High frequency modeling of power transformers: Stresses and Diagnostics

In this thesis a reliable, versatile and rigorous method for high frequency power transformer modeling is searched and established. The purpose is to apply this model to sensitivity analysis of FRA (Frequency Response Analysis) which is a quite new diagnostic method for assessing the mechanical integrity of power transformer windings on-site. The method should be versatile in terms of being able to estimate internal and external overvoltages and resonances. Another important aspect is that the method chosen is suitable for real transformer geometries. In order to verify the suitability of the model for real transformers, a specific test-object is used. This is a 20MVA transformer, and details are given in chapter 1.4. The high frequency power transformer model is established from geometrical and constructional information from the manufacturer, together with available material characteristics. All circuit parameters in the lumped circuit representation is calculated based on these data. No empirical modifications need to be performed. Comparison shows capability of reasonable accuracy in the range from 10 kHz to 1 MHz utilizing a disc-to-disc representation. A compromise between accuracy of model due to discretisation and complexity of the model in a turn-to-turn representation is inevitable. The importance of the iron core is emphasized through a comparison of representations with/without the core included. Frequency-dependent phenomena are accurately represented using an isotropic equivalent for windings and core, even with a coarse mesh for the FEM-model. This is achieved through a frequency-dependent complex permeability representation of the materials. This permeability is deduced from an analytical solution of the frequency-dependent magnetic field inside the conductors and the core. The importance of dielectric losses in a transformer model is also assessed. Since published data on the high frequency properties of pressboard are limited, some initial measurements are done on impregnated pressboard at different temperatures and moisture-levels. Tanδ is found to be twice the corresponding value for impregnated paper at frequencies from 50 kHz to 1MHz. Moisture has a minor effect on the losses when frequency approaches 1MHz. Service-aged paper (impregnated) is also tested in order to investigate other ageing-effects than produced water, but the test show the same decreasing influence at higher frequencies as impregnated pressboard with moisture added. The following main conclusions were drawn from this work: • A simple, analytical approach cannot be used to build a versatile high frequency power transformer model. The reason being mainly the lack of a proper representation of the iron core, since a FEM-representation without the core did not increase coherence to measurements significantly. • A proper representation of the iron core is very important for the calculation of inductances. Losses mainly originate from the core at intermediate frequencies (10-200 kHz), and not only from eddy currents in the windings as traditionally assumed. The permeability seem to be of less importance as long as it is well above permeability for oil, since the internal resonances mainly depends on the leakage inductances. The core leg equivalent is important for the leakage field and determines the leakage inductances and winding losses. • Using a frequency-dependent complex permeability in a FEM-simulation makes possible an accurate representation of core and windings using a coarse mesh. If coating resistivity is sufficiently low to create interlaminar currents/ losses, the iron laminates should be represented by a 2-dimensional complex permeability. Coating parameters are seldom available. • Dielectric properties of power transformer insulating materials depend on frequency, temperature, moisture, ageing and pressure. Temperature has minor influence on FRA-signatures, other parameters have practically no influence. • Impulse- and resonant overvoltages both internally and on terminals can be analysed using this method with sufficient accuracy, provided the discretisation of the winding is sufficiently refined regarding the frequencies involved. Since terminal behaviour is given by the internal geometry and material parameters, it is assumed that internal behaviour is related to the accuracy of the terminal behaviour. • FRA sensitivity to axial displacement is 1.2% of total axial height. The sensitivity to radial deformation (forced buckling) is found to be a buckling depth of 9% of the radius of the winding. Turn-to-turn short-circuits could not be modeled correctly since the lumped elements includes several turns. Disc-todisc short circuits are easily detected. Axial bending is not detectable. Detection of loose windings and aged insulation is improbable and will be dependent on the available sensitivity (mainly related to the repeatability of the measurements and the reference utilized for comparison). The contributions in this work relates to different topics such as; Frequency-dependent iron core representation in FEM, study of interlaminar currents and its effect on the internal magnetic field, characterization of high frequency dielectric properties of impregnated pressboard and service-aged impregnated paper, procedure for evaluation of internal/external overvoltages, and finally sensitivity guidelines for the application of FRA to mechanical deformations.dr.ing.dr.ing

