This dissertation thesis deals with the computational modelling of the dynamic response of the rotating electrical machine structure on the application of the magnetic forces. Apart from the dynamic response of the ideal symmetrical machine, the influence of the air gap eccentricity on the dynamics response is studied in this work. A basic type of the air gap eccentricity, which is caused by eccentric mounting of the rotor pack on the shaft of the rotor, is considered. The calculations the dependence of the magnetic forces on the time and a misalignment of the rotor pack are performed as first. The computational model of the magnetic field of the rotating electrical machine, which is based on solution of the electromagnetic coupled field analysis by finite element method, is used for this purpose. An analysis of the influence of the unbalanced magnetic pull and the stiffness of some parts of the machine on the modal properties of the machine is performed in the second part of this thesis. A third part of this thesis is focused on the calculation of the dynamic response of the machine during the steady state operation of the machine and the influence of the rotor pack misalignment on the dynamic response is studied. The obtained results showed that the tangential components of the magnetic forces, which act on the stator pack, excite significant torsional vibration of the stator. Besides the vibration of the stator of the machine, the influence of the rotor pack misalignment on the sound power of the machine, vibration of the rotor, loads of rotor bearings and air gap eccentricity is studied in this thesis.

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<p dir="ltr">The parallel growth of contemporary machine learning (ML) technologies alongside edge/-fog networking has necessitated the development of novel paradigms to effectively manage their intersection. Specifically, the proliferation of edge devices equipped with data generation and ML model training capabilities has given rise to an alternative paradigm called federated learning (FL), moving away from traditional centralized ML common in cloud-based networks. FL involves training ML models directly on edge devices where data are generated.</p><p dir="ltr">A fundamental challenge of FL lies in the extensive heterogeneity inherent to edge/fog networks, which manifests in various forms such as (i) statistical heterogeneity: edge devices have distinct underlying data distributions, (ii) structural heterogeneity: edge devices have diverse physical hardware, (iii) data quality heterogeneity: edge devices have varying ratios of labeled and unlabeled data, and (iv) adversarial compromise: some edge devices may be compromised by adversarial attacks. This dissertation endeavors to capture and model these intricate relationships at the intersection of FL and highly heterogeneous edge/fog networks. To do so, this dissertation will initially develop closed-form expressions for the trade-offs between ML performance and resource cost considerations within edge/fog networks. Subsequently, it optimizes the fundamental processes of FL, encompassing aspects such as batch size control for stochastic gradient descent (SGD) and sampling for global aggregations. This optimization is jointly formulated with networking considerations, which include communication resource consumption and device-to-device (D2D) cooperation.</p><p dir="ltr">In the former half of the dissertation, the emphasis is first on optimizing device sampling for global aggregations in FL, and then on developing a self-sufficient hierarchical meta-learning approach for FL. These methodologies maximize expected ML model performance while addressing common challenges associated with statistical and system heterogeneity. Novel techniques, such as management of D2D data offloading, adaptive CPU clock cycle control, integration of meta-learning, and much more, enable these methodologies. In particular, the proposed hierarchical meta-learning approach enables rapid integration of new devices in large-scale edge/fog networks.</p><p dir="ltr">The latter half of the dissertation directs its ocus towards emerging forms of heterogeneity in FL scenarios, namely (i) heterogeneity in quantity and quality of local labeled and unlabeled data at edge devices and (ii) heterogeneity in terms of adversarially comprised edge devices. To deal with heterogeneous labeled/unlabeled data across edge networks, this dissertation proposes a novel methodology that enables multi-source to multi-target federated domain adaptation. This proposed methodology views edge devices as sources – devices with mostly labeled data that perform ML model training, or targets - devices with mostly unlabeled data that rely on sources’ ML models, and subsequently optimizes the network relationships. In the final chapter, a novel methodology to improve FL robustness is developed in part by viewing adversarial attacks on FL as a form of heterogeneity.</p>

