4,915 research outputs found

    Design and Dynamic Control of Heteropolar Inductor Machines

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    Performance comparisons of doubly-fed machines

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    This research project aims at evaluating a conversion system based on the emerging Brushless Doubly Fed Reluctance Machine (BDFRM) through a comparative experimental study with a traditional and well established slip-ring counterpart, the Doubly Fed Induction Machine (DFIM). One of the main objectives is to establish whether this alternative machine is worthy of industrial consideration in variable speed applications with limited speed ranges (e.g. wind turbines, pump-like drives etc.) in terms of control, reliability, efficiency and power factor performance as major criteria. Such kind of work has not been reported in the open-literature to date and represents the main contribution of the project being undertaken. A conventional and widely used parameter-independent vector control (VC) scheme has been selected for the operation of both the machines using a shaft-position sensor. The VC algorithm has been simulated and implemented in real-time on state-of-the-art eZdsp development platform based on the TMS320F28335 Digital Signal Controller (DSC). The control code has been derived from a programme written in C++ using the corresponding compiler, the Code Composer Studio (CCS). Comprehensive computer simulations have been done in Matlab/Simulink using the parameters obtained by off-line testing of the DFIM and BDFRM prototypes, which have been built in the same stator frame for comparison purposes. The simulation results have been experimentally verified on two identical test rigs where a commercial 4-quadrant cage induction machine V/f drive has been used as a prime mover or load for either the DFIM or the BDFRM subject to their operating mode. The preliminary experimental results on two small-scale prototypes have shown that the BDFRM can achieve competitive performance to the similarly rated DFIM and as such should warrant further investigation and increasing interests of both academic and industrial communities as a potential large-scale wind generator or a pump drive

    Flux-Weakening Control for Permanent-Magnet Synchronous Motors Based on Z-Source Inverters

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    Permanent magnet synchronous machines (PMSMs) have high efficiency, high power density, high torque-to-inertia ratio, and fast dynamic response. These features make this kind of machines very attractive for electric vehicle (EV) applications. However, because of their nature, i.e., constant magnet flux provided by magnets, these machines have a narrow constant power speed range (CPSR). This limitation is a strong drawback for application of PMSMs in electric vehicles, where high speed is the top requirement. Two different approaches can extend the maximum speed under constant power: (1) Increasing a drive\u27s output voltage, and (2) implementing flux-weakening (FW) control methods. However, a conventional drive\u27s output voltage is limited by its dc bus. Furthermore, FW control methods are constrained by the maximum output voltage of a drive. In this work, a new approach is demonstrated to obtain a wider CPSR range by implementing a Z-source inverter as a motor-drive. Such a Z-source inverter can provide highly boosted voltage and is immune to dead time and shoot through issues. In addition, in this thesis, a constant power FW control algorithm is developed and simulated for this new approach

    Advances in the Field of Electrical Machines and Drives

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    Electrical machines and drives dominate our everyday lives. This is due to their numerous applications in industry, power production, home appliances, and transportation systems such as electric and hybrid electric vehicles, ships, and aircrafts. Their development follows rapid advances in science, engineering, and technology. Researchers around the world are extensively investigating electrical machines and drives because of their reliability, efficiency, performance, and fault-tolerant structure. In particular, there is a focus on the importance of utilizing these new trends in technology for energy saving and reducing greenhouse gas emissions. This Special Issue will provide the platform for researchers to present their recent work on advances in the field of electrical machines and drives, including special machines and their applications; new materials, including the insulation of electrical machines; new trends in diagnostics and condition monitoring; power electronics, control schemes, and algorithms for electrical drives; new topologies; and innovative applications

    Nonlinear Time-Frequency Control of Permanent Magnet Electrical Machines

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    Permanent magnet (PM) electrical machines have been widely adopted in industrial applications due to their advantages such as easy to control, compact in size, low in power loss, and fast in response, to name only a few. Contemporary control methods specifically designed for the control of PM electrical machines only focus on controlling their time-domain behaviors while completely ignored their frequency-domain characteristics. Hence, when a PM electrical machine is highly nonlinear, none of them performs well. To make up for the drawback and hence improve the performance of PM electrical machines under high nonlinearity, the novel nonlinear time-frequency control concept is adopted to develop viable nonlinear control schemes for PM electrical machines. In this research, three nonlinear time-frequency control schemes are developed for the speed and position control of PM brushed DC motors, speed and position control of PM synchronous motors, and chaos suppression of PM synchronous motors, respectively. The most significant feature of the demonstrated control schemes are their ability in generating a proper control effort that controls the system response in both the time and frequency domains. Simulation and experiment results have verified the effectiveness and superiority of the presented control schemes. The nonlinear time-frequency control scheme is therefore believed to be suitable for PM electrical machine control and is expected to have a positive impact on the broader application of PM electrical machines

    System Frequency Support of Permanent Magnet Synchronous Generator-Based Wind Power Plant

