worldwide is outlined, along with a summary of risk-sharing financing with MFIs. A review of the current regulatory framework beneath risk-sharing in structured finance with MFIs is also analysed. From here, the impact of risk-sharing and the diversification effect in infrastructure and energy projects is assessed, from the perspective of economic capital allocation for a commercial bank. CreditMetrics (J. P. Morgan, 1997) is applied over an existing well diversified portfolio of project finance infrastructure and energy investments, working with the main risk capital measures: economic capital, RAROC, and EVA. The conclusions of this research show that economic capital allocation on a portfolio of project finance along with risk-sharing with MFIs have a huge impact on capital relief whilst increasing performance profitability for commercial banks. There is an outstanding diversification effect due to the portfolio, which is combined with risk mitigation and an improvement in recovery rates through Partial Credit Guarantees issued by MFIs. A stress test scenario analysis is applied to the current assumptions and credit risk model, considering a downgrade in the rating for the commercial bank (lender) and an increase of default in emerging countries, presenting a direct impact on economic capital, through an increase in expected loss and a decrease in performance profitability. Getting capital relief through risk-sharing makes it more viable for commercial banks to finance infrastructure and energy projects, with the beneficial effect of a direct impact of these investments on GDP growth and employment. The main contribution of this work is to promote a strategic economic capital allocation in infrastructure and energy financing through innovative risk-sharing with MFIs and economic pricing to create economic value added for banks, and to allow the financing of more infrastructure and energy projects. This work suggests several topics for further research in relation to issues analysed. (Matsukawa and Habeck, 2007) analizan los principales instrumentos de mitigación de riesgos en las Instituciones Financieras Multilaterales (IFMs) para la financiación de infraestructuras. Su presentación coincidió con el inicio de la crisis financiera en Agosto de 2007, y sus consecuencias persisten en la actualidad, destacando la deuda soberana en economías desarrolladas y los problemas capitalización de los bancos. Este entorno macroeconómico ha ralentizado la financiación de proyectos de infraestructuras. El actual trabajo de investigación tiene su motivación en la búsqueda de soluciones para la financiación de proyectos de infraestructuras y de energía, mitigando los riesgos inherentes, con el objeto de reducir el consumo de capital económico en los bancos financiadores. Este objetivo se alcanza compartiendo el riesgo de la financiación con IFMs, a través de estructuras de risk-sharing. La investigación responde la pregunta: "Cuál es el impacto de risk-sharing con IFMs, en la financiación de proyectos para aumentar su eficiencia y viabilidad?". El trabajo se desarrolla desde el enfoque de un banco comercial, estimando el consumo de capital económico en la financiación de proyectos y analizando las principales variables del riesgo de crédito, Probability of Default, Loss Given Default and Recovery Rates, (Altman, 2010). La investigación presenta las cifras globales de Project Finance en los sectores de infraestructuras y de energía, y analiza el marco regulatorio internacional en relación al consumo de capital económico en la financiación de proyectos en los que participan IFMs. A continuación, el trabajo modeliza una cartera real, bien diversificada, de Project Finance de infraestructuras y de energía, aplicando la metodología CreditMet- rics (J. P. Morgan, 1997). Su objeto es estimar el consumo de capital económico y la rentabilidad de la cartera de proyectos a través del RAROC y EVA. La modelización permite estimar el efecto diversificación y la liberación de capital económico consecuencia del risk-sharing. Los resultados muestran el enorme impacto del efecto diversificación de la cartera, así como de las garantías parciales de las IFMs que mitigan riesgos, mejoran el recovery rate de los proyectos y reducen el consumo de capital económico para el banco comercial, mientras aumentan la rentabilidad, RAROC, y crean valor económico, EVA. En escenarios económicos de inestabilidad, empeoramiento del rating de los bancos, aumentos de default en los proyectos y de correlación en las carteras, hay un impacto directo en el capital económico y en la pérdida de rentabilidad. La liberación de capital económico, como se plantea en la presente investigación, permitirá financiar más proyectos de infraestructuras y de energía, lo que repercutirá en un mayor crecimiento económico y creación de empleo. La principal contribución de este trabajo es promover la gestión activa del capital económico en la financiación de infraestructuras y de proyectos energéticos, a través de estructuras innovadoras de risk-sharing con IFMs y de creación de valor económico en los bancos comerciales, lo que mejoraría su eficiencia y capitalización. La aportación metodológica del trabajo se convierte por su originalidad en una contribución, que sugiere y facilita nuevas líneas de investigación académica en las principales variables del riesgo de crédito que afectan al capital económico en la financiación de proyectos.

