303 research outputs found
Contrôle avancé des convertisseurs de puissance multi-niveaux pour applications sur réseaux faibles
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
Automation and hypermedia technology applications
This paper represents a progress report on HyLite (Hypermedia Library technology): a research and development activity to produce a versatile system as part of NASA's technology thrusts in automation, information sciences, and communications. HyLite can be used as a system or tool to facilitate the creation and maintenance of large distributed electronic libraries. The contents of such a library may be software components, hardware parts or designs, scientific data sets or databases, configuration management information, etc. Proliferation of computer use has made the diversity and quantity of information too large for any single user to sort, process, and utilize effectively. In response to this information deluge, we have created HyLite to enable the user to process relevant information into a more efficient organization for presentation, retrieval, and readability. To accomplish this end, we have incorporated various AI techniques into the HyLite hypermedia engine to facilitate parameters and properties of the system. The proposed techniques include intelligent searching tools for the libraries, intelligent retrievals, and navigational assistance based on user histories. HyLite itself is based on an earlier project, the Encyclopedia of Software Components (ESC) which used hypermedia to facilitate and encourage software reuse
Regulation of positive-strand RNA virus replication: The emerging role of phosphorylation.
Protein phosphorylation is a reversible post-translational modification that plays a fundamental role in the regulation of many cellular processes. Phosphorylation can modulate protein properties such as enzymatic activity, stability, subcellular localization or interaction with binding partners. The importance of phosphorylation of the replication proteins of negative-strand RNA viruses has previously been documented but recent evidence suggests that replication of positive-strand RNA viruses - the largest class of viruses, including significant human, animal and plant pathogens - may also be regulated by phosphorylation events. The objective of this review is to summarize current knowledge regarding the various regulatory roles played by phosphorylation of nonstructural viral proteins in the replication of positive-strand RNA viruses
Phishing attack detection using machine learning method
The development of computer networks today is increased rapidly. This can be shown based on the trend of every computer user around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether they used it for work and assignment purposes, or for the access to social media accounts, such as Instagram, Facebook and Twitter. However, in this wide use of this computer network, the privacy of computer users is in danger. This is because some of the computer users do not install security system in their computer. This problem will allow the hackers to hack and commit the network attacks. This is very dangerous, especially to the important organizations because hackers can disable the online system in the company, steal confidential information and subsequently steal company money through online without being aware of any one. The attacks that can be made includes denial-of-Service attack, DNS spoofing attack and phishing attack. The goal of this study is to apply anti-phishing tools in preventing the network security attack in an organization. In this study, phishing attacks have been studied thoroughly. After a study has been made, machine learning method is used to prevent the phishing attack. Besides, the study also shows that phishing attack is always related to the spam attack, where there might be attached phishing link in the spam message. This spam message includes the email and the SMS message that received by the user. There are several algorithms that can be used in the machine learning method to prevent the both attacks. The Naïve Bayes algorithm, Decision Tree algorithm and Support Vector Machine algorithm has been used to prevent the spam attack, as well as the phishing attack. The study of this algorithm is made thoroughly and the methods in implementing this algorithm have been discussed in detail. The experiment is conducted for the datasets that obtained by using machine learning method. The results are obtained, showing the performance of machine learning method on each dataset
Gerald Finzi and John Ireland: A Stylistic Comparison of Compositional Approaches in the Context of Ten Selected Poems by Thomas Hardy
The purpose of this paper is to provide a stylistic analysis that contrasts five Thomas Hardy settings by Gerald Finzi with five settings by John Ireland. In order to investigate the apparent intuitiveness with which both Ireland and Finzi approached Thomas Hardy\u27s poetry, biographical information is provided to reveal similarities in the backgrounds of each composer. Highlighted are the compositional techniques and text setting ideologies each composer utilized when facing the challenges and eccentricities of Hardy\u27s poetry. A brief discussion on the philosophical foundations of Thomas Hardy\u27s poetry is also included. The repertoire discussed within are the settings Summer Schemes , The Phantom , Rollicum-Rorum , The Clock of the Years , and Channel Firing by Gerald Finzi as well as Summer Schemes , The tragedy of that moment , Beckon to me to come , Dear, think not that they will forget you and Weathers by John Ireland