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One of the challenging issues with the Microgrid is that the bidirectional power flow providedby the distributed generator (DG) which modify the fault current level. Furthermore, theinverter based-renewable energy source (IB-RES) limits the total fault current contributionto the grid due to its thermal capability. Since Microgrid should be able to operate in gridconnectedand islanded mode, protection strategies are needed to solve this challenging issue.By only having IB-RES and battery storage system, the fault condition and normaloperation cannot be distinguished. Apart from fault clearing issue, there is a consideration tostudy the fault isolation in the Microgrid under the limited fault current provided by IB-RES.To have fault isolation capability, the intelligent electrical device (IED) is needed. The firststep is to find a method that can detect a fault under the fault level modification constraint.This thesis presents a zero and negative sequence current protection to detect a fault.However, to make it selective, this protection will be applied directionally. It is common thatthe distribution grid has unbalanced load operation, thus providing zero and negativesequence component in the grid. To apply the directional zero and negative sequence currentprotection, the unbalanced load flow is simulated to distinguish the fault and normaloperation under unbalanced load condition.Safety and regulation are discussed briefly in this thesis. It is important that each of theIB-RES has fault ride-through (FRT) capability that follows a regulation. However, thisregulation is expected to have a coordination with the proposed protection in the Microgridso the reliability, selectivity, and sensitivity can be achieved in grid-connected and islandedmode. This thesis shows the coordination between fuses, IED, and inverter FRT capability.After providing a protection strategy, the adaptability of the proposed protection isassessed regarding of Microgrid expansion. The result shows that by applying the schemeand following the grading margin requirement that is presented in this thesis, the Microgridexpansion will not disrupt the proposed protection coordination. Since it is known that thedistribution grid is expanding its load capacity and microgeneration in continuous basis, it isconvenient that the proposed protection in the IED is expected to be adaptable, means that ithas a fixed IED setting when the grid is expanded. The analysis is performed by electrical transient analysis program (ETAP) and MatlabSimulink. The short circuit analysis, sequence-of-operation, and unbalanced load flow aresimulated by ETAP, while the protection stability is simulated by Matlab Simulink. / Ett problem som finns med microgrid är att de distribuerade produktionsgeneratorerna harett dubbelriktat effektflöde som modifierar felströmmen. Dessutom, inverterbaseradeförnyelsebara energikällor (IB-RES) begränsar det totala felströmsbidraget på grund av desstermiska kapacitet. Eftersom microgrids ska vara operativ vid både anslutning till externt nätsamt önätsdrift behövs skyddsstrategier för att kunna hantera fel, speciellt vid önätsdrift.Om endast IB-RES och batterilager används kan feldrift och normal drift inte särskiljas.Bortsätt från felhantering är det viktigt att studera felbortkoppling för microgrid underbegränsad felström som fås av IB-RES. För att kunna åstadkomma felbortkoppling behöveren IED (från engelskans Intelligent Electronic Device). Det första steget är att finna en metodför att kunna detektera fel under fel nivå modifiering. Denna avhandling tittar på att användanoll- och minusföljds ström sekvensskydd för att detektera fel. För att göra skyddet selektivtkommer det att titta på riktningen av effektflödet. I distributionsnät är det vanligt att haobalanserade laster vilket medför noll- och negativa sekvenskomponenter i nätet. För atttillämpa riktningsskydd för noll och negativ sekvens ström simuleras ett obalanserateffektflöde för att särskilja på feldrift och normal drift vid obalanserad last.Säkerhet och förordningar diskuteras kortfattat i denna avhandling. Det är viktigt att varjeIB-RES har en feltålighet som följer vissa förordningar. Denna förordning förväntassamordna det föreslagna skyddet i micronåt så att pålitlighet, selektivitet och känslighet kanåstadkommas vid nätanslutning och önätsdrift. Denna avhandling visar samordningen mellansäkringar, IED och feltåligheten för växelomriktare.Anpassningsförmågan för det föreslagna skyddet bedöms med avseende på expansion avmicrogrid. Resultatet visar att en expansion av ett microgrid inte kommer att störa denföreslagna samordningen om skyddsmetoden och tidsfördröjningskravet som presenteras idenna avhandling följs. Eftersom det är känt att distributionsnätet kommer att fortsätta ökasin lastkapacitet och mikrogenerering, är det lämpligt att skyddet förväntas varaanpassningsbart vilket innebär att det har en fast IED inställning när nätet expanderas.Analysen genomförs med mjukvarorna electrical transient analysis program (ETAP) ochMatlab Simulink. Kortslutningsanalysen, arbetssekvensen och obalanserad lastflödesimuleras av ETAP, medan skyddsstabiliteten simuleras av Matlab Simulink.

