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Lange, Matthias. "Analysis of the uncertainty of wind power predictions." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=969985789.
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SATO, Ken-ichi, Hiroshi HASEGAWA, and Hiroyuki ITO. "Router Power Reduction through Dynamic Performance Control Based on Traffic Predictions." 電子情報通信学会, 2012. https://search.ieice.org/.
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Werngren, Simon. "Comparison of different machine learning models for wind turbine power predictions." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-362332.
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The goal of this project is to compare different machine learning algorithms ability to predict wind power output 48 hours in advance from earlier power data and meteorological wind speed predictions. Three different models were tested, two autoregressive integrated moving average (ARIMA) models one with exogenous regressors one without and one simple LSTM neural net model. It was found that the ARIMA model with exogenous regressors was the most accurate while also beingrelatively easy to interpret and at 1h 45min 32s had a comparatively short training time. The LSTM was less accurate, harder to interpretand took 14h 3min 5s to train. However the LSTM only took 32.7s to create predictions once the model was trained compared to the 33min13.7s it took for the ARIMA model with exogenous regressors to deploy.Because of this fast deployment time the LSTM might be preferable in certain situations. The ARIMA model without exogenous regressors was significantly less accurate than the other two without significantly improving on the other ARIMA model in any way
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Kossmann, de Menezes Anna Carolina. "Improving predictions of operational energy performance through better estimates of small power consumption." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/13549.
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This Engineering Doctorate aims to understand the factors that generate variability in small power consumption in commercial office buildings in order to generate more representative, building specific estimates of energy consumption. Current energy modelling practices in England are heavily focussed on simplified calculations for compliance with Building Regulations, which exclude numerous sources of energy use such as small power. When considered, estimates of small power consumption are often based on historic benchmarks, which fail to capture the significant variability of this end-use, as well as the dynamic nature of office environments. Six interrelated studies are presented in this thesis resulting in three contributions to existing theory and practice. The first contribution consists of new monitored data of energy consumption and power demand profiles for individual small power equipment in use in contemporary office buildings. These were used to inform a critical review of existing benchmarks widely used by designers in the UK. In addition, monthly and annual small power consumption data for different tenants occupying similar buildings demonstrated variations of up to 73%. The second contribution consists of a cross-disciplinary investigation into the factors influencing small power consumption. A study based on the Theory of Planned Behaviour demonstrated that perceived behavioural control may account for 17% of the variation in electricity use by different tenants. A subsequent monitoring study at the equipment level identified that user attitudes and actions may have a greater impact on variations in energy consumption than job requirements or computer specification alone. The third contribution consists of two predictive models for estimating small power demand and energy consumption in office buildings. Outputs from both models were validated and demonstrated a good correlation between predictions and monitored data. This research also led to the development and publication of industry guidance on how to stimate operational energy use at the design stage.
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COCINA, VALERIA CONCETTA. "Economy of grid-connected photovoltaic systems and comparison of irradiance/electric power predictions vs. experimental results." Doctoral thesis, Politecnico di Torino, 2014. http://hdl.handle.net/11583/2538892.
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This thesis is focused on various aspects concerning the Distributed Generation (DG) from Renewable Energy Sources (RES) and in particular from PhotoVoltaics (PV).
The PV generation strongly depends on weather conditions (irradiance and temperature), therefore the solar irradiance forecast is very important for grid-connected PV systems. The PV power injected into the grid is concentrated during sunlight hours, in which the maximum peak load demand occurs and, as a consequence, an impact on the electrical system occurs.
The task of the Transmission System Operator (TSO) is to ensure a constant balance between supply and consumption within the grid. Therefore, the presence of strong fluctuations of the solar radiation requires additional regulatory actions and compensation, through the use of short-term power backup, causing an increase in network costs.
Thus, the solar irradiance forecast is necessary for an accurate evaluation of the PV power from PV systems, for the management of electrical grids in order to minimize the costs of energy imbalance and for the decisions concerning the energy market.
This thesis essentially consists of two parts. In the first part, the profitability of investments in the rooftop grid-connected PV systems subjected to incentive and the grid-parity analysis in the two main European PV markets (Italy and Germany) are presented. In the second part, in order to minimize the costs of energy imbalance in the Italian electricity market, the comparison of irradiance and electric power predictions with respect to the experimental results of grid-connected PV systems is presented.
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Herrin, Judith Mitchell. "Clients' Evaluations of Lawyers: Predictions from Procedural Justice Ratings and Interactional Styles of Lawyers." Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-01292008-112254/.
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Alexander, Richard. "Analysis of Aircraft Power Systems, Including System Modeling and Energy Optimization, with Predictions of Future Aircraft Development." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523541008209354.
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Soldi, James D. "Arc rate predictions and flight data analysis for the photovoltaic array space power plus diagnostics (PASP Plus) experiment." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11147.
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Zastrau, David [Verfasser]. "Estimation of Uncertainty of Wind Energy Predictions : With Application to Weather Routing and Wind Power Generation / David Zastrau." Frankfurt a.M. : Peter Lang GmbH, Internationaler Verlag der Wissenschaften, 2017. http://d-nb.info/1127484524/34.
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Lledó, Ponsatí Llorenç. "Climate variability predictions for the wind energy industry: a climate services perspective." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/670882.
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In order to mitigate the climate change effects, the world is undergoing an energy transition from polluting sources towards renewable energies. This transition is turning the electricity system more dependent on atmospheric conditions and more prone to suffer the effects of climate variability. The atmospheric circulation is changing in certain aspects due to increasing concentrations of greenhouse gases in the atmosphere, but it also varies from year to year due to natural variability processes occurring in the Earth system at timescales of weeks, months and years.
The atmosphere interacts with other components of the Earth System such as the ocean, the cryosphere or the continental surface, that evolve more slowly than the atmosphere and drive the low-frequency variability. The natural climate oscillations that occur at those timescales impact wind speed and wind power generation. Therefore a better knowledge of how the wind resource varies at sub-seasonal, seasonal and decadal time scales is key to understand the risks that the electricity system is facing.
Anticipating this variability would also be helpful to many stakeholders in the energy sector to take precautionary actions. Forecasts at sub-seasonal, seasonal and decadal timescales are starting to be possible recently thanks to advances in climate modelling capabilities. Because climate variability is partly driven by coupled physical processes occurring in the Earth, numerical models that represent the interaction between different components of the Earth system can be employed to produce forecasts at these scales. The science of climate prediction deals with the challenge of producing predictions beyond meteorological timescales (i.e. weeks, months and years ahead) although not reaching the centennial timescales, which are studied with scenario-based climate projections. Climate predictions employ the current state of the atmosphere, the ocean, the cryosphere, and the land surface to produce numerical integrations of each component and the forcings and interactions between them to model the evolution of the Earth system as a whole.
However, the usage of climate predictions in the wind power sector (or more generally in any specific decision-making context) poses a series of difficulties due to many complex aspects of this type of predictions. The efforts devoted in many initiatives to bring the needs of the users to the center of the discussion have given rise to the field of climate services. In order to assist decision-making, it is not only desirable to have the best predictions available but also to tailor them to the specific needs of each user. To achieve this goal, a dialogue with stakeholders needs to be established, and a trans- disciplinary approach needs to be set up to take advantage of the developments in many research fields regarding knowledge transfer and communication.
