Dissertations / Theses: 'Power system disturbance identification'

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Manmek, Thip Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithm." Awarded by:University of New South Wales. Electrical Engineering and Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/26233.

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This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called ???efficient least squares algorithm???. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies. The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems

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Glickman, Mark. "Disturbance monitoring in distributed power systems." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16497/.

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Power system generators are interconnected in a distributed network to allow sharing of power. If one of the generators cannot meet the power demand, spare power is diverted from neighbouring generators. However, this approach also allows for propagation of electric disturbances. An oscillation arising from a disturbance at a given generator site will affect the normal operation of neighbouring generators and might cause them to fail. Hours of production time will be lost in the time it takes to restart the power plant. If the disturbance is detected early, appropriate control measures can be applied to ensure system stability. The aim of this study is to improve existing algorithms that estimate the oscillation parameters from acquired generator data to detect potentially dangerous power system disturbances. When disturbances occur in power systems (due to load changes or faults), damped oscillations (or "modes") are created. Modes which are heavily damped die out quickly and pose no threat to system stability. Lightly damped modes, by contrast, die out slowly and are more problematic. Of more concern still are "negatively damped" modes which grow exponentially with time and can ultimately cause the power system to fail. Widespread blackouts are then possible. To avert power system failures it is necessary to monitor the damping of the oscillating modes. This thesis proposes a number of damping estimation algorithms for this task. If the damping is found to be very small or even negative, then additional damping needs to be introduced via appropriate control strategies. This thesis presents a number of new algorithms for estimating the damping of modal oscillations in power systems. The first of these algorithms uses multiple orthogonal sliding windows along with least-squares techniques to estimate the modal damping. This algorithm produces results which are superior to those of earlier sliding window algorithms (that use only one pair of sliding windows to estimate the damping). The second algorithm uses a different modification of the standard sliding window damping estimation algorithm - the algorithm exploits the fact that the Signal to Noise Ratio (SNR) within the Fourier transform of practical power system signals is typically constant across a wide frequency range. Accordingly, damping estimates are obtained at a range of frequencies and then averaged. The third algorithm applied to power system analysis is based on optimal estimation theory. It is computationally efficient and gives optimal accuracy, at least for modes which are well separated in frequency.

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Looja, Tuladhar R. "Control of Custom Power System using Active Disturbance Rejection Control." Cleveland State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=csu1438913443.

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Dong, Jingyuan. "Power System Disturbance Analysis and Detection Based on Wide-Area Measurements." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/30129.

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Wide-area measurement systems (WAMS) enable the monitoring of overall bulk power systems and provide critical information for understanding and responding to power system disturbances and cascading failures. The North American Frequency Monitoring Network (FNET) takes GPS-synchronized wide-area measurements in a low-cost, easily deployable manner at the 120 V distribution level, which presents more opportunities to study power system dynamics. This work explores the topics of power system disturbance analysis and detection by utilizing the wide-area measurements obtained in the distribution networks. In this work, statistical analysis is conducted based on the major disturbances in the North American Interconnections detected by the FNET situation awareness system between 2006 and 2008. Typical frequency patterns of the generation and load loss events are analyzed for the three North American power Interconnections: the Eastern Interconnection (EI), the Western Electricity Coordinating Council (WECC), and the Electric Reliability Council of Texas (ERCOT). The linear relationship between frequency deviation and frequency change rate during generation/loss mismatch events is verified by the measurements in the three Interconnections. The relationship between the generation/load mismatch and system frequency is also examined based on confirmed generation loss events in the EI system. And a power mismatch estimator is developed to improve the current disturbance detection program. Various types of power system disturbances are examined based on frequency, voltage and phase angle to obtain the event signatures in the measurements. To better understand the propagation of disturbances in the power system, an automated visualization tool is developed that can generate frequency and angle replays of disturbances, as well as image snapshots. This visualization tool correlates the wide-area measurements with geographical information by displaying the measurements over a geographical map. This work makes an attempt to investigate the visualization of the angle profile in the wide-area power system to improve situation awareness. This work explores the viability of relying primarily on distribution-level measurements to detect and identify line outages, a topic not yet addressed in previous works. Line outage sensitivity at different voltage levels in the Tennessee Valley Authority (TVA) system is examined to analyze the visibility of disturbances from the point of view of wide-area measurements. The sensor placement strategy is proposed for better observability of the line trip disturbances. The characteristics of line outages are studied extensively with simulations and real measurements. Line trip detection algorithms are proposed that employs the information in frequency and phase angle measurements. In spite of the limited FDR coverage and confirmed training cases, an identification algorithm is developed which uses the information in the real measurements as well as the simulation cases to determine the tripped line.
Ph. D.

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Chapman, Jeffrey W. (Jeffrey Wayne). "Power system control for large-disturbance stability : security, robustness and transient energy." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/39393.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
Includes bibliographical references (p. 223-228).
by Jeffrey Wayne Chapman.
Ph.D.

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Wall, Peter Richard. "Online prediction of the post-disturbance frequency behaviour of a power system." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/online-prediction-of-the-postdisturbance-frequency-behaviour-of-a-power-system(fbbe0a82-3c88-4633-8947-ef16a3616aea).html.

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The radical changes that are currently occurring in the nature of power systems means that in the future it may no longer be possible to guarantee security of supply using offline security assessment and planning. The increased uncertainty, particularly the reduction and variation in system inertia that will be faced in the future must be overcome through the use of adaptive online solutions for ensuring system security. The introduction of synchronised measurement technology means that the wide area real time measurements that are necessary to implement these online actions are now available.The objective of the research presented in this thesis was to create methods for predicting the post-disturbance frequency behaviour of a power system with the intent of contributing to the development of real time adaptive corrective control for future power systems. Such a prediction method would generate an online prediction based on wide area measurements of frequency and active power that are recorded within the period of approximately one second after a disturbance to the active power balance of the system. Predictions would allow frequency control to respond more quickly and efficiently as it would no longer be necessary to wait for the system frequency behaviour to violate pre-determined thresholds.The research presented in this thesis includes the creation of an online method for the simultaneous detection of the time at which a disturbance occurred in a power system, or area of a power system, and the estimation of the inertia of that system, or area. An existing prediction method based on approximate models has been redesigned to eliminate its dependence on offline information. Furthermore, the thesis presents the novel application of pattern classification theory to frequency prediction and a five class example of pattern classification is implemented.

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Singhavilai, Thamvarit. "Identification of electric power system dynamic equivalent." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=15647.

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Rioual, Pascal. "Modélisation et commande d'un redresseur à MLI alimenté par un réseau déséquilibré." Cachan, Ecole normale supérieure, 1993. http://www.theses.fr/1993DENS0008.

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L'augmentation considérable ces dernières années du nombre de convertisseur sur le réseau d'alimentation se traduit par la nécessite de s'intéresser a la compatibilité entre les convertisseurs et le réseau. Le redresseur à mli est un convertisseur dont les caractéristiques lui permettent d'absorber des courants réseaux sinusoïdaux, et d'échanger de la puissance active et réactive avec le réseau. Le présent travail concerne l'étude de la modélisation et la commande de ce convertisseur ainsi que l'extension au cas d'un réseau déséquilibre. Le redresseur est contrôlé par une régulation cascade: des boucles internes régulent les courants réseaux, une boucle externe régule la tension de capacité. Les conséquences de l'apparition d'une perturbation de type creux de tension (distorsion harmonique sur les courants réseaux, oscillation a l'harmonique 2 des composantes continues) sont analysées puis simulées et vérifiées expérimentalement. Deux solutions sont étudiées: - une compensation s'appuyant sur une étude théorique du système. - la construction d'un régulateur robuste appliquant le principe du modèle interne de Wohnam et la méthode de placement de pôles par -stabilité. Les avantages obtenus permettent d'envisager une meilleure continuité de fonctionnement face aux creux de tension, un dimensionnement réduit du convertisseur, et la conservation des performances. Les domaines d'application concernes sont varies. Dans le domaine industriel, il s'agit des alimentations à bon facteur de puissance ou des procédés nécessitant le réglage du réactif

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Banejad, Mahdi. "Identification of Damping Contribution from Power System Controllers." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15851/.

