Investigation of factors driving the costs of operating the 2020 Irish power system with large-scale wind generation

The main goal of this work is to determine the true cost incurred by the Republic of Ireland and Northern Ireland in order to meet their EU renewable electricity targets. The primary all-island of Ireland policy goal is that 40% of electricity will come from renewable sources in 2020. From this it is expected that wind generation on the Irish electricity system will be in the region of 32-37% of total generation. This leads to issues resulting from wind energy being a non-synchronous, unpredictable and variable source of energy use on a scale never seen before for a single synchronous system. If changes are not made to traditional operational practices, the efficient running of the electricity system will be directly affected by these issues in the coming years. Using models of the electricity system for the all-island grid of Ireland, the effects of high wind energy penetration expected to be present in 2020 are examined. These models were developed using a unit commitment, economic dispatch tool called PLEXOS which allows for a detailed representation of the electricity system to be achieved down to individual generator level. These models replicate the true running of the electricity system through use of day-ahead scheduling and semi-relaxed use of these schedules that reflects the Transmission System Operator's of real time decision making on dispatch. In addition, it carefully considers other non-wind priority dispatch generation technologies that have an effect on the overall system. In the models developed, three main issues associated with wind energy integration were selected to be examined in detail to determine the sensitivity of assumptions presented in other studies. These three issues include wind energy's non-synchronous nature, its variability and spatial correlation, and its unpredictability. This leads to an examination of the effects in three areas: the need for system operation constraints required for system security; different onshore to offshore ratios of installed wind energy; and the degrees of accuracy in wind energy forecasting. Each of these areas directly impact the way in which the electricity system is run as they address each of the three issues associated with wind energy stated above, respectively. It is shown that assumptions in these three areas have a large effect on the results in terms of total generation costs, wind curtailment and generator technology type dispatch. In particular accounting for these issues has resulted in wind curtailment being predicted in much larger quantities than had been previously reported. This would have a large effect on wind energy companies because it is already a very low profit margin industry. Results from this work have shown that the relaxation of system operation constraints is crucial to the economic running of the electricity system with large improvements shown in the reduction of wind curtailment and system generation costs. There are clear benefits in having a proportion of the wind installed offshore in Ireland which would help to reduce variability of wind energy generation on the system and therefore reduce wind curtailment. With envisaged future improvements in day-ahead wind forecasting from 8% to 4% mean absolute error, there are potential reductions in wind curtailment system costs and open cycle gas turbine usage. This work illustrates the consequences of assumptions in the areas of system operation constraints, onshore/offshore installed wind capacities and accuracy in wind forecasting to better inform the true costs associated with running Ireland's changing electricity system as it continues to decarbonise into the near future. This work also proposes to illustrate, through the use of Ireland as a case study, the effects that will become ever more prevalent in other synchronous systems as they pursue a path of increasing renewable energy generation.

Electron beam lithography assisted high-resolution pattern generation

This thesis details the top-down fabrication of nanostructures on Si and Ge substrates by electron beam lithography (EBL). Various polymeric resist materials were used to create nanopatterns by EBL and Chapter 1 discusses the development characteristics of these resists. Chapter 3 describes the processing parameters, resolution and topographical and structural changes of a new EBL resist known as ‘SML’. A comparison between SML and the standard resists PMMA and ZEP520A was undertaken to determine the suitability of SML as an EBL resist. It was established that SML is capable of high-resolution patterning and showed good pattern transfer capabilities. Germanium is a desirable material for use in microelectronic applications due to a number of superior qualities over silicon. EBL patterning of Ge with high-resolution hydrogen silsesquioxane (HSQ) resist is however difficult due to the presence of native surface oxides. Thus, to combat this problem a new technique for passivating Ge surfaces prior to EBL processes is detailed in Chapter 4. The surface passivation was carried out using simple acids like citric acid and acetic acid. The acids were gentle on the surface and enabled the formation of high-resolution arrays of Ge nanowires using HSQ resist. Chapter 5 details the directed self-assembly (DSA) of block copolymers (BCPs) on EBL patterned Si and, for the very first time, Ge surfaces. DSA of BCPs on template substrates is a promising technology for high volume and cost effective nanofabrication. The BCP employed for this study was poly (styrene-b-ethylene oxide) and the substrates were pre-defined by HSQ templates produced by EBL. The DSA technique resulted into pattern rectification (ordering in BCP) and in pattern multiplication within smaller areas.