Development of an XAI-Based Residential Load Forecasting Model

Den stadig økende kompleksiteten i kraftsystemet har introdusert et større behov for prognoser for å holde nettet stabilt. Lastprognoser har vært en avgjørende del av planlegging og vedlikehold gjort av kraftsystemoperatører, på både kort og lang sikt. På grunn av manglende teknologi har lastprognoser i hovedsak blitt brukt på regionalt nivå. Imidlertid har revolusjonen innen sensorteknologi og databehandling for maskinlæring også muliggjort utviklingen av lastprognoser for boliger. Dagens praksis innen maskinlæring består av black box modeller, som er svært kompliserte og gir lite innsikt og pålitelighet. Forklarbar kunstig intelligens har sett en økt i utvikling, slik at domeneeksperter og andre kan forstå valgene til modellen. Denne oppgaven tar sikte på å utvikle en lastprognose-modell for strømforbruk en time frem i tid, for et bolighus ved å bruke forklarbar kunstig intelligens. Flere LSTM- og CNN-LSTM-modeller ble foreslått basert på et teoretisk grunnlag. Under utviklingsfasen ble det forklarbare kunstige intelligensverktøyet Shapley additive explanations brukt til å undersøke og øke ytelsen ved funksjonsevaluering. I tillegg ble anomalier og feilvurderinger undersøkt i håp om å få innsikt i atferden og en større forståelse av modellen og dens omgivelser. Det ble funnet at bruken av forklarbar kunstig intelligens forbedret modellens ytelse betydelig og ga innsikt om hvilke funksjoner som skulle inkluderes og utelates. Overraskende nok presterte LSTM-modellene bedre enn CNN-LSTM hybridmodellene. Dessuten ble modellen ytterlige forbedret ved å inkludere regionale lastprognoser. Det ble og konkludert ved hjelp av forklarbar kunstig intelligens at de best ytende modellene var de med et færre antall innputvariabler. Forbedringene og økt innsikt gitt av forklarbar kunstig intelligens funnet i denne oppgaven antyder at det er et potensial for forklarbar kunstig intelligens til å være en grunnleggende vei mot pålitelig kunstig intelligens. For å nå sitt potensiale vil det være nødvendig med mer forskning innen temaet.The ever-increasing complexity in the power system has introduced a higher demand for forecasting to keep the grid stable. Load forecasting has been an integral part of planning and maintenance by power system operators for both short and long horizons. Due to lacking technology, load forecasting has mainly been applied at the regional level. However, the revolution in sensor technology and data processing for machine learning has also enabled the investigation of residential load forecasting. The current practice within machine learning consists of black box models, which are highly complicated, giving little insight and reliability. Explainable artificial intelligence aims to solve this by allowing domain experts and others to understand the choices of the model. This thesis aims to develop an hour-ahead load forecasting model for a residential home using explainable artificial intelligence. Multiple LSTM and CNN-LSTM models were proposed with a foundation in theory. During the development phase, the explainable artificial intelligence tool SHapley Additive exPlanations was used to investigate and increase performance by feature evaluation. Additionally, anomalies and outliers were examined in hopes of obtaining insight into the behavior and a greater understanding of the model environment. It was found that the use of explainable artificial intelligence significantly improved the model’s performance and gave an indication of which features to include and omit. Surprisingly, the LSTM model outperformed the CNN-LSTM hybrid models. Moreover, including regional load forecasting further enhanced the model. Finally, it was found that including too many features limited performance. The improvements and increased insights provided by explainable artificial intelligence found in this thesis suggest that there is a potential for explainable artificial intelligence to be a fundamental path toward trustworthy artificial intelligence. However, to reach its potential, more research is needed

