Forecasting a Photovoltaic Power Output with Ordinary Differential Equation Solutions using the “Aladin” model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099462" target="_blank" >RIV/61989100:27240/16:86099462 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Forecasting a Photovoltaic Power Output with Ordinary Differential Equation Solutions using the “Aladin” model
Original language description
Accurate forecasting of the renewable power generation is important for the system operation, utilization and integration in the electricity grid. The photovoltaic output power is primarily dependent on the solar radiation, which short-term local forecasts, available from the numerical model “Aladin”, can enter power models, trained with corresponding real time-series of few last days, to predict the following day electricity production. Presented daily updated polynomial derivative models can describe fluctuant function relations between input solar irradiance time-series and the scalar output power, which conventional regression solutions usually fail. Differential polynomial network is a new neural network type, which can define and solve a selective form of the linear ordinary sum differential equation to model 1-variable function series. Partial sum relative fraction terms, produced in all layer nodes of the network backward structure, can substitute for the time derivatives at several time-points of data series.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</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
Advances in intelligent systems and computing. Volume 565
ISBN
978-3-319-60833-4
ISSN
2194-5357
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
28-37
Publisher name
Springer
Place of publication
Berlin
Event location
Marrákeš
Event date
Nov 21, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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