989 resultados para Meteorological parameters


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Die Maßnahmen zur Förderung der Windenergie in Deutschland haben wichtige Anstöße zur technologischen Weiterentwicklung geliefert und die Grundlagen für den enormen Anlagenzubau geschaffen. Die installierte Windleistung hat heute eine beachtliche Größenordnung erreicht und ein weiteres Wachstum in ähnlichen Dimensionen ist auch für die nächsten Jahre zu erwarten. Die aus Wind erzeugte elektrische Leistung deckt bereits heute in einigen Netzbereichen die Netzlast zu Schwachlastzeiten. Dies zeigt, dass die Windenergie ein nicht mehr zu vernachlässigender Faktor in der elektrischen Energieversorgung geworden ist. Im Rahmen der Kraftwerkseinsatzplanung sind Betrag und Verlauf der Windleistung des folgenden Tages mittlerweile zu wichtigen und zugleich schwierig zu bestimmenden Variablen geworden. Starke Schwankungen und falsche Prognosen der Windstromeinspeisung verursachen zusätzlichen Bedarf an Regel- und Ausgleichsleistung durch die Systemführung. Das im Rahmen dieser Arbeit entwickelte Prognosemodell liefert die zu erwartenden Windleistungen an 16 repräsentativen Windparks bzw. Gruppen von Windparks für bis zu 48 Stunden im Voraus. Aufgrund von prognostizierten Wetterdaten des deutschen Wetterdienstes (DWD) werden die Leistungen der einzelnen Windparks mit Hilfe von künstlichen neuronalen Netzen (KNN) berechnet. Diese Methode hat gegenüber physikalischen Verfahren den Vorteil, dass der komplexe Zusammenhang zwischen Wettergeschehen und Windparkleistung nicht aufwendig analysiert und detailliert mathematisch beschrieben werden muss, sondern anhand von Daten aus der Vergangenheit von den KNN gelernt wird. Das Prognosemodell besteht aus zwei Modulen. Mit dem ersten wird, basierend auf den meteorologischen Vorhersagen des DWD, eine Prognose für den Folgetag erstellt. Das zweite Modul bezieht die online gemessenen Leistungsdaten der repräsentativen Windparks mit ein, um die ursprüngliche Folgetagsprognose zu verbessern und eine sehr genaue Kurzzeitprognose für die nächsten drei bis sechs Stunden zu berechnen. Mit den Ergebnissen der Prognosemodule für die repräsentativen Standorte wird dann über ein Transformationsmodell, dem so genannten Online-Modell, die Gesamteinspeisung in einem größeren Gebiet berechnet. Das Prognoseverfahren hat seine besonderen Vorzüge in der Genauigkeit, den geringen Rechenzeiten und den niedrigen Betriebskosten, da durch die Verwendung des bereits implementierten Online-Modells nur eine geringe Anzahl von Vorhersage- und Messstandorten benötigt wird. Das hier vorgestellte Prognosemodell wurde ursprünglich für die E.ON-Netz GmbH entwickelt und optimiert und ist dort seit Juli 2001 im Einsatz. Es lässt sich jedoch auch leicht an andere Gebiete anpassen. Benötigt werden dazu nur die Messdaten der Leistung ausgewählter repräsentativer Windparks sowie die dazu gehörenden Wettervorhersagen, um die KNN entsprechend zu trainieren.