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    With ever-increasing penetration of wind power into modern electric grids all over the world, a trending replacement of conventional synchronous generators by large wind power plants will likely result in the poor overall frequency regulation performance. On the other hand, permanent magnet synchronous generator wind Turbine System (PMSG-WTG) with full power back to back converters tends to become one of the most promising wind turbine technologies thanks to various advantages. It possesses a significant amount of kinetic energy stored in the rotating mass of turbine blades, which can be utilized to enhance the total inertia of power system. Additionally, the deloaded operation and decoupled control of active and reactive power make it possible for PMSG-WTG to provide a fast frequency regulation through full-power converter. First of all, a comprehensive and in-depth survey is conducted to analyze the motivations for incorporating the inertial response and frequency regulation of VSWT into the system frequency regulation. Besides, control classifications, fundamental control concepts and advanced control schemes implemented for auxiliary frequency support of individual WT or wind power plant are elaborated along with a comparison of the potential frequency regulation capabilities of four major types of WTs. Secondly, a Controls Advanced Research Turbine2-Permanent Magnet Synchronous Generator wind turbine (CART2-PMSG) integrated model representing the typical configuration and operation characteristics of PMSG-WT is established in Matlab/Simulink,. Meanwhile, two different rotor-side converter control schemes, including rotor speed-based control and active power-based control, are integrated into this CART2-PMSG integrated model to perform Maximum Power Point Tracking (MPPT) operation over a wide range of wind speeds, respectively. Thirdly, a novel comprehensive frequency regulation (CFR) control scheme is developed and implemented into the CART2-PMSG model based on rotor speed control. The proposed control scheme is achieved through the coordinated control between rotor speed and modified pitch angle in accordance with different specified wind speed modes. Fourth, an improved inertial control method based on the maximum power point tracking operation curve is introduced to boost the overall frequency support capability of PMSG-WTGs based on rotor speed control. Fifth, a novel control method based on the torque limit (TLC) is proposed for the purpose of maximizing the wind turbine (WT)\u27s inertial response. To avoid the SFD caused by the deloaded operation of WT, a small-scale battery energy storage system (BESS) model is established and implemented to eliminate this impact and meanwhile assist the restoration of wind turbine to MPPT mode by means of coordinated control strategy between BESS and PMSG-WTG. Last but not the least, all three types of control strategies are implemented in the CART2-PMSG integrated model based on rotor speed control or active power control respectively to evaluate their impacts on the wind turbine\u27s structural loads during the frequency regulation process. Simulation results demonstrate that all the proposed methods can enhance the overall frequency regulation performance while imposing very slight negative impact on the major mechanical components of the wind turbine

    On power system automation: a Digital Twin-centric framework for the next generation of energy management systems

