Modelling and simulation of a photovoltaic fuel cell hybrid system

A stand-alone power system is an autonomous system that supplies electricity to the user load without being connected to the electric grid. This kind of decentralized system is frequently located in remote and inaccessible areas. It is essential for about one third of the world population which are living in developed or isolated regions and have no access to an electricity utility grid. The most people live in remote and rural areas, with low population density, lacking even the basic infrastructure. The utility grid extension to these locations is not a cost effective option and sometimes technically not feasible. The purpose of this thesis is the modelling and simulation of a stand-alone hybrid power system, referred to as “hydrogen Photovoltaic-Fuel Cell (PVFC) hybrid system”. It couples a photovoltaic generator (PV), an alkaline water electrolyser, a storage gas tank, a proton exchange membrane fuel cell (PEMFC), and power conditioning units (PCU) to give different system topologies. The system is intended to be an environmentally friendly solution since it tries maximising the use of a renewable energy source. Electricity is produced by a PV generator to meet the requirements of a user load. Whenever there is enough solar radiation, the user load can be powered totally by the PV electricity. During periods of low solar radiation, auxiliary electricity is required. An alkaline high pressure water electrolyser is powered by the excess energy from the PV generator to produce hydrogen and oxygen at a pressure of maximum 30bar. Gases are stored without compression for short- (hourly or daily) and long- (seasonal) term. A proton exchange membrane (PEM) fuel cell is used to keep the system’s reliability at the same level as for the conventional system while decreasing the environmental impact of the whole system. The PEM fuel cell consumes gases which are produced by an electrolyser to meet the user load demand when the PV generator energy is deficient, so that it works as an auxiliary generator. Power conditioning units are appropriate for the conversion and dispatch the energy between the components of the system. No batteries are used in this system since they represent the weakest when used in PV systems due to their need for sophisticated control and their short lifetime. The model library, ISET Alternative Power Library (ISET-APL), is designed by the Institute of Solar Energy supply Technology (ISET) and used for the simulation of the hybrid system. The physical, analytical and/or empirical equations of each component are programmed and implemented separately in this library for the simulation software program Simplorer by C++ language. The model parameters are derived from manufacturer’s performance data sheets or measurements obtained from literature. The identification and validation of the major hydrogen PVFC hybrid system component models are evaluated according to the measured data of the components, from the manufacturer’s data sheet or from actual system operation. Then, the overall system is simulated, at intervals of one hour each, by using solar radiation as the primary energy input and hydrogen as energy storage for one year operation. A comparison between different topologies, such as DC or AC coupled systems, is carried out on the basis of energy point of view at two locations with different geographical latitudes, in Kassel/Germany (Europe) and in Cairo/Egypt (North Africa). The main conclusion in this work is that the simulation method of the system study under different conditions could successfully be used to give good visualization and comparison between those topologies for the overall performance of the system. The operational performance of the system is not only depending on component efficiency but also on system design and consumption behaviour. The worst case of this system is the low efficiency of the storage subsystem made of the electrolyser, the gas storage tank, and the fuel cell as it is around 25-34% at Cairo and 29-37% at Kassel. Therefore, the research for this system should be concentrated in the subsystem components development especially the fuel cell.

Femtosecond time-resolved molecular multiphoton ionization: the Na_2 system

We report here the first experimental study of femtosecond time-resolved molecular multiphoton ionization. Femtosecond pump-probe techniques are combined with time-of-flight spectroscopy to measure transient ionization spectra of Na_2 in a molecular-beam experiment. The wave-packet motions in different molecular potentials show that incoherent contributions from direct photoionization of a singly excited state and from excitation and autoionization of a bound doubly excited molecular state determine the observed transient ionization signal.

Patent DE10 2004 037 519 B4 “Sensor Process and Device for Determining a Physical Value“. A Proof of Concept

