Electricity Load Forecasting Using Autoregressive And Artificial Neural Network Model

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F16%3APU119744" target="_blank" >RIV/00216305:26220/16:PU119744 - isvavai.cz</a>

Result on the web

<a href="http://www.feec.vutbr.cz/EEICT/2016/sbornik/EEICT-2016-sborn%C3%ADk-komplet.pdf" target="_blank" >http://www.feec.vutbr.cz/EEICT/2016/sbornik/EEICT-2016-sborn%C3%ADk-komplet.pdf</a>

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

Electricity Load Forecasting Using Autoregressive And Artificial Neural Network Model

Original language description

Abstract-In this paper a short review of two forecasting models Autoregressive and Artificial neural network is presented. Both models were used to demonstrate its superior performance in load forecasting issues. In the third section the results of load forecasting experiment are given. For obtained forecasted results mean absolute percentage error for autoregressive model was 0.644 % and for artificial neural network model 2.31 %. In this paper error distribution for both models is also shown.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

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

OECD FORD branch

—

Project

<a href="/en/project/LO1210" target="_blank" >LO1210: Energy for Sustainable Development</a><br>

Continuities

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

Publication year

2016

Confidentiality

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

Article name in the collection

Proceedings of the 22nd conference Student EEICT

ISBN

978-80-214-5350-0

ISSN

—

e-ISSN

—

Number of pages

777

Pages from-to

472-476

Publisher name

Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních

Place of publication

Brno

Event location

Brno

Event date

Apr 28, 2016

Type of event by nationality

CST - Celostátní akce

UT code for WoS article

—