The introduction of communication technology into the electric power grid has made the grid more reliable. Power system operators gain visibility over the power system and are able to resolve operational issues remotely via Supervisory Control And Data Acquisition (SCADA) technology. This reduces outage periods. Nonetheless, the remote-control capability has rendered the power grid vulnerable to cyberattacks. In December 2015, over 200,000 people in Ukraine became victims of the first publicly reported cyberattack on the power grid. Consequently, cyber-physical security research for the power system as a critical infrastructure is in critical need. Research on cybersecurity for power grids has produced a diverse literature; the multi-faceted nature of the grid makes it vulnerable to different types of cyberattacks, such as direct power grid, supply chain and ransom attacks. The attacks may also target different levels of grid operation, such as the transmission system, distribution system, microgrids, and generation. As these levels are characterized by varying operational constraints, the literature may be categorized not only according to the type of attack it targets, but also according to the level of power system operation under consideration. It is noteworthy that cybersecurity research for the transmission system dominates the literature, although the distribution system is noted to have a larger attack surface. For the distribution system, a notable attack type is the so-called direct switching attack, in which an attacker aims to disrupt power supply by compromising switching devices that connect equipment such as generators, and power grid lines. To maximize the damage, this attack tends to be coordinated as the attacker optimally selects the nodes and switches to attack. This decision-making process is often a bi- or tri-level optimization problem which models the interaction between the attacker and the power system defender. It is necessary to detect attacks and establish coordination/correlation among them. Determining coordination is a necessary step to predict the targets of an attack before attack completion, and aids in the mitigation strategy that ensues. While the literature has addressed the direct switching attack on the distribution system in different ways, there are also shortcomings. These include: (i) techniques to establish coordination among attacks are centralized, making them prone to single-point failures; (ii) techniques to establish coordination among attacks leverage only power system models, ignoring the influence of communication network vulnerabilities and load criticality in the decisions of the attacker; (iii) attacker-defender optimization models assume specific knowledge of the attacker resources and constraints by the defender, a strong unrealistic assumption that reduces their usability; (iv) and, mitigation strategies tend to be static and one-sided, being implemented only at the physical level, or at the communication network level. In light of this, this dissertation culminates in major contributions concerning real-time decentralized correlation of detected direct switching attacks and hybrid mitigation for electric power distribution systems. Concerning this, four novel contributions are presented: (i) a framework for decentralized correlation of attacks and mitigation; (ii) an attacker-defender optimization model that accounts for power system laws, load criticality, and cyber vulnerabilities in the decision-making process of the attacker; (iii) a real-time learning-based mechanism for determining correlation among detected attacks and predicting attack targets, and which does not assume knowledge of the attacker's resources and constraints by the power system defender; (iv) a hybrid mitigation strategy optimized in real-time based on information learned from detected attacks, and which combines both physical level and communication network level mitigation. Since the execution of intrusion detection systems and mechanisms such as the ones proposed in this dissertation may deter attackers from directly attacking the power grid, attackers may perform a supply chain cyberattack to yield the same results. Although, supply chain cyberattacks have been acknowledged as potentially far-reaching, and compliance directives put forward for this, the detection of supply chain cyberattacks is in a nascent stage. Consequently, this dissertation also proposes a novel method for detecting supply chain cyberattacks. To the best of the knowledge of the author, this work is the first preliminary work on supply chain cyberattack detection. / Doctor of Philosophy / The electric power grid is the network that transports electricity from generation to consumers, such as homes and factories. The power grid today is highly remote-monitored and controlled. Should there be a fault on the grid, the human operator, often remotely located, may only need to resolve it by sending a control signal to telemetry points, called nodes, via a communication network. This significantly reduces outage periods and improves the reliability of the grid. Nonetheless, the high level connectivity also exposes the grid to cyberattacks. The cyber connectivity between the power grid and the human operator, like all communication networks, is vulnerable to cyberattacks that may allow attackers to gain control of the power grid. If and when successful, wide-spread and extended outages, equipment damage, etc. may ensue. Indeed, in December 2015, over 200,000 people in Ukraine became victims to the first publicly reported cyberattack on a power grid. As a critical infrastructure, cybersecurity for the power grid is, therefore, in critical need. Research on cybersecurity for power grids has produced a diverse literature; the multi-faceted