1,720,958 research outputs found
Programación Dinámica Estocástica Dual aplicada a la optimización del sistema eléctrico uruguayo.
Get PDFLa operación de la red eléctrica en sistemas con un gran componente hidroeléctrico u otro tipo de almacenamiento de energía a menudo se presenta como un problema de programación dinámica, en el que las variables de estado representan la energía almacenada. Para evitar la maldición de la dimensionalidad al discretizar tales estados, se ha aplicado con éxito la técnica SDDP. Sin embargo, están surgiendo nuevos desafíos al abordar la optimización, con la penetración de fuentes renovables de mayor variabilidad, y la posible incorporación de almacenamiento de energía de plazos cortos. Estos nuevos componentes exponen dos dificultades. La alta variabilidad de los recursos renovables y el almacenamiento a corto plazo requieren representar escalas de tiempo más rápidas, lo que hace más complejo plantear el problema de despacho de un paso de tiempo. Además, surgen nuevas fuentes de incertidumbre y esto conduce a mitigar la maldición de la dimensionalidad estocástica, un aspecto no abordado por la técnica SDDP estándar. En primer lugar, se presenta una extensión preliminar de la técnica SDDP para considerar dos escalas de tiempo diferentes y un modelo markoviano para representar la situación hidrológica. El método se aplica a un modelo estilizado del sistema eléctrico uruguayo, apoyándose en nuevas implementaciones de código abierto de SDDP para realizar los cálculos. El análisis de los resultados se centra en los tiempos de ejecución e indica que el método sigue siendo tratable a pesar de la mayor dimensión del problema. Luego, se aborda el problema de mitigar la maldición de la dimensionalidad estocástica. Para esto, se desarrolló una biblioteca de software específica para poder incorporar aspectos técnicos no considerados en las bibliotecas existentes. Con esta herramienta se analizaron métodos para representar la incertidumbre, buscando reducir el número de problemas de optimización a resolver. Los resultados muestran una reducción considerable en los tiempos de ejecución, pero no lo suficiente como para abordar problemas de un tamaño similar a los que requiere la industria. Finalmente, se implementan diversas técnicas de poda de cortes buscando reducir la complejidad de cada uno de los problemas de despacho. Se obtienen buenos resultados en términos de convergencia algorítmica con una reducción en los tiempos de ejecución. Sin embargo, esta reducción sigue siendo insuficiente. Se concluye que la técnica SDDP aplicada a la planificación de largo plazo de sistemas pequeños con un alto componente de recursos renovables, debe ser considerada solamente cuando la dimensión del espacio de estados es alta. Cuando la dimensión del espacio de estados es pequeña, la maldición de la dimensionalidad estocástica es la que aparece como una limitante, obligando a aumentar el número de problemas lineales a resolver. Se evidencia también que el impacto en los tiempos de ejecución asociado a la complejidad del problema de despacho, como el número de restricciones o el número de variables enteras, no es significativo frente al impacto producido por las dos maldiciones de dimensionalidad estudiadas.The operation of the electric grid in systems with a large hydroelectric componentor other type of energy storage is often cast as a dynamic programming problem, inwhich state variables represent the stored energy. To avoid the curse of dimensionalityin discretizing such states, the SDDP technique has been successfully applied. Ho-wever, new demands are being placed on the optimization, with the penetration ofrenewable sources of faster variability, and the possible incorporation of shorter termenergy storage. These new components expose two difficulties. The high variability ofrenewable resources and short-term storage requires representing faster time scales,making it more complex to represent the dispatch problem of a stage. Also, new sour-ces of uncertainty arise wich lead to mitigating the curse of stochastic dimensionality,an aspect not addressed by the standard SDDP technique.A preliminary extension of the SDDP framework is presented to consider twodifferent time scales and a markovian model to represent the hydrological situation.The method is applied to a stylized model of the Uruguayan electricity system, relyingon new open source implementations of SDDP to carry out the computations. Theanalysis of the results focuses on the execution times and indicates that the methodremains treatable despite the increased dimension of the problem.Then, the problem of mitigating the curse of stochastic dimensionality