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With the growth of power system interconnections, the economic drivers encourage the electric companies to load the transmission lines near their limits, therefore it is critical to know those limits well. One important limiting issue is the damping of inter-area oscillation (IAO) between groups of synchronous machines. In this Ph.D. thesis, the contribution of power system components such as load and static var compensators (SVC) that affect the IAO of the power system, are analysed. The original contributions of this thesis are as follows: 1-Identification of eigenvalues and mode shapes of the IAO: In the first contribution of this thesis, the eigenvalues of the IAO are identified using a correlation based method. Then, the mode shape at each identified resonant frequency is determined to show how the synchronous generators swing against each other at the specific resonant frequencies. 2-Load modelling and load contribution to damping: The first part of this contribution lies in identification of the load model using cross-correlation and autocorrelation functions . The second aspect is the quantification of the load contribution to damping and sensitivity of system eigenvalues with respect to the load. 3- SVC contribution to damping: In this contribution the criteria for SVC controller redesign based on complete testing is developed. Then the effect of the SVC reactive power on the measured power is investigated. All of the contributions of this thesis are validated by simulation on test systems. In addition, there are some specific application of the developed methods to real data to find a.) the mode shape of the Australian electricity network, b.) the contribution of the Brisbane feeder load to damping and c.) the effect of the SVC reactive power of the Blackwall substations on the active power supplying Brisbane.

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Liang, Wuxing. "Moving window subspace identification for power system oscillations." Thesis, Queen's University Belfast, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517098.

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Whitlock, Rogers Jr. "Identification of Power System Stability Using Relevant Modes." ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/1384.

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The purpose of this investigation is to identify appropriate location of capacitor banks and sources of reactive power by studying power system stability in the vicinity of system equilibrium states. The locations for reactive power sources are determined by identifying those modes of the system that participate most in the system behavior in general and in dictating the final state of the system after experiencing faults or disturbances. To identify the relevant modes of the system that participate most in the system dynamic, we shall make use of modal and participation analysis for different system conditions. We also apply modal and participation analysis to a system in order to identify the components of greatest impact that result in the most efficient system control. The ideas developed in this study are used to analyze and identify weak boundaries of the IEEE 39- Bus system that contribute to the system’s instability.

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Fan, Dawei. "Synchronized Measurements And Applications During Power System Dynamics." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/26115.

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Synchronized phasor measurements during dynamics tend to be affected by prevailing system frequency. Some major blackouts in power systems are indeed featured with very large frequency disturbance. Quantitative study done in this dissertation shows that small frequency disturbance may lead to measurement errors, and large frequency disturbance may lead to wrong measurements as well as catastrophic results if applied in system protection and control. The purpose of this dissertation is to bring up this issue, point to some possible solutions and application examples. A synchronized frequency measurement method, which has better dynamic performance, is proposed in this dissertation. Based on this accurate synchronized frequency, a phasor compensation algorithm is proposed to correct the errors due to frequency disturbance in legacy PMUs or as alternative frequency tracking algorithm in new PMUs. Phasor positioning and unbalance issues are also investigated in this dissertation. With these improved synchronized measurements, wide area protection and control can be achieved with higher reliability. As an application example, traditional preset out-of-step protection could be replaced by the adaptive out-of-step protection using wide area measurements. Real-time swing curve and real-time EEAC based adaptive out-of-step protection schemes are developed respectively in this dissertation. Numerical Simulations are performed for validation of the proposed concepts.
Ph. D.

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Khan, Kevin Jamil Hiroshi. "Wide Area Power System Monitoring Device Design and Data Analysis." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/34052.

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The frequency disturbance recorder (FDR) is a cost effective data acquisition device used to measure power system frequency at the distribution level. FDRs are time synchronized via the global positioning system (GPS) timing and data recorded by FDRs are time stamped to allow for comparative analysis between FDRs. The data is transmitted over the internet to a central server where the data is collected and stored for post mortem analysis. Currently, most of the analysis is done with power system frequency.

The purpose of this study is to take a first in depth look at the angle data collected by FDRs. Different data conditioning techniques are proposed and tested before one is chosen. The chosen technique is then used to extract useable angle data for angle analysis on eight generation trip events. The angle differences are then used to create surface plot angle difference movies for further analysis.

A new event detection algorithm, the k-means algorithm, is also presented in this paper. The algorithm is proposed as a simple and fast alternative to the current detection method. Next, this thesis examines several GPS modules and recommends one for a replacement of the current GPS chip, which is no longer in production. Finally, the manufacturing process for creating an FDR is documented.

This thesis may have raised more questions than it answers and it is hoped that this work will lay the foundation for further analysis of angles from FDR data.

Master of Science

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Zhou, Ning. "Subspace methods of system identification applied to power systems." Laramie, Wyo. : University of Wyoming, 2005. http://proquest.umi.com/pqdweb?did=1095432761&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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Shuck, Timothy A. "In-Node, Low Power Vehicle Classification and Identification System." Thesis, California State University, Long Beach, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10978575.

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Traffic in major metropolitan areas is only increasing, requiring transportation authorities to mitigate traffic congestion. Intelligent Transportation Systems (ITS) offer transportation authorities the data needed to accurately measure current traffic patterns and to make accurate predictions of future patterns.

The proposed system is a wireless sensor network (WSN) incorporating small embedded processing nodes equipped with anisotropic magneto resistive (AMR) sensors which detect the magnetic field of passing vehicles for vehicle classification and identification. Machine learning algorithms are implemented to produce a Machine-Learning Vehicle Classification (MLVC) system capable of classifying vehicles without external computation—only transmitting the aggregated results of the classification to system handlers. Various machine-learning algorithms were compared to determine their viability in being deployed in a manner befitting a system with an emphasis in wireless sensor node duration. An in-node decision tree-based implementation was selected to perform the analysis as it offers low-power utilization awhile retaining a high degree of accuracy.

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Tbaileh, Ahmad Anan. "Power System Coherency Identification Using Nonlinear Koopman Mode Analysis." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/49261.

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In this thesis, we apply nonlinear Koopman mode analysis to decompose the swing dynamics of a power system into modes of oscillation, which are identified by analyzing the Koopman operator, a linear infinite-dimensional operator that may be defined for any nonlinear dynamical system. Specifically, power system modes of oscillation are identified through spectral analysis of the Koopman operator associated with a particular observable. This means that they can be determined directly from measurements. These modes, referred to as Koopman modes, are single-frequency oscillations, which may be extracted from nonlinear swing dynamics under small and large disturbances. They have an associated temporal frequency and growth rate. Consequently, they may be viewed as a nonlinear generalization of eigen-modes of a linearized system. Koopman mode analysis has been also applied to identify coherent swings and coherent groups of machines of a power system. This will allow us to carry out a model reduction of a large-scale system and to derive a precursor to monitor the loss of transient stability.
Master of Science

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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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Källman, Jonas. "Ship Power Estimation for Marine Vessels Based on System Identification." Thesis, Linköpings universitet, Reglerteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79248.

