Recently, we released a framework called windML ( http://www.windml.org), which provides an easy-to-use access to wind data sources for Python building upon numpy, scipy, sklearn, and matplotlib. It contains data mining methods and examples for various learning tasks like time-series prediction, classification, clustering, dimensionality reduction, and related tasks. We currently use two data sets, i.e., the NREL western wind integration study and an Australian data set named AEMO. The NREL data set is really awesome with 10-minute data of 32000 wind turbines for 3 years. But it's partly based on simulations. Does anyone know of another (large, public) data set with spatial distributed wind turbines? Thanks in advance.
Dear Oliver.
Are you familiar with this paper:
A. Panangadan, S-S. Ho, A. Talukder "Cyclone Tracking using Multiple Satellite Image Sources" GIS 2009
No guarantee it is public domain, but it is worth asking the authors.
Best regards,
Myra Spiliopoulou
We still have no not found a novel appropriate data set, but we added new methods and have just released a new version of windML .... see windML.org.
http://www.windml.org
If you are interested in our Wind and Machine Learning research, check out our line of research:
https://dl.dropboxusercontent.com/u/6507267/publications/icann2.pdf
https://dl.dropboxusercontent.com/u/6507267/publications/ki2.pdf
https://dl.dropboxusercontent.com/u/6507267/publications/soco2014.pdf
https://dl.dropboxusercontent.com/u/6507267/publications/enviroinfo1.pdf
https://dl.dropboxusercontent.com/u/6507267/publications/enviroinfo1.pdf
https://dl.dropboxusercontent.com/u/6507267/publications/hais2014.pdf
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