Among the renewable energies, wind energy presents the highest growth in installed capacity and penetration in modern power systems. This is why reliability of wind turbines becomes an important topic in research and industry. To this end, condition monitoring (or health monitoring) systems are needed for wind turbines. The core of any condition monitoring system (CMS) are fault diagnosis algorithms whose task is to provide early warnings upon the occurrence of incipient (small magnitude) faults. Thanks to the use of CMS we can avoid premature breakdowns and reduce significatively maintenance costs. The present thesis deals with fault diagnosis in sensors of a doubly-fed induction generator (DFIG) for wind turbine (WT) applications. In particular we are interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents and voltages) in a controlled DFIG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems. In this work we propose a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias, drifts) and multiplicative (changes in the sensor gain) faults, ii) robust against changes in the references/disturbances affecting the controlled DFIG as well as modelling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, iv) decision system based on statistical-change detection algorithms to treat the entire residual and perform fault detection and isolation at once. Three novel sensor FDI approaches are proposed. The first is a signal-based approach, that uses the model of the balanced three-phase signals (currents or voltages) for residual generation purposes. The second is a model-based approach that accounts for variation in the parameters. Finally, a third approach that combines the benefits of both the signal- and the model-based approaches is proposed. The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG and a speed-controlled induction motor. In addition, in this work we propose a discrete-time multiple input multiple output (MIMO) regulator for each power converter, namely for the rotor side converter (RSC) and for the grid side converter (GSC). In particular, for RSC control, we propose a modified feedback linearization technique to obtain a linear time invariant (LTI) model dynamics for the compensated DFIG. The novelty of this approach is that the compensation does not depend on highly uncertain parameters such as the rotor resistance. For GSC control, a LTI model dynamics is derived using the ideas behind feedback linearization. The obtained LTI model dynamics are used to design Linear Quadratic Gaussian (LQG) regulators. A single design is needed for all the possible operating conditions.

Due to growing concerns over climate change, more and more countries are looking to renewable energy sources to generate electricity. Therefore, wind turbines are increasing in popularity, along with doubly-fed induction machines (DFIGs) used in generation mode. Current grids codes require DFIGs to provide voltage support during a grid fault. The fault ride-through (FRT) capability of DFIGs is the focus of this thesis, in which modifications to the DFIG controller have been proposed to improve the FRT capability. The static synchronous compensator (STATCOM) controller has been applied with proposed method to study its influence on the voltage at the point of common coupling (PCC). The proposed method was also compared with other FRT capability improvement methods, including the conventional crowbar method. The simulation of the dynamic behaviour of DFIG-based wind turbines during grid fault is simulated using MATLAB/Simulink. The results obtained clearly demonstrate the efficacy of the proposed method.

Διάφοροι τύποι αιολικών συστημάτων . Έμφαση σε αιολικά συστήματα με ανεμογεννήτριες μεταβλητής ταχύτητας και κυρίως στην επαγωγική μαχανή διπλής τροφοδοσίας . Περιγραφή του ηλεκτρονικού μετατροπέα που χρησιμοποιείται σε αυτού του είδους το σύστημα . Έλεγχος της ισχύος και προσομοίωση για δύο τύπους ελεγκτών , PI και RST . Σύγκριση των αποκρίσεων . Απόκριση PI ελεγκτή για διάφορα κέρδη . / Different types of wind energy systems . Wind energy systems with variable speed wind turbines are studied . The doubly fed induction generator . Description of the power electronic converter which is used . Power control for two regulator types , PI and RST . We compare the dynamic performances . Dynamic performance for different values of the PI regulator parameters .

Η παρούσα διπλωματική εργασία πραγματεύεται τη μελέτη ανεμογεννήτριας με επαγωγική μηχανή διπλής τροφοδοσίας η οποία συνδέεται στο στάτη απευθείας με το δίκτυο και στο δρομέα μέσω ενός back to back μετατροπέα και η συνεχής λειτουργίας της μηχανής σε περιπτώσεις σφαλμάτων στο δίκτυο. Σκοπός της εργασίας είναι αρχικά να μελετηθεί το συνολικό σύστημα της ανεμογεννήτριας θεωρητικά χρησιμοποιώντας το μετασχηματισμό Park για τη μοντελοποίηση του συστήματος στο σύγχρονα στρεφόμενο d-q πλαίσιο αναφοράς. Στη συνέχεια παρατέθηκαν οι εξισώσεις στο χώρο κατάστασης που περιγράφουν το μαθηματικό μοντέλο του συστήματος, το επόμενο βήμα ήταν να περιγραφεί ένα σύστημα ελέγχου το οποίο βασίζεται στους PI ελεγκτές επιλέγοντας τα κατάλληλα κέρδη. Τέλος, προσομοιώνουμε το παραπάνω σύστημα με τη βοήθεια της εφαρμογής Simulink του λογισμικού MATLAB και μελετώντας τα αποτελέσματα, εξάγουμε τα ανάλογα συμπεράσματα. / The present thesis deals with the study of the wind turbine doubly-fed induction generator (DFIG), in which the stator is connected immediately to the grid and the rotor is connected to the grid with a back-to-back converter and the continuous operation of the machine in case of network errors. This thesis will initially consider the overall system of wind turbine theoretically using the Park transformation to model the system in the d-q synchronous rotating reference frame. The following goal was to quote in the state space equations that describe the mathematical model of the system, the next step was to describe a control system based on PI controllers selecting the appropriate profits. Finally, the above system was simulated by using the Simulink of MATLAB and studying the results were exported the appropriate conclusions.