The application of next generation sequencing to profile microbe related cheese quality defects

High throughput next generation sequencing, together with advanced molecular methods, has considerably enhanced the field of food microbiology. By overcoming biases associated with culture dependant approaches, it has become possible to achieve novel insights into the nature of food-borne microbial communities. In this thesis, several different sequencing-based approaches were applied with a view to better understanding microbe associated quality defects in cheese. Initially, a literature review provides an overview of microbe-associated cheese quality defects as well as molecular methods for profiling complex microbial communities. Following this, 16S rRNA sequencing revealed temporal and spatial differences in microbial composition due to the time during the production day that specific commercial cheeses were manufactured. A novel Ion PGM sequencing approach, focusing on decarboxylase genes rather than 16S rRNA genes, was then successfully employed to profile the biogenic amine producing cohort of a series of artisanal cheeses. Investigations into the phenomenon of cheese pinking formed the basis of a joint 16S rRNA and whole genome shotgun sequencing approach, leading to the identification of Thermus species and, more specifically, the pathway involved in production of lycopene, a red coloured carotenoid. Finally, using a more traditional approach, the effect of addition of a facultatively heterofermentative Lactobacillus (Lactobacillus casei) to a Swiss-type cheese, in which starter activity was compromised, was investigated from the perspective of its ability to promote gas defects and irregular eye formation. X-ray computed tomography was used to visualise, using a non-destructive method, the consequences of the undesirable gas formation that resulted. Ultimately this thesis has demonstrated that the application of molecular techniques, such as next generation sequencing, can provide a detailed insight into defect-causing microbial populations present and thereby may underpin approaches to optimise the quality and consistency of a wide variety of cheeses.

Adding Run-Time Monitoring to UML-RT by Modifying the Papyrus-RT Code Generator

In Model-Driven Engineering (MDE), the developer creates a model using a language such as Unified Modeling Language (UML) or UML for Real-Time (UML-RT) and uses tools such as Papyrus or Papyrus-RT that generate code for them based on the model they create. Tracing allows developers to get insights such as which events occur and timing information into their own application as it runs. We try to add monitoring capabilities using Linux Trace Toolkit: next generation (LTTng) to models created in UML-RT using Papyrus-RT. The implementation requires changing the code generator to add tracing statements for the events that the user wants to monitor to the generated code. We also change the makefile to automate the build process and we create an Extensible Markup Language (XML) file that allows developers to view their traces visually using Trace Compass, an Eclipse-based trace viewing tool. Finally, we validate our results using three models we create and trace.

Next generation e-learning platform: virtual laboratory simulations

Bioscience subjects require a significant amount of training in laboratory techniques to produce highly skilled science graduates. Many techniques which are currently used in diagnostic, research and industrial laboratories require expensive equipment for single users; examples of which include next generation sequencing, quantitative PCR, mass spectrometry and other analytical techniques. The cost of the machines, reagents and limited access frequently preclude undergraduate students from using such cutting edge techniques. In addition to cost and availability, the time taken for analytical runs on equipment such as High Performance Liquid Chromatography (HPLC) does not necessarily fit with the limitations of timetabling. Understanding the theory underlying these techniques without the accompanying practical classes can be unexciting for students. One alternative from wet laboratory provision is to use virtual simulations of such practical which enable students to see the machines and interact with them to generate data. The Faculty of Science and Technology at the University of Westminster has provided all second and third year undergraduate students with iPads so that these students all have access to a mobile device to assist with learning. We have purchased licences from Labster to access a range of virtual laboratory simulations. These virtual laboratories are fully equipped and require student responses to multiple answer questions in order to progress through the experiment. In a pilot study to look at the feasibility of the Labster virtual laboratory simulations with the iPad devices; second year Biological Science students (n=36) worked through the Labster HPLC simulation on iPads. The virtual HPLC simulation enabled students to optimise the conditions for the separation of drugs. Answers to Multiple choice questions were necessary to progress through the simulation, these focussed on the underlying principles of the HPLC technique. Following the virtual laboratory simulation students went to a real HPLC in the analytical suite in order to separate of asprin, caffeine and paracetamol. In a survey 100% of students (n=36) in this cohort agreed that the Labster virtual simulation had helped them to understand HPLC. In free text responses one student commented that "The terminology is very clear and I enjoyed using Labster very much”. One member of staff commented that “there was a very good knowledge interaction with the virtual practical”.