The work presented in this dissertation advances the knowledge required to produce and successfully apply climate predictions to decision-making in the wind power sector and deals with the three aforementioned challenges: a) understanding the impact of climate oscillations at sub-seasonal and seasonal timescales on wind resource; b) developing methods to produce forecasts of wind speed and wind power generation at this scales; and c) facilitating the uptake of those predictions by means of a climate-services-based approach.<br>Per tal de mitigar els efectes del canvi climàtic, tots els països del món estan duent a terme una transició energètica de fonts contaminants cap a energies renovables. Aquesta transició està incrementant la sensibilitat del sistema elèctric a les condicions atmosfèriques i fent-lo més vulnerable als efectes de la variabilitat climàtica. A escales de setmanes, mesos i anys, l'atmosfera interacciona amb altres components del sistema Terra com l'oceà, la criosfera o la superfície continental, que evolucionen més lentament que l'atmosfera, condicionant-ne la seva variabilitat a baixa freqüència. Al seu torn, les oscil·lacions que tenen lloc a aquestes escales temporals impacten el vent i la generació d'energia eòlica. Per tant, un millor coneixement de com varia el recurs eòlic a escales sub-estacionals, estacionals i decadals permetrà anticipar els riscs a què el sistema elèctric està sotmès.
En segon lloc, anticipar aquesta variabilitat climàtica seria de gran utilitat a diversos actors del sistema energètic. L'ús de models climàtics que representen les interaccions entre les diferents components del sistema Terra permet abordar el repte de produir pronòstics més enllà de l'escala meteorològica (és a dir, a setmanes, mesos i anys vista). Malgrat tot, l'ús de les prediccions climàtiques en el sector de l'energia eòlica presenta una sèrie de dificultats degut a les complexitats d'aquest tipus de previsions. Per tal d'assistir la presa de decisions, no només és necessari disposar de les millors prediccions possibles sinó que cal també ajustar-les a les necessitats específiques de cada ús. Aquest objectiu només es pot assolir amb un diàleg constant i transdisciplinari entre els científics i les parts interessades que integri els avenços en diferents àmbits respecte la transferència de coneixement i la comunicació.
Aquesta tesi avança el coneixement necessari per tal de produir i aplicar prediccions climàtiques a la presa de decisions per part de la indústria eòlica, abordant tres reptes: a) avaluar l'impacte d'oscil·lacions climàtiques sub-estacionals i estacional en el recurs eòlic; b) desenvolupar mètodes per produir prediccions de vent o de generació eòlica a aquestes escales; i c) facilitar l'adopció d'aquestes previsions mitjançant una aproximació basada en els serveis climàtics.
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Fetzek, Charles A. "Behavior-based power management in autonomous mobile robots." Wright-Patterson AFB : Air Force Institute of Technology, 2008. http://handle.dtic.mil/100.2/ADA487084.
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Dedes, Nonell Irene. "Stochastic approach to the problem of predictive power in the theoretical modeling of the mean-field." Thesis, Strasbourg, 2017. http://www.theses.fr/2017STRAE017/document.
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Les résultats de notre étude des capacités de modélisation théorique axées sur les approches phénoménologiques nucléaires dans le cadre de la théorie du champ-moyen sont présentés. On s’attend à ce qu’une théorie réaliste soit capable de prédire de manière satisfaisante les résultats des expériences à venir, c’est-à-dire avoir ce qu’on appelle un bon pouvoir prédictif. Pour étudier le pouvoir prédictif d’un modèle théorique, nous avons dû tenir compte non seulement des erreurs des données expérimentales, mais aussi des incertitudes issues des approximations du formalisme théorique et de l’existence de corrélations paramétriques. L’une des techniques centrales dans l’ajustement des paramètres est la solution de ce qu’on appelle le Problème Inverse. Les corrélations paramétriques induisent généralement un problème inverse mal-posé; elles doivent être étudiées et le modèle doit être régularisé. Nous avons testé deux types de hamiltoniens phénoménologiques réalistes montrant comment éliminer théoriquement et en pratique les corrélations paramétriques.Nous calculons les intervalles de confiance de niveau, les distributions d’incertitude des prédictions des modèles et nous avons montré comment améliorer les capacités de prédiction et la stabilité de la théorie<br>Results of our study of the theoretical modelling capacities focussing on the nuclear phenomenological mean-field approaches are presented. It is expected that a realistic theory should be capable of predicting satisfactorily the results of the experiments to come, i.e., having what is called a good predictive power. To study the predictive power of a theoretical model, we had to take into account not only the errors of the experimental data but also the uncertainties originating from approximations of the theoretical formalism and the existence of parametric correlations. One of the central techniques in the parameter adjustment is the solution of what is called the Inverse Problem. Parametric correlations usually induce ill-posedness of the inverse problem; they need to be studied and the model regularised. We have tested two types of realistic phenomenological Hamiltonians showing how to eliminate the parametric correlations theoretically and in practice. We calculate the level confidence intervals, the uncertainty distributions of model predictions and have shown how to improve theory’s prediction capacities and stability
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Umbach, Valentin. "The power of prediction." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2014. http://dx.doi.org/10.18452/16873.
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Unsere Fähigkeit Erwartungen auszubilden über zukünftige Ereignisse oder die Ergebnisse unserer eigenen Handlungen ist von entscheidender Bedeutung für zielgerichtetes Verhalten. Obgleich diese Ansicht einer Reihe von einflussreichen theoretischen Strömungen in der kognitiven Psychologie zugrunde liegt, bleiben bislang wichtige Fragen dazu offen. Jüngere Ergebnisse aus neurophysiologischen und Bildgebungsstudien legen nahe, dass bewusste Ziele – ähnlich expliziter Erwartung – nicht mehr sind als ein Nebenprodukt von automatischen und unbewussten Aktivierungsmustern und keinen echten Einfluss auf Verhalten haben. Explizite subjektive Erwartung wird vielmals abgetan, weil sie kein zuverlässiges Maß „wahrer“ mentaler Prozesse darstelle, oder weil sie nicht notwendig sei, um Verhalten zu erklären. In der vorliegenden Arbeit beschäftige ich mich mit der Rolle expliziter subjektiver Erwartung und untersuche die folgenden Fragen: (1) Sind verbalisierte Vorhersagen ein valider Indikator für intern generierte Erwartungen? (2) Haben solche Erwartungen tatsächlich einen Einfluss auf Handlungsvorbereitung? (3) Worin besteht der Unterschied zwischen Erwartungen, die auf äußeren oder inneren Quellen beruhen? Die Ergebnisse aus drei Studien, die ich im Rahmen dieser Dissertation durchgeführt habe, belegen, dass verbalisierte Vorhersagen ein valider Indikator von subjektiver Erwartung sind. Subjektive Erwartung kann nicht als ein Nebenprodukt von Handlungsvorbereitung verstanden werden, sondern trägt zu dieser bei und spielt daher eine wichtige Rolle in der Handlungskontrolle. Selbstgenerierte Erwartung beeinflusst gegenüber Cue-induzierter Erwartung verstärkt frühe Aufmerksamkeits- und zentrale Entscheidungsprozesse. Selbstgenerierte Vorhersagen führen zu verstärkten Verhaltenseffekten, und zwar sowohl bei Stimuluserwartungen als auch bei Erwartungen bezüglich einer Aufgabe. Subjektive Erwartung ist demnach auch entscheidend für kognitive Kontrolle.<br>Our ability to form expectations about future events or the results of our own actions is crucial for efficient behavior. While this notion underlies a range of influential theoretical approaches in cognitive psychology, from reinforcement learning to ideo-motor theory, a number of open questions remain. Recent results from neurophysiological and brain imaging studies suggest that conscious intention – or explicit expectation – is nothing more than a by-product of automatic and unconscious activation patterns, without any real impact on behavior. Explicit subjective expectation has been dismissed by many researchers who regard it either an unreliable measure of “true” mental processes, or question its necessity in explaining behavior in general. In the current work, I focus on the role of explicit subjective expectation and attempt to answer the following questions: (1) Are verbalized predictions a valid indicator of internally generated expectations? (2) Do such expectations really affect action preparation? (3) What are the differences between expectations arising from external or internal sources? Results from the three studies conducted within the scope of this dissertation demonstrate that verbalized predictions are in fact a valid indicator of subjective expectation and are suitable for use in experimental paradigms. Also, subjective expectation cannot be described as a mere by-product of preparation, but instead feeds into preparation and therefore plays a role in action control. Self-generated expectation was shown to involve early attentional and central decision processes to a greater degree than cue-induced expectation. Consequently, self-generated predictions entailed greater behavioral effects not only for stimulus expectations, but also for expectations regarding a task set. Subjective expectation is therefore also elemental in cognitive control.
