7 resultados para Wind speed extrapolation

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This paper analyzes data captured by a phasor measurement unit at a wind farm, employing two-speed induction generators, and investigates aspects of the control system's interaction with the power system. Composite superimposed transient events are proposed as a method to improve the quality of the analysis and reduce errors caused by unknowns, such as wind speed variation. A Mathworks SimPowerSystems model validates the inertia contribution of the wind farm, which is an important parameter in power systems with high wind penetration. Transients caused by turbine speed transitions are identified and explained. The analysis also highlights areas where wind farm control should be improved if useful inertia contribution is to be provided.

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This paper studies the system modelling and control aspects of switched reluctance generator (SRG) based variable speed wind turbines. A control system is implemented to provide proper operation of the SRG as well as power tracking capabilities for varying wind speeds. The control system for the grid side inverter that will allow the SRG to properly generate power to the system is also presented. Studies are presented of both the SRG and inverter control systems capabilities during a balanced three-phase fault. The paper will demonstrate that the SRG based wind turbine presents a feasible variable wind speed solution with good fault response capabilities.

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In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys. © 2012 IEEE.

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In the coming decade installed offshore wind capacity is expected to expand rapidly. This will be both technically and economically challenging. Precise wind resource assessment is one of the more imminent challenges. It is more difficult to assess wind power offshore than onshore due to the paucity of representative wind speed data. Offshore site-specific data is less accessible and is far more costly to collect. However, offshore wind speed data collected from sources such as wave buoys, remote sensing from satellites, national weather ships, and coastal meteorological stations and met masts on barges and platforms may be extrapolated to assess offshore wind power. This study attempts to determine the usefulness of pre-existing offshore wind speed measurements in resource assessment, and presents the results of wind resource estimation in the Atlantic Ocean and in the Irish Sea using data from two offshore meteorological buoys

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Artificial neural networks (ANNs) can be easily applied to short-term load forecasting (STLF) models for electric power distribution applications. However, they are not typically used in medium and long term load forecasting (MLTLF) electric power models because of the difficulties associated with collecting and processing the necessary data. Virtual instrument (VI) techniques can be applied to electric power load forecasting but this is rarely reported in the literature. In this paper, we investigate the modelling and design of a VI for short, medium and long term load forecasting using ANNs. Three ANN models were built for STLF of electric power. These networks were trained using historical load data and also considering weather data which is known to have a significant affect of the use of electric power (such as wind speed, precipitation, atmospheric pressure, temperature and humidity). In order to do this a V-shape temperature processing model is proposed. With regards MLTLF, a model was developed using radial basis function neural networks (RBFNN). Results indicate that the forecasting model based on the RBFNN has a high accuracy and stability. Finally, a virtual load forecaster which integrates the VI and the RBFNN is presented.

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PTF11iqb was initially classified as a TypeIIn event caught very early after explosion. It showed narrow Wolf-Rayet (WR) spectral features on day 2, but the narrow emission weakened quickly and the spectrum morphed to resemble those of Types II-L and II-P. At late times, Halpha emission exhibited a complex, multipeaked profile reminiscent of SN1998S. In terms of spectroscopic evolution, we find that PTF11iqb was a near twin of SN~1998S, although with weaker interaction with circumstellar material (CSM) at early times, and stronger CSM interaction at late times. We interpret the spectral changes as caused by early interaction with asymmetric CSM that is quickly (by day 20) enveloped by the expanding SN ejecta photosphere, but then revealed again after the end of the plateau when the photosphere recedes. The light curve can be matched with a simple model for weak CSM interaction added to the light curve of a normal SN~II-P. This plateau requires that the progenitor had an extended H envelope like a red supergiant, consistent with the slow progenitor wind speed indicated by narrow emission. The cool supergiant progenitor is significant because PTF11iqb showed WR features in its early spectrum --- meaning that the presence of such WR features in an early SN spectrum does not necessarily indicate a WR-like progenitor. [abridged] Overall, PTF11iqb bridges SNe~IIn with weaker pre-SN mass loss seen in SNe II-L and II-P, implying a continuum between these types.

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1. We analysed 41 years of data (1968–2008) from Blelham Tarn, U.K., to determine the consequences of eutrophication and climate warming on hypolimnetic dissolved oxygen (DO).
2. The establishment of thermal stratification was strongly related to the onset of DO depletion in the lower hypolimnion. As a result of a progressively earlier onset of stratification and later overturn, the duration of stratification increased by 38 ± 8 days over the 41 years.
3. The observed rate of volumetric hypolimnetic oxygen depletion (VHODobs) ranged from 0.131 to 0.252 g O2 m−3 per day and decreased significantly over the study period, despite the increase in the mean chlorophyll a (Chl a) concentration in the growing season. The vertical transport of DO represented from 0 to 30% of VHODobs, while adjustments for interannual differences in hypolimnetic temperature were less important, ranging from −11 to 9% of VHODobs.
4. The mean wind speed during May made the strongest significant contribution to the variation in VHODobs. VHODobs adjusted for the vertical transport of DO and hypolimnetic temperature differences, VHODadj, was significantly related to the upper mixed layer Chl a concentration during spring.
5. Hypolimnetic anoxia (HA) ranged from 27 to 168 days per year and increased significantly over time, which undoubtedly had negative ecological consequences for the lake.
6. In similar small temperate lakes, the negative effects of eutrophication on hypolimnetic DO are likely to be exacerbated by changes in lake thermal structure brought about by a warming climate, which may undermine management efforts to alleviate the effects of anthropogenic eutrophication.