nature of the grid makes it vulnerable to different types of cyberattacks, such as direct power grid, supply chain and ransom attacks. Notable is the so-called direct switching attack, in which an attacker aims to compromise the power grid communication network in order to toggle switches that connect equipment such as generators, and power grid lines. The aim is to disrupt electricity service. To maximize the damage, this attack tends to be coordinated; the attacker optimally selects several grid elements to attack. Thus, it is necessary to both detect attacks and establish coordination among them. Determining coordination is a necessary step to predict the targets of an attack before attack completion. This aids the power grid owner to intercept and mitigate attacks. While the literature has addressed the direct switching attack in different ways, there are also shortcomings. Three outstanding ones are: (i) techniques to determine coordination among attacks and predict attack targets are centralized, making them prone to single-point failures; (ii) techniques to establish coordination among attacks leverage only power system physical laws, ignoring the influence of communication network vulnerabilities in the decisions of the attacker; (iii) and, studies on the interaction between the attacker and the defender (i.e., power grid owner) assume specific knowledge of the attacker resources and constraints by the defender, a strong unrealistic assumption that reduces their usability. This research project addresses several of the shortcomings in the literature, particularly the aforementioned. The work focuses on the electric distribution system, which is the power grid that connects directly to consumers. Indeed, this choice is ideal, as the distribution system has a larger attack surface than other parts of the grid and is characterized by computing devices with more constrained computational capability. Thus, adaptability to simple computing devices is a priority. The contributions of this dissertation provide leverage to the power grid owner to intercept and mitigate attacks in a resilient manner. The original contributions of the work are: (i) a novel realistic model that shows the decision making process of the attacker and their interactions with the defender; (ii) a novel decentralized mechanism for predicting the targets of coordinated cyberattacks on the electric distribution grid in real-time and which is guided by the attack model, (iii) and a novel hybrid optimized mitigation strategy that provides security to the power grid at both the communication network level and the physical power grid level. Since the power grid is constructed with smart equipment from various vendors, attackers may launch effective attacks by compromising the devices deployed in the power grid through a compromised supply chain. By nature, such an attack is evasive to traditional intrusion detection systems and algorithms such as the aforementioned. Therefore, this work also provides a new method to defend the grid against supply chain attacks, resulting in a mechanism for its detection in a critical power system communication device.

L'objet de cette thèse est d'étudier les systèmes de cointégration fractionnaire de forme triangulaire mais également d'analyser l'apport de ces systèmes dans la modélisation des co-mouvements au sein des marchés financiers internationaux. La thèse s'articule autour de six chapitres équitablement répartis entre contributions économétriques et économiques. Concernant l'approche économétrique, un intérêt particulier est donné à l'estimation de ces systèmes en absence d'information sur les paramètres d'intérêts. Dans cette optique, plusieurs techniques d'estimation sont analysées et développées, essentiellement dans le domaine des fréquences car celui-ci permet un traitement semi-paramétrique des paramètres de nuisances. Les performances de ses estimateurs sont étudiés à travers des simulations mais également à travers l'étude des propriétés asymptotiques. Concernant l'approche économique, une première contribution exploite la cointégration fractionnaire pour révéler l'existence d'un système de taux de change entre certains pays Asiatiques. Une deuxième contribution porte sur l'analyse des interdépendances entre le marché du pétrole et divers taux de change au niveau de la volatilité. Une troisième contribution introduit un processus d'apprentissage adaptatif dans un modèle monétaire à plusieurs pays afin d'étudier sous quelles conditions un système de taux de change peut émerger. / The aim of the thesis is to study a triangular form of fractional cointegration systems and to investigate whether these systems allow to model the comovements in international financial markets. The thesis is organized around six chapters. Three of them are theory-oriented and the three others are empirics-oriented. Concerning the econometric approach, a particular interest is devoted to the estimation of these systems when all parameters of interest are unknown. To this extent, several estimation techniques are investigated and introduced, essentially in frequency domain as it allows a semi-parametric treatment of the nuisance parameters. Most of times, the performance of these estimators are studied by means of simulations but the asymptotic theory is also developed. Concerning the economic approach, a first contribution applies the fractional cointegration theory to reveal the existence of an exchange rate system between several Asian countries. A second contribution deals with the risk interdependences between the crude oil market and several exchange rates. A third contribution considers an adaptive learning mechanism in a multi-country monetary model to investigate the conditions under which an exchange rate system is likely to emerge.

