Analysis of Wind Ramp Events Using PCA of 3D Tables of their Conditional Probabilities

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F15%3A39899391" target="_blank" >RIV/00216275:25530/15:39899391 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/EPE.2015.7161121" target="_blank" >http://dx.doi.org/10.1109/EPE.2015.7161121</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE.2015.7161121" target="_blank" >10.1109/EPE.2015.7161121</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Wind Ramp Events Using PCA of 3D Tables of their Conditional Probabilities

Popis výsledku v původním jazyce

Wind is one of the fastest growing sources of renewable energy. However, its intermittency and stochastic nature often hamper integration of wind-generated energy in electric power networks. The most significant obstacles to efficient wind integration are the wind ramps, sudden changes of wind power output caused by dramatic changes in wind speed. Most ramp prediction methods derive future ramp estimates from forecast power series. This contribution suggests a different approach that would directly analyze wind power time series and other weather parameters to identify specific patterns and dependencies signaling approaching ramp events. In this paper, the 3D tables of ramp events' conditional probabilities are evaluated using principal component analysis. Two different datasets are analyzed. First one contains power production hourly collected from August 2011 to July 2012 on sample wind farm located close to Lethbridge, AB Canada. The other consists of total BPA wind power production

Název v anglickém jazyce

Analysis of Wind Ramp Events Using PCA of 3D Tables of their Conditional Probabilities

Popis výsledku anglicky

Wind is one of the fastest growing sources of renewable energy. However, its intermittency and stochastic nature often hamper integration of wind-generated energy in electric power networks. The most significant obstacles to efficient wind integration are the wind ramps, sudden changes of wind power output caused by dramatic changes in wind speed. Most ramp prediction methods derive future ramp estimates from forecast power series. This contribution suggests a different approach that would directly analyze wind power time series and other weather parameters to identify specific patterns and dependencies signaling approaching ramp events. In this paper, the 3D tables of ramp events' conditional probabilities are evaluated using principal component analysis. Two different datasets are analyzed. First one contains power production hourly collected from August 2011 to July 2012 on sample wind farm located close to Lethbridge, AB Canada. The other consists of total BPA wind power production

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2015 16th International Scientific Conference on Electric Power Engineering, EPE 2015

ISBN

9781467367882

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

158-162

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Kouty nad Desnou

Datum konání akce

20. 5. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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