467 research outputs found

    MATLAB

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    A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

    Computer aided design of 3D of renewable energy platform for Togo's smart grid power system infrastructure

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    The global requirement for sustainable energy provision will become increasingly important over the next fifty years as the environmental effects of fossil fuel use become apparent. Therefore, the issues surrounding integration of renewable energy supplies need to be considered carefully. The focus of this work was the development of an innovative computer aided design of a 3 Dimensional renewable energy platform for Togo’s smart grid power system infrastructure. It demonstrates its validation for industrial, commercial and domestic applications. The Wind, Hydro, and PV system forming our 3 Dimensional renewable energy power generation systems introduces a new path for hybrid systems which extends the system capacities to include, a stable and constant clean energy supply, a reduced harmonic distortion, and an improved power system efficiency. Issues requiring consideration in high percentage renewable energy systems therefore includes the reliability of the supply when intermittent sources of electricity are being used, and the subsequent necessity for storage and back-up generation The adoption of Genetic algorithms in this case was much suited in minimizing the THD as the adoption of the CHB-MLI was ideal for connecting renewable energy sources with an AC grid. Cascaded inverters have also been proposed for use as the main traction drive in electric vehicles, where several batteries or ultra-capacitors are well suited to serve as separate DC sources. The simulation done in various non-linear load conditions showed the proportionality of an integral control based compensating cascaded passive filter thereby balancing the system even in non-linear load conditions. The measured total harmonic distortion of the source currents was found to be 2.36% thereby in compliance with IEEE 519-1992 and IEC 61000-3 standards for harmonics This work has succeeded in developing a more complete tool for analysing the feasibility of integrated renewable energy systems. This will allow informed decisions to be made about the technical feasibility of supply mix and control strategies, plant type, sizing and storage sizing, for any given area and range of supply options. The developed 3D renewable energy platform was examined and evaluated using CAD software analysis and a laboratory base mini test. The initial results showed improvements compared to other hybrid systems and their existing control systems. There was a notable improvement in the dynamic load demand and response, stability of the system with a reduced harmonic distortion. The derivatives of this research therefore proposes an innovative solution and a path for Togo and its intention of switching to renewable energy especially for its smart grid power system infrastructure. It demonstrates its validation for industrial, commercial and domestic applicationsN/

    Real-Time Selective Harmonic Minimization for Multilevel Inverters Using Genetic Algorithm and Artificial Neural Network Angle Generation

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    This work approximates the selective harmonic elimination problem using Artificial Neural Networks (ANN) to generate the switching angles in an 11-level full bridge cascade inverter powered by five varying DC input sources. Each of the five full bridges of the cascade inverter was connected to a separate 195W solar panel. The angles were chosen such that the fundamental was kept constant and the low order harmonics were minimized or eliminated. A non-deterministic method is used to solve the system for the angles and to obtain the data set for the ANN training. The method also provides a set of acceptable solutions in the space where solutions do not exist by analytical methods. The trained ANN is a suitable tool that brings a small generalization effect on the angles\u27 precision and is able to perform in real time (50/60Hz time window)

    Power Converters in Power Electronics

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    In recent years, power converters have played an important role in power electronics technology for different applications, such as renewable energy systems, electric vehicles, pulsed power generation, and biomedical sciences. Power converters, in the realm of power electronics, are becoming essential for generating electrical power energy in various ways. This Special Issue focuses on the development of novel power converter topologies in power electronics. The topics of interest include, but are not limited to: Z-source converters; multilevel power converter topologies; switched-capacitor-based power converters; power converters for battery management systems; power converters in wireless power transfer techniques; the reliability of power conversion systems; and modulation techniques for advanced power converters

    Data Mining Applications to Fault Diagnosis in Power Electronic Systems: A Systematic Review

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    Power Electronics and Energy Management for Battery Storage Systems