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The design of an electrodynamic tether is a complex task that involves the control of dynamic instabilities, optimization of the generated power (or the descent time in deorbiting missions), and minimization of the tether mass. The electrodynamic forces on an electrodynamic tether are responsible for variations in the mechanical energy of the tethered system and can also drive the system to dynamic instability. Energy sources and sinks in this system include the following: 1) ionospheric impedance, 2) the potential drop at the cathodic contactor, 3) ohmic losses in the tether, 4) the corotational plasma electric field, and 5) generated power and/or 6) input power. The analysis of each of these energy components, or bricks, establishes parameters that are useful tools for tether design. In this study, the nondimensional parameters that govern the orbital energy variation, dynamic instability, and power generation were characterized, and their mutual interdependence was established. A space-debris mitigation mission was taken as an example of this approach for the assessment of tether performance. Numerical simulations using a dumbbell model for tether dynamics, the International Geomagnetic Reference Field for the geomagnetic field, and the International Reference Ionosphere for the ionosphere were performed to test the analytical approach. The results obtained herein stress the close relationships that exist among the velocity of descent, dynamic stability, and generated power. An optimal tether design requires a detailed tradeoff among these performances in a real-world scenario.

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We address a cognitive radio scenario, where a number of secondary users performs identification of which primary user, if any, is trans- mitting, in a distributed way and using limited location information. We propose two fully distributed algorithms: the first is a direct iden- tification scheme, and in the other a distributed sub-optimal detection based on a simplified Neyman-Pearson energy detector precedes the identification scheme. Both algorithms are studied analytically in a realistic transmission scenario, and the advantage obtained by detec- tion pre-processing is also verified via simulation. Finally, we give details of their fully distributed implementation via consensus aver- aging algorithms.

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Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

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La planificación de la movilidad sostenible urbana es una tarea compleja que implica un alto grado de incertidumbre debido al horizonte de planificación a largo plazo, la amplia gama de paquetes de políticas posibles, la necesidad de una aplicación efectiva y eficiente, la gran escala geográfica, la necesidad de considerar objetivos económicos, sociales y ambientales, y la respuesta del viajero a los diferentes cursos de acción y su aceptabilidad política (Shiftan et al., 2003). Además, con las tendencias inevitables en motorización y urbanización, la demanda de terrenos y recursos de movilidad en las ciudades está aumentando dramáticamente. Como consecuencia de ello, los problemas de congestión de tráfico, deterioro ambiental, contaminación del aire, consumo de energía, desigualdades en la comunidad, etc. se hacen más y más críticos para la sociedad. Esta situación no es estable a largo plazo. Para enfrentarse a estos desafíos y conseguir un desarrollo sostenible, es necesario considerar una estrategia de planificación urbana a largo plazo, que aborde las necesarias implicaciones potencialmente importantes. Esta tesis contribuye a las herramientas de evaluación a largo plazo de la movilidad urbana estableciendo una metodología innovadora para el análisis y optimización de dos tipos de medidas de gestión de la demanda del transporte (TDM). La metodología nueva realizado se basa en la flexibilización de la toma de decisiones basadas en utilidad, integrando diversos mecanismos de decisión contrariedad‐anticipada y combinados utilidad‐contrariedad en un marco integral de planificación del transporte. La metodología propuesta incluye dos aspectos principales: 1) La construcción de escenarios con una o varias medidas TDM usando el método de encuesta que incorpora la teoría “regret”. La construcción de escenarios para este trabajo se hace para considerar específicamente la implementación de cada medida TDM en el marco temporal y marco espacial. Al final, se construyen 13 escenarios TDM en términos del más deseable, el