<div class="csl-bib-body">
<div class="csl-entry">Ballauri, E. (2016). <i>Error analysis of wind energy prediction models</i> [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.34643</div>
</div>
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dc.identifier.uri
https://doi.org/10.34726/hss.2016.34643
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/5492
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dc.description
Abweichender Titel nach Übersetzung der Verfasserin/des Verfassers
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dc.description.abstract
The importance of methods using renewable resources for the energy production has increased drastically in the recent years. In the electricity market the method that has grown most rapidly is the generation of power through wind. Forecasts of this power production are crucial. However, difficulties arise in these forecasts due to the high volatility of the wind and the complexity of the terrain where the wind facilities are installed. This thesis examines five different models for the forecast of wind energy and analyses the behaviour of its errors. The scope is to build a confidence interval for the errors of these forecasts. In this framework two major setups are considered for constructing a confidence interval. The first one is based on applying a GARCH model in order to forecast the conditional variance of the errors. The second uses a regression model to describe the absolute or square errors as a function of explanatory variables like the predicted wind speed and predicted wind power. These models were then used to build the confidence intervals. Both approaches were implemented sucessfully.
en
dc.language
English
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dc.language.iso
en
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dc.rights.uri
http://rightsstatements.org/vocab/InC/1.0/
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dc.subject
Windkraft
de
dc.subject
Prognose
de
dc.subject
Konfidenzbereich
de
dc.subject
GARCH
de
dc.subject
wind power
en
dc.subject
forecast
en
dc.subject
confidence region
en
dc.subject
GARCH
en
dc.title
Error analysis of wind energy prediction models
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dc.title.alternative
Modelierung der Unsicherheit von Windenergieprognosen
de
dc.type
Thesis
en
dc.type
Hochschulschrift
de
dc.rights.license
In Copyright
en
dc.rights.license
Urheberrechtsschutz
de
dc.identifier.doi
10.34726/hss.2016.34643
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dc.contributor.affiliation
TU Wien, Österreich
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dc.rights.holder
Eni Ballauri
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dc.publisher.place
Wien
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tuw.version
vor
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tuw.thesisinformation
Technische Universität Wien
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tuw.publication.orgunit
E105 - Institut für Stochastik und Wirtschaftsmathematik
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dc.type.qualificationlevel
Diploma
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dc.identifier.libraryid
AC13439119
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dc.description.numberOfPages
80
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dc.identifier.urn
urn:nbn:at:at-ubtuw:1-93568
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dc.thesistype
Diplomarbeit
de
dc.thesistype
Diploma Thesis
en
dc.rights.identifier
In Copyright
en
dc.rights.identifier
Urheberrechtsschutz
de
tuw.advisor.staffStatus
staff
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item.fulltext
with Fulltext
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item.cerifentitytype
Publications
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item.mimetype
application/pdf
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item.openairecristype
http://purl.org/coar/resource_type/c_bdcc
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item.languageiso639-1
en
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item.openaccessfulltext
Open Access
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item.openairetype
master thesis
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item.grantfulltext
open
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crisitem.author.dept
E105 - Institut für Stochastik und Wirtschaftsmathematik