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    The ubiquitous digital transformation also influences power system operation. Emerging real-time applications in information (IT) and operational technology (OT) provide new opportunities to address the increasingly demanding power system operation imposed by the progressing energy transition. This IT/OT convergence is epitomised by the novel Digital Twin (DT) concept. By integrating sensor data into analytical models and aligning the model states with the observed system, a power system DT can be created. As a result, a validated high-fidelity model is derived, which can be applied within the next generation of energy management systems (EMS) to support power system operation. By providing a consistent and maintainable data model, the modular DT-centric EMS proposed in this work addresses several key requirements of modern EMS architectures. It increases the situation awareness in the control room, enables the implementation of model maintenance routines, and facilitates automation approaches, while raising the confidence into operational decisions deduced from the validated model. This gain in trust contributes to the digital transformation and enables a higher degree of power system automation. By considering operational planning and power system operation processes, a direct link to practice is ensured. The feasibility of the concept is examined by numerical case studies.The electrical power system is in the process of an extensive transformation. Driven by the energy transition towards renewable energy resources, many conventional power plants in Germany have already been decommissioned or will be decommissioned within the next decade. Among other things, these changes lead to an increased utilisation of power transmission equipment, and an increasing number of complex dynamic phenomena. The resulting system operation closer to physical boundaries leads to an increased susceptibility to disturbances, and to a reduced time span to react to critical contingencies and perturbations. In consequence, the task to operate the power system will become increasingly demanding. As some reactions to disturbances may be required within timeframes that exceed human capabilities, these developments are intrinsic drivers to enable a higher degree of automation in power system operation. This thesis proposes a framework to create a modular Digital Twin-centric energy management system. It enables the provision of validated and trustworthy models built from knowledge about the power system derived from physical laws, and process data. As the interaction of information and operational technologies is combined in the concept of the Digital Twin, it can serve as a framework for future energy management systems including novel applications for power system monitoring and control, which consider power system dynamics. To provide a validated high-fidelity dynamic power system model, time-synchronised phasor measurements of high-resolution are applied for validation and parameter estimation. This increases the trust into the underlying power system model as well as the confidence into operational decisions derived from advanced analytic applications such as online dynamic security assessment. By providing an appropriate, consistent, and maintainable data model, the framework addresses several key requirements of modern energy management system architectures, while enabling the implementation of advanced automation routines and control approaches. Future energy management systems can provide an increased observability based on the proposed architecture, whereby the situational awareness of human operators in the control room can be improved. In further development stages, cognitive systems can be applied that are able to learn from the data provided, e.g., machine learning based analytical functions. Thus, the framework enables a higher degree of power system automation, as well as the deployment of assistance and decision support functions for power system operation pointing towards a higher degree of automation in power system operation. The framework represents a contribution to the digital transformation of power system operation and facilitates a successful energy transition. The feasibility of the concept is examined by case studies in form of numerical simulations to provide a proof of concept.Das elektrische Energiesystem befindet sich in einem umfangreichen Transformations-prozess. Durch die voranschreitende Energiewende und den zunehmenden Einsatz erneuerbarer Energieträger sind in Deutschland viele konventionelle Kraftwerke bereits stillgelegt worden oder werden in den nächsten Jahren stillgelegt. Diese Veränderungen führen unter anderem zu einer erhöhten Betriebsmittelauslastung sowie zu einer verringerten Systemträgheit und somit zu einer zunehmenden Anzahl komplexer dynamischer Phänomene im elektrischen Energiesystem. Der Betrieb des Systems näher an den physikalischen Grenzen führt des Weiteren zu einer erhöhten Störanfälligkeit und zu einer verkürzten Zeitspanne, um auf kritische Ereignisse und Störungen zu reagieren. Infolgedessen wird die Aufgabe, das Stromnetz zu betreiben anspruchsvoller. Insbesondere dort wo Reaktionszeiten erforderlich sind, welche die menschlichen Fähigkeiten übersteigen sind die zuvor genannten Veränderungen intrinsische Treiber hin zu einem höheren Automatisierungsgrad in der Netzbetriebs- und Systemführung. Aufkommende Echtzeitanwendungen in den Informations- und Betriebstechnologien und eine zunehmende Menge an hochauflösenden Sensordaten ermöglichen neue Ansätze für den Entwurf und den Betrieb von cyber-physikalischen Systemen. Ein vielversprechender Ansatz, der in jüngster Zeit in diesem Zusammenhang diskutiert wurde, ist das Konzept des so genannten Digitalen Zwillings. Da das Zusammenspiel von Informations- und Betriebstechnologien im Konzept des Digitalen Zwillings vereint wird, kann es als Grundlage für eine zukünftige Leitsystemarchitektur und neuartige Anwendungen der Leittechnik herangezogen werden. In der vorliegenden Arbeit wird ein Framework entwickelt, welches einen Digitalen Zwilling in einer neuartigen modularen Leitsystemarchitektur für die Aufgabe der Überwachung und Steuerung zukünftiger Energiesysteme zweckdienlich einsetzbar macht. In Ergänzung zu den bereits vorhandenen Funktionen moderner Netzführungssysteme unterstützt das Konzept die Abbildung der Netzdynamik auf Basis eines dynamischen Netzmodells. Um eine realitätsgetreue Abbildung der Netzdynamik zu ermöglichen, werden zeitsynchrone Raumzeigermessungen für die Modellvalidierung und Modellparameterschätzung herangezogen. Dies erhöht die Aussagekraft von Sicherheitsanalysen, sowie das Vertrauen in die Modelle mit denen operative Entscheidungen generiert werden. Durch die Bereitstellung eines validierten, konsistenten und wartbaren Datenmodells auf der Grundlage von physikalischen Gesetzmäßigkeiten und während des Betriebs gewonnener Prozessdaten, adressiert der vorgestellte Architekturentwurf mehrere Schlüsselan-forderungen an moderne Netzleitsysteme. So ermöglicht das Framework einen höheren Automatisierungsgrad des Stromnetzbetriebs sowie den Einsatz von Entscheidungs-unterstützungsfunktionen bis hin zu vertrauenswürdigen Assistenzsystemen auf Basis kognitiver Systeme. Diese Funktionen können die Betriebssicherheit erhöhen und stellen einen wichtigen Beitrag zur Umsetzung der digitalen Transformation des Stromnetzbetriebs, sowie zur erfolgreichen Umsetzung der Energiewende dar. Das vorgestellte Konzept wird auf der Grundlage numerischer Simulationen untersucht, wobei die grundsätzliche Machbarkeit anhand von Fallstudien nachgewiesen wird

    Provision of Frequency Response from Wind Farms: A Review

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    Renewable sources of energy play a key role in the process of decarbonizing modern electric power systems. However, some renewable sources of energy operate in an intermittent, non-dispatchable way, which may affect the balance of the electrical grid. In this scenario, wind turbine generators must participate in the system frequency control to avoid jeopardizing the transmission and distribution systems. For that reason, additional control strategies are needed to ensure the frequency response of variable-speed wind turbines. This review article analyzes diverse control strategies at different levels which are aimed at contributing to power balancing and system frequency control, including energy storage systems.This research was funded by the Basque Government, through the project EKOHEGAZ (ELKARTEK KK-2021/00092), Diputación Foral de Álava (DFA) through the project CONAVANTER, and UPV/EHU through the project GIU20/063
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