Identifying Power Profiles in the Photovoltaic Power Station Data by Self-organizing Maps and Dimension Reduction by Sammon's Projection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86099419" target="_blank" >RIV/61989100:27240/13:86099419 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/13:86099419

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/7054150/?reload=true" target="_blank" >http://ieeexplore.ieee.org/document/7054150/?reload=true</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SOCPAR.2013.7054150" target="_blank" >10.1109/SOCPAR.2013.7054150</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Identifying Power Profiles in the Photovoltaic Power Station Data by Self-organizing Maps and Dimension Reduction by Sammon's Projection

Popis výsledku v původním jazyce

This paper presents results of the identification of clusters in the hourly recorded data of power from a small photovoltaic power station. Our main aim was to find a method of how to identify typical patterns of generated power. Although one can think that sunny days are the same, the power of the sun light is very volatile during a day. We were not interested in finding the absolute values of this power but just its patterns according to the day's maximal power. Our proposed method is based on several techniques. We used network algorithm as a method for removing noise from the data, Sammon's projection for visualization and dimensionality reduction and final clustering by the self-organizing maps. (C) 2013 IEEE.

Název v anglickém jazyce

Identifying Power Profiles in the Photovoltaic Power Station Data by Self-organizing Maps and Dimension Reduction by Sammon's Projection

Popis výsledku anglicky

This paper presents results of the identification of clusters in the hourly recorded data of power from a small photovoltaic power station. Our main aim was to find a method of how to identify typical patterns of generated power. Although one can think that sunny days are the same, the power of the sun light is very volatile during a day. We were not interested in finding the absolute values of this power but just its patterns according to the day's maximal power. Our proposed method is based on several techniques. We used network algorithm as a method for removing noise from the data, Sammon's projection for visualization and dimensionality reduction and final clustering by the self-organizing maps. (C) 2013 IEEE.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

2013 International Conference on Soft Computing and Pattern Recognition, SoCPaR 2013

ISBN

978-1-4799-3400-3

ISSN

—

e-ISSN

—

Počet stran výsledku

6

Strana od-do

315-320

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Hanoj

Datum konání akce

15. 12. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000380467000053