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Large marine vessels carry their loads all over the world. It can be a container ship carrying over 10 000 containers filled with foods, textiles and electronics or a bulk freighter carrying 400 000 tons of coal. Vessels usually have a ballast system that pumps water into ballast tanks to stabilize the vessel. The ballast system can be used to change the vessel’s trim and list angles. Trim and list are the ship equivalents of pitch and roll. By changing the trim angle the water resistance can be reduced and thus also the fuel consumption. Since the vessel is consuming a couple of hundred tons of fuel per day, a small reduction in fuel consumption can save a considerable amount of money, and it is good for the environment. In this thesis, the ship’s power consumption has been estimated using an artificial neural network, which is a mathematical model based on data. The name refers to certain structural similarities with the neural synapse system in animals. The idea with neural networks has been to create brain-like systems. For applications such as learning to interpret sensor data, artificial neural networks are an effective learning method. The goal is to estimate the ship power using a artificial neural network and then use it to calculate the trim angle, to be able to save fuel. The data used in the artificial neural network come from sensor systems mounted on a container ship sailing between Europe and Asia. The sensor data have been thoroughly preprocessed and this includes for example removing the parts when the ship is docked in harbour, data patching and synchronisation and outlier detection based on a Kalman filter. A physical model of a marine craft including wind, wave, hydrodynamic and hydrostatic effects, has also been introduced to help analyse the performance and behaviour of the artificial neural network. The artificial neural network developed in this thesis could successfully estimate the power consumption of the ship. Based on the developed networks it can be seen that the fuel consumption is reduced by trimming the ship by bow, i.e., the ship is angled so the bow is closer to the water line than the stern. The method introduced here could also be applied on other marine vessels, such as bulk freighters or tank ships.

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Bogodorova, Tetiana. "Modeling, Model Validation and Uncertainty Identification for Power System Analysis." Doctoral thesis, KTH, Elkraftteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-218008.

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It is widely accepted that correct system modeling and identification are among the most important issues power system operators face when managing instability and post-contingency scenarios. The latter is usually performed involving special computational tools that allow the operator to forecast, prevent system failure and take appropriate actions according to protocols for different contingency cases in the system. To ensure that operators make the correct simulation-based decisions, the power system models have to be validated continuously. This thesis investigates power system modeling, identification and validation problems that are formulated and based on data provided by operators, and offers new methods and deeper insight into stages of an identification cycle considering the specifics of power systems. One of the problems this thesis tackled is the selection of a modeling and simulation environment that provides transparency and possibility for unambiguous model exchange between system operators. Modelica as equation-based language fulfills these requirements. In this thesis Modelica phasor time domain models were developed and software-to-software validated against conventional simulation environments, i.e. SPS/Simulink and PSAT in MATLAB. Parameter estimation tasks for Modelica models require a modular and extensible toolbox. Thus, RaPiD Toolbox, a framework that provides system identification algorithms for Modelica models, was developed in MATLAB. Contributions of this thesis are an implementation of the Particle Filter algorithm and validation metrics for parameter identification. The performance of the proposed algorithm has been compared with Particle Swarm Optimization (PSO) algorithm when combined with simplex search and parallelized to get computational speed up. The Particle Filter outperformed PSO when estimating turbine-governor model parameters in the Greek power plant model relying on real measurements. This thesis also analyses different model structures (Nonlinear AutoRegressive eXogenous (NARX) model, Hammerstein-Wiener model, and high order transfer function) that are selected to reproduce nonlinear dynamics of a Static VAR Compensator (SVC) under incomplete information available for National Grid system operator. The study has shown that standard SVC model poorly reproduces the measured dynamics of the real system. Therefore, black-box mathematical modeling and identification approach has been proposed to solve the problem. Also, the introduced combination of first-principle and black-box approach has shown the best output fit. The methodology following identification cycle together with model order selection and model validation issues was presented in detail. Finally, one of the major contributions is a new method to formulate the uncertainty of parameters estimated in the form of a multimodal Gaussian mixture distribution that is estimated from the Particle Filter output by applying statistical methods to select the standard deviations. The proposed methodology gives additional insight into power system properties when estimating the parameters of the model. This allows power system analysts to decide on the design of validation tests for the chosen model.
Det är allmänt accepterat att korrekt modellering och identifiering av systemet är bland de mest viktiga utmaningarna som kraftsystemoperatörer ställs inför när de hanterar scenarior med instabiliteter och oförutsedda händelser. Det senare är vanligen hanterat med speciella beräkningsverktyg som låter operatören förutse utvecklingen och utföra lämpliga åtgärder enligt de protokoll som finns vid olika systemhändelser. För att försäkra sig om att operatörer tar de korrekta, simuleringsbaseda besluten måste kraftsystemsmodellen kontinuerligt valideras. Denna avhandling undersöker problem inom modellering, identifiering och validering av kraftsystem, formulerade och baserade på data tillhandahållet av operatörer, samt erbjuder nya metoder och fördjupade insikter i delar av en identifieringscykel som beaktar kraftsystemets. Ett av de problem som denna avhandling tar upp är val av en programmiljö för simulering och modellering som ger transparens och möjlighet till otvetydigt modellutbyte mellan systemoperatörer. Modelica är ett ekvationsbaserat programspråk som uppfyller dessa krav. I denna avhandling utvecklades enfasekvivalenter i Modelica som blev validerade mot konventionella program för simulering, såsom SPS/Simulink och PSAT i MATLAB. Parameterestimering i Modelica-modellerna kräver en modulär och utbyggbar verktygslåda. Därför har verktyget RaPiD Toolbox, som tillhandahåller systemidentifieringsalgoritmer för Modelica-modeller, utvecklats i MATLAB. Bidrag från denna avhandling är en implementation av ett partikelfilter (en sekventiell Monte Carlo-metod) och valideringsmetrik för parameteridentifiering. Prestandan i den föreslagna algoritmen har jämförts med partikelsvärmoptimering (PSO) då den är kombinerad med simplexsök och parallellisering. Partikelfiltret överträffade PSO när modellparametrar i turbinregulatorn i ett grekiskt kraftverk skulle estimeras utifrån verklig mätdata. Avhandling analyserar också olika modellstrukturer (NARX, Hammerstein-Wiener-modeller, och överföringsfunktioner med höga ordningstal) som används för att reproducera den ickelinjära dynamiken hos statiska reaktiv effekt-kompenserare (SVC) vid ofullständig information som är tillgänglig för systemoperatören National Grid. Undersökningen visar att den vanliga SVC-modellen är dålig på att reproducera den verkliga, uppmätta dynamiken. Genom att matematiskt modellera problemet som en svart låda har en identifieringsmetod föreslagits. Vidare, genom att kombinera modelleringen som en svart låda med fysikaliska principer har givit den bästa anpassningen till utdata. Metodologin för identifieringscykeln tillsammans med valet av modellkomplexitet och svårigheter med modellvalidering har utförligt presenterats. Slutligen, ett av de främsta bidragen är en ny metod för att formulera osäkerheten i parameteruppskattningarna i form av en blandning av normalfördelningar med flera typvärden som estimeras med partikelfiltrets utdata genom att använda statistiska metoder för att välja standardavvikelsen. Detta ger kraftsystemanalytiker möjlighet att utforma valideringstest för den valda modellen.