Near-real-time service provision during effusive crises at Etna and Stromboli: basis and implementation of satellite-based IR operations

Using the NEODAAS-Dundee AVHRR receiving station (Scotland), NEODAAS-Plymouth can provide calibrated brightness temperature data to end users or interim users in near-real time. Between 2000 and 2009 these data were used to undertake volcano hot spot detection, reporting and time-average discharge rate dissemination during effusive crises at Mount Etna and Stromboli (Italy). Data were passed via FTP, within an hour of image generation, to the hot spot detection system maintained at Hawaii Institute of Geophysics and Planetology (HIGP, University of Hawaii at Manoa, Honolulu, USA). Final product generation and quality control were completed manually at HIGP once a day, so as to provide information to onsite monitoring agencies for their incorporation into daily reporting duties to Italian Civil Protection. We here describe the processing and dissemination chain, which was designed so as to provide timely, useable, quality-controlled and relevant information for ‘one voice’ reporting by the responsible monitoring agencies.

Near-real-time service provision during effusive crises at Etna and Stromboli: basis and implementation of satellite-based IR operations

Using the NEODAAS-Dundee AVHRR receiving station (Scotland), NEODAAS-Plymouth can provide calibrated brightness temperature data to end users or interim users in near-real time. Between 2000 and 2009 these data were used to undertake volcano hot spot detection, reporting and time-average discharge rate dissemination during effusive crises at Mount Etna and Stromboli (Italy). Data were passed via FTP, within an hour of image generation, to the hot spot detection system maintained at Hawaii Institute of Geophysics and Planetology (HIGP, University of Hawaii at Manoa, Honolulu, USA). Final product generation and quality control were completed manually at HIGP once a day, so as to provide information to onsite monitoring agencies for their incorporation into daily reporting duties to Italian Civil Protection. We here describe the processing and dissemination chain, which was designed so as to provide timely, useable, quality-controlled and relevant information for ‘one voice’ reporting by the responsible monitoring agencies.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.

Statistical Analysis of Wind Power Generation in Europe

Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.

Optimization models and methods for real-time transportation planning in forestry