más posible y el de menor grado de “regret” como resultado de una encuesta en dos rondas a expertos en el tema. 2) A continuación se procede al desarrollo de un marco de evaluación estratégica, basado en un Análisis Multicriterio de Toma de Decisiones (Multicriteria Decision Analysis, MCDA) y en un modelo “regret”. Este marco de evaluación se utiliza para comparar la contribución de los distintos escenarios TDM a la movilidad sostenible y para determinar el mejor escenario utilizando no sólo el valor objetivo de utilidad objetivo obtenido en el análisis orientado a utilidad MCDA, sino también el valor de “regret” que se calcula por medio del modelo “regret” MCDA. La función objetivo del MCDA se integra en un modelo de interacción de uso del suelo y transporte que se usa para optimizar y evaluar los impactos a largo plazo de los escenarios TDM previamente construidos. Un modelo de “regret”, llamado “referencedependent regret model (RDRM)” (modelo de contrariedad dependiente de referencias), se ha adaptado para analizar la contribución de cada escenario TDM desde un punto de vista subjetivo. La validación de la metodología se realiza mediante su aplicación a un caso de estudio en la provincia de Madrid. La metodología propuesta define pues un procedimiento técnico detallado para la evaluación de los impactos estratégicos de la aplicación de medidas de gestión de la demanda en el transporte, que se considera que constituye una herramienta de planificación útil, transparente y flexible, tanto para los planificadores como para los responsables de la gestión del transporte. Planning sustainable urban mobility is a complex task involving a high degree of uncertainty due to the long‐term planning horizon, the wide spectrum of potential policy packages, the need for effective and efficient implementation, the large geographical scale, the necessity to consider economic, social, and environmental goals, and the traveller’s response to the various action courses and their political acceptability (Shiftan et al., 2003). Moreover, with the inevitable trends on motorisation and urbanisation, the demand for land and mobility in cities is growing dramatically. Consequently, the problems of traffic congestion, environmental deterioration, air pollution, energy consumption, and community inequity etc., are becoming more and more critical for the society (EU, 2011). Certainly, this course is not sustainable in the long term. To address this challenge and achieve sustainable development, a long‐term perspective strategic urban plan, with its potentially important implications, should be established. This thesis contributes on assessing long‐term urban mobility by establishing an innovative methodology for optimizing and evaluating two types of transport demand management measures (TDM). The new methodology aims at relaxing the utility‐based decision‐making assumption by embedding anticipated‐regret and combined utilityregret decision mechanisms in an integrated transport planning framework. The proposed methodology includes two major aspects: 1) Construction of policy scenarios within a single measure or combined TDM policy‐packages using the survey method incorporating the regret theory. The purpose of building the TDM scenarios in this work is to address the specific implementation in terms of time frame and geographic scale for each TDM measure. Finally, 13 TDM scenarios are built in terms of the most desirable, the most expected and the least regret choice by means of the two‐round Delphi based survey. 2) Development of the combined utility‐regret analysis framework based on multicriteria decision analysis (MCDA). This assessment framework is used to compare the contribution of the TDM scenario towards sustainable mobility and to determine the best scenario considering not only the objective utility value obtained from the utilitybased MCDA, but also a regret value that is calculated via a regret‐based MCDA. The objective function of the utility‐based MCDA is integrated in a land use and transport interaction model and is used for optimizing and assessing the long term impacts of the constructed TDM scenarios. A regret based model, called referente dependent regret model (RDRM) is adapted to analyse the contribution of each TDM scenario in terms of a subjective point of view. The suggested methodology is implemented and validated in the case of Madrid. It defines a comprehensive technical procedure for assessing strategic effects of transport demand management measures, which can be useful, transparent and flexible planning tool both for planners and decision‐makers.