QC 20171121

EU FP7 iTesla project

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20

Raich, Raviv. "Nonlinear system identification and analysis with applications to power amplifier modeling and power amplifier predistortion." Diss., Available online, Georgia Institute of Technology, 2004:, 2004. http://etd.gatech.edu/theses/available/etd-04072004-130800/unrestricted/raich%5Fraviv%5F200405%5Fphd.pdf.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2004.
Xiaoming Huo, Committee Member ; J. Stevenson Kenney, Committee Member ; Douglas Williams, Committee Member ; Erik Verriest, Committee Member ; G. Tong Zhou, Committee Chair. Vita. Includes bibliographical references (leaves 170-179).

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CANTERA, JOSE MARIA CALVO. "DETECTION AND IDENTIFICATION OF ANOMALIES IN POWER SYSTEM DYNAMIC STATE ESTIMATION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1987. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9891@1.

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ELETROBRAS - CENTRAIS ELÉTRICAS BRASILEIRAS S. A.
Este trabalho apresenta uma comparação entre o desempenho dos estimadores dinâmicos e rastreador, em sistemas de potência operando sob condições quase-estacionárias, considerando suas características de previsão e filtragem. A partir desta comparação, propõe-se um estimador dinâmico que incorpora as principais vantagens dos estimadores previamente mencionados. Além disso, apresenta-se um novo esquema de detecção e identificação de anormalidades (erros grosseiros nas medidas, mudanças brusca no ponto de operação do sistema e erros na configuração da rede), esquema este apropriadamente construído para algoritmos de estimação dinâmica. Resultados numéricos ilustram o desempenho deste novo algoritmo sob diferentes condições operativas.
This work presents a comparison between the performance of dynamic and tracking estimators, in power systems operating under quasi-static conditions, concerning their characteristics of forecasting and filtering. From this comparison, a new dynamic estimator which incorporates the main advantages of the previous estimators is proposed. Also, a new scheme of detection and identification of anomalies (gross errors in the measurements, sudden changes in the system operating point and errors in the network configuration) is presented. This scheme is properly built for dynamic algorithms. Numerical results showing the performance of the new algorithm under different operational conditions are discussed.

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Wang, Lei. "Printed Circuit Board Design for Frequency Disturbance Recorder." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/30917.

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The FDR (Frequency Disturbance Recorder) is a data acquisition device for the power system. The device is portable and can be used with any residential wall outlet for frequency data collection. Furthermore, the FDR transmits calculated frequency data to the web for access by authorized users via Ethernet connection. As a result, Virginia Tech implemented Frequency Monitoring Network (FNET) with these FDR devices. FNET is a collection of identical FDRs placed in different measurement sites to allow for data integration and comparison. Frequency is an important factor for power system control and stabilization. With funding and support provided by ABB, TVA and NSF the FDRs are placed strategically all over the United States for frequency analysis, power system protection and monitoring.

The purpose of this study is to refine the current FDR hardware design and establish a new design that will physically fit all the components on one Printed Circuit Board (PCB). At the same time, the software that is to be implemented on the new board is to be kept similar if not the same as that of the current design. The current FDR uses the Axiom CME555 development board and it is interfaced to the external devices through its communication ports. Even through the CME555 board is able to meet the demands of the basic FDR operations, there are still several problems associated with this design. This paper will address some of those hardware problems, as well as propose a new board design that is specifically aimed for operations of FDR.

Master of Science

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23

Zhong, Zhian. "Power Systems Frequency Dynamic Monitoring System Design and Applications." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28707.

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Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet. The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation.
Ph. D.

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24

Chen, Jie. "Fault Section Identification for Power Distribution Systems Using Online Measurements." UKnowledge, 2015. http://uknowledge.uky.edu/ece_etds/70.

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Fault location is very important for distribution systems, and quickly identifying the fault and restoring the system can help reduce the outage time and make the system more reliable. In this thesis, a method for locating faults on distribution systems is introduced to quickly identify the faulted feeder sections by using the overcurrent information from the switches in the system. Fuzzy logic is utilized. The proposed method can quickly and accurately locate faulted sections with different fault locations, fault types and fault resistances. The method is applicable to cases with single-faults or multi-faults, and is applicable to networks with multi-sources. The case study has demonstrated the effectiveness of the proposed method.

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25

Altintas, Erinc. "Flicker Source Identification At A Point Of Common Coupling Of The Power System." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611919/index.pdf.

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Voltage fluctuations under 30 Hz in the electricity grid, leads to oscillations in the light intensity that can be perceived by human eye, which is called flicker. In this thesis, the sources of the flicker at a point of common coupling is investigated. When there are more than one flicker sources connected to a PCC, individual effects of each flicker source is determined by using a new method which depends on the reactive current components of the sources. This method is mainly based on the flickermeter design defined by the International Electrotechnical Commission (IEC), but uses the current variations in addition to the voltage variations to compute flicker. The proposed method is applied to several different types of loads supplied from a PCC and their flicker contributions on the busbar are investigated. Experiments are performed on field data obtained by the power quality analyzers (PQ+) developed by the National Power Quality Project and the method has been found to provide accurate results for flicker contributions of various loads. The PQ+ analyzers with the proposed flicker contribution detection algorithm are called Flicker Contribution Meters (FCM) and they will be installed at the points of the Turkish Electricity Transmission Network when required.

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26

Abusorrah, Abdullah. "The application of the continuous wavelet transform to power system identification and protection." Thesis, University of Nottingham, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.438559.

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27

Wang, Joshua Kevin. "Identification, Analysis, and Control of Power System Events Using Wide-Area Frequency Measurements." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26250.

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The power system has long been operated in a shroud of introspection. Only recently have dynamic, wide-area time synchronized grid measurements brought to light the complex relationships between large machines thousands of miles apart. These measurements are invaluable to understanding the health of the system in real time, for disturbances to the balance between generation and load are manifest in the propagation of electromechanical waves throughout the grid. The global perspective of wide-area measurements provides a platform from which the destructive effects of these disturbances can be avoided. Virginia Tech's distributed network of low voltage frequency monitors, FNET, is able to track these waves as they travel throughout the North American interconnected grids. In contrast to other wide-area measurement systems, the ability to easily measure frequency throughout the grid provides a way to identify, locate, and analyze disturbances with high dynamic accuracy. The unique statistical properties of wide-area measurements require robust tools in order to accurately understand the nature of these events. Expert systems and data conditioning can then be used to quantify the magnitude and location of these disturbances without requiring any knowledge of the system state or topology. Adaptive application of these robust methods form the basis for real-time situational awareness and control. While automated control of the power system rarely utilize wide-area measurements, global insight into grid behavior can only improve disturbance rejection.
Ph. D.

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28

Ha, Jaejoo. "CBDS : constraint based diagnostic system for malfunction identification in the nuclear power plant /." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487776210792359.

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29

Dieker, Joseph. "High impedance fault location identification using Bayesian analysis in a shipboard power system." Thesis, Kansas State University, 2012. http://hdl.handle.net/2097/14643.

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Master of Science
Department of Electrical and Computer Engineering
Sanjoy Das
Noel Schulz
In a shipboard power system (SPS) there are many possible locations for faults along power lines. It is important to identify the location and isolate these faults in order to protect the equipment and loads. The shipboard systems represented in this research are based on an all-electric ship that is presented by Corzine and a simplified version of the same ship. This research considers faults at the ends on the lines. Sensors collect data in order to determine where the fault has occurred. The fault location identification algorithm being presented uses data collected from simulations of different switch configurations and different loads. After the data is collected, Bayesian techniques are used to determine where the fault is located. An online training technique is presented to adjust to changes in loads over time to increase the accuracy of the algorithm.

