Sensitivity Analysis of PCA method for Wind Ramp event Detection

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Sensitivity Analysis of PCA method for Wind Ramp event Detection

Popis výsledku v původním jazyce

Wind is one of the fastest growing sources of green energy in the last few decades. A special attention has been recently focused on the wind ramps, sudden changes in wind power production caused by surges of wind speed (both increases and decreases). In this paper, sensitivity analysis of Principal Component Analysis (PCA) method is preformed on wind speed dataset with the 5 minute time resolution. Principal Component Analysis results can be used to evaluate conditional probability of forthcoming wind ramp event. Advantage of PCA method compared to conventional approaches is that numerical weather prediction model producing wind forecasts is not required. Two important input parameters are analyzed: the wind ramp duration and the wind ramp magnitude, respectively. Results show rapid increase of the first principal component value, when ramp duration is prolonging, nevertheless other two components seems to be insensitive in this case. Boxplots are illustrated for simple comparability of resultant distributions. The number of down ramp events is always lower than the number of up ramps, and with increasing percentage threshold these numbers are decreasing exponentially. Moreover trends of average PCA values for down ramp events are not monotone with significant jumps and drops.

Název v anglickém jazyce

Sensitivity Analysis of PCA method for Wind Ramp event Detection

Popis výsledku anglicky

Wind is one of the fastest growing sources of green energy in the last few decades. A special attention has been recently focused on the wind ramps, sudden changes in wind power production caused by surges of wind speed (both increases and decreases). In this paper, sensitivity analysis of Principal Component Analysis (PCA) method is preformed on wind speed dataset with the 5 minute time resolution. Principal Component Analysis results can be used to evaluate conditional probability of forthcoming wind ramp event. Advantage of PCA method compared to conventional approaches is that numerical weather prediction model producing wind forecasts is not required. Two important input parameters are analyzed: the wind ramp duration and the wind ramp magnitude, respectively. Results show rapid increase of the first principal component value, when ramp duration is prolonging, nevertheless other two components seems to be insensitive in this case. Boxplots are illustrated for simple comparability of resultant distributions. The number of down ramp events is always lower than the number of up ramps, and with increasing percentage threshold these numbers are decreasing exponentially. Moreover trends of average PCA values for down ramp events are not monotone with significant jumps and drops.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC) : proceedings

ISBN

978-1-5090-2320-2

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

123-131

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Florencie

Datum konání akce

7. 6. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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