Estimation of wind direction distribution with genetic algorithms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F13%3A86096969" target="_blank" >RIV/61989100:27240/13:86096969 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CCECE.2013.6567681" target="_blank" >http://dx.doi.org/10.1109/CCECE.2013.6567681</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CCECE.2013.6567681" target="_blank" >10.1109/CCECE.2013.6567681</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Estimation of wind direction distribution with genetic algorithms

Popis výsledku v původním jazyce

Abstract Directional and stream data are common in many research fields. Wind speed and direction are the most important variables for effective wind energy utilization. It is also well known, that wind significantly influences the current-carrying capacity of overhead power transmission lines. This shows the importance of knowing the annual wind direction distribution for specific locations, e.g. where wind farms or power transmission lines are situated. In this paper, a new method of wind direction distribution determination is presented. The statistical model is composed of a finite mixture of circular von Mises distributions. Parameters of the model are estimated using the heuristic search method of genetic algorithms. The quality of computed distribution is evaluated by Pearson's chi-squared test. The entire proposed procedure is tested using a case study. The results show that the model composed of a finite mixture of von Mises distribution corresponds to the input data with high

Název v anglickém jazyce

Estimation of wind direction distribution with genetic algorithms

Popis výsledku anglicky

Abstract Directional and stream data are common in many research fields. Wind speed and direction are the most important variables for effective wind energy utilization. It is also well known, that wind significantly influences the current-carrying capacity of overhead power transmission lines. This shows the importance of knowing the annual wind direction distribution for specific locations, e.g. where wind farms or power transmission lines are situated. In this paper, a new method of wind direction distribution determination is presented. The statistical model is composed of a finite mixture of circular von Mises distributions. Parameters of the model are estimated using the heuristic search method of genetic algorithms. The quality of computed distribution is evaluated by Pearson's chi-squared test. The entire proposed procedure is tested using a case study. The results show that the model composed of a finite mixture of von Mises distribution corresponds to the input data with high

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

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

Canadian Conference on Electrical and Computer Engineering 2013

ISBN

978-1-4799-0032-9

ISSN

0840-7789

e-ISSN

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Počet stran výsledku

4

Strana od-do

1-4

Název nakladatele

IEEE

Místo vydání

New York

Místo konání akce

Regina

Datum konání akce

5. 5. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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