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Visualização de sistemas de potência com dados georreferenciados / Display of Power Systems with Georeferenced dataGOMES JUNIOR, Daniel Lima 15 July 2010 (has links)
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Previous issue date: 2010-07-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / This paper presents a study about the electric power systems visualization presenting as results: the implementation of the main visualization techniques used in the operation and control of these systems; a new representation of electrical magnitudes with the use of Thiessen polygons; and finally, the presentation of a new paradigm in information management and manipulation of the power system graphics in a three-dimensional environment. Moreover, it presents the architecture used in the construction of this threedimensional viewing environment, which in our work, enabled the creation of a virtual control room where operators can build and add to the virtual environment the wanted and available visualization in the management of the electric system, enabling the analysis of the problem from several di erent aspects. / Este trabalho apresenta um estudo sobre visualização de sistemas elétricos de potência e tem como resultados: a implementação das principais técnicas de visualização utilizadas no controle e operação destes sistemas; uma nova representação de grandezas elétricas com a utilização dos polígonos de Thiessen; e por fim, a apresentação de um novo paradigma no gerenciamento das informações e manipulação dos gréficos dos sistemas de potência em um ambiente tridimensional. Ademais, apresenta-se a arquitetura utilizada na construção deste ambiente de visualização tridimensional que, em nosso trabalho, possibilitou a criação de uma sala virtual de controle, na qual os operadores podem construir e adicionar ao ambiente virtual as visualizações desejadas e disponíveis no gerenciamento do sistema elétrico, possibilitando a análise do problema sob vários aspectos diferentes.
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Comparison of Hydrologic Model Performance Statistics Using Thiessen Polygon Rain Gauge and NEXRAD Precipitation Input Methods at Different Watershed Spatial Scales and Rainfall Return FrequenciesTancreto, Amanda E 01 January 2015 (has links)
As hydrological computer modeling software continues to increase in complexity, the need for further understanding of the value of different model input datasets becomes apparent. Frequently used precipitation model input include rain gauge data and next-generation radar–based (NEXRAD) rainfall data. Rain gauge data are usually interpolated across a model domain using various methods including the Thiessen Polygon methodology, which may be data-sparse in some areas and overly data-dense in others. However, rain gauge data are generally very easy to use in hydrologic model development, often requiring little to no data processing. NEXRAD data have the potential to improve hydrologic runoff estimates due to the increased spatial resolution of the data: but has its own issues regarding accuracy, false precipitation indications, and difficulties due to data processing. Previous studies have investigated the value of NEXRAD input versus traditional rain gauge data inputs for hydrologic studies; however, results are inconclusive as to which precipitation source provides more accurate results. Limited work has been done to compare the value of these datasets at multiple spatial scales, especially in Florida, a study area dominated by low topographic drive and sub-tropical weather. In addition, little to no research has been done regarding the value of NEXRAD versus rain gauge data inputs at different rainfall return frequencies. The proposed research will utilize a hydrological rain-runoff model (HEC-HMS) of the Upper St. Johns River Basin, Florida to compare the performance of the two precipitation data input types at various watershed spatial scales and rainfall return frequencies. Statistical analysis of the hydrological model “goodness-of-fit” results will be utilized to assess the watershed scaling and rainfall frequency requirements to xii which NEXRAD data provide little to no advantage over standard rain gauges using the Thiessen Polygon method for estimating rainfall totals across a model domain.
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