At present, a fraction of 0.1 - 0.2% of the patients undergoing surgery become aware during the process. The situation is referred to as anesthesia awareness and is obviously very traumatic for the person experiencing it. The reason for its occurrence is mostly an insufficient dosage of the narcotic Propofol combined with the incapability of the technology monitoring the depth of the patient’s anesthetic state to notice the patient becoming aware. A solution can be a highly sensitive and selective real time monitoring device for Propofol based on optical absorption spectroscopy. Its working principle has been postulated by Prof. Dr. habil. H. Hillmer and formulated in DE10 2004 037 519 B4, filed on Aug 30th, 2004. It consists of the exploitation of Intra Cavity Absorption effects in a two mode laser system. In this Dissertation, a two mode external cavity semiconductor laser, which has been developed previously to this work is enhanced and optimized to a functional sensor. Enhancements include the implementation of variable couplers into the system and the implementation of a collimator arrangement into which samples can be introduced. A sample holder and cells are developed and characterized with a focus on compatibility with the measurement approach. Further optimization concerns the overall performance of the system: scattering sources are reduced by re-splicing all fiber-to-fiber connections, parasitic cavities are eliminated by suppressing the Fresnel reflexes of all one fiber ends by means of optical isolators and wavelength stability of the system is improved by the implementation of thermal insulation to the Fiber Bragg Gratings (FBG). The final laser sensor is characterized in detail thermally and optically. Two separate modes are obtained at 1542.0 and 1542.5 nm, tunable in a range of 1nm each. Mode Full Width at Half Maximum (FWHM) is 0.06nm and Signal to Noise Ratio (SNR) is as high as 55 dB. Independent of tuning the two modes of the system can always be equalized in intensity, which is important as the delicacy of the intensity equilibrium is one of the main sensitivity enhancing effects formulated in DE10 2004 037 519 B4. For the proof of concept (POC) measurements the target substance Propofol is diluted in the solvents Acetone and DiChloroMethane (DCM), which have been investigated for compatibility with Propofol beforehand. Eight measurement series (two solvents, two cell lengths and two different mode spacings) are taken, which draw a uniform picture: mode intensity ratio responds linearly to an increase of Propofol in all cases. The slope of the linear response indicates the sensitivity of the system. The eight series are split up into two groups: measurements taken in long cells and measurements taken in short cells.

Growth and yield of groundnut, sesame and roselle in an Acacia senegal agroforestry system in North Kordofan, Sudan

A field experiment was conducted under rainfed conditions in western Sudan at El-Obeid Research Farm and Eldemokeya Forest Reserve, North Kordofan State, during the growing seasons 2004/05 and 2005/06. The main objective was to investigate the soil physical and chemical properties and yield of groundnut (Arachis hypogea), sesame (Sesamum indicum) and roselle (Hibiscus sabdariffa) of an Acacia senegal agroforestry system in comparison with the sole cropping system. Data were recorded for soil physical and chemical properties, soil moisture content, number of pods per plant, fresh weight (kg ha^−1) and crop yield (kg ha^−1). The treatments were arranged in Randomized Complete Block Design (RCBD) and replicated four times. Significant differences (P < 0.05) were obtained for sand and silt content on both sites, while clay content was not significantly different on both sites. The nitrogen (N) and organic carbon were significantly (P < 0.05) higher in the intercropping system in Eldemokeya Forest Reserve compared with sole cropping. Soil organic carbon, N and pH were not significant on El-Obeid site. Yet the level of organic carbon, N, P and pH was higher in the intercropping system. Fresh weight was significantly different on both sites. The highest fresh weight was found in the intercropping system. Dry weights were significantly different for sesame and roselle on both sites, while groundnut was not significantly different. On both sites intercropping systems reduced groundnut, sesame and roselle yields by 26.3, 12 and 20.2%, respectively. The reduction in yield in intercropping plots could be attributed to high tree density, which resulted in water and light competition between trees and the associated crops.

From First Contact to Close Encounters: A Developmentally Deep Perceptual System for a Humanoid Robot

This thesis presents a perceptual system for a humanoid robot that integrates abilities such as object localization and recognition with the deeper developmental machinery required to forge those competences out of raw physical experiences. It shows that a robotic platform can build up and maintain a system for object localization, segmentation, and recognition, starting from very little. What the robot starts with is a direct solution to achieving figure/ground separation: it simply 'pokes around' in a region of visual ambiguity and watches what happens. If the arm passes through an area, that area is recognized as free space. If the arm collides with an object, causing it to move, the robot can use that motion to segment the object from the background. Once the robot can acquire reliable segmented views of objects, it learns from them, and from then on recognizes and segments those objects without further contact. Both low-level and high-level visual features can also be learned in this way, and examples are presented for both: orientation detection and affordance recognition, respectively. The motivation for this work is simple. Training on large corpora of annotated real-world data has proven crucial for creating robust solutions to perceptual problems such as speech recognition and face detection. But the powerful tools used during training of such systems are typically stripped away at deployment. Ideally they should remain, particularly for unstable tasks such as object detection, where the set of objects needed in a task tomorrow might be different from the set of objects needed today. The key limiting factor is access to training data, but as this thesis shows, that need not be a problem on a robotic platform that can actively probe its environment, and carry out experiments to resolve ambiguity. This work is an instance of a general approach to learning a new perceptual judgment: find special situations in which the perceptual judgment is easy and study these situations to find correlated features that can be observed more generally.

