Clean Coal Technologies Scenario and Evaluation of Present CO2 Dwindling Initiatives to Approach Zero Emission Power Stations By Coal Combustion. Deployment Situation and Evaluation Study

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.

Stopping power dependence of nitrogen sputtering yields in copper nitride films under swift-ion irradiation: Exciton model approach

Nitrogen sputtering yields as high as 104 atoms/ion, are obtained by irradiating N-rich-Cu3N films (N concentration: 33 ± 2 at.%) with Cu ions at energies in the range 10?42 MeV. The kinetics of N sputtering as a function of ion fluence is determined at several energies (stopping powers) for films deposited on both, glass and silicon substrates. The kinetic curves show that the amount of nitrogen release strongly increases with rising irradiation fluence up to reaching a saturation level at a low remaining nitrogen fraction (5?10%), in which no further nitrogen reduction is observed. The sputtering rate for nitrogen depletion is found to be independent of the substrate and to linearly increase with electronic stopping power (Se). A stopping power (Sth) threshold of ?3.5 keV/nm for nitrogen depletion has been estimated from extrapolation of the data. Experimental kinetic data have been analyzed within a bulk molecular recombination model. The microscopic mechanisms of the nitrogen depletion process are discussed in terms of a non-radiative exciton decay model. In particular, the estimated threshold is related to a minimum exciton density which is required to achieve efficient sputtering rates.

Prediction of wake effects on wind farm power production using a RANS approach. Part II. Offshore: Case studies from the UPWIND project

The estimation of power losses due to wind turbine wakes is crucial to understanding overall wind farm economics. This is especially true for large offshore wind farms, as it represents the primary source of losses in available power, given the regular arrangement of rotors, their generally largerdiameter and the lower ambient turbulence level, all of which conspire to dramatically affect wake expansion and, consequently, the power deficit. Simulation of wake effects in offshore wind farms (in reasonable computational time) is currently feasible using CFD tools. An elliptic CFD model basedon the actuator disk method and various RANS turbulence closure schemes is tested and validated using power ratios extracted from Horns Rev and Nysted wind farms, collected as part of the EU-funded UPWIND project. The primary focus of the present work is on turbulence modeling, as turbulent mixing is the main mechanism for flow recovery inside wind farms. A higher-order approach, based on the anisotropic RSM model, is tested to better take into account the imbalance in the length scales inside and outside of the wake, not well reproduced by current two-equation closure schemes.

A wavelet-based approach for large wind power ramp characterisation

A wavelet-based approach for large wind power ramp characterisation

Characteristic study, its identification and self-tuned approach to control hydro-power plants

The water time constant and mechanical time constant greatly influences the power and speed oscillations of hydro-turbine-generator unit. This paper discusses the turbine power transients in response to different nature and changes in the gate position. The work presented here analyses the characteristics of hydraulic system with an emphasis on changes in the above time constants. The simulation study is based on mathematical first-, second-, third- and fourth-order transfer function models. The study is further extended to identify discrete time-domain models and their characteristic representation without noise and with noise content of 10 & 20 dB signal-to-noise ratio (SNR). The use of self-tuned control approach in minimising the speed deviation under plant parameter changes and disturbances is also discussed.

A control theoretic approach to solve a constrained uplink power dynamic game

This paper addresses an uplink power control dynamic game where we assume that each user battery represents the system state that changes with time following a discrete-time version of a differential game. To overcome the complexity of the analysis of a dynamic game approach we focus on the concept of Dynamic Potential Games showing that the game can be solved as an equivalent Multivariate Optimum Control Problem. The solution of this problem is quite interesting because different users split the activity in time, avoiding higher interferences and providing a long term fairness.

Impact assessment of an integrated approach for thermal power generation plants asset management in the current energy market

