Using active learning for monitoring networks design: The example of wind power plants sites evaluation
Details
Serval ID
serval:BIB_05580F750B3B
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Using active learning for monitoring networks design: The example of wind power plants sites evaluation
Title of the conference
9th International Geostatistics Congress, Oslo, Norway
Publication state
Published
Issued date
2012
Pages
6 p.
Language
english
Notes
Tuia2012a
Abstract
Locating new wind farms is of crucial importance for energy policies
of the next decade. To select the new location, an accurate picture
of the wind fields is necessary. However, characterizing wind fields
is a difficult task, since the phenomenon is highly nonlinear and
related to complex topographical features. In this paper, we propose
both a nonparametric model to estimate wind speed at different time
instants and a procedure to discover underrepresented topographic
conditions, where new measuring stations could be added. Compared
to space filling techniques, this last approach privileges optimization
of the output space, thus locating new potential measuring sites
through the uncertainty of the model itself.
of the next decade. To select the new location, an accurate picture
of the wind fields is necessary. However, characterizing wind fields
is a difficult task, since the phenomenon is highly nonlinear and
related to complex topographical features. In this paper, we propose
both a nonparametric model to estimate wind speed at different time
instants and a procedure to discover underrepresented topographic
conditions, where new measuring stations could be added. Compared
to space filling techniques, this last approach privileges optimization
of the output space, thus locating new potential measuring sites
through the uncertainty of the model itself.
Create date
25/11/2013 18:18
Last modification date
20/08/2019 13:27
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