A power quality forecasting model as an integrate part of active demand side management using Artificial Intelligence Technique - Multilayer Neural Network with Backpropagation Learning Algorithm

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86096190" target="_blank" >RIV/61989100:27240/15:86096190 - isvavai.cz</a>

Alternative codes found

RIV/61989100:27730/15:86096190

Result on the web

<a href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=7165233" target="_blank" >http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&tp=&arnumber=7165233</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EEEIC.2015.7165233" target="_blank" >10.1109/EEEIC.2015.7165233</a>

Result language

angličtina

Original language name

A power quality forecasting model as an integrate part of active demand side management using Artificial Intelligence Technique - Multilayer Neural Network with Backpropagation Learning Algorithm

Original language description

This paper presents a power quality forecasting model with using Artificial Intelligence Technique, more precisely the Multilayer Neural Network with Backpropagation Learning Algorithm. This forecasting model is used as a supporting tool for a keeping ofpower quality parameters within the limits in the Off-Grid systems with renewables sources connected via AC By-Pass topology. Results of the most important power quality parameters forecasting are introduced in this paper. The developed algorithm of this model will be implemented into system for controlling the power flows inside the Off-Grid systems operated under Active Demand Side Management.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JE - Non-nuclear power engineering, energy consumption and utilization

OECD FORD branch

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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)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2015

Confidentiality

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

Article name in the collection

Environment and Electrical Engineering (EEEIC), 2015 IEEE 15th International Conference on

ISBN

978-1-4799-7992-9

ISSN

—

e-ISSN

—

Number of pages

6

Pages from-to

611 - 616

Publisher name

IEEE

Place of publication

Vienna

Event location

Řím

Event date

Jun 10, 2015

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000366654400105