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In dieser Arbeit werden verschiedene Computermodelle, Rechenverfahren und Methoden zur Unterstützung bei der Integration großer Windleistungen in die elektrische Energieversorgung entwickelt. Das Rechenmodell zur Simulation der zeitgleich eingespeisten Windenergie erzeugt Summenganglinien von beliebig zusammengestellten Gruppen von Windenergieanlagen, basierend auf gemessenen Wind- und Leistungsdaten der nahen Vergangenheit. Dieses Modell liefert wichtige Basisdaten für die Analyse der Windenergieeinspeisung auch für zukünftige Szenarien. Für die Untersuchung der Auswirkungen von Windenergieeinspeisungen großräumiger Anlagenverbünde im Gigawattbereich werden verschiedene statistische Analysen und anschauliche Darstellungen erarbeitet. Das im Rahmen dieser Arbeit entwickelte Modell zur Berechnung der aktuell eingespeisten Windenergie aus online gemessenen Leistungsdaten repräsentativer Windparks liefert wertvolle Informationen für die Leistungs- und Frequenzregelung der Netzbetreiber. Die zugehörigen Verfahren zur Ermittlung der repräsentativen Standorte und zur Überprüfung der Repräsentativität bilden die Grundlage für eine genaue Abbildung der Windenergieeinspeisung für größere Versorgungsgebiete, basierend auf nur wenigen Leistungsmessungen an Windparks. Ein weiteres wertvolles Werkzeug für die optimale Einbindung der Windenergie in die elektrische Energieversorgung bilden die Prognosemodelle, die die kurz- bis mittelfristig zu erwartende Windenergieeinspeisung ermitteln. In dieser Arbeit werden, aufbauend auf vorangegangenen Forschungsarbeiten, zwei, auf Künstlich Neuronalen Netzen basierende Modelle vorgestellt, die den zeitlichen Verlauf der zu erwarten Windenergie für Netzregionen und Regelzonen mit Hilfe von gemessenen Leistungsdaten oder prognostizierten meteorologischen Parametern zur Verfügung stellen. Die softwaretechnische Zusammenfassung des Modells zur Berechnung der aktuell eingespeisten Windenergie und der Modelle für die Kurzzeit- und Folgetagsprognose bietet eine attraktive Komplettlösung für die Einbindung der Windenergie in die Leitwarten der Netzbetreiber. Die dabei entwickelten Schnittstellen und die modulare Struktur des Programms ermöglichen eine einfache und schnelle Implementierung in beliebige Systemumgebungen. Basierend auf der Leistungsfähigkeit der Online- und Prognosemodelle werden Betriebsführungsstrategien für zu Clustern im Gigawattbereich zusammengefasste Windparks behandelt, die eine nach ökologischen und betriebswirtschaftlichen Gesichtspunkten sowie nach Aspekten der Versorgungssicherheit optimale Einbindung der geplanten Offshore-Windparks ermöglichen sollen.

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Chemical and meteorological parameters measured on board the Facility for Airborne Atmospheric Measurements (FAAM) BAe 146 Atmospheric Research Aircraft during the African Monsoon Multidisciplinary Analysis (AMMA) campaign are presented to show the impact of NOx emissions from recently wetted soils in West Africa. NO emissions from soils have been previously observed in many geographical areas with different types of soil/vegetation cover during small scale studies and have been inferred at large scales from satellite measurements of NOx. This study is the first dedicated to showing the emissions of NOx at an intermediate scale between local surface sites and continental satellite measurements. The measurements reveal pronounced mesoscale variations in NOx concentrations closely linked to spatial patterns of antecedent rainfall. Fluxes required to maintain the NOx concentrations observed by the BAe-146 in a number of cases studies and for a range of assumed OH concentrations (1×106 to 1×107 molecules cm−3) are calculated to be in the range 8.4 to 36.1 ng N m−2 s−1. These values are comparable to the range of fluxes from 0.5 to 28 ng N m−2 s−1 reported from small scale field studies in a variety of non-nutrient rich tropical and sub-tropical locations reported in the review of Davidson and Kingerlee (1997). The fluxes calculated in the present study have been scaled up to cover the area of the Sahel bounded by 10 to 20 N and 10 E to 20 W giving an estimated emission of 0.03 to 0.30 Tg N from this area for July and August 2006. The observed chemical data also suggest that the NOx emitted from soils is taking part in ozone formation as ozone concentrations exhibit similar fine scale structure to the NOx, with enhancements over the wet soils. Such variability can not be explained on the basis of transport from other areas. Delon et al. (2008) is a companion paper to this one which models the impact of soil NOx emissions on the NOx and ozone concentration over West Africa during AMMA. It employs an artificial neural network to define the emissions of NOx from soils, integrated into a coupled chemistry-dynamics model. The results are compared to the observed data presented in this paper. Here we compare fluxes deduced from the observed data with the model-derived values from Delon et al. (2008).

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Recently, studies have shown that the classroom environment is very important for students' health and performance. Thus, the evaluation of indoor air quality (IAQ) in a classroom is necessary to ensure students' well-being. In this paper the emphasis is on airborne concentration of particulate matter (PM) in adult education rooms. The mass concentration of PM10 particulates was measured in two classrooms under different ventilation methods in the University of Reading, UK, during the winter period of 2008. In another study the measurement of the concentration of particles was accompanied with measurements of CO2 concentration in these classrooms but this study is the subject of another publication. The ambient PM10, temperature, relative humidity, wind speed and direction, and rainfall events were monitored as well. In general, this study showed that outdoor particle concentrations and outdoor meteorological parameters were identified as significant factors influencing indoor particle concentration levels. Ventilation methods showed significant effects on air change rate and on indoor/outdoor (I/O) concentration ratios. Higher levels of indoor particulates were seen during occupancy periods. I/O ratios were significantly higher when classrooms were occupied than when they were unoccupied, indicating the effect of both people presence and outdoor particle concentration levels. The concentrations of PM10 indoors and outdoors did not meet the requirements of WHO standards for PM10 annual average.