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    The deployment of distributed renewable generation and e-mobility systems is creating a demand for improved dynamic performance, flexibility, and resilience in electrical grids. Various energy storages, such as stationary and electric vehicle batteries, together with power electronic interfaces, will play a key role in addressing these requests thanks to their enhanced functionality, fast response times, and configuration flexibility. For the large-scale implementation of this technology, the associated enabling developments are becoming of paramount importance. These include energy management algorithms; optimal sizing and coordinated control strategies of different storage technologies, including e-mobility storage; power electronic converters for interfacing renewables and battery systems, which allow for advanced interactions with the grid; and increase in round-trip efficiencies by means of advanced materials, components, and algorithms. This Special Issue contains the developments that have been published b researchers in the areas of power electronics, energy management and battery storage. A range of potential solutions to the existing barriers is presented, aiming to make the most out of these emerging technologies

    Applications of Power Electronics:Volume 1

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    Contrôle avancé des convertisseurs de puissance multi-niveaux pour applications sur réseaux faibles

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    139 p.El advenimiento progresivo de las microrredes que incorporan fuentes de energía renovable está dando lugar a un nuevo paradigma de distribución de la electricidad. Este nuevo planteamiento sirve de interfaz entre consumidores no controlados y fuentes intermitentes, implicando desafíos adicionales en materia de conversión, almacenamiento y gestión de la energía.Los convertidores de potencia se adaptan en consecuencia, en particular con el desarrollo de los convertidores multinivel, que integrando los mismos componentes que sus predecesores y un control más complejo, soportan potencias más altas y aseguran una mejor calidad de la energía.Debido al carácter híbrido de los convertidores de potencia, su control se divide comúnmente en dos partes: por un lado, el control de los objetivos continuos vinculados a la función principal de los convertidores de servir de interfaz, y, por otro, el control discreto de los interruptores de potencia, conocido con el nombre de modulación.En este contexto, las exigencias crecientes en términos de eficiencia, fiabilidad, versatilidad y rendimiento hacen necesaria una mejora de la inteligencia de la estructura de control. Para cumplir conestos requisitos, se propone tratar mediante un solo controlador ambas problemáticas, la vinculada a la función de interfaz de los convertidores y la relacionada con su naturaleza discreta. Esta decisión implica incorporar la no-linealidad de los convertidores de potencia en el controlador, lo que equivale a suprimir el bloque de modulación, que constituye la solución tradicional para linealizar el comportamiento interno de los convertidores. Se adopta un planteamiento de Control Predictivo basado en Modelos (MPC) para abordar la no-linealidad y la gran diversidad de objetivos de control que acompañan a los convertidores de potencia.El algoritmo desarrollado combina teoría de grafos ¿con algoritmos de Dijkstra, A* y otros¿ con un modelo de estado especial para sistemas conmutados al objeto de proporcionar una herramienta potente y universal, capaz de manipular simultáneamente el carácter cuantificado de los interruptores de potencia y el continuo de las entidades interconectadas por el convertidor. Se han obtenido resultados sobre la estabilidad y la controlabilidad de los modelos de estado conmutados aplicados al caso particular de los convertidores de potencia.El controlador así desarrollado y descrito se ha examinado en simulación frente a varios casos y aplicaciones: inversor aislado o conectado a la red, rectificador y convertidor bidireccional. Se ha empleado la misma estructura de control para tres topologías de convertidor multinivel: Neutral-Point Clamped, Flying Capacitor y Cascaded H-Bridge. Al objeto de adaptarse a los cambios citados, lo único que varía en el controlador es el modelo del convertidor adoptado para la predicción, así como la función de coste, que traduce los requisitos de control en un problema de optimización a solucionar por el algoritmo. Un cambio de topología resulta en una modificación del modelo interno, sin impacto sobre la función de coste, mientras que variaciones de esta función son suficientes para adaptarse a la aplicación.Los resultados muestran que el controlador logra actuar directamente sobre los interruptores de potencia en función de diversos requisitos. Los desempeños de la estructura de control propuesta son similares a los de las numerosas estructuras dedicadas a cada uno de los casos estudiados, excepto en el caso de operación en modo rectificador, en el que la versatilidad y rapidez de control obtenidos son particularmente interesantes.En definitiva, el controlador planteado puede emplearse para diferentes aplicaciones, topologías, objetivos y limitaciones. Si bien las estructuras de control lineal tradicionales han de modificarse, a menudo en profundidad, para afrontar diferentes modos de operación o requisitos de control, dichas alteraciones no tienen ningún impacto sobre la arquitectura del controlador MPC obtenido, lo que pone de manifiesto su versatilidad, así como su universalidad, también demostrada por su capacidad para adaptarse a diferentes convertidores de potencia sin modificaciones importantes. Finalmente, la solución propuesta elude por completo la complejidad de la modulación, ofreciendo simplicidad y flexibilidad al diseño del control