Brand Reputation and Product Recall

Every year, firms make numerous announcements to recall products that are deemed unsafe or defective. These recalls pose a significant threat to a firm\u27s brand reputation. The strong, negative reactions of consumers and the media to the recalls initiated by Toyota in 2010 show how fragile brands are in the wake of a recall. Firms spend a great amount of resources on building strong brands and it is unclear how such brands influence the firm\u27s decision to announce a recall and the consumer\u27s decision to return the recalled product. The objective of this dissertation is to shed some light on these subjects through two essays. The first essay focuses on the role of brands on the firm\u27s recall timing decision whereas the second essay focuses on the role of brands on the consumer\u27s product return decision. The findings from both studies have important implications for managers and policy makers regarding the management of product recalls

Application of natural antioxidants and modified atmosphere packaging to prolong shelf life and enhance quality of fish products

Markedet for fersk havbruksfisk er økende ettersom fisk kan være en kilde for viktige næringsstoffer i den menneskelige dietten, som omega-3 fettsyrer. Bruken av ferske råvarer er derimot begrenset grunnet høy sensitivitet for mikrobiell og biokjemisk bedervelse. Tidligere studier viser at modifisert atmosfærepakning (MAP), antioksidanter og temperatur kontroll kan forlenge holdbarheten for fersk fisk. Målet med denne studien var å undersøke kombinasjonen av naturlige antioksidanter, MAP og temperaturkontroll for å forlenge holdbarheten for atlantisk laks. Studien ble gjennomført i to lagringsforsøk som varte i 16 dager hver. Det første forsøket kombinerte MAP (CO2:N2 60:40) og vakuumpakkede prøver med kjøling på 4°C og 0°C. Det andre lagringsforsøket kombinerte MAP (CO2:N2 60:40) ved 0°C med antioksidant behandling av rosmarinekstrakt (0,5% og 0,05% vekt/volum) og tokoferoler (0,5% og 0,05% vekt/volum) i etanol. Endringer i kvalitet under lagring ble analysert gjennom drypptap, mikrobiell vekst og målinger av primære og sekundære oksidasjon produkter i from av PV og TBARS. Vakuumpakkede prøver fra det første lagringsforsøket hadde høyre drypptap enn prøver lagret i MAP. Ingen signifikant forskjell i drypptap mellom prøver behandlet med antioksidanter sammenlignet med kontrollen ble funnet i det andre forsøket. Prøver lagret ved 4°C i det første lagringsforsøket hadde høyere mikrobiell vekst enn prøver lagret ved 0°C uavhengig av pakkemetode. Det var ingen signifikant forskjell i mikrobiell vekst mellom antioksidant behandlede prøver og kontroll i det andre lagringsforsøket. Det var en signifikant forskjell i PV mellom dag 1 og dag 16 for både det første og det andre lagringsforsøket, men ingen signifikant forskjell mellom behandling og/eller lagrings metoder for enten det første eller det andre lagringsforsøket ble funnet. Det var ingen signifikant forskjell mellom TBARS verdier mellom dag 1 og dag 16, eller mellom lagrings og/eller behandlingsmetode for noen av prøvene i det første eller det andre lagringsforsøket. Til oppsummering viste denne studien effekten av temperatur på mikrobiell vekst i atlantisk laks, og effekten av MAP for å bevare kvaliteten. Studien klarte ikke å oppdage noen effekt med antioksidant behandling på lipid oksidasjon, mikrobiell vekts eller drypptap.The marked for fresh aquaculture fish is increasing as fish can provide several important nutrients to the human diet including essential omega-3 fatty acids. The use of fresh produce is however limited due to high susceptibility of microbial and biochemical spoilage. Earlier studies show that modified atmosphere packaging (MAP), antioxidant addition and temperature control can prolong the shelf life of fresh fish. The aim of the current study was to investigate the combination of natural antioxidant, MAP and temperature control in order to prolong the shelf life of Atlantic salmon. The study was conducted in two storage experiments lasting 16 days each. The first storage experiment combined MAP (CO2:N2 60:40) and vacuum-packed samples with cold storage at 4°C and 0°C. The second combined MAP (CO2:N2 60:40) at 0°C with treatment of rosemary extract (0,5% and 0,05 w/v) and tocopherols (0,5% and 0,05% w/v) in ethanol. Quality changes during storage were analysed in terms of drip loss, microbial growth, and measurement of primary and secondary oxidation products by PV and TBARS. Vacuum packed samples form the first storage experiment had a higher drip loss than samples stored in MAP. No significant difference in drip loss between samples treated with antioxidants compared to the control in the second storage experiment was found. Samples stored at 4°C had a higher microbial growth than samples stored at 0°C regardless of packaging method in the first experiment. There was no significant difference in microbial growth between antioxidant treated samples and the control in the second storage experiment. There was a significant difference between PV values from day 1 and day 16 for both the first and second storage experiment, but no significant difference between treatment and/or storage was found in either. There were no significant differences in TBARS values between day 1 and day 16, or between storage and/or treatment between any samples from either the first or the second storage experiment. In conclusion, this study showed the effect of temperature in terms of microbial growth on Atlantic salmon, and the effect of MAP in retaining the quality. The study was unable to detect any effect of antioxidant treatment to lipid oxidation, microbial growth or drip loss