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This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

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The decision to select the most suitable type of energy storage system for an electric vehicle is always difficult, since many conditionings must be taken into account. Sometimes, this study can be made by means of complex mathematical models which represent the behavior of a battery, ultracapacitor or some other devices. However, these models are usually too dependent on parameters that are not easily available, which usually results in nonrealistic results. Besides, the more accurate the model, the more specific it needs to be, which becomes an issue when comparing systems of different nature. This paper proposes a practical methodology to compare different energy storage technologies. This is done by means of a linear approach of an equivalent circuit based on laboratory tests. Via these tests, the internal resistance and the self-discharge rate are evaluated, making it possible to compare different energy storage systems regardless their technology. Rather simple testing equipment is sufficient to give a comparative idea of the differences between each system, concerning issues such as efficiency, heating and self-discharge, when operating under a certain scenario. The proposed methodology is applied to four energy storage systems of different nature for the sake of illustration.

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High-Performance Computing, Cloud computing and next-generation applications such e-Health or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of CO2 and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters needed to integrate the Data Center in a holistic optimization framework and leverages the usage of Cyber-Physical systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Net- work (WSN). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68% without information loss, doubling the lifetime of the WSN nodes and allowing runtime energy minimization techniques in a real scenario.

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Global demand for mobility is increasing and the environmental impact of transport has become an important issue in transportation network planning and decision-making, as well as in the operational management phase. Suitable methods are required to assess emissions and fuel consumption reduction strategies that seek to improve energy efficiency and furthering decarbonization. This study describes the development and application of an improved modeling framework – the HERA (Highway EneRgy Assessment) methodology – that enables to assess the energy and carbon footprint of different highways and traffic flow scenarios and their comparison. HERA incorporates an average speed consumption model adjusted with a correction factor which takes into account the road gradient. It provides a more comprehensive method for estimating the footprint of particular highway segments under specific traffic conditions. It includes the application of the methodology to the Spanish highway network to validate it. Finally, a case study shows the benefits from using this methodology and how to integrate the objective of carbon footprint reductions into highway design, operation and scenario comparison.

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A first-rate e-Health system saves lives, provides better patient care, allows complex but useful epidemiologic analysis and saves money. However, there may also be concerns about the costs and complexities associated with e-health implementation, and the need to solve issues about the energy footprint of the high-demanding computing facilities. This paper proposes a novel and evolved computing paradigm that: (i) provides the required computing and sensing resources; (ii) allows the population-wide diffusion; (iii) exploits the storage, communication and computing services provided by the Cloud; (iv) tackles the energy-optimization issue as a first-class requirement, taking it into account during the whole development cycle. The novel computing concept and the multi-layer top-down energy-optimization methodology obtain promising results in a realistic scenario for cardiovascular tracking and analysis, making the Home Assisted Living a reality.