Ao longo das últimas décadas, o advento de geradores síncronos distribuídos têm modificado significativamente a operação dinâmica de sistemas de distribuição. Características dinâmicas que antes eram típicas de sistemas de transmissão estão agora também presentes em sistemas de distribuição. Problemas relacionados a oscilações eletromecânica mal amortecidas, um dos focos de análise do estudo da estabilidade a pequenas perturbações, podem agora afetar também os sistemas de distribuição devido à inserção de geradores síncronos. Ferramentas usualmente utilizadas em sistemas de transmissão para a análise de tais oscilações não são completamente adequadas para analisar os fenômenos que ocorrem nos sistemas de distribuição com geração distribuída, devido a características peculiares desses sistemas, tais como o desequilíbrio de suas fases. Assim, essa pesquisa propõe um procedimento alternativo para analisar a estabilidade a pequenas perturbações de sistemas de distribuição, através da aplicação de técnicas de estimação modal. Abordam-se duas técnicas de estimação modal: os métodos de Prony e o ESPRIT. O primeiro método consiste em uma ferramenta já consagrada para a identificação de oscilações eletromecânicas de baixa frequência. Enquanto o segundo é uma t´técnica usualmente aplicada em análise de transitórios com desempenho satisfatório no contexto de qualidade de energia. Simulações não lineares são realizadas no software ATP, inicialmente sobre um sistema trifásico equilibrado e tais técnicas são aplicadas e comparadas, tornando possível a validação cruzada de ambos os métodos na identificação do modo eletromecânico do sistema. Na sequência, simulações são realizadas em um um sistema trifásico desequilibrado, permitindo avaliar o efeito do desbalanço da carga sobre as oscilações eletromecânicas, sendo essa uma das maiores contribuições desse trabalho. A principal conclusão adquirida é o fato de que um Power System Stabilizer (PSS) pode ser usado para mitigar os impactos prejudiciais das oscilações eletromecânicas em um gerador síncrono distribuído, sendo que esse PSS pode ser projetado a partir de técnicas típicas, assumindo um funcionamento equilibrado desse gerador, e ainda assim ter um desempenho satisfatório para os casos desequilibrados estudados. / Over the last few decades, the advent of distributed synchronous generators has significantly modified the operation and dynamics of distribution systems. Dynamic behaviors that were typical of transmission systems are now also present in distribution systems. Problems related to poorly damped electromechanical oscillations, the focus of small-signal stability studies, can now also affect the distribution systems due to the insertion of synchronous generators. Tools usually employed in large systems for the analysis of these oscillations are not completely appropriate to analyze this phenomena in distribution systems with distributed generation, due to particular characteristics of these systems, such as load imbalance. Therefore, this research proposes an alternative procedure to analyze the small-signal stability of distribution systems, through the application of modal estimation techniques. Two modal estimation techniques are used: the Prony and ESPRIT methods. The former consists of a well-established tool for identifying low-frequency oscillations and the latter was chosen due to its satisfactory performance in works related to power quality, where it is applied in transient analysis. Initially, both modal estimation techniques are applied to the results of nonlinear simulations performed in the Alternative Transients Program for balanced three-phase systems. The modes identified by both techniques exhibit a close match, which provides a cross validation between these techniques. In the sequence, simulations are performed in three-phase unbalanced systems, allowing an evaluation of the effect of load imbalance on the electromechanical oscillations (which is another major contribution of this work). Furthermore, it is concluded from the obtained results that a Power System Stabilizer, designed under the assumption of a balanced operation of the distribution system, can be effectively used to mitigate the detrimental effects of the poorly damped oscillations even when the system operates under unbalanced load conditions.