is addressed.For this, a specific software library was developed to be able to incorporate technicalaspects not considered in existing libraries. With this tool, methods were analyzed torepresent uncertainty, seeking to reduce the number of optimization problems to besolved. The results show a considerable reduction in execution times, but not enoughto address problems of a size similar to those required by the industry.Finally, various cutting pruning techniques are implemented seeking to reduce thecomplexity of each of the dispatch problems. Good results are obtained in terms ofalgorithmic convergence with a reduction in execution times. However, this reductionis still insufficient.It is concluded that the SDDP technique applied to the long-term planning of smallsystems with a high component of renewable resources should be considered only whenthe dimension of the state space is high. When the state space dimension is small, thecurse of stochastic dimensionality is the one that appears as a limitation, forcing anincrease in the number of linear problems to be solved. It is also observed that theimpact on execution times associated with the complexity of the dispatch problem,such as the number of constraints or the number of integer variables, is not significantcompared to the impact produced by the two curses of dimesionality studied
Redes neuronales artificiales para la predicción de flujos de carga aplicadas al sistema de trasmisión de Uruguay
Get PDFVol. especial. Diciembre 2021 Congreso de Alta Tensión y Aislamiento ElectrónicoEn el presente trabajo se propone el uso de redes neuronales artificiales para la resolución del problema de flujos de carga. El estudio del flujo de carga de la red eléctrica constituye una herramienta fundamental para la operación y la planificación de un sistema eléctrico. En términos matemáticos el problema de flujos de carga se resuelve a través de un sistema de ecuaciones no lineales. Para dicha resolución tradicionalmente se han utilizado diversos métodos numéricos, principalmente el método de Newton-Raphson y sus variantes. Estos métodos numéricos aplicados a sistemas eléctricos de gran tamaño tienen un alto costo computacional asociado. Resolver una cantidad considerable de flujos de carga utilizando estos métodos implica incurrir en tiempos de ejecución que resultan prohibitivos en estudios sobre la red eléctrica. Este problema se vuelve crítico en estudios de casos de contingencia, incluso utilizando el criterio simple de contingencia N-1. La construcción de redes neuronales que aproximen la resolución de flujos de carga permite reducir significativamente los tiempos de ejecución de los estudios anteriormente mencionados. En este trabajo se propone el diseño de una arquitectura de red neuronal para la aproximación de flujos de carga. Utilizando la arquitectura diseñada se implementa un modelo de aproximación de flujos de carga. La validación de la herramienta se realiza utilizando la red de trasmisión de Uruguay. La aproximación obtenida para este caso de estudio es evaluada aplicando la métrica MAPE y se obtiene un valor de 2.6%, lo que constituye un resultado muy prometedor.In the present work, the use of artificial neural networks is proposed to solve the load flow problem. The study of the load flow of the electrical network constitutes a fundamental tool for the operation and planning of an electrical system. The load flow problem is solved by a system of non-linear equations. For this resolution, numerical methods have traditionally been used, mainly the Newton-Raphson method and its variants. These numerical methods applied to large electrical systems are very expensive in terms of computational cost. Solving a considerable number of load flows using these methods involves incurring in execution times that are prohibitive in studies of the electrical network. This problem becomes critical in contingency case studies, even using the simple N-1 contingency criterion. The construction of neural networks that approximate the resolution of load flows allows to significantly reducing the execution time of the aforementioned studies. In this work, the design of a neural network architecture for the approximation of load flows is proposed. Using the designed architecture, a load flow approximation model is implemented. The validation of the tool is carried out using the Uruguayan transmission network. The approximation obtained for this case study is evaluated by applying the MAPE metric and a value of 2.6% is obtained, which constitutes a very promising result.ANII_FSE_1_2018_1_15306
Programación Dinámica Estocástica Dual aplicada a la optimización del sistema eléctrico uruguayo.