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30

Radesjö, Fanny. "Parameter Identification and Information Modeling of Gas Turbine Models for Power System Simulations." Thesis, KTH, Industriell ekologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-210738.

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In the future renewable generation sources will have to co-exist with traditional generation sources that can overcome their limitations in providing secure power supply to society, such as gas turbines. In this project we proposed to substitute a simple model of a gas turbine by a detailed model to simulate the turbine´s behavior in a real system. Parameter identification of a simple gas turbine model was performed based on measurements from a detailed model. By this, the project contributes to a library of electric grid component models. The library is meant to allow operators and engineers to predict the system behavior by simulations. This can facilitate to anticipate possible instability in the grid and thereby contribute to the transition to the Smart Grid. Further, another gas turbine model was in the Modelica language was represented using the Unified Modeling Language (UML). This is a standard form of modelling that simplifies exchange of model information between project groups.

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Oveisi, Atta [Verfasser], Tamara [Gutachter] Nestorović, and Dirk [Gutachter] Söffker. "System identification and model-based robust nonlinear disturbance rejection control / Atta Oveisi ; Gutachter: Tamara Nestorović, Dirk Söffker ; Fakultät für Maschinenbau." Bochum : Ruhr-Universität Bochum, 2021. http://d-nb.info/1235224309/34.

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Man, Sau Wing. "Low power VLSI baseband system design for EPC C1G2 radio frequency identification (RFID) applications /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?ECED%202007%20MAN.

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Guo, Tingyan. "On-line identification of power system dynamic signature using PMU measurements and data mining." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/online-identification-of-power-system-dynamic-signature-using-pmu-measurements-and-data-mining(989938d4-c236-48a7-a653-17326937f5b4).html.

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This thesis develops a robust methodology for on-line identification of power system dynamic signature based on incoming system responses from Phasor Measurement Units (PMUs) in Wide Area Measurement Systems (WAMS). Data mining techniques are used in the methodology to convert real-time monitoring data into transient stability information and the pattern of system dynamic behaviour in the event of instability. The future power system may operate closer to its stability limit in order to improve its efficiency and economic value. The changing types and patterns of load and generation are resulting in highly variable operating conditions. Corrective control and stabilisation is becoming a potentially viable option to enable safer system operation. In the meantime, the number of WAMS projects and PMUs is rising, which will significantly improve the system situational awareness. The combination of all these factors means that it is of vital importance to exploit a new and efficient Transient Stability Assessment (TSA) tool in order to use real-time PMU data to support decisions for corrective control actions. Data mining has been studied as the innovative solution and considered as promising. This work contributes to a number of areas of power systems stability research, specifically around the data driven approach for real-time emergency mode TSA. A review of past research on on-line TSA using PMU measurements and data mining is completed, from which the Decision Tree (DT) method is found to be the most suitable. This method is implemented on the test network. A DT model is trained and the sensitivity of its prediction accuracy is assessed according to a list of network uncertainties. Results showed that DT is a useful tool for on-line TSA for corrective control approach. Following the implementation, a generic probabilistic framework for the assessment of the prediction accuracy of data mining models is developed. This framework is independent of the data mining technique. It performs an exhaustive search of possible contingencies in the testing process and weighs the accuracies according to the realistic probability distribution of uncertain system factors, and provides the system operators with the confidence level of the decisions made under emergency conditions. After that, since the TSA for corrective control usually focuses on transient stability status without dealing with the generator grouping in the event of instability, a two-stage methodology is proposed to address this gap and to identify power system dynamic signature. In this methodology, traditional binary classification is used to identify transient stability in the first stage; Hierarchical Clustering is used to pre-define patterns of unstable dynamic behaviour; and different multiclass classification techniques are investigated to identify the patterns in the second stage. Finally, the effects of practical issues related to WAMS on the data mining methodologies are investigated. Five categories of issues are discussed, including measurement error, communication noise, wide area signal delays, missing measurements, and a limited number of PMUs.

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34

Gianto, Rudy. "Coordination of power system controllers for optimal damping of electromechanical oscillations." University of Western Australia. School of Electrical, Electronic and Computer Engineering, 2008. http://theses.library.uwa.edu.au/adt-WU2009.0056.

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This thesis is devoted to the development of new approaches for control coordination of PSSs (power system stabilisers) and FACTS (flexible alternating current transmission system) devices for achieving and enhancing small-disturbance stability in multi-machine power systems. The key objectives of the research reported in the thesis are, through optimal control coordination of PSSs and/or FACTS devices, those of maintaining satisfactory power oscillation damping and secure system operation when the power system is subject to persisting disturbances in the form of load demand fluctuations and switching control. Although occurring less frequently, fault disturbances are also considered in the assessment of the control coordination performance. Based on the constrained optimisation method in which the eigenvalue-based objective function is minimised to identify the optimal parameters of power system damping controllers, the thesis first develops a procedure for designing the control coordination of PSSs and FACTS devices controllers. The eigenvalue-eigenvector equations associated with the selected electromechanical modes form a set of equality constraints in the optimisation. The key advance of the procedure is that there is no need for any special software system for eigenvalue calculations, and the use of sparse Jacobian matrix for forming the eigenvalue-eigenvector equations leads to the sparsity formulation which is essential for large power systems. Inequality constraints include those for imposing bounds on the controller parameters. Constraints which guarantee that the modes are distinct ones are derived and incorporated in the control coordination formulation, using the property that eigenvectors associated with distinct modes are linearly independent. The robustness of the controllers is achieved very directly through extending the sets of equality constraints and inequality constraints in relation to selected eigenvalues and eigenvectors associated with the state matrices of power systems with loading conditions and/or network configurations different from that of the base case. On recognising that the fixed-parameter controllers, even when designed with optimal control coordination, have an inherent limitation which precludes optimal system damping for each and every possible system operating condition, the second part of ii the research has a focus on adaptive control techniques and their applications to power system controllers. In this context, the thesis reports the development of a new design procedure for online control coordination which leads to adaptive PSSs and/or supplementary damping controllers (SDCs) of FACTS devices for enhancing the stability of the electromechanical modes in a multi-machine power system. The controller parameters are adaptive to the changes in system operating condition and/or configuration. Central to the design is the use of a neural network synthesised to give in its output layer the optimal controller parameters adaptive to system operating condition and configuration. A novel feature of the neural adaptive controller is that of representing the system configuration by a reduced nodal impedance matrix which is input to the neural network.

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35

Ghasemi, Hassan. "On-line Monitoring and Oscillatory Stability Margin Prediction in Power Systems Based on System Identification." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/834.

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Poorly damped electromechanical modes detection in a power system and corresponding stability margins prediction are very important in power system planning and operation, and can provide significant help to power system operators with preventing stability problems.

Stochastic subspace identification is proposed in this thesis as a technique to extract the critical mode(s) from the measured ambient noise without requiring artificial disturbances (e. g. a line outage), allowing these critical modes to be used as an on-line index, which is referred here to as System Identification Stability Indices (SISI) to predict the closest oscillatory instability. The SISI is not only independent of system models and truly representative of the actual system, but also computationally efficient. In addition, readily available signals in a power system and several identification methods are categorized, and merits and pitfalls of each one are addressed in this work.

The damping torque of linearized models of power systems is studied in this thesis as another possible on-line security index. This index is estimated by means of proper system identification techniques applied to both power system transient response and ambient noise. The damping torque index is shown to address some of drawbacks of the SISI.