Restructuring through spinoffs : the effect on shareholder wealth

Masteroppgave(MSc) in Master of Science in Business, Finance - Handelshøyskolen BI, 2013This paper investigates the shareholder wealth created through spinoff restructuring at Oslo Stock Exchange, over the period 1991-2010. By using a proxy for the transaction announcement, I find no support for an abnormal return in this period except for small fraction spinoffs. However, significant positive abnormal returns over a period reaching from 231 trading days before the spinoff until the first day of separate trading for the divested firms, is documented for cross-industry transactions, small fraction transactions as well as my whole sample. The study also provides significant results of long-run post abnormal returns for the spun-off companies up until 756 trading days after the divestiture. Finally, I find the portfolios of respectively small fraction- as well as own-industry spinoffs, to perform significantly better than their counterparts of large fraction- and cross-industry spinoffs

History and Theory of Near-Infrared Spectroscopic Analysis (NIRS)

The use of near infrared spectroscopy (NIRS) as an analytical technique has evolved greatly since it was first demonstrated to be a viable method of obtaining molecular compositional information from the “scanning” of a sample. Potential applications of the technology envisioned by early pioneers in the field have been realized or exceeded time after time, and it has now become a very broadly applied means of instrumental analysis. It is worth recalling the historical progression of the technology and the fact that the earliest applications were developed to meet the challenges of agricultural product analysis. In particular, forage analysis is one of the areas where the advantages and possibilities made development of systems dedicated to overcoming the challenges well worth the effort, and helped usher in innovations that could be more widely used in other areas. Various attributes of the technology combine or individually lend themselves to development of systems that can be routinely used for rapid multiconsitiuent analysis, with either limited or no sample preparation. When developed to their ultimate potential, such systems can be utilized with littleto-no understanding of the underlying principles. In many cases a user can simply “scan” a sample using the NIRS “black box” and obtain results on a computer screen or in a printout in less time than it would take to write them down in a notebook. However, an understanding of how NIRS works, and the inherent theoretical capabilities and limitations of what it can do, will give the user a deeper appreciation for the technology and a basis for ensuring that it is operating properly and being optimally utilized

The Effect of Opponent on Player Experience: Solo Play vs. Human vs. Artificial Intelligence

