Daily Power Load Forecasting using the Differential Polynomial Neural Network

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F14%3A86090329" target="_blank" >RIV/61989100:27740/14:86090329 - isvavai.cz</a>

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-07617-1_42#page-1" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-07617-1_42#page-1</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Daily Power Load Forecasting using the Differential Polynomial Neural Network

Popis výsledku v původním jazyce

The purpose of the short-term electricity demand prediction is to forecast in advance the system load, represented by the sum of all consumers load at the same time. Power demand forecasting is important for economically efficient operation and effectivecontrol of power systems and enables to plan the load of generating unit. A precise load forecasting is required to avoid high generation cost and the spinning reserve capacity. Under-prediction of the demands leads to an insufficient reserve capacity preparation and can threaten the system stability, on the other hand, over-prediction leads to an unnecessarily large reserve that leads to a high cost preparations. Differential polynomial neural network is a new neural network type, which forms and resolves an unknown general partial differential equation of an approximation of a searched function, described by data observations. It generates convergent sum series of relative polynomial derivative terms, which can substitute for the ord

Název v anglickém jazyce

Daily Power Load Forecasting using the Differential Polynomial Neural Network

Popis výsledku anglicky

The purpose of the short-term electricity demand prediction is to forecast in advance the system load, represented by the sum of all consumers load at the same time. Power demand forecasting is important for economically efficient operation and effectivecontrol of power systems and enables to plan the load of generating unit. A precise load forecasting is required to avoid high generation cost and the spinning reserve capacity. Under-prediction of the demands leads to an insufficient reserve capacity preparation and can threaten the system stability, on the other hand, over-prediction leads to an unnecessarily large reserve that leads to a high cost preparations. Differential polynomial neural network is a new neural network type, which forms and resolves an unknown general partial differential equation of an approximation of a searched function, described by data observations. It generates convergent sum series of relative polynomial derivative terms, which can substitute for the ord

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Lecture Notes in Computer Science. Volume 8480

ISBN

978-3-319-07616-4

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

12

Strana od-do

478-489

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Salamanca

Datum konání akce

11. 6. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—