Among the renewable energies, wind energy presents the highest growth in installed capacity and penetration in modern power systems. This is why reliability of wind turbines becomes an important topic in research and industry. To this end, condition monitoring (or health monitoring) systems are needed for wind turbines. The core of any condition monitoring system (CMS) are fault diagnosis algorithms whose task is to provide early warnings upon the occurrence of incipient (small magnitude) faults. Thanks to the use of CMS we can avoid premature breakdowns and reduce significatively maintenance costs.<p><p>The present thesis deals with fault diagnosis in sensors of a doubly-fed induction generator (DFIG) for wind turbine (WT) applications. In particular we are interested in performing fault detection and isolation (FDI) of incipient faults affecting the measurements of the three-phase signals (currents and voltages) in a controlled DFIG. Although different authors have dealt with FDI for sensors in induction machines and in DFIGs, most of them rely on the machine model with<p>constant parameters. However, the parameter uncertainties due to changes in the operating conditions will produce degradation in the performance of such FDI systems.<p><p>In this work we propose a systematic methodology for the design of sensor FDI systems with the following characteristics: i) capable of detecting and isolating incipient additive (bias, drifts) and multiplicative (changes in the sensor<p>gain) faults, ii) robust against changes in the references/disturbances affecting the controlled DFIG as well as modelling/parametric uncertainties, iii) residual generation system based on a multi-observer strategy to enhance the isolation process, iv) decision system based on statistical-change detection algorithms to treat the entire residual and perform fault detection and isolation at once.<p><p>Three novel sensor FDI approaches are proposed. The first is a signal-based approach, that uses the model of the balanced three-phase signals (currents or voltages) for residual generation purposes. The second is a model-based approach<p>that accounts for variation in the parameters. Finally, a third approach that combines the benefits of both the signal- and the model-based approaches is proposed. The designed sensor FDI systems have been validated using measured voltages, as well as simulated data from a controlled DFIG and a speed-controlled induction<p>motor. <p><p>In addition, in this work we propose a discrete-time multiple input multiple output (MIMO) regulator for each power converter, namely for the rotor side converter (RSC) and for the grid side converter (GSC). In particular, for RSC<p>control, we propose a modified feedback linearization technique to obtain a linear time invariant (LTI) model dynamics for the compensated DFIG. The novelty of this approach is that the compensation does not depend on highly uncertain parameters such as the rotor resistance. For GSC control, a LTI model dynamics<p>is derived using the ideas behind feedback linearization. The obtained LTI model dynamics are used to design Linear Quadratic Gaussian (LQG) regulators. A single design is needed for all the possible operating conditions. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

In zukünftigen Elektroenergiesystemen wird die dezentrale, häufig auf erneuerbaren Quellen basierende Energieversorgung eine große Bedeutung einnehmen. Die wachsende Präsenz der dezentralen Erzeugung in verschiedenen Spannungsebenen des elektrischen Netzes erfordert neue Konzepte zur Regelung des elektrischen Energieversorgungssystems. Insbesondere gibt es eine Tendenz auch kleine Netzbereiche autonome, d.h. vom Verbundnetz unabhängig zu betreiben. In diesem Zusammenhang müssen die Stabilitäts- und Regelungsaspekte immer stärker berücksichtigt werden. Die vorliegende Untersuchung konzentriert sich auf die Beurteilung und die Verbesserung der Stabilität von Windkraftanlagen (WKA). Die Integration von WKA zur dezentralen Energieversorgung in lokale Energienetze unter besonderer Berücksichtigung der Systemsstabilität ist das Ziel dieser Arbeit. Hierfür muss die Analyse der Stabilität einer WKA sowohl qualitativ als auch quantitativ durchgeführt werden, um die Faktoren zu ermitteln, die zur Verbesserung der Systemsstabilität beitragen. Der darauf basierte Entwurf von Regelstrategien für ein verbessertes dynamisches und transientes Verhalten wird theoretisch und durch numerische Simulationen validiert.