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Huang, Hui. "Lifetime prediction for power converters." Thesis, University of Warwick, 2012. http://wrap.warwick.ac.uk/54844/.
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Renewable energy is developing rapidly and gaining more and more commercial viability. High reliability of the generation system is essential to maximize the output power. The power inverter is an important unit in this system and is believed to be one of the most unreliable parts. In the case of wind power generation, especially in off-shore wind, when the system reliability requirement is high, a technique to predict the inverter lifetime is invaluable as it would help the inverter designer optimize his design for minimal maintenance. Previous researchers studying inverter lifetime prediction, focus either at device level such as device fatigue damage models, or at system level which require experimental data for their selected device. This work presents a new method to estimate the inverter lifetime from a given mission profile within a reasonable simulation time. Such model can be used as a converter design tool or an on-line lifetime estimation tool after being configured to a real converter system. The key contribution of this work is to link the physics of the power devices to a large scale system simulation within a reasonable framework of time. With this technique, the system down time can be reduced and therefore more power can be generated. Also, the failure damage to the system is avoided which reduces the maintenance cost. A power cycling test is designed to gather the lifetime data of a selected IGBT module. Die-attach solder fatigue is found out to be the dominant failure mode of this IGBT module. The accuracy of widely accepted Miner’s rule, which accumulates damage linearly, is discussed and a nonlinear accumulation method is promoted to predict the lifetime of power inverters.
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Bielby, Matthew Iain. "Ultra low power cooperative branch prediction." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14187.
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Branch Prediction is a key task in the operation of a high performance processor. An inaccurate branch predictor results in increased program run-time and a rise in energy consumption. The drive towards processors with limited die-space and tighter energy requirements will continue to intensify over the coming years, as will the shift towards increasingly multicore processors. Both trends make it increasingly important and increasingly difficult to find effective and efficient branch predictor designs. This thesis presents savings in energy and die-space through the use of more efficient cooperative branch predictors achieved through novel branch prediction designs. The first contribution is a new take on the problem of a hybrid dynamic-static branch predictor allocating branches to be predicted by one of its sub-predictors. A new bias parameter is introduced as a mechanism for trading off a small amount of performance for savings in die-space and energy. This is achieved by predicting more branches with the static predictor, ensuring that only the branches that will most benefit from the dynamic predictor’s resources are predicted dynamically. This reduces pressure on the dynamic predictor’s resources allowing for a smaller predictor to achieve very high accuracy. An improvement in run-time of 7-8% over the baseline BTFN predictor is observed at a cost of a branch predictor bits budget of much less than 1KB. Next, a novel approach to branch prediction for multicore data-parallel applications is presented. The Peloton branch prediction scheme uses a pack of cyclists as an illustration of how a group of processors running similar tasks can share branch predictions to improve accuracy and reduce runtime. The results show that sharing updates for conditional branches across the existing interconnect for I-cache and D-cache updates results in a reduction of mispredictions of up to 25% and a reduction in run-time of up to 6%. McPAT is used to present an energy model that suggests the savings are achieved at little to no increase in energy required. The technique is then extended to architectures where the size of the branch predictors may differ between cores. The results show that such heterogeneity can dramatically reduce the die-space required for an accurate branch predictor while having little impact on performance and up to 9% energy savings. The approach can be combined with the Peloton branch prediction scheme for reduction in branch mispredictions of up to 5%.
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Bergsek, Mattias. "THRUST PREDICTION PROGRAM FOR MARINE JET POWER." Thesis, KTH, Marina system, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-77794.
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Marine Jet Power, MJP wishes to investigate the possibility of transforming their current Thrust Prediction Program, TPP written in C++ source code into a more up to date tool for their sales staff. The old TPP, though an accurate and precise tool, is not documented and lacks commentaries in the source code. Therefore the beginning of this master thesis was about documenting and investigates what methods were used to calculate the performance of the water jet system.The next step was splitting the long C++ source code in to smaller functions, this was done using MatLab where several m-files were created with the different functions in. C++ syntax and structure differs from MatLab so the source code must be translated in to MatLab syntax. Once the new TPP was translated and the calculation results were identical with the old TPP a Graphical User Interface, GUI was created and presented to MJP. The current MatLab TPP is not finished, only two of four calculation modes have been translated and MJP wants modifications in the GUI. The additional work needed in order to have the sales tool MJP wishes is currently discussed.
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Al-Ashwal, Natheer Ali Mohammed. "Power system oscillatory instability and collapse prediction." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/power-system-oscillatory-instability-and-collapse-prediction(18ffc3fa-9b1b-40c6-b614-d757eb641046).html.
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This thesis investigates the capabilities of the Collapse Prediction Relay (CPR-D) and also investigates the use of system identification for detection of oscillatory instability. Both the CPR-D and system identification are based on system measurements and do not require modelling of the power system. Measurement based stability monitors can help to avoid instability and blackouts, in cases where the available system model can not predict instability. The CPR-D uses frequency patterns in voltage oscillation to detect system instability. The relay is based on non-linear dynamics Theory. If a collapse is predicted, measures could be taken to prevent a blackout. The relay was tested using the output of simulators and was later installed in a substation. The data from laboratory tests and site installations is analysed enabling a detailed evaluation of the CPR-D.Oscillatory instability can be detected by monitoring the damping ratio of oscillations in the power system. Poor damping indicates a smaller stability margin. Subspace identification is used to estimate damping ratios. The method is tested under different conditions and using several power system models. The results show that using several measurements gives more accurate estimates and requires shorter data windows. A selection method for measurements is proposed in the thesis.
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Dutta, Bishwajit. "Power Analysis and Prediction for Heterogeneous Computation." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/92870.
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Power, performance, and cost dictate the procurement and operation of high-performance computing (HPC) systems. These systems use graphics processing units (GPUs) for performance boost. In order to identify inexpensive-to-acquire and inexpensive-to-operate systems, it is important to do a systematic comparison of such systems with respect to power, performance and energy characteristics with the end use applications. Additionally, the chosen systems must often achieve performance objectives without exceeding their respective power budgets, a task that is usually borne by a software-based power management system. Accurately predicting the power consumption of an application at different DVFS levels (or more generally, different processor configurations) is paramount for the efficient functioning of such a management system.
