There are open issues within the uctuation theory owing to the approximations invoked in regimes outside fully ionized collisionless plasmas. This includes laboratory and space environments where e ects of Coulomb collisions or collisions with neutrals or dust particles cannot be ignored. Molecular Dynamics simulations have the potential to address such parameter regimes which are intractable by the analytical approach. The numerical method employed in this work for the calculation of the space-time correlation function of density uctuations is based on molecular dynamics in (r, v) space using an importance sampling Monte Carlo. The outcome of these MD simulation is then transformed into Fourier space to enable comparison with the analytical results of the uctuation theory. The comparison is carried out in the regime of thermal collisionless fully ionized plasmas, with no drifts and neutral component, in order to verify the numerical approach, choose appropriate simulation and FFT settings and to estimate error bars on the features of the electron spectral density of uctuations.

Several previous theses and reports have shown that voltage variations, and other types of supply changes, can influence the performance and movements of trains. As part of a modular software package for railway focused calculations, the need to take into account for the electrical behavior of the system was needed, to be used for both planning and operational uses. In this thesis, different static models are presented and used for train related power flow calculations. A previous model used for converter stations is also extended to handle different configurations of multiple converters. A special interest in the train type IORE, which is used for iron ore transports along Malmbanan, and the power systems influence to its performance, as available modules, for mechanical calculations, in the software uses the same train type. A part of this project was to examine changes in the power systems performance if the control of the train converters were changed, both during motoring and regenerative braking. A proposed node model, for the static parts of a railway power system, has been used to simplify the building of the power system model and implementation of the simulation environment. From the results it can be concluded that under normal conditions, for the used train schedule, the voltage variation should not restrict the trains traction performance. It can also be seen from the results that a more optimized power factor control with a higher regenerative brake power or generation of reactive power could be used to limit the need for investments in infrastructure or to increase the traffic for a given system layout. / I ett flertal tidigare undersökningar och rapporter har konstaterats att spänningsvariationer, och andra förändringar, hos strömförsörjningen till tåg kan påverka dess prestanda och dess färd längs rälsen. Som en del av ett modulärt programpaket för tågrelaterade beräkningar uppstod därför ett behov av elkraftsberäkningar, både för planering och operativ drift. I denna rapport sammanställs och används ett antal olika statiska modeller för tågrelaterade effektflödesberäkningar. Modellen för omformarstationer har även utökats för att hantera konfigurationer då olika typer av omformare används. Ett särskilt intresse för tågtypen IORE, som används för malmtransporter längs Malmbanan, och dess påverkan av en förändrad strömförsörjning, har funnits då olika typer av mekaniska beräkningar för denna tågtyp utförs i andra befintliga moduler. En del av projektet bestod i att undersöka förändringar i elförsörjningen, på grund av en ändrad styrning av tågens omformare, både vid återmatning och motordrift. En föreslagen nodmodell för den statiska delen av elnätet har använts för att förenkla elsystemsmodellen och uppbyggnaden av simuleringsmiljön. Av resultaten från simuleringarna kan man anta att under normala förhållanden, och med det använda körschemat, bör ej spänningen vara en begränsande faktor för tågens drift. Övriga simuleringar visar också att en mer optimerad effektfaktor för högre återmatad bromseffekt eller för generering av reaktiv effekt kan användas för att slippa investeringar i infrastrukturen, eller för att utöka trafikmängden för ett givet system.