In zukünftigen Elektroenergiesystemen wird die dezentrale, häufig auf erneuerbaren Quellen basierende Energieversorgung eine große Bedeutung einnehmen. Die wachsende Präsenz der dezentralen Erzeugung in verschiedenen Spannungsebenen des elektrischen Netzes erfordert neue Konzepte zur Regelung des elektrischen Energieversorgungssystems. Insbesondere gibt es eine Tendenz auch kleine Netzbereiche autonome, d.h. vom Verbundnetz unabhängig zu betreiben. In diesem Zusammenhang müssen die Stabilitäts- und Regelungsaspekte immer stärker berücksichtigt werden. Die vorliegende Untersuchung konzentriert sich auf die Beurteilung und die Verbesserung der Stabilität von Windkraftanlagen (WKA). Die Integration von WKA zur dezentralen Energieversorgung in lokale Energienetze unter besonderer Berücksichtigung der Systemsstabilität ist das Ziel dieser Arbeit. Hierfür muss die Analyse der Stabilität einer WKA sowohl qualitativ als auch quantitativ durchgeführt werden, um die Faktoren zu ermitteln, die zur Verbesserung der Systemsstabilität beitragen. Der darauf basierte Entwurf von Regelstrategien für ein verbessertes dynamisches und transientes Verhalten wird theoretisch und durch numerische Simulationen validiert.

Actuellement, les machines Asynchrones à Double Alimentation (MADA) sont omniprésentes dans le secteur éolien, grâce à leur simplicité de construction, leur faible coût d’achat et leur robustesse mécanique ainsi que le nombre faible d’interventions pour la maintenance. Cependant, comme toute autre machine électrique, ces génératrices sont sujettes aux défauts de différent ordre (électrique, mécanique, électromagnétique…) ou de différents types (capteur, actionneur ou composants du système). C’est pourquoi, il est primordial de concevoir une approche de diagnostic permettant de manière anticipée, de détecter, localiser et identifier tout défaut ou anomalie pouvant altérer le fonctionnement sain de ce type de machine. Motivés par les points forts des méthodes de diagnostic de défauts à base d’observateurs, nous proposons d’une part, dans cette thèse, une approche de détection, localisation et identification des défauts de la MADA d’une éolienne à vitesse variable, à base des observateurs de Kalman, performants et largement utilisés. Les erreurs d’estimation d’état du filtre de Kalman linéaire et de ses variantes non-linéaires, à noter : le Filtre de Kalman Etendu (EKF) et le Filtre de Kalman sans-Parfum (UKF), sont utilisés comme résidus sensibles aux défauts. En vue d’éviter les fausses alarmes et de découpler les défauts des perturbations et des bruits, l’analyse des résidus générés est réalisée par des tests statistiques tels que : Test de Page Hinkley (PH) et Test DCS (Dynamic Cumulative Sum). Pour la localisation des défauts multiples et simultanés, la Structure d’Observateurs Dédiés (DOS) et la Structure d’Observateurs Généralisés (GOS) sont appliquées. De plus, l’amplitude du défaut est déterminée dans l’étape d’identification de défaut. Les défauts capteurs, actionneurs et composants de la MADA, sont traités dans ce travail de recherche. D’autre part, une étude comparative entre les différents observateurs de Kalman, est élaborée. La comparaison porte sur les critères suivants : le temps de calcul, la précision et la vitesse de convergence des estimations. / Actually, the Doubly Fed Induction Generators (DFIG) are omnipresent in the wind power market, owing to their construction simplicity, their low purchase cost and their mechanical robustness. However, as any other electrical machine, these generators are subject to defects of different order (electrical, mechanical, electromagnetic ...) or of different type (sensor, actuator or system). That’s why, it is important to design an effective diagnostic approach, able to early detect, locate and identify any defect or abnormal behavior, which could undermine the healthy operation of this machine On the one hand, motivated by the observer-based fault diagnosis methods strengths, we proposed, in this thesis, a diagnostic approach for the faults detection, localization and identification of the DFIG used in variable speed wind turbine. This approach is based on the use of the efficient and widely used Kalman observers. The state estimation errors of the linear Kalman filter and the non-linear Kalman filters, named: The Extended Kalman Filter (EKF) and the Unscented Kalman Filter (UKF) are used as faults sensitive residuals. In order to avoid false alarms and to decouple faults from disturbances and noises, the faults detection is carried out by the analysis of the residuals generated, by the mean of statistical tests such as: Hinkley Page Test (PH) and DCS Test (Dynamic) Cumulative Sum). For the localization step in case of multiple and simultaneous faults, the Dedicated Observer scheme (DOS) and the Generalized Observer scheme (GOS) are applied. In addition, the fault level is determined in the fault identification step. Sensor faults, actuator and system faults of DFIG, are treated in this research work. On the other hand, a comparative study between the three Kalman observers proposed is performed. The comparison was done in terms of (1) the computation time, (2) the estimation accuracy, and (3) the convergence speed.