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La fiabilidad está pasando a ser el principal problema de los circuitos integrados según la tecnología desciende por debajo de los 22nm. Pequeñas imperfecciones en la fabricación de los dispositivos dan lugar ahora a importantes diferencias aleatorias en sus características eléctricas, que han de ser tenidas en cuenta durante la fase de diseño. Los nuevos procesos y materiales requeridos para la fabricación de dispositivos de dimensiones tan reducidas están dando lugar a diferentes efectos que resultan finalmente en un incremento del consumo estático, o una mayor vulnerabilidad frente a radiación. Las memorias SRAM son ya la parte más vulnerable de un sistema electrónico, no solo por representar más de la mitad del área de los SoCs y microprocesadores actuales, sino también porque las variaciones de proceso les afectan de forma crítica, donde el fallo de una única célula afecta a la memoria entera. Esta tesis aborda los diferentes retos que presenta el diseño de memorias SRAM en las tecnologías más pequeñas. En un escenario de aumento de la variabilidad, se consideran problemas como el consumo de energía, el diseño teniendo en cuenta efectos de la tecnología a bajo nivel o el endurecimiento frente a radiación. En primer lugar, dado el aumento de la variabilidad de los dispositivos pertenecientes a los nodos tecnológicos más pequeños, así como a la aparición de nuevas fuentes de variabilidad por la inclusión de nuevos dispositivos y la reducción de sus dimensiones, la precisión del modelado de dicha variabilidad es crucial. Se propone en la tesis extender el método de inyectores, que modela la variabilidad a nivel de circuito, abstrayendo sus causas físicas, añadiendo dos nuevas fuentes para modelar la pendiente sub-umbral y el DIBL, de creciente importancia en la tecnología FinFET. Los dos nuevos inyectores propuestos incrementan la exactitud de figuras de mérito a diferentes niveles de abstracción del diseño electrónico: a nivel de transistor, de puerta y de circuito. El error cuadrático medio al simular métricas de estabilidad y prestaciones de células SRAM se reduce un mínimo de 1,5 veces y hasta un máximo de 7,5 a la vez que la estimación de la probabilidad de fallo se mejora en varios ordenes de magnitud. El diseño para bajo consumo es una de las principales aplicaciones actuales dada la creciente importancia de los dispositivos móviles dependientes de baterías. Es igualmente necesario debido a las importantes densidades de potencia en los sistemas actuales, con el fin de reducir su disipación térmica y sus consecuencias en cuanto al envejecimiento. El método tradicional de reducir la tensión de alimentación para reducir el consumo es problemático en el caso de las memorias SRAM dado el creciente impacto de la variabilidad a bajas tensiones. Se propone el diseño de una célula que usa valores negativos en la bit-line para reducir los fallos de escritura según se reduce la tensión de alimentación principal. A pesar de usar una segunda fuente de alimentación para la tensión negativa en la bit-line, el diseño propuesto consigue reducir el consumo hasta en un 20 % comparado con una célula convencional. Una nueva métrica, el hold trip point se ha propuesto para prevenir nuevos tipos de fallo debidos al uso de tensiones negativas, así como un método alternativo para estimar la velocidad de lectura, reduciendo el número de simulaciones necesarias. Según continúa la reducción del tamaño de los dispositivos electrónicos, se incluyen nuevos mecanismos que permiten facilitar el proceso de fabricación, o alcanzar las prestaciones requeridas para cada nueva generación tecnológica. Se puede citar como ejemplo el estrés compresivo o extensivo aplicado a los fins en tecnologías FinFET, que altera la movilidad de los transistores fabricados a partir de dichos fins. Los efectos de estos mecanismos dependen mucho del layout, la posición de unos transistores afecta a los transistores colindantes y pudiendo ser el efecto diferente en diferentes tipos de transistores. Se propone el uso de una célula SRAM complementaria que utiliza dispositivos pMOS en los transistores de paso, así reduciendo la longitud de los fins de los transistores nMOS y alargando los de los pMOS, extendiéndolos a las células vecinas y hasta los límites de la matriz de células. Considerando los efectos del STI y estresores de SiGe, el diseño propuesto mejora los dos tipos de transistores, mejorando las prestaciones de la célula SRAM complementaria en más de un 10% para una misma probabilidad de fallo y un mismo consumo estático, sin que se requiera aumentar el área. Finalmente, la radiación ha sido un problema recurrente en la electrónica para aplicaciones espaciales, pero la reducción de las corrientes y tensiones de los dispositivos actuales los está volviendo vulnerables al ruido generado por radiación, incluso a nivel de suelo. Pese a que tecnologías como SOI o FinFET reducen la cantidad de energía colectada por el circuito durante el impacto de una partícula, las importantes variaciones de proceso en los