This thesis intends to apply the latest in the state-of-the-art in green computing research to optimize the total cost of acquisition and ownership of heterogeneous computing systems. To achieve this we take a two-fold approach. First, we explore the issue of greener device selection by characterizing device power and performance. For this, we explore previously untapped opportunities arising from a special type of graphics processor --- the low-power integrated GPU --- which is commonly available in commodity systems. We compare the greenness (power, energy, and energy-delay product $rightarrow$ EDP) of the integrated GPU against a CPU running at different frequencies for the specific application domain of scientific visualization. Second, we explore the problem of predicting the power consumption of a GPU at different DVFS states via machine-learning techniques. Specifically, we perform statistically rigorous experiments to uncover the strengths and weaknesses of eight different machine-learning techniques (namely, ZeroR, simple linear regression, KNN, bagging, random forest, SMO regression, decision tree, and neural networks) in predicting GPU power consumption at different frequencies. Our study shows that a support vector machine-aided regression model (i.e., SMO regression) achieves the highest accuracy with a mean absolute error (MAE) of 4.5%. We also observe that the random forest method produces the most consistent results with a reasonable overall MAE of 7.4%. Our results also show that different models operate best in distinct regions of the application space. We, therefore, develop a novel, ensemble technique drawing the best characteristics of the various algorithms, which reduces the MAE to 3.5% and maximum error to 11% from 20% for SMO regression.<br>MS
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Al-Hinai, Amer. "Voltage collapse prediction for interconnected power systems." Morgantown, W. Va. : [West Virginia University Libraries], 2000. http://etd.wvu.edu/templates/showETD.cfm?recnum=1639.
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Thesis (M.S.)--West Virginia University, 2000.<br>Title from document title page. Document formatted into pages; contains xii, 94 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 66-67).
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Jingchao, Sun. "Prediction of Sound Propagation From Power Transmission Plant." Thesis, KTH, MWL Marcus Wallenberg Laboratoriet, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-121356.
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In ABB, Soundplan is the usually used software to predict the industrial noise for power transmission plants. However, the sound sources in Soundplan are modeled as point sources between which there are no sound reflections. For the real situation, the sound sources are very big and can be regarded as noise barriers. So it is important to take the reflections between sound sources into consideration.COMSOL Multiphysics is Finite Element Method (FEM) software which can model acoustic object with sound-reflective boundaries. First, the COMSOL model for single component inside the power transmission plant will be discussed. Then the COMSOL model for the whole plant will be calculated at different frequencies. The total sound pressure level at different receivers will be compared between COMSOL and Soundplan results. COMSOL can be used to predict the sound propagation of the power transmission plant and it can give different results when the outline of the plant is changed.
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Vlasova, Julija. "Spatio-temporal analysis of wind power prediction errors." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2007. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2007~D_20070816_142259-79654.
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Nowadays there is no need to convince anyone about the necessity of renewable energy. One of the most promising ways to obtain it is the wind power. Countries like Denmark, Germany or Spain proved that, while professionally managed, it can cover a substantial part of the overall energy demand. One of the main and specific problems related to the wind power management — development of the accurate power prediction models. Nowadays State-Of-Art systems provide predictions for a single wind turbine, wind farm or a group of them. However, the spatio-temporal propagation of the errors is not adequately considered. In this paper the potential for improving modern wind power prediction tool WPPT, based on the spatio-temporal propagation of the errors, is examined. Several statistical models (Linear, Threshold, Varying-coefficient and Conditional Parametric) capturing the cross-dependency of the errors, obtained in different parts of the country, are presented. The analysis is based on the weather forecast information and wind power prediction errors obtained for the territory of Denmark in the year 2004.<br>Vienas iš perspektyviausių bei labiausiai plėtojamų atsinaujinančių energijos šaltinių - vėjas. Tokios Europos Sąjungos šalys kaip Danija, Vokietija bei Ispanija savo patirtimi įrodė, jog tinkamai valdomas bei vystomas vėjo ūkis gali padengti svarią šalies energijos paklausos dalį.
Pagal Europos Sąjungos direktyvą 2001/77/EC Lietuva yra įsipareigojusi iki 2010 m. pasiekti, kad elektros energijos gamyba iš atsinaujinančių energijos išteklių sudarytų 7% suvartojamos elektros energijos. Šių įsipareigojimų įvykdymui Lietuvos vyriausybės priimtu nutarimu yra nustatyta atsinaujinančių energijos išteklių naudojimo skatinimo tvarka, pagal kurią numatyta palaipsniui plėsti vėjo energijos naudojimą šalyje. Planuojama, kad iki 2010 m. bus pastatyta 200 MW bendros galios vėjo elektrinių, kurios gamins apie 2,2% visos suvartojamos elektros energijos [Marčiukaitis, 2007]. Didėjant vėjo energijos daliai energetikos sistemoje, Lietuvoje ateityje kils sistemos balansavimo problemų dėl nuolatinių vėjo jėgainių galios svyravimų. Kaip rodo kitų šalių patirtis, vėjo elektrinių galios prognozė yra efektyvi priemonė, leidžianti išspręsti šias problemas.
Šiame darbe pristatyti keletas statistinių modelių bei metodų, skirtų išgaunamos vėjo energijos prognozėms gerinti. Analizė bei modeliavimas atlikti nagrinėjant Danijos WPPT (Wind Power Prediction Tool) duomenis bei meteorologines prognozes. Pagrindinis darbo tikslas - modifikuoti WPPT, atsižvelgiant į vėjo krypties bei stiprio įtaką energijos... [toliau žr. visą tekstą]
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Wan, Sunny. "Facility Power Usage Prediction with Artificial Neural Networks." DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/135.
Full textAbstract:
Residential and commercial buildings accounted for about 68% of the total U.S. electricity consumption in 2002. Improving the energy efficiency of buildings can save energy, reduce cost, and protect the global environment.
In this research, artificial neural network is employed to model and predict the facility power usage of campus buildings. The prediction is based on the building and the weather conditions such as temperature, humidity, wind speed, etc. Various neural network configurations are discussed; satisfactory computer simulation results are obtained and presented.
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Beeravolu, Nagendrakumar. "Predicting Voltage Abnormality Using Power System Dynamics." ScholarWorks@UNO, 2013. http://scholarworks.uno.edu/td/1722.
Full textAbstract:
The purpose of this dissertation is to analyze dynamic behavior of a stressed power system and to correlate the dynamic responses to a near future system voltage abnormality. It is postulated that the dynamic response of a stressed power system in a short period of time-in seconds-contains sufficient information that will allow prediction of voltage abnormality in future time-in minutes. The PSSE dynamics simulator is used to study the dynamics of the IEEE 39 Bus equivalent test system. To correlate dynamic behavior to system voltage abnormality, this research utilizes two different pattern recognition methods one being algorithmic method known as Regularized Least Square Classification (RLSC) pattern recognition and the other being a statistical method known as Classification and Regression Tree (CART). Dynamics of a stressed test system is captured by introducing numerous contingencies, by driving the system to the point of abnormal operation, and by identifying those simulated contingencies that cause system voltage abnormality.
Normal and abnormal voltage cases are simulated using the PSSE dynamics tool. The results of simulation from PSSE dynamics will be divided into two sets of training and testing set data. Each of the two sets of data includes both normal and abnormal voltage cases that are used for development and validation of a discriminator. This research uses stressed system simulation results to train two RLSC and CART pattern recognition models using the training set obtained from the dynamic simulation data. After the training phase, the trained pattern recognition algorithm will be validated using the remainder of data obtained from simulation of the stressed system. This process will determine the prominent features and parameters in the process of classification of normal and abnormal voltage cases from dynamic simulation data.
Each of the algorithmic or statistical pattern recognition methods have their advantages and disadvantages and it is the intention of this dissertation to use them only to find correlations between the dynamic behavior of a stressed system in response to severe contingencies and the outcome of the system behavior in a few minutes into the future.
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Cutler, Nicholas Jeffrey Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Characterising the uncertainty in potential large rapid changes in wind power generation." Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2009. http://handle.unsw.edu.au/1959.4/43570.
