An aggregated wind power generation model based on MERRA reanalysis data: MATLAB model and example data for the April 2014 wind farm distribution of Great Britain.

The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

April 2000: Internet Caveats, Electronic Classroom

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Ninety eight strains of glucose-nonfermenting Gram-negative bacilli were analyzed and isolated from several clinical materials of 95 patients admitted at the Dr. Domingos Leonardo Cerávolo University Hospital and three from outpatients. All of them were assisted in the Laboratory of Clinical Analysis of Unoeste University, Presidente Prudente, SP, from the period of October of 1999 to April of 2001. In this work, the level of agreement between the semi-automated commercial system AutoScan-4 and the conventional system for the identification of those bacteria were studied comparatively. There was agreement in 81 (82.7%), showing that both methodologies are useful for identification; partial agreement in six strains (6.1%) and disagreement in 11 (11.2%). The comercial system did not identify nine (9.2%) of the strains and reported them as very rare biotypes.

Note on Caribbean Development Bank Eighth Annual Meeting of the Board of Governors, Georgetown, Guyana, 26-27 April 1978

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Refuge Update – March/April 2006, Volume 3, Number 2

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