Load shedding events are a major concern today for the Senegalese power grid, which production, transport, distribution and selling are operated by the national power company SENELEC. Even if some improvements have been made these last years through important power plant renovation campaigns, unserved energy still represented 1.5% of the total power demand in 2013. These events are mainly due to two factors: grid failure or work on the one hand (65% of unserved energy in 2013) and production lack or failure on the other hand (35% of unserved energy in 2013). If grid failure problems are being tackled by some rehabilitations and extension of the network, production lack problems will only be solved on the long term by setting up new power plants to face the increasing power demand. In order to face these power shortages, many customers have installed their own generation sources, mostly diesel generators used in case of emergency, but also more recently photovoltaic panels to both ensure power supply reliability thanks to storing batteries and reduce their electricity bills. These installations represent an important power production still unexploited today by SENELEC. The goal of this Master Thesis was then to see the potential use that could be made of these generation sources to reduce unserved energy in the short term. Diesel generators could thus be used for voluntary load shedding if properly implemented and photovoltaic installations could be connected to the grid to inject their production surplus. These two solutions were studied both from a technical and economical point of view, and their potential impact on unserved energy reduction was quantified. The results show that voluntary load shedding could actually reduce the amount of unserved energy due to production lack or failure by 40% to 80%, and that it is economically viable compared with other solutions such as production capacity renting. They also show that it is possible to connect domestic-scale photovoltaic installations to the low voltage grid without any negative impact on its operation in most of the situations met today. Finally, some recommendations were made, including proposals for voluntary load shedding implementation and the setting up of a dedicated team at Senelec for photovoltaic integration studies.

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When a fault is detected in the engine, the check engine light will come on. After that, it is often up to the mechanic to diagnose the engine fault. Manual fault classification by a mechanic can be time-consuming and expensive. Recent technological advancements have granted us immense computing power, which can be utilized to diagnose faults using data-driven classifiers. Data-driven classifiers generally require a lot of training data to be able to accurately diagnose system faults by comparing sensor data to training data because labeled training data is required for a wide variety of different realizations of the same faults. In this study an algorithm is proposed that does not rely on labeled training data, instead the proposed algorithm clusters similar fault data together by combining an engine model and unsupervised learning in the form of a modified Gaussian mixture model using Expectation Maximization. If one or more of the fault scenarios in a cluster is later diagnosed, the rest of the data in the same cluster is likely to have the same diagnosis. The modified Gaussian mixture model proposed in this study takes into account that residual data, in some cases including the case in this study when the data is from an internal combustion engine, seem to diverge from the nominal case (data points near the origin) along a linear trajectory as the fault size increases. This is taken into account by modeling the clusters as Gaussian distributions around fault vectors that each represent the trajectories the data moves along as the fault size increases for each cluster or fault mode. The algorithm also takes into account that data from one scenario are likely to belong to the same fault class i.e. it is not necessary to classify each data point separately, instead the data can be clustered as batches. This study also evaluates the proposed model as a semi-supervised learner, where some data is known. In this case, the algorithm can also be used to estimate the fault sizes of unknown faults by using the acquired fault vectors, given that there are known fault sizes for other data in the same cluster. The algorithm is evaluated with data collected from an engine test bench using a commercial Volvo engine and shows promising results as most fault scenarios can be correctly clustered. However, results show that there are clustering ambiguities for data from small faults, as they are more similar to the nominal case and overlap more with data from other fault modes.

Electronics engineers rely on component tolerances to create functional designs. It isimportant to be aware that each component brings some uncertainty to the functionality ofthe assembly and therefore to the performance. To deal with this problem there are differentapproaches within the tolerance analysis field. Currently Veoneer uses the Worst CaseCircuit Analysis methodology that assumes that the worst scenario for every componentis possible, achieving very safe but pessimistic results. Electronics design can therefore beoptimized through statistical analysis.This work focuses on modelling the variance in the performance of a set of electroniccomponents that compose a device or assembly by means of statistical techniques. It usesdifferent methodologies to find models to explain the behaviour of these assemblies andit tests its results through different statistical tests to decide which one performs the best.From this point the work is focused upon finding the tolerance limits that are optimalfor the design while fulfilling safety requirements imposed by the automotive regulatorybody. The result obtained substantially improves the previousWorst Case Circuit Analysismodel while being as safe as required. This is a methodology that does not require of hugeamounts of data; making the process affordable for industry. Finally, it can be concludedthat statistical tolerance analysis can improve substantially the current results and boost thedesign of safety elements in electronics in the automotive industry while being as reliableas always.

