Accessibility navigation


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.

Cannon, D. and Brayshaw, D. ORCID: https://orcid.org/0000-0002-3927-4362 (2014) 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. University of Reading.

[img]
Preview
Text (Message from the authors, License information and Introduction to the model)
· Please see our End User Agreement before downloading.

236kB
[img] Archive (Compressed folder containing all model files and Readme file: .tgz version)
· Restricted to Repository staff only

237kB
[img] Archive (Compressed folder containing all model files and Readme file: .zip version)
· Restricted to Repository staff only

237kB
[img] Text (Hourly time series of GB-aggregated wind power generation from 1980-2013: ASCII .dat file)
· Restricted to Repository staff only

6MB
[img] Other (Hourly time series of GB-aggregated wind power generation from 1980-2013: MATLAB .mat file) - Other
· Restricted to Repository staff only

3MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

Official URL: http://www.met.reading.ac.uk/~energymet/data/Canno...

Abstract/Summary

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/

Item Type:Other
Divisions:Interdisciplinary Research Centres (IDRCs) > Walker Institute
Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
Interdisciplinary centres and themes > Energy Research
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:37430
Publisher:University of Reading
Publisher Statement:Copyright 2014 University of Reading Author: Dirk Cannon, David Brayshaw Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation