Solar irradiance forecasting model based on extreme learning machine
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86100512" target="_blank" >RIV/61989100:27240/16:86100512 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27730/16:86100512 RIV/61989100:27740/16:86100512
Result on the web
<a href="http://dx.doi.org/10.1109/EEEIC.2016.7555445" target="_blank" >http://dx.doi.org/10.1109/EEEIC.2016.7555445</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EEEIC.2016.7555445" target="_blank" >10.1109/EEEIC.2016.7555445</a>
Alternative languages
Result language
angličtina
Original language name
Solar irradiance forecasting model based on extreme learning machine
Original language description
The Off-Grid systems are systems with an independence on the energy supply from external grid, whereas renewables (RES) are used as a sources of electric and heat energy. The main RES is photovoltaic power plant (PVP), however this source has the stochastic character of power supply. The stochastic character of PVP is given by dependency on a weather conditions. This brings a need of solar irradiance forecasting. The solar irradiance forecasting is very important tool for the forecasting of the PVP energy production and it can be used for the optimization of the power flows in the Off-Grid systems. This paper presents a solar irradiance forecasting model based on extreme learning machine.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/LO1404" target="_blank" >LO1404: Sustainable Development of Center ENET</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2016 IEEE 16TH INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING (EEEIC)
ISBN
978-1-5090-2320-2
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
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Publisher name
IEEE
Place of publication
NEW YORK
Event location
Florence
Event date
Jun 7, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000387085800025