Lors du transport du bois de la forêt vers les usines, de nombreux événements imprévus peuvent se produire, événements qui perturbent les trajets prévus (par exemple, en raison des conditions météo, des feux de forêt, de la présence de nouveaux chargements, etc.). Lorsque de tels événements ne sont connus que durant un trajet, le camion qui accomplit ce trajet doit être détourné vers un chemin alternatif. En l’absence d’informations sur un tel chemin, le chauffeur du camion est susceptible de choisir un chemin alternatif inutilement long ou pire, qui est lui-même "fermé" suite à un événement imprévu. Il est donc essentiel de fournir aux chauffeurs des informations en temps réel, en particulier des suggestions de chemins alternatifs lorsqu’une route prévue s’avère impraticable. Les possibilités de recours en cas d’imprévus dépendent des caractéristiques de la chaîne logistique étudiée comme la présence de camions auto-chargeurs et la politique de gestion du transport. Nous présentons trois articles traitant de contextes d’application différents ainsi que des modèles et des méthodes de résolution adaptés à chacun des contextes. Dans le premier article, les chauffeurs de camion disposent de l’ensemble du plan hebdomadaire de la semaine en cours. Dans ce contexte, tous les efforts doivent être faits pour minimiser les changements apportés au plan initial. Bien que la flotte de camions soit homogène, il y a un ordre de priorité des chauffeurs. Les plus prioritaires obtiennent les volumes de travail les plus importants. Minimiser les changements dans leurs plans est également une priorité. Étant donné que les conséquences des événements imprévus sur le plan de transport sont essentiellement des annulations et/ou des retards de certains voyages, l’approche proposée traite d’abord l’annulation et le retard d’un seul voyage, puis elle est généralisée pour traiter des événements plus complexes. Dans cette ap- proche, nous essayons de re-planifier les voyages impactés durant la même semaine de telle sorte qu’une chargeuse soit libre au moment de l’arrivée du camion à la fois au site forestier et à l’usine. De cette façon, les voyages des autres camions ne seront pas mo- difiés. Cette approche fournit aux répartiteurs des plans alternatifs en quelques secondes. De meilleures solutions pourraient être obtenues si le répartiteur était autorisé à apporter plus de modifications au plan initial. Dans le second article, nous considérons un contexte où un seul voyage à la fois est communiqué aux chauffeurs. Le répartiteur attend jusqu’à ce que le chauffeur termine son voyage avant de lui révéler le prochain voyage. Ce contexte est plus souple et offre plus de possibilités de recours en cas d’imprévus. En plus, le problème hebdomadaire peut être divisé en des problèmes quotidiens, puisque la demande est quotidienne et les usines sont ouvertes pendant des périodes limitées durant la journée. Nous utilisons un modèle de programmation mathématique basé sur un réseau espace-temps pour réagir aux perturbations. Bien que ces dernières puissent avoir des effets différents sur le plan de transport initial, une caractéristique clé du modèle proposé est qu’il reste valable pour traiter tous les imprévus, quelle que soit leur nature. En effet, l’impact de ces événements est capturé dans le réseau espace-temps et dans les paramètres d’entrée plutôt que dans le modèle lui-même. Le modèle est résolu pour la journée en cours chaque fois qu’un événement imprévu est révélé. Dans le dernier article, la flotte de camions est hétérogène, comprenant des camions avec des chargeuses à bord. La configuration des routes de ces camions est différente de celle des camions réguliers, car ils ne doivent pas être synchronisés avec les chargeuses. Nous utilisons un modèle mathématique où les colonnes peuvent être facilement et naturellement interprétées comme des itinéraires de camions. Nous résolvons ce modèle en utilisant la génération de colonnes. Dans un premier temps, nous relaxons l’intégralité des variables de décision et nous considérons seulement un sous-ensemble des itinéraires réalisables. Les itinéraires avec un potentiel d’amélioration de la solution courante sont ajoutés au modèle de manière itérative. Un réseau espace-temps est utilisé à la fois pour représenter les impacts des événements imprévus et pour générer ces itinéraires. La solution obtenue est généralement fractionnaire et un algorithme de branch-and-price est utilisé pour trouver des solutions entières. Plusieurs scénarios de perturbation ont été développés pour tester l’approche proposée sur des études de cas provenant de l’industrie forestière canadienne et les résultats numériques sont présentés pour les trois contextes.

Investigating Social Mobility: Cultural Frames and Cultural Frame Switching in First-Generation College Students