A system to reduce the effect of CCDs saturation

Colour image segmentation based on the hue component presents some problems due to the physical process of image formation. One of that problems is colour clipping, which appear when at least one of the sensor components is saturated. We have designed a system, that works for a trained set of colours, to recover the chromatic information of those pixels on which colour has been clipped. The chromatic correction method is based on the fact that hue and saturation are invariant to the uniform scaling of the three RGB components. The proposed method has been validated by means of a specific colour image processing board that has allowed its execution in real time. We show experimental results of the application of our method

The Ergonomic Analysis and Back Injuries in Flexible Production System

Back injuries identification and diagnoses in the transition of the Taylor model to the flexiblemodel of production organization, demands a parallel intervention of prevention actors at work. This study uses simultaneously three intervention models (structured action analysis, muscle skeletal symptoms questionnaires and muscle skeletal assessment) for work activities in a packaging plant. In this study seventy and two (72) operative workers participated (28 workers with muscle skeletal evaluation). In an intervention period of 10 months, the physical, cognitive, organizational components and productive process dynamics were evaluated from the muscle skeletal demands issues. The differences established between objective exposure at risk, back injury risk perception, appreciation and a vertebral spine evaluation, in prior and post intervention, determines the structure for a muscle skeletal risk management system. This study explains that back injury symptoms can be more efficiently reduced among operative workers combining measures registered and the adjustment between dynamics, the changes at work and efficient gestures development. Relevance: the results of this study can be used to pre ent back injuries in workers of flexible production processes.

Studies of dynamics of physical agent ecosystems

This thesis addresses the problem of learning in physical heterogeneous multi-agent systems (MAS) and the analysis of the benefits of using heterogeneous MAS with respect to homogeneous ones. An algorithm is developed for this task; building on a previous work on stability in distributed systems by Tad Hogg and Bernardo Huberman, and combining two phenomena observed in natural systems, task partition and hierarchical dominance. This algorithm is devised for allowing agents to learn which are the best tasks to perform on the basis of each agent's skills and the contribution to the team global performance. Agents learn by interacting with the environment and other teammates, and get rewards from the result of the actions they perform. This algorithm is specially designed for problems where all robots have to co-operate and work simultaneously towards the same goal. One example of such a problem is role distribution in a team of heterogeneous robots that form a soccer team, where all members take decisions and co-operate simultaneously. Soccer offers the possibility of conducting research in MAS, where co-operation plays a very important role in a dynamical and changing environment. For these reasons and the experience of the University of Girona in this domain, soccer has been selected as the test-bed for this research. In the case of soccer, tasks are grouped by means of roles. One of the most interesting features of this algorithm is that it endows MAS with a high adaptability to changes in the environment. It allows the team to perform their tasks, while adapting to the environment. This is studied in several cases, for changes in the environment and in the robot's body. Other features are also analysed, especially a parameter that defines the fitness (biological concept) of each agent in the system, which contributes to performance and team adaptability. The algorithm is applied later to allow agents to learn in teams of homogeneous and heterogeneous robots which roles they have to select, in order to maximise team performance. The teams are compared and the performance is evaluated in the games against three hand-coded teams and against the different homogeneous and heterogeneous teams built in this thesis. This section focuses on the analysis of performance and task partition, in order to study the benefits of heterogeneity in physical MAS. In order to study heterogeneity from a rigorous point of view, a diversity measure is developed building on the hierarchic social entropy defined by Tucker Balch. This is adapted to quantify physical diversity in robot teams. This tool presents very interesting features, as it can be used in the future to design heterogeneous teams on the basis of the knowledge on other teams.