In recent years, with the introduction of renewable energy sources (RES) and digital technologies, grids in Europe have become smarter.This is motivated by the need to effectively use the infrastructure incases of high penetration of RES. Consumer participation is one of the important features of smart grids. This customer participation can be individually controlled or collectively controlled by an aggregator. This thesis simulates a neighbourhood where each house is equipped with a photovoltaic (PV) system and a battery storage system such that each house is a net-zero energy building (NZEB). A comparison is made between the cost savings for the households when the battery is individually controlled and when an aggregator controls all batteries. The battery scheduling is optimized using genetic algorithm(GA). The results show higher savings in the case of aggregator control: the self-consumption (SC) increased with 4 percentage points, and the total energy costs for the whole neighbourhood was reduced by more than 40%. This thesis prepares the training data needed to implement the energy management system (EMS) using recurrent neuralnetworks (RNNs).

In this study, the usage of charging posts at S:t Eriks torg in Uppsala was investigated with a goal of reducing the energy consumption and thereby decrease electricity costs for UPAB, but also to alleviate the grid because of Uppsala grid’s capacity shortage. Using energy consumption data from the parking lot, we processed the information, analyzed the data, and identified trends and patterns to gather a basis for problem solving. The results showed that the highest peaks occur on Sundays but that the average consumption for a Sunday is only 10% above the average for all weekdays. To reach our goal, three ideas were devised. One solution to reach the goal could be to bill the consumer per kWh during working hours to generate revenue, another was to install solar panels which would both save money and alleviate the grid, and lastly to use a battery and implement some form of peak shaving. Billing per kWh proved both cost efficient and easy to implement, whereas solar panels are more expensive initially but alleviates the grid more. Batteries were found to be a non-viable solution. Our conclusion was that for S:t Eriks torg, which is a small parking lot, billing per kWh would be the best solution and solar panels would be disproportionally expensive in relation to the yearly costs for the parking lot. However, solar panels should be considered for larger parking lots where the toll on the grid is more noticeable, therefore saving money while also alleviating the grid.

ABB Hitachi currently has 10-20 year old software’s in use during their lab testing and a lack of in-depth knowledge of how the source code works due to corporate mergers and retiring staff. The programs were outdated and the expertise of how the software’s backend works were no longer available at Hitachi ABB. The project's aim is to determine some key features and give more in depth knowledge into how the existing software’s works and document this. The project is performed by students at the bachelors-masters program in electrical engineering at Uppsala University, and the work was performed remotely.

The aim of this study is to find out what factors generate intrinsic and extrinsic motivations in video games. A stimulated recall method is used to conduct a study, where nine participants played The Legend of Zelda: Breath of the Wild (Nintendo, 2017) for 20 minutes before participating in an interview about their game session. The interviews are later transcribed and analyzed using thematic analysis. The conclusions drawn from this study are that game systems and intrinsic integration have aspects which generate both intrinsic and extrinsic motivation, while behavioural components such as the Immersion, Achievement, and Social components, can influence which of those aspects players will be drawn to. This has implications for research into education, where several discovered factors of creating motivation (game systems and intrinsic integration) can be used into creating more motivation for students to play education games. / Målet med denna studie är att ta reda på vilka faktorer skapar inre och yttre motivation i spel. En stimulerat återsamling (översatt från stimulated recall) metod används för studien där nio deltagare spelar spelet The Legend of Zelda: Breath of the Wild (Nintendo, 2017) i 20 minuter och deltar sen i en intervju som handlar om deras spel session. Intervjuerna är senare transkriberade och analyserade med hjälp av tematisk analys. Studiens slutsatser är att spelsystem och inre integration (översatt från intrinsic integration) innefattar aspekter som skapar både inre och yttre motivation, medan olika beteende komponenterna Nedsänkning (översatt från immersion), Prestation (översatt från achievement) och Social komponenter, påverkar vilka av de aspekter som spelare dras till. Detta har implikationer för forskning inom utbildning eftersom flera upptäckta faktorer för att skapa motivation (spelsystem och inre integration) kan användas för att skapa motivation för elever att spela utbildningsspel.