Thesis (Ph.D.)--University of Washington, 2016-08

Saccharomycotin transcriptomics by next-generation sequencing

The non-standard decoding of the CUG codon in Candida cylindracea raises a number of questions about the evolutionary process of this organism and other species Candida clade for which the codon is ambiguous. In order to find some answers we studied the transcriptome of C. cylindracea, comparing its behavior with that of Saccharomyces cerevisiae (standard decoder) and Candida albicans (ambiguous decoder). The transcriptome characterization was performed using RNA-seq. This approach has several advantages over microarrays and its application is booming. TopHat and Cufflinks were the software used to build the protocol that allowed for gene quantification. About 95% of the reads were mapped on the genome. 3693 genes were analyzed, of which 1338 had a non-standard start codon (TTG/CTG) and the percentage of expressed genes was 99.4%. Most genes have intermediate levels of expression, some have little or no expression and a minority is highly expressed. The distribution profile of the CUG between the three species is different, but it can be significantly associated to gene expression levels: genes with fewer CUGs are the most highly expressed. However, CUG content is not related to the conservation level: more and less conserved genes have, on average, an equal number of CUGs. The most conserved genes are the most expressed. The lipase genes corroborate the results obtained for most genes of C. cylindracea since they are very rich in CUGs and nothing conserved. The reduced amount of CUG codons that was observed in highly expressed genes may be due, possibly, to an insufficient number of tRNA genes to cope with more CUGs without compromising translational efficiency. From the enrichment analysis, it was confirmed that the most conserved genes are associated with basic functions such as translation, pathogenesis and metabolism. From this set, genes with more or less CUGs seem to have different functions. The key issues on the evolutionary phenomenon remain unclear. However, the results are consistent with previous observations and shows a variety of conclusions that in future analyzes should be taken into consideration, since it was the first time that such a study was conducted.

Generation and Characterisation of a Canine EGFP-HMGA2 Prostate Cancer In Vitro Model

The architectural transcription factor HMGA2 is abundantly expressed during embryonic development. In several malignant neoplasias including prostate cancer, high re-expression of HMGA2 is correlated with malignancy and poor prognosis. The let-7 miRNA family is described to regulate HMGA2 negatively. The balance of let-7 and HMGA2 is discussed to play a major role in tumour aetiology. To further analyse the role of HMGA2 in prostate cancer a stable and highly reproducible in vitro model system is precondition. Herein we established a canine CT1258-EGFP-HMGA2 prostate cancer cell line stably overexpressing HMGA2 linked to EGFP and in addition the reference cell line CT1258-EGFP expressing solely EGFP to exclude EGFP-induced effects. Both recombinant cell lines were characterised by fluorescence microscopy, flow cytometry and immunocytochemistry. The proliferative effect of ectopically overexpressed HMGA2 was determined via BrdU assays. Comparative karyotyping of the derived and the initial CT1258 cell lines was performed to analyse chromosome consistency. The impact of the ectopic HMGA2 expression on its regulator let-7a was analysed by quantitative real-time PCR. Fluorescence microscopy and immunocytochemistry detected successful expression of the EGFP-HMGA2 fusion protein exclusively accumulating in the nucleus. Gene expression analyses confirmed HMGA2 overexpression in CT1258-EGFP-HMGA2 in comparison to CT1258-EGFP and native cells. Significantly higher let-7a expression levels were found in CT1258-EGFP-HMGA2 and CT1258-EGFP. The BrdU assays detected an increased proliferation of CT1258-HMGA2-EGFP cells compared to CT1258-EGFP and native CT1258. The cytogenetic analyses of CT1258-EGFP and CT1258-EGFP-HMGA2 resulted in a comparable hyperdiploid karyotype as described for native CT1258 cells. To further investigate the impact of recombinant overexpressed HMGA2 on CT1258 cells, other selected targets described to underlie HMGA2 regulation were screened in addition. The new fluorescent CT1258-EGFP-HMGA2 cell line is a stable tool enabling in vitro and in vivo analyses of the HMGA2-mediated effects on cells and the development and pathogenesis of prostate cancer.

Natural Language Generation enhances human decision-making with uncertain information.

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different informa- tion presentations for uncertain data and, for the first time, measure their effects on human decision-making. We show that the use of Natural Language Genera- tion (NLG) improves decision-making un- der uncertainty, compared to state-of-the- art graphical-based representation meth- ods. In a task-based study with 442 adults, we found that presentations using NLG lead to 24% better decision-making on av- erage than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better re- sults when presented with NLG output (an 87% increase on average compared to graphical presentations).