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Wind energy forecasting can facilitate wind energy integration into a power system. In particular, the management of power system security would benefit from forecast information on plausible large, rapid change in wind power generation. Numerical Weather Prediction (NWP) systems are presently the best available tools for wind energy forecasting for projection times between 3 and 48 hours. In this thesis, the types of weather phenomena that cause large, rapid changes in wind power in southeast Australia are classified using observations from three wind farms. The results show that the majority of events are due to horizontal propagation of spatial weather features. A study of NWP systems reveals that they are generally good at forecasting the broad large-scale weather phenomena but may misplace their location relative to the physical world. Errors may result from developing single time-series forecasts from a single NWP grid point, or from a single interpolation of proximate grid points. This thesis presents a new approach that displays NWP wind forecast information from a field of multiple grid points around the wind farm location. Displaying the NWP wind speeds at the multiple grid points directly would potentially be misleading as they each reflect the estimated local surface roughness and terrain at a particular grid point. Thus, a methodology was developed to convert the NWP wind speeds at the multiple grid points to values that reflect surface conditions at the wind farm site. The conversion method is evaluated with encouraging results by visual inspection and by comparing with an NWP ensemble. The multiple grid point information can also be used to improve downscaling results by filtering out data where there is a large chance of a discrepancy between an NWP time-series forecast and observations. The converted wind speeds at multiple grid points can be downscaled to site-equivalent wind speeds and transformed to wind farm power assuming unconstrained wind farm operation at one or more wind farm sites. This provides a visual decision support tool that can help a forecast user assess the possibility of large, rapid changes in wind power from one or more wind farms.
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Al, Mahmud Shamsul Arefeen. "Wireless Power Transfer : Machine Learning Assisted Characteristics Prediction for Effective Wireless Power Transfer Systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286673.
Full textAbstract:
One of the main challenges in wireless power transfer (WPT) devices is performance degradation when the receiver’s position and characteristics vary. The variations in the system parameters such as load impedance and coupling strength in WPT devices affect performance characteristics such as output voltage and power. When the system parameters are different from the optimal operating conditions, the performances are degraded. Therefore, the load impedance and coupling strength must be monitored to do the necessary optimization and control. However, such control approaches require additional sensing circuits and a data communication link between transmitter- and receiver-sides. This study proposes a new machine learning (ML) assisted WPT system that predicts the power delivered to the receiver by only using measurements at the transmitter-side. In addition, a method is also proposed to estimate load impedance and coupling coefficient using machine learning approach. We study what parameters measurable at the transmitter-side can be used to predict the output power delivered to receivers at variable load impedance and coupling strengths. In the proposed method, the output power of an inductor-capacitor-capacitor (LCC)-Series tuned WPT system is successfully predicted only using the measured root-mean-square (RMS) of the input current. Random forest algorithm has shown best accuracy to estimate the output power based on transmitter-side parameters only. The proposed approach is experimentally validated using a laboratory prototype. Harmonic components of the input current are used to assess the load impedance and coupling coefficient successfully. Multi-output regression has the highest accuracy for estimating the load impedance and coupling coefficient. The proposed ML algorithm is also used to classify the turn-on and -off regimes to ensure high-efficient operation.<br>En av de viktigaste utmaningarna med trådlösa kraftöverföring enheter är degraderingen av prestandan när mottagarens position och egenskaper varierar. Variationerna av systemets parametrar, såsom belastningsmotstånd och kopplings styrka i WPT-anordning, påverkar prestanda egenskaperna såsom spänning och effekt. När system parametrarna skiljer sig från de optimala drifts förhållandena, försämras prestandan. Därför måste luftmotståndet och kopplings styrkan övervakas, för att göra nödvändig optimering och kontroll. Sådana styrmetoder kräver emellertid ytterligare avkännings kretsar, och en data kommunikationslänk mellan sändar- och mottagarsidan. Denna studie föreslår ett nytt maskininlärning assisterat WPT-system, som förutsäger kraften som levereras till mottagaren genom att endast använda mätningar på sändarsidan. Dessutom föreslås en metod för att detektera belastningsimpedans och kopplings koefficient med användning av maskin inlärningsmetoder. Vi studerar vilka parametrar som är mätbara på sändarsidan och som kan användas för att förutsäga utgången effekten som levereras till mottagare vid varierande belastningsmotstånd och kopplings nivåer. I den föreslagna metoden förutses framgångs effekten för ett induktor-kondensator-kondensator LCCserie avstämt WPT-system endast framgångsrikt med hjälp av det uppmätta effektivvärdet för ingångs strömmen. Slumpmässig skogsalgoritm har visat exceptionell noggrannhet för att uppskatta uteffekten endast baserat på sändarsidans parametrar. Den föreslagna metoden valideras experimentellt med användning av en laboratorium prototyp. Harmoniska komponenter i ingångs strömmen används för att framgångsrikt bedöma last motståndet och kopplings koefficienten. Multi-utgångsregression har verkat vara mycket exakt för att uppskatta belastningsimpedans och kopplingskoefficient. Den föreslagna maskininlärning algoritmen används också för att klassificera start-och-off-regimer för att säkerställa hög effektiv drift.
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Uurtonen, Tommi. "Optimized Power Control for CDMA System using Channel Prediction." Thesis, Linköping University, Department of Science and Technology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-3697.
Full textAbstract:
<p>In an optimal power control scheme for a Code Division Multiple Access (CDMA) system all mobile stations signals should arrive to the base station at equal power. If not, stronger singals may cause too much interference and block out weaker ones. Commonly used power control schemes utilizes the Signal to Interference Ratio (SIR) to design a Power Control Command (PCC) to adjust the transmit power of the mobile station. A significant problem within the conventional methods is the slow SIR recovery due to deep channel fades. Conventional methods base the PCC on the previous channel state when in fact, the channel state may have significantly changed when transmission occurs. These channel changes may cause the SIR to drop or rise drastically and lead to uncontrollable Multi Access Interference (MAI) resulting in power escalation and making the system unstable. In order to overcome power escalation and improve the recovery from deep fades a novel power control method has been developed. Based on Linear Quadratic Control and Kalman filtering for channel prediction this method designs the PCC based on the coming channel state instead of the current. This optimizes the PCC for the channel state where transmission occurs. Simulations show that this control scheme outperforms previous methods by making the impacts of the deep fades less severe on the SIR and also improves the overall SIR behaviour.</p>
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Lepard, Robert F. (Robert Frederick). "Power quality prediction based on determination of supply impedance." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/40171.
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Urban, Rodney Gordon. "Power line corona noise prediction from small cage measurement." Thesis, Stellenbosch : Stellenbosch University, 2004. http://hdl.handle.net/10019.1/50063.
Full textAbstract:
Thesis (PhD) -- Stellenbosch University, 2004.<br>Some digitised pages may appear illegible due to the condition of the original hard copy.<br>ENGLISH ABSTRACT: The radio noise (RN) performance of an AC high voltage transmission line is a determining
factor when accessing the reliability of the design. The conducted RN level across the terminals
of a PLC receiver, used in the teleprotection system of the line, is of particular concern. In this
dissertation, existing empirical and semi-analytical RN prediction methods are evaluated by
comparing the conducted RN levels of four South African lines to the predicted levels.
Existing RN measurement protocols are consolidated and a new RN measurement protocol is
proposed for the comparison. A prediction methodology, based on the EdF, EPRI and IREQ
semi-analytical methods, is formulated. The semi-analytical methods are not able to accurately
predict the variation of the conducted RN with frequency in the PLC band, nor are they able to
predict the RN performance of short lines. A wideband excitation function, which considers the
statistical characteristics of the measured RN pulse train, is therefore proposed in this
dissertation. Having investigated the extraction of this excitation function from ESKOM’s
Megawatt Park corona cage, it is concluded that a small corona cage is required. The design of
a small cage is presented and the extraction of the excitation function is described. Attention is
given to assessing the effect of changes in space charge distributions. The effect of space charge
collision with an insulated cage on the extracted pulse parameters is linear, provided space charge
diffusion is negligible. The onset streamer, positive streamer and negative streamer corona modes
were identified as the only modes with measurable RN in the frequency regime 150 kHz to 30
MHz. Formulas are derived for the prediction of the inception gradients for these modes. The RN
performance of an ACSR Hare conductor is extracted from the small cage. The RN performance
of the Acacia-Koeberg line is also approximated in the PLC band.