Texture recognition under varying imaging geometries

La visió és probablement el nostre sentit més dominant a partir del qual derivem la majoria d'informació del món que ens envolta. A través de la visió podem percebre com són les coses, on són i com es mouen. En les imatges que percebem amb el nostre sistema de visió podem extreure'n característiques com el color, la textura i la forma, i gràcies a aquesta informació som capaços de reconèixer objectes fins i tot quan s'observen sota unes condicions totalment diferents. Per exemple, som capaços de distingir un mateix objecte si l'observem des de diferents punts de vista, distància, condicions d'il·luminació, etc. La Visió per Computador intenta emular el sistema de visió humà mitjançant un sistema de captura d'imatges, un ordinador, i un conjunt de programes. L'objectiu desitjat no és altre que desenvolupar un sistema que pugui entendre una imatge d'una manera similar com ho realitzaria una persona. Aquesta tesi es centra en l'anàlisi de la textura per tal de realitzar el reconeixement de superfícies. La motivació principal és resoldre el problema de la classificació de superfícies texturades quan han estat capturades sota diferents condicions, com ara distància de la càmera o direcció de la il·luminació. D'aquesta forma s'aconsegueix reduir els errors de classificació provocats per aquests canvis en les condicions de captura. En aquest treball es presenta detalladament un sistema de reconeixement de textures que ens permet classificar imatges de diferents superfícies capturades en diferents condicions. El sistema proposat es basa en un model 3D de la superfície (que inclou informació de color i forma) obtingut mitjançant la tècnica coneguda com a 4-Source Colour Photometric Stereo (CPS). Aquesta informació és utilitzada posteriorment per un mètode de predicció de textures amb l'objectiu de generar noves imatges 2D de les textures sota unes noves condicions. Aquestes imatges virtuals que es generen seran la base del nostre sistema de reconeixement, ja que seran utilitzades com a models de referència per al nostre classificador de textures. El sistema de reconeixement proposat combina les Matrius de Co-ocurrència per a l'extracció de característiques de textura, amb la utilització del Classificador del veí més proper. Aquest classificador ens permet al mateix temps aproximar la direcció d'il·luminació present en les imatges que s'utilitzen per testejar el sistema de reconeixement. És a dir, serem capaços de predir l'angle d'il·luminació sota el qual han estat capturades les imatges de test. Els resultats obtinguts en els diferents experiments que s'han realitzat demostren la viabilitat del sistema de predicció de textures, així com del sistema de reconeixement.

Dental training system using haptic technology

In the U.K., dental students require to perform training and practice on real human tissues at the very early stage of their courses. Currently, the human tissues, such as decayed teeth, are mounted in a human head like physical model. The problems with these models in teaching are; (1) every student operates on tooth, which are always unique; (2) the process cannot be recorded for examination purposes and (3) same training are not repeatable. The aim of the PHATOM Project is to develop a dental training system using Haptic technology. This paper documents the project background, specification, research and development of the first prototype system. It also discusses the research in the visual display, haptic devices and haptic rendering. This includes stereo vision, motion parallax, volumetric modelling, surface remapping algorithms as well as analysis design of the system. A new volumetric to surface model transformation algorithm is also introduced. This paper includes the future work on the system development and research.

Seasonal variations of the physical and optical characteristics of Saharan Dust: results from the Dust outflow and Deposition to the Ocean (DODO) experiment

North African dust is important for climate through its direct radiative effect on solar and terrestrial radiation and its role in the biogeochemical system. The Dust Outflow and Deposition to the Ocean project (DODO) aimed to characterize the physical and optical properties of airborne North African dust in two seasons and to use these observations to constrain model simulations, with the ultimate aim of being able to quantify the deposition of iron to the North Atlantic Ocean. The in situ properties of dust from airborne campaigns measured during February and August 2006, based at Dakar, Senegal, are presented here. Average values of the single scattering albedo (0.99, 0.98), mass specific extinction (0.85 m^2 g^-1 , 1.14 m^2 g^-1 ), asymmetry parameter (0.68, 0.68), and refractive index (1.53--0.0005i,1.53--0.0014i) for the accumulation mode were found to differ by varying degrees between the dry and wet season, respectively. It is hypothesized that these differences are due to different source regions and transport processes which also differ between the DODO campaigns. Elemental ratios of Ca/Al were found to differ between the dry and wet season (1.1 and 0.5, respectively). Differences in vertical profiles are found between seasons and between land and ocean locations and reflect the different dynamics of the seasons. Using measurements of the coarse mode size distribution and illustrative Mie calculations, the optical properties are found to be very sensitive to the presence and amount of coarse mode of mineral dust, and the importance of accurate measurements of the coarse mode of dust is highlighted.