Représentation d’état directe pour la commandeprédictive de convertisseurs de puissance multi-niveaux
International audienceRESUME-De nouveaux paradigmes de production et de distribution de l'électricité émergent, impactant entre autres les convertisseurs de puissance. En conséquence, les convertisseurs et leur contrôle évoluent rapidement. Malheureusement, ces derniers, gênés par la composante discrète qu'apportent les composants actifs des convertisseurs, se spécialisent au fur et à mesure. L'objectif de cet article est de proposer un contrôleur intelligent capable de traiter la plus grande variété possible d'applications, d'objectifs et de contraintes. Pour ce faire, un algorithme MPC permettant de se passer de modulation est développé conjointement à un modèle applicable à tous les convertisseurs de puissance
Review of the machine learning methods in the classification of phishing attack
The development of computer networks today has increased rapidly. This can be seen based on the trend of computer users around the world, whereby they need to connect their computer to the Internet. This shows that the use of Internet networks is very important, whether for work purposes or access to social media accounts. However, in widely using this computer network, the privacy of computer users is in danger, especially for computer users who do not install security systems in their computer. This problem will allow hackers to hack and commit network attacks. This is very dangerous, especially for Internet users because hackers can steal confidential information such as bank login account or social media login account. The attacks that can be made include phishing attacks. The goal of this study is to review the types of phishing attacks and current methods used in preventing them. Based on the literature, the machine learning method is widely used to prevent phishing attacks. There are several algorithms that can be used in the machine learning method to prevent these attacks. This study focused on an algorithm that was thoroughly made and the methods in implementing this algorithm are discussed in detail
Hierarchical Model Predictive Control to Coordinate a Vehicle-to-Grid System Coupled to Building Microgrids
Aiming to take full advantage of Electric Vehicles' (EVs) batteries, this paper proposes a two-level hierarchical model predictive controller coupled with an innovative charging-discharging scheduler for EVs in Building Microgrids (BMGs). This paper provides a complete framework for the design of this control structure and analyses its performance regarding the state of charge of the EVs at departure time, the self-consumption rate, and the coverage rate, considering a residential BMG equipped with photovoltaic panels and static Li-ion batteries. The results and performance of the proposed control architecture are compared to two other solutions: a hierarchical predictive controller with no scheduler and a rule-based algorithm. A technological and economical study is also performed considering variables such as the dimension of the EV's park, the price of energy, the cost of maintenance, the possibility to discharge or not into the grid, and the execution time of the control architecture. The simulation results conducted in MATLAB Simulink demonstrated that the proposed control structure ensures the full charging of all vehicles at departure time while also improving the self-consumption rate of the BMG with a relatively low stress on the needed computation capacities, even when considering a large fleet of vehicles
Autonomous observer of hydrogen storage to enhance a model predictive control structure for building microgrids
Hydrogen energy storage has emerged as a promising technology to improve the integration of renewable energy sources in building microgrids. However, inaccuracies in the modelling of fuel cells and electrolysers reduce the performance of building microgrids' energy management system. To improve the flexibility of building microgrids, this paper proposes to associate a two-level hierarchical model predictive controller empowered with an Autonomous Observer of Hydrogen Storage (AOHS). This novel observer evaluates the hydrogen production and consumption rates, storing little past data and needing no tuning of the parameters. Relying only on instantaneous data measurement, the algorithm can estimate the tank's level of hydrogen with an average relative error inferior to 2 %, even under measurement noise. A case-study based on a building microgrid currently under construction serves as the basis for all simulations. The performance of the AOHS is evaluated by comparing the self-consumption rates of the case-study when governed by two-level energy management system: one level using a fixed parameters model and the other one equipped with the proposed AOHS algorithm. Results show that the microgrid associated to the AOHS has better self-consumption compared to the microgrid with fixed parameters, as well as a better robustness regarding the measurement noise and modelling error. Furthermore, this algorithm demonstrates a planning function as it facilitates the energy planning from the aggregator's point of view and the external grid management
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