This thesis also demonstrates the connection between the second order statistical properties, including confidence intervals, of the estimated electromechanical modes and the variance of model parameters. These analyses show that Monte-Carlo type of experiments or simulations can be avoided, hence resulting in a significant reduction in the number of samples.

In these types of studies, the models available in simulation packages are extremely important due to their unquestionable impact on modal analysis results. Hence, in this thesis, the validity of generator subtransient model and a typical STATCOM transient stability (TS) model are also investigated by means of system identification, illustrating that under certain conditions the STATCOM TS model can yield results that are too optimistic, which can lead to errors in power system planning and operation.

In addition to several small test systems used throughout this thesis, the feasibility of the proposed indices are tested on a realistic system with 14,000 buses, demonstrating their usefulness in practice.

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36

Kuo, Shih-Kang. "Development of a magnetic suspension system and its applications in nano-imprinting and nano-metrology." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1054236218.

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Thesis (Ph. D.)--Ohio State University, 2003.
Title from first page of PDF file. Document formatted into pages; contains x, 175 p.; also includes graphics (some col.) Includes bibliographical references (p. 170-175). Available online via OhioLINK's ETD Center

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37

Xu, Chunchun. "High Accuracy Real-time GPS Synchronized Frequency Measurement Device for Wide-area Power Grid Monitoring." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/27007.

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Frequency dynamics is one of the most important signals of a power system, and it is an indicator of imbalance between generation and load in the system. The Internet-based real-time GPS-synchronized wide-area Frequency Monitoring Network (FNET) was proposed to provide imperative frequency dynamics information for a variety of system-wide monitoring, analysis and control applications. The implementation of FNET has for the first time made the synchronized observation of the entire U.S. power network possible with very little cost. The FNET is comprised of many Frequency Disturbance Recorders (FDR) geographically dispersed throughout the U.S. and an Information Management System (IMS), currently located at Virginia Tech. The FDR works as a sensor, which performs local measurements and transmits calculations of frequency, voltage magnitude and voltage angle to the remote servers via the Internet. Compared with its commercial counterpart Phasor Measurement Unit (PMU), FDR provides less expensive version for networked high-resolution real-time synchronized. The improved single phase algorithm in the FDRs made it possible to measure at 110V level which is much more challenging than PMUs due to the noise involved at this level. This research work presents the challenges and issues of both software and hardware design for the novel measurement device FDR, which is one of the devices with the highest dynamic precision for power system frequency measurement. The DFT-based Phasor Angle Analysis algorithm has been improved to make sure the high-resolution measuring FDRs are installed at residential voltage outlets, instead of substation high-voltage inputs. An embedded 12-channel timing GPS receiver has been integrated to provide an accurate timing synchronization signal, UTC time stamp, and unit location. This research work also addresses the harmonics, voltage swing and other noise components' impacts on the measurement results, and the optimized design of filters and a coherent sampling scheme to reduce or eliminate those impacts. The verification test results show that the frequency measurement accuracy of the FDR is within +/-0.0005Hz, and the time synchronization error is within +/-500ns with suitable GPS antenna installation. The preliminary research results show the measurement accuracy and real-time performance of the FDR are satisfactory for a variety of FNET applications, such as disturbance identification and event location triangulation.
Ph. D.

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38

Ahmeid, Mohamed. "Real-time system identification and self-tuning control of DC-DC power converter using Kalman Filter approach." Thesis, University of Newcastle upon Tyne, 2017. http://hdl.handle.net/10443/3772.

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Switch-mode power converters (SMPCs) are employed in many industrial and consumer devices. Due to the continuous reduction in cost of microprocessors, and improvements in the processing power, digital control solutions for SMPCs have become a viable alternative to traditional analogue controllers. However, in order to achieve high-performance control of modern DC-DC converters, using direct digital design techniques, an accurate discrete model of the converter is necessary. This model can be acquired by means of prior knowledge about the system parameters or using system identification methods. For the best performance of the designed controller, the system identification methods are preferred to handle the model uncertainties such as component variations and load changes. This process is called indirect adaptive control, where the model is estimated from input and output data using a recursive algorithm and the controller parameters are tuned and adjusted accordingly. In the parameter estimation step, Recursive Least Squares (RLS) method and its modifications exhibit very good identification metrics (fast convergence rate, accurate estimate, and small prediction error) during steady-state operation. However, in real-time implementation, the accuracy of the estimated model using the RLS algorithm is affected by measurement noise. Moreover, there is a need to continuously inject an excitation signal to avoid estimator wind-up. In addition, the computational complexity of RLS algorithm is high which demands significant hardware resources and hence increase the overall cost of the digital system. For these reasons, this thesis presents a robust parametric identification method, which has the ability to provide accurate estimation and computationally efficient self-tuning controller suitable for real-time implementation in SMPCs systems. This thesis presents two complete real-time solutions for parametric system identification and explicit self-tuning control for SMPCs. The first is a new parametric estimation method, based on a state of the art Kalman Filter (KF) algorithm to estimate the discrete model of a synchronous DC-DC buck converter. The proposed method can accurately identify the discrete coefficients of the DC-DC converter. This estimator possesses the advantage of providing an independent strategy for adaptation of each individual parameter; thus offering a robust and reliable solution for real-time parameter estimation. To improve the tracking performance of the proposed KF, an adaptive tuning technique is proposed. Unlike many other published schemes, this approach offers the unique advantage of updating the parameter vector coefficients at different rates. This thesis also validates the performance of the identification algorithm with time-varying parameters; such as an abrupt load change. Furthermore, the proposed method demonstrates robust estimation with and without an excitation signal, which makes it very well suited for real-time power electronic control applications. Additionally, the estimator convergence time is significantly shorter compared to many other schemes, such as the classical Exponentially weighted Recursive Least Square (ERLS) method. To design a computationally efficient self-tuning controller for DC-DC SMPCs, the second part of the thesis develops a complete package for real-time explicit self-tuning control. The novel partial update KF (PUKF) is introduced for real-time parameter estimation. In this approach, a significant complexity reduction is attained as the number of arithmetic operations are reduced, more specifically the computation of adaptation gains and covariance updates. The explicit self-tuning control scheme is constructed via integrating the developed PUKF with low complexity control algorithm such as Bányász/Keviczky PID controller. Experimental and simulation results clearly show an enhancement in the overall dynamic performance of the closed loop control system compared to the conventional PID controller designed based on a pre-calculated average model. Importantly, in this thesis, unlike a significant proportion of existing literature, the entire system identification, and closed loop control process is seamlessly implemented in real-time hardware, without any remote intermediate post processing analysis.

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Tuffner, Francis K. "Computationally efficient weighted updating of statistical parameter estimates for time varying signals with application to power system identification." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1674094221&sid=4&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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40

Graham, James. "Intelligent power management for unmanned vehicles." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/18026.