The dissertation concludes that the proposed wideband excitation function method is capable of
accurately predicting the variation of RN levels with frequency. It can also be used to predict the
RN performance of short line sections, as well as the relationship between RMS, QP and average
RN levels from a transmission line.<br>AFRIKAANSE OPSOMMING: Die korona-werkverrigting van ‘n WS hoogspanningstransmissielyn het belangrike gevolge vir
die betroubaarheid van die ontwerp van die lyn. Die geleide radioruis (RR) vlak op die kraglyndragolf
kommunikasie sisteem, wat vir tele-beveiliging gebruik word, is veral van belang. In
hierdie werkstuk word bestaande metodes gebruik om die korona-werkverrigting te bepaal en
dan met gemete waardes van vier Suid Afrikaanse lyne te vergelyk.
Bestaande RR meetmetodes word saamgevat en ‘n nuwe metingsprotokol word voorgestel om
resultate te vergelyk. Na aanleiding van hierdie vergelykings word ‘n tegniek ontwikkel om die
RR van ‘n lyn te voorspel. Hierdie tegniek gebruik die EdF, EPRI en IREQ metodes. Die
voorgestelde tegniek kan nie die verandering van die RR met frekwensie bepaal nie. Dit kan ook
nie die RR van kort lyne bepaal nie. ‘n Wyeband RR bron word dus voorgestel. Nadat ESKOM
se Megawatt Park korona-kou ondersoek is, is die gevolgtrekking gemaak dat ‘n klein koronakou
die nodige wyeband RR bron sal voorsien. Ruimtelading bots met die klein korona-kou. Die
effek van hierdie botsings op die pulsparameters is lineer indien ladingsdiffusie nie plaasvind nie.
Die aanvangs, positiewe en negatiewe kanaalontladings (“streamers”) is identifiseer as die
enigste koronamodusse wat RR veroorsaak tussen 150 kHz en 30 MHz. Die spanning waarby
hierdie modusse voorkom, is bepaal. Die korona-werkverrigting van ‘n “ACSR Hare” geleier is
bepaal. Die korona-werkverrigting van die Acacia-Koeberg transmissie lyn is ook gekwantifiseer
by die kraglyn-dragolf kommunikasie frekwensies.
Die wyebandbron metode kan die verandering in RR met frekwensie goed voorspel. Die nuwe
metode kan ook gebruik word om die RR van kort lyne te bepaal, asook die verband tussen RMS,
QP en gemiddelde RR vlakke.
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Zeng, Guang. "Some aspects in lifetime prediction of power semiconductor devices." Universitätsverlag Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A34891.
Full textAbstract:
Power electronics, which fully covers the generation, conversion, transmission and usage of electrical energy, is a key technology for human welfare. With the development of technologies, the requirements on the reliability of power electronic systems are keep increasing. Long term operation under harsh environments is often accompanied by higher switching frequency and higher power density. To allow a reliable and sustainable performance of the power electronic systems, precise lifetime estimation of the power semiconductor devices is of significant importance. This work covers some aspects in the lifetime prediction of power semiconductor devices, especially IGBT and diode, in power module and transfer-molded discrete package. Difference in device temperature determination was illustrated using analytical calculation, simulation and measurement. In addition, temperature calculation in the frequency domain was demonstrated which gives benefits in the application with several hundred devices. Furthermore, different control strategies in the power cycling test were compared. The linear cumulative damage theory was validated by using the power cycling test. For the high power IGBT module used in the MMC HVDC application, power cycling lifetime with 50 Hz heating processes was investigated. For the transfer-molded discrete package, the first lifetime model with comparable scope like the lifetime model of power modules was proposed.<br>Leistungselektronik, welche direkt relevant für die Erzeugung, Umwandlung, Übertragung und Nutzung elektrischer Energie ist, ist eine Schlüsseltechnologie für das Wohl der Menschen. Mit der Entwicklung von Technologien steigen die Anforderungen an die Zuverlässigkeit leistungselektronischer Systeme. Der Langzeitbetrieb unter rauen Umgebungsbedingungen geht häufig mit einer höheren Schaltfrequenz und einer höheren Leistungsdichte einher. Um eine zuverlässige und nachhaltige Operation der leistungselektronischen Systeme zu ermöglichen, ist die genaue Lebensdauerabschätzung der Halbleiter-Leistungsbauelemente von großer Bedeutung. Diese Arbeit befasst sich mit einigen Aspekten der Lebensdauerabschätzung von den Halbleiter-Leistungsbauelementen. Unterschied in der Temperaturabstimmung der Halbleiter-Leistungsbauelemente wird anhand von Berechnung, Simulation und Messung veranschaulicht. Darüber hinaus bietet die Temperaturberechnung im Frequenzbereich Vorteile bei der Anwendung mit mehreren hundert Bauelementen. Darüber hinaus wurden verschiedene Regelstrategien im Lastwechseltest verglichen. Die lineare kumulative Alterungstheorie wurde unter Verwendung des Lastwechseltests validiert. Für das in der MMC-HGÜ-Anwendung verwendete Hochleistungs-IGBT-Modul wurden Alterungsprozesse bei 50 Hz Erwärmung untersucht. Für das Diskrete-Gehäuse wird das erste Lebensdauermodell vorgestellt, welches ein vergleichbares Anwendungsbereich wie das Lebensdauermodell von Leistungsmodulen hat.
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Earl, David James. "Predictions of helical twisting powers and molecular chirality." Thesis, Durham University, 2003. http://etheses.dur.ac.uk/4043/.
Full textAbstract:
When chiral molecules are added to an achiral nematic liquid crystalline solvent, they can transmit their molecular chirality to the whole system over distances many times their molecular length. The helical twisting power, βm, is a measure of the degree of twist a chiral molecule can induce in a nematic liquid crystal. The work in this thesis is primarily concerned with calculating helical twisting powers for a variety of chiral molecules using computational and theoretical methods. The first technique used to calculate βm employed Monte Carlo simulations of an atomistic chiral dopant molecule in a chiral liquid crystal phase composed of generic liquid crystalline molecules. The method was found to be computationally expensive, but provided reasonable predictions of when compared with experimental results. Prior to these calculations, a liquid crystal solvent for use in this method was studied. Computer simulations of L/D = 4 soft repulsive spherocylinder (SRS) molecules were performed and two liquid crystalline phases were found in the SRS phase diagram. The scaled chiral index and the chirality order parameter are quantitative measures of molecular chirality. Both of these methods have been found to show a good correlation with experimentally determined helical twisting powers of relatively rigidchiral molecules. The chiral measures have also been incorporated in Monte Carlo simulations of flexible chiral molecules. This method has been successful in predicting βm for flexible chiral dopants, in predicting the temperature dependence of βm, has demonstrated a temperature induced helical twist inversion, and has been used in a predictive study to aid in future synthetic strategies. The final part of the thesis uses Monte Carlo simulations of a chiral molecule in an achiral liquid crystal phase. These simulations have shown that it is possible to relate the torque the chiral molecule induces in the solvent to βm.
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Wong, Yuen-wah, and 黃婉華. "Performance prediction model for a solar water pump." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31223722.