    Real-Time Machine Learning Based Open Switch Fault Detection and Isolation for Multilevel Multiphase Drives

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    Due to the rapid proliferation interest of the multiphase machines and their combination with multilevel inverters technology, the demand for high reliability and resilient in the multiphase multilevel drives is increased. High reliability can be achieved by deploying systematic preventive real-time monitoring, robust control, and efficient fault diagnosis strategies. Fault diagnosis, as an indispensable methodology to preserve the seamless post-fault operation, is carried out in consecutive steps; monitoring the observable signals to generate the residuals, evaluating the observations to make a binary decision if any abnormality has occurred, and identifying the characteristics of the abnormalities to locate and isolate the failed components. It is followed by applying an appropriate reconfiguration strategy to ensure that the system can tolerate the failure. The primary focus of presented dissertation was to address employing computational and machine learning techniques to construct a proficient fault diagnosis scheme in multilevel multiphase drives. First, the data-driven nonlinear model identification/prediction methods are used to form a hybrid fault detection framework, which combines module-level and system-level methods in power converters, to enhance the performance and obtain a rapid real-time detection. Applying suggested nonlinear model predictors along with different systems (conventional two-level inverter and three-level neutral point clamped inverter) result in reducing the detection time to 1% of stator current fundamental period without deploying component-level monitoring equipment. Further, two methods using semi-supervised learning and analytical data mining concepts are presented to isolate the failed component. The semi-supervised fuzzy algorithm is engaged in building the clustering model because the deficient labeled datasets (prior knowledge of the system) leads to degraded performance in supervised clustering. Also, an analytical data mining procedure is presented based on data interpretability that yields two criteria to isolate the failure. A key part of this work also dealt with the discrimination between the post-fault characteristics, which are supposed to carry the data reflecting the fault influence, and the output responses, which are compensated by controllers under closed-loop control strategy. The performance of all designed schemes is evaluated through experiments

    Cascaded- and Modular-Multilevel Converter Laboratory Test System Options: A Review

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    The increasing importance of cascaded multilevel converters (CMCs), and the sub-category of modular multilevel converters (MMCs), is illustrated by their wide use in high voltage DC connections and in static compensators. Research is being undertaken into the use of these complex pieces of hardware and software for a variety of grid support services, on top of fundamental frequency power injection, requiring improved control for non-traditional duties. To validate these results, small-scale laboratory hardware prototypes are often required. Such systems have been built by many research teams around the globe and are also increasingly commercially available. Few publications go into detail on the construction options for prototype CMCs, and there is a lack of information on both design considerations and lessons learned from the build process, which will hinder research and the best application of these important units. This paper reviews options, gives key examples from leading research teams, and summarizes knowledge gained in the development of test rigs to clarify design considerations when constructing laboratory-scale CMCs.This work was supported in part by The University of Manchester supported by the National Innovation Allowance project ``VSC-HVDC Model Validation and Improvement'' and Dr. Heath's iCASE Ph.D. studentship supported through Engineering and Physical Sciences Research Council (EPSRC) and National Grid, in part by the Imperial College London supported by EPSRC through the HubNet Extension under Grant EP/N030028/1, in part by an iCASE Ph.D. Studentship supported by EPSRC and EDF Energy and the CDT in Future Power Networks under Grant EP/L015471/1, in part by University of New South Wales (UNSW) supported by the Solar Flagships Program through the Education Infrastructure Fund (EIF), in part by the Australian Research Council through the Discovery Early Career Research Award under Grant DECRA_DE170100370, in part by the Basque Government through the project HVDC-LINK3 under Grant ELKARTEK KK-2017/00083, in part by the L2EP research group at the University of Lille supported by the French TSO (RTE), and in part by the Hauts-de-France region of France with the European Regional Development Fund under Grant FEDER 17007725
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