Modeling the Photovoltaic Output Power using the Differential Polynomial Network and Evolutional Fuzzy Rules

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A86099463" target="_blank" >RIV/61989100:27240/17:86099463 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27730/17:86099463 RIV/61989100:27740/17:86099463

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Modeling the Photovoltaic Output Power using the Differential Polynomial Network and Evolutional Fuzzy Rules

Original language description

The unstable production of renewable energy sources, which is difficult to model using conventional computational techniques, may be predicted to advantage by means of biologically inspired soft-computing methods. The photovoltaic output power is primarily dependent on the solar direct or global radiation, which short-term numerical forecasts are possible to apply for daily power predictions. The study compares two methods, which can successfully model dynamic fluctuant variances of the solar irradiance and corresponding output power time-series. Differential polynomial network is a new neural network class, which defines and substitutes for the general partial differential equation to model an unknown system function. Its total output is composed from selected neurons, i.e. relative polynomial substitution terms, formed in all network layers of a multi-layer structure. The proposed derivative polynomial regression using relative dimensionless fraction units, formed according to the Similarity analysis, can describe and generalize data relations on a wider range of values than defined by the training interval when using standard soft-computing composing techniques that apply only absolute data. 1-variable time-series observations are possible to model by time derivatives of a converted ordinary differential equation, solved analogously with partial derivative substitution terms of several time-point variables.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

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)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

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

Name of the periodical

Mathematical Modelling and Analysis

ISSN

1392-6292

e-ISSN

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Volume of the periodical

22

Issue of the periodical within the volume

1

Country of publishing house

LT - LITHUANIA

Number of pages

17

Pages from-to

78-94

UT code for WoS article

000393085600006

EID of the result in the Scopus database

2-s2.0-85009186295