Motstanderen er en viktig del når det kommer til å skape en morsom spillopplevelse; den utfordrer spilleren, hjelper dem med å forbedre sine evner og får dem til å overvinne hindringer. I video spill finnes det to hovedtyper motstandere, kunstig intelligens-kontrollerte og menneskelige. Begge disse gir unike opplevelser og har egenskaper som definerer hvordan de oppfattes sammenlignet med det å spille alene (solospill). Det vil alltid være utfordringer ved det å finne spill som passer en gitt spiller, ettersom det er mange faktorer som påvirker hvordan et spill oppleves. Med den raske fremveksten av kunstig intelligens i samfunnet vårt øker dens betydning også i spill, og er en del av mange trinn i spilldesignprosessen. Ettersom kunstig intelligens blir mer og mer naturtro, hvordan skiller spillerens opplevelse seg når de spiller mot menneskelige motstandere, kunstig intelligens-motstandere og solospill, og hvorfor har det betydning? I dette designprosjektet ble dette spørsmålet besvart ved å kartlegge hvordan hver av disse tre modusene påvirket spillopplevelsen, slik at mer informerte beslutninger kan tas. Når spilldesignere har muligheten til å få en bedre forståelse for hvordan spillene deres blir ansett, så kan designet deres gjøres enda mer spesifikt for å passe en målgruppe enda bedre. Det kan føre til en mer lojal fanskare og færre skuffelser for folk som ikke fikk den opplevelsen de hadde håpet på. Denne oppgaven argumenterer for at selv om spillererfaring har blitt utforsket utallige ganger før, er det fortsatt et behov for å få større kunnskap om motstanderens påvirkning. Til slutt kan det argumenteres for at det å designe for en spesifikk motstander vil være til fordel for spillere som er usikre på hva de skal spille eller ikke vet så mye om spill fra før.The opponent is a vital part of a fun gameplay experience; it challenges the player, helps improve their abilities and guides them to overcome obstacles. In gaming, there are two main types of opponents, Artificial intelligence-controlled advisories, and human opponents. Both offer unique experiences with characteristics defining how they are perceived compared to just playing alone (solo play). There are always challenges in finding a game that suits a given player, as many factors impact how a game is played. With the rapid rise of artificial intelligence in our society, its importance in gaming is ever-increasing, being part of every step of the game design process. As it becomes more and more lifelike, how does the player's experience in video games differ when engaging in gameplay against human opponents, artificial intelligence opponents, and solo play, and why does it matter? In this game design project, this question was answered by mapping how each of these three conditions impacted the player experience so that more informed decisions could be made. When game designers can get a better understanding of how their games are viewed by players, their design can be made even more specific to suit a target audience. It can lead to a more loyal fan base and fewer disappointments for people who the game did not resonate with. This thesis argues that even if player experience has been explored innumerable times before, there is still the need to gain greater knowledge about the opponent's effects. Finally, an argument can be made that designing for a specific opponent will benefit players who are unsure about what to play or do not know much about games

Defense Contractor Profit

This research seeks to achieve two objectives: 1) to provide a comprehensive survey of research related to defense contractor profitability, and 2) to conduct an updated analysis of such profitability. No previous comprehensive survey of the topic was found in the academic literature. Therefore, the provision of such a survey may significantly benefit future researchers. A paucity of recent defense contractor profit research related was identified; only one published study analyzed data after 2000 and none used data more recent than 2010. This research reconciles the gap in recent defense contractor profit studies via objective two. Panel data analysis is employed to examine the profitability of defense contractors between 2009 and 2018. The relationship between contractor influence in the defense marketplace and profits from defense business is explored as well as the relationship between contractor operating risk and defense business profits. Additionally, the relationship between defense contractor profitability and the percentage of total sales attributed to defense (versus commercial sales) is investigated. Neither contractor influence, nor risk was found to have a moderating effect on defense business profits. The empirical evidence did however indicate a positive relationship between contractor profitability and the percentage of total sales from defense business