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As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.

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Numerical weather prediction can be regarded as an initial value problem whereby the governing atmospheric equations are integrated forward from fully determined initial values of the meteorological parameters. However, in spite of the considerable improvements of the observing systems in recent years, the initial values are known only incompletely and inaccurately and one of the major tasks of any forecasting centre is to determine the best possible initial state from available observations.

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The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

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dIn this work, a perceptron neural-network technique is applied to estimate hourly values of the diffuse solar-radiation at the surface in São Paulo City, Brazil, using as input the global solar-radiation and other meteorological parameters measured from 1998 to 2001. The neural-network verification was performed using the hourly measurements of diffuse solar-radiation obtained during the year 2002. The neural network was developed based on both feature determination and pattern selection techniques. It was found that the inclusion of the atmospheric long-wave radiation as input improves the neural-network performance. on the other hand traditional meteorological parameters, like air temperature and atmospheric pressure, are not as important as long-wave radiation which acts as a surrogate for cloud-cover information on the regional scale. An objective evaluation has shown that the diffuse solar-radiation is better reproduced by neural network synthetic series than by a correlation model. (C) 2004 Elsevier Ltd. All rights reserved.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A poluição atmosférica é considerada atualmente um dos maiores problemas da sociedade contemporânea, por ameaçar sua qualidade de vida, pois gera impactos negativos no meio ambiente natural e antrópico. Dentre as formas de controle da poluição atmosférica de fontes fixas podem-se destacar a diluição das emissões na atmosfera devido aos efeitos de dispersão, a adoção de equipamentos de controle antes do lançamento dos gases ou a realocação de fonte, visto ser uma possibilidade a ser sugerida durante o procedimento de licenciamento ambiental de empreendimentos com potencial poluidor do ar. Atualmente modelos computacionais de dispersão de poluentes na atmosfera vêm sendo amplamente utilizados na simulação da concentração de poluentes, visando auxiliar órgãos ambientais no prognóstico da qualidade do ar ou suprir deficiências de monitoramento de emissões atmosféricas. O presente trabalho estudou a qualidade do ar e avaliou a dispersão de poluentes atmosféricos sobre Vila do Conde e áreas de influência do Distrito Industrial de Barcarena, no município de Barcarena, estado do Pará, com auxílio do modelo AERMOD View, visto a possibilidade de se estabelecer uma relação entre os níveis de emissões dos poluentes na fonte, com as concentrações dos mesmos no ar, bem como identificar pontos críticos de poluição. O Índice de Qualidade do Ar – IQA e as fragilidades das populações humanas das áreas afetadas pelos poluentes atmosféricos, também foram mensurados na pesquisa. A metodologia empregada permitiu mensurar a concentração média de poluentes atmosféricos durante um determinado tempo de modelagem, informações quanto ao alcance da pluma de poluentes foram alcançados também. São fornecidos ainda informações quanto à relação entre o valor de pico e o valor médio da concentração nas áreas receptoras, provocadas por empreendimentos com características operacionais similares ao modelado. Os resultados demostram que a influência de parâmetros meteorológicos, na dispersão de poluentes são indispensáveis e determinantes na previsão do impacto na qualidade do ar e no planejamento do uso e ocupação do solo de áreas que abrigam atividades poluidoras da atmosfera.

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O presente trabalho teve como objetivo verificar o efeito da cobertura plástica de polietileno de baixa densidade (PEBD) sobre a temperatura do ar, umidade relativa do ar, déficit de saturação e tensão de vapor d'água no ar. Pelos resultados encontrados neste trabalho as médias mensais de temperatura do ar no interior da estufa plástica foram superiores em 7,5%, a umidade relativa do ar em 7%, o déficit de saturação em 34% e a tensão atual de vapor d'água no ar em 4,7%, em relação aos valores determinados à campo. Observou-se maior efeito da cobertura plástica sobre as temperaturas máximas, as quais levaram as médias mensais a ficar entre 3,8 a 7,8 oC acima dos valores médios determinados no campo. Os valores médios mensais mínimos de temperatura e umidade relativa do ar entre a estufa e o campo apresentaram menor amplitude de variação que os valores máximos.