Developing the next-generation climate system models: challenges and achievements

Although climate models have been improving in accuracy and efficiency over the past few decades, it now seems that these incremental improvements may be slowing. As tera/petascale computing becomes massively parallel, our legacy codes are less suitable, and even with the increased resolution that we are now beginning to use, these models cannot represent the multiscale nature of the climate system. This paper argues that it may be time to reconsider the use of adaptive mesh refinement for weather and climate forecasting in order to achieve good scaling and representation of the wide range of spatial scales in the atmosphere and ocean. Furthermore, the challenge of introducing living organisms and human responses into climate system models is only just beginning to be tackled. We do not yet have a clear framework in which to approach the problem, but it is likely to cover such a huge number of different scales and processes that radically different methods may have to be considered. The challenges of multiscale modelling and petascale computing provide an opportunity to consider a fresh approach to numerical modelling of the climate (or Earth) system, which takes advantage of the computational fluid dynamics developments in other fields and brings new perspectives on how to incorporate Earth system processes. This paper reviews some of the current issues in climate (and, by implication, Earth) system modelling, and asks the question whether a new generation of models is needed to tackle these problems.

The influence of physical processes on extratropical singular vectors

An investigation is made of the impact of a full linearized physical (moist) parameterization package on extratropical singular vectors (SVs) using the ECMWF integrated forecasting system (IFS). Comparison is made for one particular period with a dry physical package including only vertical diffusion and surface drag. The crucial extra ingredient in the full package is found to be the large-scale latent heat release. Consistent with basic theory, its inclusion results in a shift to smaller horizontal scales and enhanced growth for the SVs. Whereas, for the dry SVs, T42 resolution is sufficient, the moist SVs require T63 to resolve their structure and growth. A 24-h optimization time appears to be appropriate for the moist SVs because of the larger growth of moist SVs compared with dry SVs. Like dry SVs, moist SVs tend to occur in regions of high baroclinicity, but their location is also influenced by the availability of moisture. The most rapidly growing SVs appear to enhance or reduce large-scale rain in regions ahead of major cold fronts. The enhancement occurs in and ahead of a cyclonic perturbation and the reduction in and ahead of an anticyclonic perturbation. Most of the moist SVs for this situation are slightly modified versions of the dry SVs. However, some occur in new locations and have particularly confined structures. The most rapidly growing SV is shown to exhibit quite linear behavior in the nonlinear model as it grows from 0.5 to 12 hPa in 1 day. For 5 times this amplitude the structure is similar but the growth is about half as the perturbation damps a potential vorticity (PV) trough or produces a cutoff, depending on its sign.

Toward a combined seasonal weather and crop productivity forecasting system: Determination of the working spatial scale

A methodology is presented for the development of a combined seasonal weather and crop productivity forecasting system. The first stage of the methodology is the determination of the spatial scale(s) on which the system could operate; this determination has been made for the case of groundnut production in India. Rainfall is a dominant climatic determinant of groundnut yield in India. The relationship between yield and rainfall has been explored using data from 1966 to 1995. On the all-India scale, seasonal rainfall explains 52% of the variance in yield. On the subdivisional scale, correlations vary between variance r(2) = 0.62 (significance level p < 10(-4)) and a negative correlation with r(2) = 0.1 (p = 0.13). The spatial structure of the relationship between rainfall and groundnut yield has been explored using empirical orthogonal function (EOF) analysis. A coherent, large-scale pattern emerges for both rainfall and yield. On the subdivisional scale (similar to 300 km), the first principal component (PC) of rainfall is correlated well with the first PC of yield (r(2) = 0.53, p < 10(-4)), demonstrating that the large-scale patterns picked out by the EOFs are related. The physical significance of this result is demonstrated. Use of larger averaging areas for the EOF analysis resulted in lower and (over time) less robust correlations. Because of this loss of detail when using larger spatial scales, the subdivisional scale is suggested as an upper limit on the spatial scale for the proposed forecasting system. Further, district-level EOFs of the yield data demonstrate the validity of upscaling these data to the subdivisional scale. Similar patterns have been produced using data on both of these scales, and the first PCs are very highly correlated (r(2) = 0.96). Hence, a working spatial scale has been identified, typical of that used in seasonal weather forecasting, that can form the basis of crop modeling work for the case of groundnut production in India. Last, the change in correlation between yield and seasonal rainfall during the study period has been examined using seasonal totals and monthly EOFs. A further link between yield and subseasonal variability is demonstrated via analysis of dynamical data.