nodos más pequeños va a afectar su inmunidad frente a la radiación. Se demuestra que los errores inducidos por radiación pueden aumentar hasta en un 40 % en el nodo de 7nm cuando se consideran las variaciones de proceso, comparado con el caso nominal. Este incremento es de una magnitud mayor que la mejora obtenida mediante el diseño de células de memoria específicamente endurecidas frente a radiación, sugiriendo que la reducción de la variabilidad representaría una mayor mejora. ABSTRACT Reliability is becoming the main concern on integrated circuit as the technology goes beyond 22nm. Small imperfections in the device manufacturing result now in important random differences of the devices at electrical level which must be dealt with during the design. New processes and materials, required to allow the fabrication of the extremely short devices, are making new effects appear resulting ultimately on increased static power consumption, or higher vulnerability to radiation SRAMs have become the most vulnerable part of electronic systems, not only they account for more than half of the chip area of nowadays SoCs and microprocessors, but they are critical as soon as different variation sources are regarded, with failures in a single cell making the whole memory fail. This thesis addresses the different challenges that SRAM design has in the smallest technologies. In a common scenario of increasing variability, issues like energy consumption, design aware of the technology and radiation hardening are considered. First, given the increasing magnitude of device variability in the smallest nodes, as well as new sources of variability appearing as a consequence of new devices and shortened lengths, an accurate modeling of the variability is crucial. We propose to extend the injectors method that models variability at circuit level, abstracting its physical sources, to better model sub-threshold slope and drain induced barrier lowering that are gaining importance in FinFET technology. The two new proposed injectors bring an increased accuracy of figures of merit at different abstraction levels of electronic design, at transistor, gate and circuit levels. The mean square error estimating performance and stability metrics of SRAM cells is reduced by at least 1.5 and up to 7.5 while the yield estimation is improved by orders of magnitude. Low power design is a major constraint given the high-growing market of mobile devices that run on battery. It is also relevant because of the increased power densities of nowadays systems, in order to reduce the thermal dissipation and its impact on aging. The traditional approach of reducing the voltage to lower the energy consumption if challenging in the case of SRAMs given the increased impact of process variations at low voltage supplies. We propose a cell design that makes use of negative bit-line write-assist to overcome write failures as the main supply voltage is lowered. Despite using a second power source for the negative bit-line, the design achieves an energy reduction up to 20% compared to a conventional cell. A new metric, the hold trip point has been introduced to deal with new sources of failures to cells using a negative bit-line voltage, as well as an alternative method to estimate cell speed, requiring less simulations. With the continuous reduction of device sizes, new mechanisms need to be included to ease the fabrication process and to meet the performance targets of the successive nodes. As example we can consider the compressive or tensile strains included in FinFET technology, that alter the mobility of the transistors made out of the concerned fins. The effects of these mechanisms are very dependent on the layout, with transistor being affected by their neighbors, and different types of transistors being affected in a different way. We propose to use complementary SRAM cells with pMOS pass-gates in order to reduce the fin length of nMOS devices and achieve long uncut fins for the pMOS devices when the cell is included in its corresponding array. Once Shallow Trench isolation and SiGe stressors are considered the proposed design improves both kinds of transistor, boosting the performance of complementary SRAM cells by more than 10% for a same failure probability and static power consumption, with no area overhead. While radiation has been a traditional concern in space electronics, the small currents and voltages used in the latest nodes are making them more vulnerable to radiation-induced transient noise, even at ground level. Even if SOI or FinFET technologies reduce the amount of energy transferred from the striking particle to the circuit, the important process variation that the smallest nodes will present will affect their radiation hardening capabilities. We demonstrate that process variations can increase the radiation-induced error rate by up to 40% in the 7nm node compared to the nominal case. This increase is higher than the improvement achieved by radiation-hardened cells suggesting that the reduction of process variations would bring a higher improvement.