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Wong, Yuen-wah. "Performance prediction model for a solar water pump /." Hong Kong : University of Hong Kong, 2000. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21607424.
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Sayler, Kent Alexander Halpin S. Mark. "Predicting generator coupling using power system impedance matrices." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Spring/master's/SAYLER_KENT_33.pdf.
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Sarkar, Avranil. "Power Prediction in Large Scale Multiple Testing: A Fourier Approach." Research Showcase @ CMU, 2010. http://repository.cmu.edu/dissertations/2.
Full textAbstract:
A problem that is frequently found in large-scale multiple testing is that, in the present stage of experiment (e.g. gene microarray, functional MRI), the signals are so faint that it is impossible to attain a desired level of testing power, and one has to enroll more samples in the follow-up experiment. Suppose we are going to enlarge the sample size by a times in the follow-up experiment, where a > 1 is not necessary an integer. A problem of great interest is, given data based on the current stage of experiment, how to predict the testing power after the sample size is enlarged by a times.
We consider test z-scores and model the test statistics in the current experiment as Xj ~ N(μj , 1), 1 ≤ j ≤ n. We propose a Fourier approach to predicting the testing power after n replicates. The approach produces a very accurate prediction for moderately large values of a ( a ≤ 7). Finally, we discuss potential applications of this method on real data with emphasis on gene microarray data.
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Moody, Robert D. "Preliminary power prediction during early design stages of a ship." Thesis, Cape Technikon, 1996. http://hdl.handle.net/20.500.11838/1261.
Full textAbstract:
Thesis (Masters Diploma (Mechanical Engineering)) -- Cape Technikon, Cape Town,1996<br>A need exists whereby the preliminary power requirement of a ship can be rapidly
estimated. Because the majority of methods available for this purpose are manual and
consist of a number of independent components, they are tedious and time consuming to
use. With the advent of the personal computer and its widespread acceptance, it was
logical to examine the various components involved to determine their suitability for
computerisation and general accuracy. In total eleven hull resistance prediction methods
were examined, eight of which were computerised. Model test data of four vessels were
used to evaluate these eight programs. The methodproviding the best results was selected
to form the core of an integrated Power Prediction program.
Factors such as appendage resistance, fouling and hull roughness were examined and
appropriate methods selected for inclusion into the integrated program.
Various propeller series were examined and evaluated against a variety of examples and
model data. Two propeller optimisation programs were written and a general method for
determining the optimum characteristics from Kr-KQ polynomials is described.
Methods for determining propulsion coefficients were examined and their results compared
with those obtained from model tests. The method providing the best overall results was
incorporated into the Power Prediction program
Added resistance due to sea state was broken down into two components, namely wind
and wave resistance. Only the head sea and wind conditions were considered. Various
methods for estimating wind resistance were examined and a program developed capable
of providing resistance estimates regardless of wind direction. The problem of added
resistance due to waves was examined and two programs written around the methods
examined. To facilitate prediction estimates, sea state was chosen as the prime function.
Wave height is estimated for the appropriate sea state and wind speed in turn from the
wave height
Actual sea trial data ofa twin screw channel ship is used to determine the overall accuracy
ofthe Power Prediction Program
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Allenspach, Mark 1967. "Prediction and hardening techniques for SEGR in power MOSFET devices." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282345.
Full textAbstract:
Single Event Gate Rupture (SEGR) induced by an energetic ion traversing a MOSFET may cause catastrophic failure of the device. The mechanism for SEGR in a power MOSFET structure is investigated in this work. A simple analytical prediction method is introduced. This prediction method allows evaluation of device SEGR sensitivity through 2-D computer simulations and therefore avoids the need for time consuming and costly experiments on an ion accelerator. A thorough investigation of SEGR sensitivity dependence is shown for a variety of influencing factors such as (i) device parametric variations, (ii) ion strike characteristics, and (iii) device operation temperature. Based on knowledge of the physical model for the SEGR mechanism and the utilization of simulation results and experimental SEGR data, useful SEGR hardening techniques are suggested.
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Yang, Xianzhen. "Power Spectrum Prediction of Amplified Dual-Band LTE-Advanced Signals." PDXScholar, 2018. https://pdxscholar.library.pdx.edu/open_access_etds/4351.
Full textAbstract:
In wireless communication, the nonlinearity of a radio frequency (RF) power amplifier is an important issue for power amplifier designers. Since the nonlinearity is generated by the properties of physical components, it is hard to avoid it in producing power amplifiers. Power amplifier designers should know about the nonlinearity in order to compensate for it.
A two-tone test is a relatively widely used method to measure the nonlinearity of a power amplifier, which means the third order intercept point (IP3) can be measured from the two-tone test. Through the two-tone test, researchers have proposed some formulae to present what the amplified Code Division Multiple Access (CDMA) signal is like. They derived formulae in terms of output power, bandwidth, IP3, and IP5 to express the amplified CDMA signal and further to Orthogonal Frequency Division Multiplexing (OFDM) signals. With the development of wireless communication, researchers put their interest increasingly in Multiple Input Multiple Output (MIMO) systems. A formula expressing amplified dual two-tone signals has been proposed. In their research, they discussed what the expressions of intermodulation and cross modulation are and what their locations are.
In this research, dual band LTE-Advanced signals, whose modulation is OFDM are utilized, which means this research proposes a formula expression about the power spectrum of dual-band LTE-Advanced signals. Intermodulation and cross modulation caused by nonlinearity of power amplifiers are then specially discussed. This study will help RF designers to continuously compensate for them.
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James, Peter Andrew. "Health monitoring of IGBTs in automotive power converter systems." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/health-monitoring-of-igbts-in-automotive-power-converter-systems(224a6b3c-a1f0-4379-9ff7-eb5603f8deb9).html.
Full textAbstract:
The use of IGBT power modules in the automotive industry is becoming increasingly common as manufacturers develop more hybrid and all electric vehicles. In an industry such as this, the reliability of a component is critical and vehicle manufacturers have conducted much research into diagnostic and prognostic systems for internal combustion engines that run in real time on the vehicle to determine when components will fail. Power electronic components do not have similar prognostics available. The traditional use of power electronic modules has been in applications where their life or duty cycle is well defined, and accelerated life tests are carried out to determine a mean time to failure. This type of prognostics is not appropriate for the automotive industry because the operating cycle of the vehicle varies greatly, both in driving style, duty cycle and environment. A new type of prognostics is therefore required which will calculate the life remaining in the power module in real time as the device is being used.Because of the high robustness of IGBT power modules, testing for time to failure can be a very lengthy process. A novel procedure and test rig based on Peltier effect thermoelectric coolers was developed, which can automatically temperature cycle IGBT power modules in a very short time and determine their life expectancy, all within their operating specifications. This was tested using several power modules. The failure modes of IGBT power modules are also investigated with a view to developing a failure prediction algorithm. The causes of failure are analysed and a prognostics algorithm is proposed. This prognostics algorithm uses thermal cycle history as a means to predict the life consumed for the power module. The data obtained by the accelerated life tests is used to calculate the coefficients for the prognostic algorithm. A simulation of a vehicle drive cycle is used to show how the prognostics algorithm can be used, and a value indicating the extent to which the IGBT power module has aged is calculated. It is also proved that by intelligently controlling the heat flowing from the heat sink on which the power module is mounted, the life of the IGBT power module can be increased by approximately three times.Hardware and software were developed to implement the health monitoring algorithm. Measurement and control circuits were designed, built and tested together with software that processes the input data, records the thermal cycle history of the IGBT power modules and calculates a value of age for the IGBT power modules in real time. This was tested on several modules to prove the validity of the algorithm.The new algorithms and methodology developed could enable vehicle manufacturers to predict the failure of power modules in hybrid and all electric vehicles. This technology could also benefit other industries such as the renewables (eg wind turbines) and aerospace, where the industry is moving towards all electric aircraft.
