Clustering Weather Situations with Respect to Prediction of Solar Irradiance by Multiple NWP Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F14%3A00434056" target="_blank" >RIV/67985807:_____/14:00434056 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3233/978-1-61499-419-0-1207" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-419-0-1207</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/978-1-61499-419-0-1207" target="_blank" >10.3233/978-1-61499-419-0-1207</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Clustering Weather Situations with Respect to Prediction of Solar Irradiance by Multiple NWP Models

Popis výsledku v původním jazyce

With the photovoltaic (PV) and concentrating solar power (CSP) forming a growing portion of European power sources, there is a strong demand for a reliable prediction of solar power. Such predictions are mostly provided by physical or statistical models,both of which rely on accurate forecast of solar irradiance. For the short-to-medium-term forecast horizon (hours to days), irradiance forecast is provided mostly by numerical weather prediction (NWP) models. However, in spite of a recent effort to improve irradiance prediction within current NWP models, its quality is still not satisfactory and it is responsible for a majority of uncertainty in photovoltaic power forecasting. A promising method of improving NWP solar irradiance prediction is multi-model approach. This paper presents preliminary results from a data mining approach to combining irradiance forecasts from multiple NWP models.

Název v anglickém jazyce

Clustering Weather Situations with Respect to Prediction of Solar Irradiance by Multiple NWP Models

Popis výsledku anglicky

With the photovoltaic (PV) and concentrating solar power (CSP) forming a growing portion of European power sources, there is a strong demand for a reliable prediction of solar power. Such predictions are mostly provided by physical or statistical models,both of which rely on accurate forecast of solar irradiance. For the short-to-medium-term forecast horizon (hours to days), irradiance forecast is provided mostly by numerical weather prediction (NWP) models. However, in spite of a recent effort to improve irradiance prediction within current NWP models, its quality is still not satisfactory and it is responsible for a majority of uncertainty in photovoltaic power forecasting. A promising method of improving NWP solar irradiance prediction is multi-model approach. This paper presents preliminary results from a data mining approach to combining irradiance forecasts from multiple NWP models.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

ECAI 2014

ISBN

978-1-61499-418-3

ISSN

0922-6389

e-ISSN

—

Počet stran výsledku

2

Strana od-do

1207-1208

Název nakladatele

IOS Press

Místo vydání

Amsterdam

Místo konání akce

Prague

Datum konání akce

18. 8. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

000349444700265