El sector energético, en España en particular, y de forma similar en los principales países de Europa, cuenta con una significativa sobrecapacidad de generación, debido al rápido y significativo crecimiento de las energías renovables en los últimos diez años y la reducción de la demanda energética, como consecuencia de la crisis económica. Esta situación ha hecho que las centrales térmicas de generación de electricidad, y en concreto los ciclos combinados de gas, operen con un factor de utilización extremadamente bajo, del orden del 10%. Además de la reducción de ingresos, esto supone para las plantas trabajar continuamente fuera del punto de diseño, provocando una significativa pérdida de rendimiento y mayores costes de explotación. En este escenario, cualquier contribución que ayude a mejorar la eficiencia y la condición de los equipos, es positivamente considerada. La gestión de activos está ganando relevancia como un proceso multidisciplinar e integrado, tal y como refleja la reciente publicación de las normas ISO 55000:2014. Como proceso global e integrado, la gestión de activos requiere el manejo de diversos procesos y grandes volúmenes de información, incluso en tiempo real. Para ello es necesario utilizar tecnologías de la información y aplicaciones de software. Esta tesis desarrolla un concepto integrado de gestión de activos (Integrated Plant Management – IPM) aplicado a centrales de ciclo combinado y una metodología para estimar el beneficio aportado por el mismo. Debido a las incertidumbres asociadas a la estimación del beneficio, se ha optado por un análisis probabilístico coste-beneficio. Así mismo, el análisis cuantitativo se ha completado con una validación cualitativa del beneficio aportado por las tecnologías incorporadas al concepto de gestión integrada de activos, mediante una entrevista realizada a expertos del sector de generación de energía. Los resultados del análisis coste-beneficio son positivos, incluso en el desfavorable escenario con un factor de utilización de sólo el 10% y muy prometedores para factores de utilización por encima del 30%. ABSTRACT The energy sector particularly in Spain, and in a similar way in Europe, has a significant overcapacity due to the big growth of the renewable energies in the last ten years, and it is seriously affected by the demand decrease due to the economic crisis. That situation has forced the thermal plants and in particular, the combined cycles to operate with extremely low annual average capacity factors, very close to 10%. Apart from the incomes reduction, working in out-of-design conditions, means getting a worse performance and higher costs than expected. In this scenario, anything that can be done to improve the efficiency and the equipment condition is positively received. Asset Management, as a multidisciplinary and integrated process, is gaining prominence, reflected in the recent publication of the ISO 55000 series in 2014. Dealing Asset Management as a global, integrated process needs to manage several processes and significant volumes of information, also in real time, that requires information technologies and software applications to support it. This thesis proposes an integrated asset management concept (Integrated Plant Management-IPM) applied to combined cycle power plants and develops a methodology to assess the benefit that it can provide. Due to the difficulties in getting deterministic benefit estimation, a statistical approach has been adopted for the cot-benefit analysis. As well, the quantitative analysis has been completed with a qualitative validation of the technologies included in the IPM and their contribution to key power plant challenges by power generation sector experts. The cost- benefit analysis provides positive results even in the negative scenario of annual average capacity factor close to 10% and is promising for capacity factors over 30%.

Design and Optimization of Power Delivery and Distribution Systems Using Evolutionary Computation Techniques

Nowadays computing platforms consist of a very large number of components that require to be supplied with diferent voltage levels and power requirements. Even a very small platform, like a handheld computer, may contain more than twenty diferent loads and voltage regulators. The power delivery designers of these systems are required to provide, in a very short time, the right power architecture that optimizes the performance, meets electrical specifications plus cost and size targets. The appropriate selection of the architecture and converters directly defines the performance of a given solution. Therefore, the designer needs to be able to evaluate a significant number of options in order to know with good certainty whether the selected solutions meet the size, energy eficiency and cost targets. The design dificulties of selecting the right solution arise due to the wide range of power conversion products provided by diferent manufacturers. These products range from discrete components (to build converters) to complete power conversion modules that employ diferent manufacturing technologies. Consequently, in most cases it is not possible to analyze all the alternatives (combinations of power architectures and converters) that can be built. The designer has to select a limited number of converters in order to simplify the analysis. In this thesis, in order to overcome the mentioned dificulties, a new design methodology for power supply systems is proposed. This methodology integrates evolutionary computation techniques in order to make possible analyzing a large number of possibilities. This exhaustive analysis helps the designer to quickly define a set of feasible solutions and select the best trade-off in performance according to each application. The proposed approach consists of two key steps, one for the automatic generation of architectures and other for the optimized selection of components. In this thesis are detailed the implementation of these two steps. The usefulness of the methodology is corroborated by contrasting the results using real problems and experiments designed to test the limits of the algorithms.