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Raoofsheibani, Davood [Verfasser]. "Online Power System Security Analysis and State Prediction : Enhanced Power System Models and Tools / Davood Raoofsheibani." Düren : Shaker, 2021. http://d-nb.info/1240853947/34.
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Li, Qian. "Correlation between Simulation and Measurement of Microwave Resonator Power Handling." Thesis, Linköpings universitet, Fysik och elektroteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-101981.
Full textAbstract:
In modern mobile wireless communication, Base Stations (BS) are the most important equipment to build up the mobile network. One of the key elements in BS is the RF filter, which plays a key role to secure the coverage and reliability of the BS. Especially, at Transmitter (Tx) side, the filter must have a high capability to handle the power sent from Power Amplifier (PA) to antenna in any circumstances to ensure the coverage demand. Otherwise, the breakdown will be encountered, setting the power flow in the BS system in an abnormal manner that, finally can lead to the shut down of BS or destroy the system permanently. In this project, three methods using two simulation tools to predict the power handling capability of the RF/microwave resonator which is the elementary component in the BS’s filter are proposed. Power handling tests of selected configurations corresponding to the simulations are implemented as well. In the next stage, the results from the prediction and measurement are compared. Finally, the conclusions of correlation between the prediction and measurement of microwave resonator power handling will be derived.
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Austin, Richard Arthur. "The development of a multi-tide tidal energy prediction model and its application to the proposed Mersey Barrage." Thesis, University of Salford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280754.
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Li, Gang. "A study of value-at-risk models and their prediction power." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B32029718.
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Szerszen, Lukas, and Mosulet Paul-Philip. "Subject-Independent Epileptic Seizure Prediction using Spectral Power and Correlation Coefficients." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208684.
Full textAbstract:
Epileptic seizure prediction algorithms with prediction rates above random have been produced, with varying success, during the last ten to twenty years. The algorithms produced have been tailored to the specific characteristics of a subject’s epilepsy, referred to as subject-specific prediction algorithms. Such customization entails the training of the algorithm’s classifier on the specific EEG-data pertaining to the subject. An inherent requirement is the time-intensive task of recording and labeling the subjects EEG, which will be used for the training of the classifier. As such, this thesis investigates the possibility of adjusting the training of a subject-specific algorithm’s classifier to make it subject-independent. The investigation is based on whether the subject-independent version could achieve prediction rates equal to or better than that of the original subject-specific version. The methodology carried out employs a subjectspecific algorithm, sourced from a Kaggle competition, which utilizes a Support Vector Machine and spectral power and correlation coefficients as its features. The training of the classifier was modified to be subjectindependent and then compared to the performance of the subject-specific version. The results indicate that the subject-independent version performed worse than the original subject-specific one, in fact it performs below or equal to random prediction rates. It is concluded that: due to the dependency of epileptic seizure prediction algorithms on the strict characteristics of a subjects epilepsy, a subject-independent algorithm, produced with the adjustment of a subject-specific version, can’t, at this time, achieve prediction rates equal to or higher than that of the subjectspecific version.<br>De senaste 20 åren har algoritmer som kan förutspå epileptiska anfall utvecklats. Dessa har, med varierande resultat, kunnat förutspå epileptiska anfall med sannolikhetsestimeringar som varit bättre än en slumpmässig estimering. Algoritmerna är skräddarsydda för att användas på specifika egenskaper för epilepsin hos en specifik patient. Detta medför att en klassificerare anpassas efter träningen på den specifika EEG-datan för patienten. Att producera en ny patient-specifik algoritm är tidskrä- vande då det kräver både inspelning och att det sätts etiketter på ny EEGdata för varje patient. Därav undersöker denna rapport möjligheten att justera träningen av den patientspecifika algoritmens klassificerare för att göra den oberoende av patienten. För att kunna mäta detta undersöktes om en patientoberoende algoritm kunde uppnå sannolikhetsestimeringar som var lika bra eller bättre än en patientspecifik algoritm. Metoden har anpassats efter en algoritm som varit tillgänglig från en Kaggle-tävling. Algoritmens träning har ändrats för att bli patient-oberoende och resultaten har jämförts med resultaten från den patient-specifika algoritmen. Denna algoritm använder sig utav egenskaperna hos den spektrala energifördelningen, och korrelations koefficienter tillsammans med en Support Vector Machine. Resultaten visar att den patient-oberoende algoritmen presterar sämre än den ursprungliga patient-specifika versionen. Resultaten visar även att den inte överskrider en slumpmässig estimeringsmetod. Utifrån dessa resultat kan en slutsats dras; att baserat på de specifika egenskaperna hos en patients epilepsi, kan inte idag en patientoberoende algoritm, utvecklad genom att anpassa en patient-specifik algoritm, nå sannolikhetsestimeringar som är lika bra med eller bättre än en patient-specifik.
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Li, Gang, and 李剛. "A study of value-at-risk models and their prediction power." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B32029718.
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Koh, Yong-Khiang. "Prediction and control of vibrational power transmission between coupled structural systems." Thesis, University of Southampton, 1992. https://eprints.soton.ac.uk/428197/.
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Uchaipichat, Nopadol. "The prediction of defibrillation outcome using time-frequency power spectrum methods." Thesis, Edinburgh Napier University, 2005. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.418238.
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Lange, Matthias [Verfasser]. "Analysis of the uncertainty of wind power predictions / Matthias Lange." 2003. http://d-nb.info/969985789/34.
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Aydogan, Fatih. "Development of uncertainty methodology for cobra-tf void distribution and critical power predictions." 2008. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-2503/index.html.
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Zhang, Xiaozhu. "Dynamic Responses of Networks under Perturbations: Solutions, Patterns and Predictions." Doctoral thesis, 2018. http://hdl.handle.net/11858/00-1735-0000-002E-E409-2.
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Hering, Amanda S. "Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions." 2009. http://hdl.handle.net/1969.1/ETD-TAMU-2009-08-910.
Full textAbstract:
High-quality short-term forecasts of wind speed are vital to making wind power a
more reliable energy source. Gneiting et al. (2006) have introduced a model for the average
wind speed two hours ahead based on both spatial and temporal information. The
forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution
is sharp, i.e., highly concentrated around its center. However, this model is split
into nonunique regimes based on the wind direction at an off-site location. This work both
generalizes and improves upon this model by treating wind direction as a circular variable
and including it in the model. It is robust in many experiments, such as predicting at new
locations. This is compared with the more common approach of modeling wind speeds and
directions in the Cartesian space and use a skew-t distribution for the errors. The quality
of the predictions from all of these models can be more realistically assessed with a loss
measure that depends upon the power curve relating wind speed to power output. This
proposed loss measure yields more insight into the true value of each model's predictions.
One method of evaluating time series forecasts, such as wind speed forecasts, is to
test the null hypothesis of no difference in the accuracy of two competing sets of forecasts. Diebold and Mariano (1995) proposed a test in this setting that has been extended and
widely applied. It allows the researcher to specify a wide variety of loss functions, and the
forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously
correlated. In this work, a similar unconditional test of forecast accuracy for spatial
data is proposed. The forecast errors are no longer potentially serially correlated but spatially
correlated. Simulations will illustrate the properties of this test, and an example with
daily average wind speeds measured at over 100 locations in Oklahoma will demonstrate
its use. This test is compared with a wavelet-based method introduced by Shen et al. (2002)
in which the presence of a spatial signal at each location in the dataset is tested.