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Unmanned Air Vehicles (UAVs) are becoming more widely used in both military and civilian applications. Some of the largest UAVs have power systems equivalent to that of a military strike jet making power management an important aspect of their design. As they have developed, the amount of power needed for loads has increased. This has placed increase strain on the on-board generators and a need for higher reliability. In normal operation these generators are sized to be able to power all on-board systems with out overheating. Under abnormal operating conditions these generators may start to overheat, causing the loss of the generator's power output. The research presented here aims to answer two main questions: 1) Is it possible to predict when an overheat fault will occur based on the expected power usage defined by mission profiles? 2) Can an overheat fault be prevented while still allowing power to be distributed to necessary loads to allow mission completion? This is achieved by a load management algorithm, which adjusts the load profile for a mission, by either displacing the load to spare generators, or resting the generator to cool it down. The result is that for non-catastrophic faults the faulty generator does not need to be fully shut down and missions can continue rather than having to be aborted. This thesis presents the development of the load management system including the algorithm, prediction method and the models used for prediction. Ultimately, the algorithms developed are tested on a generator test rig. The main contribution of this work is the design of a prognostic load management algorithm. Secondary contributions are the use of a lumped parameter thermal model within a condition monitoring application, and the creation of a system identification model to describe the thermal dynamics of a generator.

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41

Mailhot, Nathaniel. "Pupil Tracking and Control of a Laser Based Power System for a Vision Restoring Retinal Implant." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/38709.

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For elderly Canadians, the prevalence of vision impairment caused by degenerative retinal pathologies, such as age-related macular degeneration and retinitis pigmentosa, is at an occurrence rate of 14 percent, and on the rise. It has been shown that visual function can be restored by electrically stimulating intact retinal tissue with an array of micro-electrodes with suitable signals. Commercial retinal implants carrying such a micro-electrode array achieve this, but to date must receive power and data over copper wire cable passing through a permanent surgical incision in the eye wall (sclera). This project is defined by a collaboration with iBIONICS, who are developing retinal implants for treatment of such conditions. iBIONICS has developed the Diamond Eye retinal implant, along with several technology sub-systems to form a comprehensive and viable medical solution. Notably, the Diamond Eye system can be powered wirelessly, with no need for a permanent surgical incision. The thesis work is focused on the formulation, simulation and hardware demonstration of a powering system, mounted on glasses frame, for a retinal implant. The system includes a Micro-Electro-Mechanical System (MEMS) mirror that directs a laser beam to the implant through the pupil opening. The work presented here is built on two main components: an iterative predictor-corrector algorithm (Kalman filter) that estimates pupil coordinates from measurements provided by an image-based eye tracking algorithm; and an misalignment compensation algorithm that maps eye pupil coordinates into mirror coordinates, and compensates for misalignment caused by rigid body motions of the glasses lens mirror and the MEMS mirror with respect to the eye. Pupil tracker and misalignment compensation control performance are illustrated through simulated scenarios. The project also involves the development of a hardware prototype that is used to test algorithms and related software.

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42

Schmitt, Andreas Joachim. "Power System Parameter Estimation for Enhanced Grid Stability Assessment in Systems with Renewable Energy Sources." Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/83459.

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The modern day power grid is a highly complex system; as such, maintaining stable operations of the grid relies on many factors. Additionally, the increased usage of renewable energy sources significantly complicates matters. Attempts to assess the current stability of the grid make use of several key parameters, however obtaining these parameters to make an assessment has its own challenges. Due to the limited number of measurements and the unavailability of information, it is often difficult to accurately know the current value of these parameters needed for stability assessment. This work attempts to estimate three of these parameters: the Inertia, Topology, and Voltage Phasors. Without these parameters, it is no longer possible to determine the current stability of the grid. Through the use of machine learning, empirical studies, and mathematical optimization it is possible to estimate these three parameters when previously this was not the case. These three methodologies perform estimations through measurement-based approaches. This allows for the obtaining of these parameters without required system knowledge, while improving results when systems information is known.
Ph. D.

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43

Kalkan, Ekrem. "Demand Estimation, Relevant Market Definition And Identification Of Market Power In Turkish Beverage Industry." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611636/index.pdf.

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This dissertation aims to contribute to the field of economics of competition policy by analyzing the demand structure and the market power in the Turkish beverage industry and in the cola market in particular. First, a demand system for the beverage products has been estimated by using a multi-stage linearized Almost Ideal Demand System (AIDS). Using the own-price elasticity of cola in a SSNIP test (Small but Significant Non-Transitory Increase in Price), it is shown that cola market consists of a distinct relevant product market. Then, the demand elasticities of cola products at brand and package level have been estimated by the simple and nested logit models. Finally, the estimated demand elasticities of cola products have been used in measuring the degree of market power and predicting the effects of a hypothetical merger between Pepsi and Cola Turca by using a merger simulation technique. The results show that all cola suppliers have large price-cost margins for most of their products. Prices of the merging parties increase in average by 15 - 21% after the merger. The merger also causes the market price to increase by 16- 22% and consumer surplus to decrease by nearly 5% in average. Finally, depending on these results, the thesis recommends a stricter merger control criterion than dominance criterion for competition policy in Turkey.

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Gerini, Francesco. "Locating lightning strikes and flashovers along overhead power transmission lines using electromagnetic time reversal based similarity characteristics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.

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Questo lavoro di tesi si pone l’obiettivo di analizzare, verificare e implementare un nuovo metodo per la localizzazione di guasti in rete e fulminazioni basato sulla teoria ”Electromagnetic Time Reversal”. L’applicabilità della teoria è inizialmente discussa, successivamente utilizzando le classiche equazioni delle linee e le basi della teoria EMTR viene proposta una soluzione analitica per la localizzazione del guasto e/o della fulminazione. La accuratezza del metodo utilizzato viene discussa in relazione al numero di misure necessarie alla localizzazione mettendo in evidenza pro e contro rispetto alle tecniche attuali. Viene in seguito presentato un secondo metodo di localizzazione anch’esso basato sulla teoria EMTR ma non ancora verificato su un grande numero di casi, chiamato Similarity Property Method. Utilizzando il software EMTP per l’analisi di transitori e con l’ausilio di MatLab entrambi i metodi vengono testati su diverse tipologie di reti e con diverse condizioni al contorno. Infine una analisi conclusiva viene proposta, indicando come e se i metodi presentati possono essere da considerare migliorativi delle attuali tecniche di localizzazione di guasti e/o fulminazioni.

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Axelberg, Peter. "On Tracing Flicker Sources and Classification of Voltage Disturbances." Doctoral thesis, Högskolan i Borås, Institutionen Ingenjörshögskolan, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-3416.

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Developments in measurement technology, communication and data storage have resulted in measurement systems that produce large amount of data. Together with the long existing need for characterizing the performance of the power system this has resulted in demand for automatic and efficient information-extraction methods. The objective of the research work presented in this thesis was therefore to develop new robust methods that extract additional information from voltage and current measurements in power systems. This work has contributed to two specific areas of interest.The first part of the work has been the development of a measurement method that gives information how voltage flicker propagates (with respect to a monitoring point) and how to trace a flicker source. As part of this work the quantity of flicker power has been defined and integrated in a perceptionally relevant measurement method. The method has been validated by theoretical analysis, by simulations, and by two field tests (at low-voltage and at 130-kV level) with results that matched the theory. The conclusion of this part of the work is that flicker power can be used for efficient tracing of a flicker source and to determine how flicker propagates.The second part of the work has been the development of a voltage disturbance classification system based on the statistical learning theory-based Support Vector Machine method. The classification system shows always high classification accuracy when training data and test data originate from the same source. High classification accuracy is also obtained when training data originate from one power network and test data from another. The classification system shows, however, lower performance when training data is synthetic and test data originate from real power networks. It was concluded that it is possible to develop a classification system based on the Support Vector Machine method with “global settings” that can be used at any location without the need to retrain. The conclusion is that the proposed classification system works well and shows sufficiently high classification accuracy when trained on data that originate from real disturbances. However, more research activities are needed in order to generate synthetic data that have statistical characteristics close enough to real disturbances to replace actual recordings as training data.