Get PDFLa operación de la red eléctrica en sistemas con un gran componente hidroeléctrico u otro tipo de almacenamiento de energía a menudo se presenta como un problema de programación dinámica, en el que las variables de estado representan la energía almacenada. Para evitar la maldición de la dimensionalidad al discretizar tales estados, se ha aplicado con éxito la técnica SDDP. Sin embargo, están surgiendo nuevos desafíos al abordar la optimización, con la penetración de fuentes renovables de mayor variabilidad, y la posible incorporación de almacenamiento de energía de plazos cortos. Estos nuevos componentes exponen dos dificultades. La alta variabilidad de los recursos renovables y el almacenamiento a corto plazo requieren representar escalas de tiempo más rápidas, lo que hace más complejo plantear el problema de despacho de un paso de tiempo. Además, surgen nuevas fuentes de incertidumbre y esto conduce a mitigar la maldición de la dimensionalidad estocástica, un aspecto no abordado por la técnica SDDP estándar. En primer lugar, se presenta una extensión preliminar de la técnica SDDP para considerar dos escalas de tiempo diferentes y un modelo markoviano para representar la situación hidrológica. El método se aplica a un modelo estilizado del sistema eléctrico uruguayo, apoyándose en nuevas implementaciones de código abierto de SDDP para realizar los cálculos. El análisis de los resultados se centra en los tiempos de ejecución e indica que el método sigue siendo tratable a pesar de la mayor dimensión del problema. Luego, se aborda el problema de mitigar la maldición de la dimensionalidad estocástica. Para esto, se desarrolló una biblioteca de software específica para poder incorporar aspectos técnicos no considerados en las bibliotecas existentes. Con esta herramienta se analizaron métodos para representar la incertidumbre, buscando reducir el número de problemas de optimización a resolver. Los resultados muestran una reducción considerable en los tiempos de ejecución, pero no lo suficiente como para abordar problemas de un tamaño similar a los que requiere la industria. Finalmente, se implementan diversas técnicas de poda de cortes buscando reducir la complejidad de cada uno de los problemas de despacho. Se obtienen buenos resultados en términos de convergencia algorítmica con una reducción en los tiempos de ejecución. Sin embargo, esta reducción sigue siendo insuficiente. Se concluye que la técnica SDDP aplicada a la planificación de largo plazo de sistemas pequeños con un alto componente de recursos renovables, debe ser considerada solamente cuando la dimensión del espacio de estados es alta. Cuando la dimensión del espacio de estados es pequeña, la maldición de la dimensionalidad estocástica es la que aparece como una limitante, obligando a aumentar el número de problemas lineales a resolver. Se evidencia también que el impacto en los tiempos de ejecución asociado a la complejidad del problema de despacho, como el número de restricciones o el número de variables enteras, no es significativo frente al impacto producido por las dos maldiciones de dimensionalidad estudiadas.The operation of the electric grid in systems with a large hydroelectric componentor other type of energy storage is often cast as a dynamic programming problem, inwhich state variables represent the stored energy. To avoid the curse of dimensionalityin discretizing such states, the SDDP technique has been successfully applied. Ho-wever, new demands are being placed on the optimization, with the penetration ofrenewable sources of faster variability, and the possible incorporation of shorter termenergy storage. These new components expose two difficulties. The high variability ofrenewable resources and short-term storage requires representing faster time scales,making it more complex to represent the dispatch problem of a stage. Also, new sour-ces of uncertainty arise wich lead to mitigating the curse of stochastic dimensionality,an aspect not addressed by the standard SDDP technique.A preliminary extension of the SDDP framework is presented to consider twodifferent time scales and a markovian model to represent the hydrological situation.The method is applied to a stylized model of the Uruguayan electricity system, relyingon new open source implementations of SDDP to carry out the computations. Theanalysis of the results focuses on the execution times and indicates that the methodremains treatable despite the increased dimension of the problem.Then, the problem of mitigating the curse of stochastic dimensionality is addressed.For this, a specific software library was developed to be able to incorporate technicalaspects not considered in existing libraries. With this tool, methods were analyzed torepresent uncertainty, seeking to reduce the number of optimization problems to besolved. The results show a considerable reduction in execution times, but not enoughto address problems of a size similar to those required by the industry.Finally, various cutting pruning techniques are implemented seeking to reduce thecomplexity of each of the dispatch problems. Good results are obtained in terms ofalgorithmic convergence with a reduction in execution times. However, this reductionis still insufficient.It is concluded that the SDDP technique applied to the long-term planning of smallsystems with a high component of renewable resources should be considered only whenthe dimension of the state space is high. When the state space dimension is small, thecurse of stochastic dimensionality is the one that appears as a limitation, forcing anincrease in the number of linear problems to be solved. It is also observed that theimpact on execution times associated with the complexity of the dispatch problem,such as the number of constraints or the number of integer variables, is not significantcompared to the impact produced by the two curses of dimesionality studied
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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