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Environmental monitoring of aquatic systems is an important tool to support policy makers and environmental managers' decisions. Long-term, continuous collection of environmental data is fundamental to the understanding of an aquatic system. This paper aims to present the integrated system for environmental monitoring (SIMA), a long-term temporal series system with a web-based archive for limnological and meteorological data. The following environmental parameters are measured by SIMA: chlorophyll-a (µgL-1), water surface temperature (ºC), water column temperature by a thermistor string (ºC), turbidity (NTU), pH, dissolved oxygen concentration (mg L-1), electric conductivity (µS cm-1), wind speed (ms-1) and direction (º), relative humidity (%), shortwave radiation (Wm-2) and barometric pressure (hPa). The data were collected in a preprogrammed time interval (1 hour) and were transmitted by satellite in quasi-real time for any user within 2500 km of the acquisition point. So far, 11 hydroelectric reservoirs are being monitored with the SIMA buoy. Basic statistics (mean and standard deviation) and an example of the temporal series of some parameters were displayed at a database with web access. However, sensor and satellite problems occurred due to the high data acquisition frequency. Sensors problems occurred due to the environmental characteristics of each aquatic system. Water quality sensors rapidly degrade in acidic waters, rendering the collected data invalid. Data is also rendered invalid when sensors become infested with periphyton. Problems occur with the satellites' reception of system data when satellites pass over the buoy antenna. However, the data transfer at some inland locations was not completed due to the satellite constellation position. Nevertheless, the integrated system of water quality and meteorological parameters is an important tool in understanding the aquatic system dynamic. It can also be used to create hydrodynamics models of the aquatic system to allow for the study of meteorological implications to the water body.

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The objective of this work was to evaluate the sediment production in the initial part of the Pardo River Basin - Botucatu/SP from 1994 to 1999, using the mathematical hydrological model SWAT. It was used topographic maps and satellite data manipulated in GIS using the software SPRING 5.1.6. The simulation of sediment production was generated with the aid of an interface between the hydrological model SWAT 2009 with ArcView ®, version 9.3. The maps of Soil, Land Use and Digital Elevation Model (DEM) were generated in the GIS-SPRING 5.1.6 and exported to ArcSWAT 2009. The tabular data related to the parameters of soil and meteorological parameters were entered directly to the SWAT. The model allowed to estimate the sediment production. A sediment average production rate of 33.866 ton ha-1 over the six years of study was computed in the point of discharge of the basin.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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The quality of astronomical sites is the first step to be considered to have the best performances from the telescopes. In particular, the efficiency of large telescopes in UV, IR, radio etc. is critically dependent on atmospheric transparency. It is well known that the random optical effects induced on the light propagation by turbulent atmosphere also limit telescope’s performances. Nowadays, clear appears the importance to correlate the main atmospheric physical parameters with the optical quality reachable by large aperture telescopes. The sky quality evaluation improved with the introduction of new techniques, new instrumentations and with the understanding of the link between the meteorological (or synoptical parameters and the observational conditions thanks to the application of the theories of electromagnetic waves propagation in turbulent medias: what we actually call astroclimatology. At the present the site campaigns are evolved and are performed using the classical scheme of optical seeing properties, meteorological parameters, sky transparency, sky darkness and cloudiness. New concept are added and are related to the geophysical properties such as seismicity, microseismicity, local variability of the climate, atmospheric conditions related to the ground optical turbulence and ground wind regimes, aerosol presence, use of satellite data. The purpose of this project is to provide reliable methods to analyze the atmospheric properties that affect ground-based optical astronomical observations and to correlate them with the main atmospheric parameters generating turbulence and affecting the photometric accuracy. The first part of the research concerns the analysis and interpretation of longand short-time scale meteorological data at two of the most important astronomical sites located in very different environments: the Paranal Observatory in the Atacama Desert (Chile), and the Observatorio del Roque de Los Muchachos(ORM) located in La Palma (Canary Islands, Spain). The optical properties of airborne dust at ORM have been investigated collecting outdoor data using a ground-based dust monitor. Because of its dryness, Paranal is a suitable observatory for near-IR observations, thus the extinction properties in the spectral range 1.00-2.30 um have been investigated using an empirical method. Furthermore, this PhD research has been developed using several turbulence profilers in the selection of the site for the European Extremely Large Telescope(E-ELT). During the campaigns the properties of the turbulence at different heights at Paranal and in the sites located in northern Chile and Argentina have been studied. This given the possibility to characterize the surface layer turbulence at Paranal and its connection with local meteorological conditions.