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Men, Kun. "Long term voltage stability analysis for small disturbances." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2499.

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Zhong, Shan. "Measurement calibration/tuning & topology processing in power system state estimation." Texas A&M University, 2003. http://hdl.handle.net/1969.1/1595.

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State estimation plays an important role in modern power systems. The errors in the telemetered measurements and the connectivity information of the network will greatly contaminate the estimated system state. This dissertation provides solutions to suppress the influences of these errors. A two-stage state estimation algorithm has been utilized in topology error identification in the past decade. Chapter II discusses the implementation of this algorithm. A concise substation model is defined for this purpose. A friendly user interface that incorporates the two-stage algorithm into the conventional state estimator is developed. The performances of the two-stage state estimation algorithms rely on accurate determination of suspect substations. A comprehensive identification procedure is described in chapter III. In order to evaluate the proposed procedure, a topology error library is created. Several identification methods are comparatively tested using this library. A remote measurement calibration method is presented in chapter IV. The un-calibrated quantities can be related to the true values by the characteristic functions. The conventional state estimation algorithm is modified to include the parameters of these functions. Hence they can be estimated along with the system state variables and used to calibrate the measurements. The measurements taken at different time instants are utilized to minimize the influence of the random errors. A method for auto tuning of measurement weights in state estimation is described in chapter V. Two alternative ways to estimate the measurement random error variances are discussed. They are both tested on simulation data generated based on IEEE systems. Their performances are compared. A comprehensive solution, which contains an initialization process and a recursively updating process, is presented. Chapter VI investigates the errors introduced in the positive sequence state estimation due to the usual assumptions of having fully balanced bus loads/generations and continuously transposed transmission lines. Several tests are conducted using different assumptions regarding the availability of single and multi-phase measurements. It is demonstrated that incomplete metering of three-phase system quantities may lead to significant errors in the positive sequence state estimates for certain cases. A novel sequence domain three-phase state estimation algorithm is proposed to solve this problem.

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Antoine, Olivier. "Wide area measurement-based approach for assessing the power flow influence on inter-area oscillations." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209368.

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Power systems have been historically designed at a time when the production was

centralized and the electricity had to be transmitted to the loads from the closest power

plant. Nowadays, there is an increasing integration of decentralized and intermittent pro-

duction. Moreover, the energy market coupling has enabled the transfer of electric power

for economical purposes. Also, former isolated power systems are now interconnected for

reliability and financial reasons.

All of these changes make difficult to predict the future behavior of the grid. Studies

are done in order to plan for the future needs of the system. However, building new in-

frastructures takes time and it is expected that these needs will not be completely fulfilled

in all the parts of the grid. Therefore, transmission of active power could be limited by

the existing infrastructure. For example, the presence of inter-area oscillations is often

the limiting factor when a high active power is transmitted on a long transmission line

between two groups of generators. Since higher levels of active power are exchanged on

longer distances, problems of inter-area oscillations may arise in power systems previously

not affected by this phenomenon.

In this work, a measurement-based approach, able to predict in the short-term the

future behavior of oscillations, is presented. This approach is complementary to the

long-term planning of the grid.

The mandatory first step towards a measurement-based approach is to have the ability

to extract useful information among a huge quantity of data. To face this issue, some

comparisons of data mining algorithms are performed. The proposed method combines

two decision tree algorithms to obtain both prediction accuracy and comprehensibility.

The second required step for building a measurement-based model is to take into

account the limitations of the measurements. Two types of wide area measurements are

used, synchronized measurements from PMUs and traditional unsynchronized data from

the SCADA/EMS system. Oscillation monitoring using PMUs is especially of interest

and an approach is presented to post-process damping estimates. This post-processing

method consists in a noise reduction technique followed by a damping change detection

algorithm.

Finally, the method, combining these two steps, is implemented to analyze the Con-

tinental European grid. This implementation takes place in the context of the European

project Twenties. The results, using several months of measurements, are described in

detail before being discussed.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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Netto, Marcos. "Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/87728.

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The study of nonlinear dynamical systems via the spectrum of the Koopman operator has emerged as a paradigm shift, from the Poincaré's geometric picture that centers the attention on the evolution of states, to the Koopman operator's picture that focuses on the evolution of observables. The Koopman operator-theoretic framework rests on the idea of lifting the states of a nonlinear dynamical system to a higher dimensional space; these lifted states are referred to as the Koopman eigenfunctions. To determine the Koopman eigenfunctions, one performs a nonlinear transformation of the states by relying on the so-called observables, that is, scalar-valued functions of the states. In other words, one executes a change of coordinates from the state space to another set of coordinates, which are denominated Koopman canonical coordinates. The variables defined on these intrinsic coordinates will evolve linearly in time, despite the underlying system being nonlinear. Since the Koopman operator is linear, it is natural to exploit its spectral properties. In fact, the theory surrounding the spectral properties of linear operators has well-known implications in electric power systems. Examples include small-signal stability analysis and direct methods for transient stability analysis based on the Lyapunov function. From the applications' standpoint, this framework based on the Koopman operator is attractive because it is capable of revealing linear and nonlinear modes by only applying well-established tools that have been developed for linear systems. With the challenges associated with the high-dimensionality and increasing uncertainties in the power systems models, researchers and practitioners are seeking alternative modeling approaches capable of incorporating information from measurements. This is fueled by an increasing amount of data made available by the wide-scale deployment of measuring devices such as phasor measurement units and smart meters. Along these lines, the Koopman operator theory is a promising framework for the integration of data analysis into our mathematical knowledge and is bringing an exciting perspective to the community. The present dissertation reports on the application of the Koopman operator for identification, estimation, and control of electric power systems. A dynamic state estimator based on the Koopman operator has been developed and compares favorably against model-based approaches, in particular for centralized dynamic state estimation. Also, a data-driven method to compute participation factors for nonlinear systems based on Koopman mode decomposition has been developed; it generalizes the original definition of participation factors under certain conditions.
PHD
Electric power systems are complex, large-scale, and given the bidirectional causality between economic growth and electricity consumption, they are constantly being expanded. In the U.S., some of the electric power grid facilities date back to the 1880s, and this aging system is operating at its capacity limits. In addition, the international pressure for sustainability is driving an unprecedented deployment of renewable energy sources into the grid. Unlike the case of other primary sources of electric energy such as coal and nuclear, the electricity generated from renewable energy sources is strongly influenced by the weather conditions, which are very challenging to forecast even for short periods of time. Within this context, the mathematical models that have aided engineers to design and operate electric power grids over the past decades are falling short when uncertainties are incorporated to the models of such high-dimensional systems. Consequently, researchers are investigating alternative data-driven approaches. This is not only motivated by the need to overcome the above challenges, but it is also fueled by the increasing amount of data produced by today’s powerful computational resources and experimental apparatus. In power systems, a massive amount of data will be available thanks to the deployment of measuring devices called phasor measurement units. Along these lines, the Koopman operator theory is a promising framework for the integration of data analysis into our mathematical knowledge, and is bringing an exciting perspective on the treatment of high-dimensional systems that lie in the forefront of science and technology. In the research work reported in this dissertation, the Koopman operator theory has been exploited to seek for solutions to some of the challenges that are threatening the safe, reliable, and efficient operation of electric power systems.

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Brus, Linda. "Nonlinear Identification and Control with Solar Energy Applications." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8594.

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Dissertations / Theses on the topic 'Power system disturbance identification'

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