Amorphization kinectics under swift heavy ion irradiation: a cumulative overlapping-track approach

A simple illustrative physical model is presented to describe the kinetics of damage and amorphization by swiftheavyions (SHI) in LiNbO3. The model considers that every ion impact generates initially a defective region (halo) and a full amorphous core whose relative size depends on the electronic stopping power. Below a given stopping power threshold only a halo is generated. For increasing fluences the amorphized area grows monotonically via overlapping of a fixed number N of halos. In spite of its simplicity the model, which provides analytical solutions, describes many relevant features of the kinetic behaviour. In particular, it predicts approximate Avrami curves with parameters depending on stopping power in qualitative accordance with experiment that turn into Poisson laws well above the threshold value

Non-linear gain - look-up table based approach for modeling a family of DC to DC converters based on transient response analysis

The purpose of this work is to propose a structure for simulating power systems using behavioral models of nonlinear DC to DC converters implemented through a look-up table of gains. This structure is specially designed for converters whose output impedance depends on the load current level, e.g. quasi-resonant converters. The proposed model is a generic one whose parameters can be obtained by direct measuring the transient response at different operating points. It also includes optional functionalities for modeling converters with current limitation and current sharing in paralleling characteristics. The pusposed structured also allows including aditional characteristics of the DC to DC converter as the efficency as a function of the input voltage and the output current or overvoltage and undervoltage protections. In addition, this proposed model is valid for overdamped and underdamped situations.

On-chip Monitoring: A Light-Weight Interconnection Network Approach

Current nanometer technologies are subjected to several adverse effects that seriously impact the yield and performance of integrated circuits. Such is the case of within-die parameters uncertainties, varying workload conditions, aging, temperature, etc. Monitoring, calibration and dynamic adaptation have appeared as promising solutions to these issues and many kinds of monitors have been presented recently. In this scenario, where systems with hundreds of monitors of different types have been proposed, the need for light-weight monitoring networks has become essential. In this work we present a light-weight network architecture based on digitization resource sharing of nodes that require a time-to-digital conversion. Our proposal employs a single wire interface, shared among all the nodes in the network, and quantizes the time domain to perform the access multiplexing and transmit the information. It supposes a 16% improvement in area and power consumption compared to traditional approaches.

A computer vision approach for weeds identification through Support Vector Machines

This paper outlines an automatic computervision system for the identification of avena sterilis which is a special weed seed growing in cereal crops. The final goal is to reduce the quantity of herbicide to be sprayed as an important and necessary step for precision agriculture. So, only areas where the presence of weeds is important should be sprayed. The main problems for the identification of this kind of weed are its similar spectral signature with respect the crops and also its irregular distribution in the field. It has been designed a new strategy involving two processes: image segmentation and decision making. The image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and weeds. The decision making is based on the SupportVectorMachines and determines if a cell must be sprayed. The main findings of this paper are reflected in the combination of the segmentation and the SupportVectorMachines decision processes. Another important contribution of this approach is the minimum requirements of the system in terms of memory and computation power if compared with other previous works. The performance of the method is illustrated by comparative analysis against some existing strategies.

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

A syntactic approach to combining functional notation, lazy evaluation, and higher-order in LP systems

Nondeterminism and partially instantiated data structures give logic programming expressive power beyond that of functional programming. However, functional programming often provides convenient syntactic features, such as having a designated implicit output argument, which allow function cali nesting and sometimes results in more compact code. Functional programming also sometimes allows a more direct encoding of lazy evaluation, with its ability to deal with infinite data structures. We present a syntactic functional extensión, used in the Ciao system, which can be implemented in ISO-standard Prolog systems and covers function application, predefined evaluable functors, functional definitions, quoting, and lazy evaluation. The extensión is also composable with higher-order features and can be combined with other extensions to ISO-Prolog such as constraints. We also highlight the features of the Ciao system which help implementation and present some data on the overhead of using lazy evaluation with respect to eager evaluation.

A practical approach for outdoors distributed target localization in wireless sensor networks

Wireless sensor networks are posed as the new communication paradigm where the use of small, low-complexity, and low-power devices is preferred over costly centralized systems. The spectra of potential applications of sensor networks is very wide, ranging from monitoring, surveillance, and localization, among others. Localization is a key application in sensor networks and the use of simple, efficient, and distributed algorithms is of paramount practical importance. Combining convex optimization tools with consensus algorithms we propose a distributed localization algorithm for scenarios where received signal strength indicator readings are used. We approach the localization problem by formulating an alternative problem that uses distance estimates locally computed at each node. The formulated problem is solved by a relaxed version using semidefinite relaxation technique. Conditions under which the relaxed problem yields to the same solution as the original problem are given and a distributed consensusbased implementation of the algorithm is proposed based on an augmented Lagrangian approach and primaldual decomposition methods. Although suboptimal, the proposed approach is very suitable for its implementation in real sensor networks, i.e., it is scalable, robust against node failures and requires only local communication among neighboring nodes. Simulation results show that running an additional local search around the found solution can yield performance close to the maximum likelihood estimate.