Detail publikačního výsledku

FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH

KHAN, M., ŽÁK, L., ONDRŮŠEK, Č.

Original Title

FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH

English Title

FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

A hybrid approach utilizing a fuzzy system and artificial neural network (ANN) for short-term load forecasting of the Czech Electric Power Company (ČEZ) is proposed in this paper. Expert knowledge represented by fuzzy rules is used for preprocessing input data fed to a neural network. For training the neural network for one-week ahead load forecasting, fuzzy ‘If-Then’ rules are used, in addition to historical load and temperature data that are usually employed in conventional supervised training algorithms. The fuzzy-neural network is trained on real data for the years 1994 through 1998 and evaluated on the data for the year 1999 for forecasting next-week load profiles. A very good prediction performance is attained as shown in the simulation results, which verify the effectiveness and superiority of the modeling technique.

English abstract

A hybrid approach utilizing a fuzzy system and artificial neural network (ANN) for short-term load forecasting of the Czech Electric Power Company (ČEZ) is proposed in this paper. Expert knowledge represented by fuzzy rules is used for preprocessing input data fed to a neural network. For training the neural network for one-week ahead load forecasting, fuzzy ‘If-Then’ rules are used, in addition to historical load and temperature data that are usually employed in conventional supervised training algorithms. The fuzzy-neural network is trained on real data for the years 1994 through 1998 and evaluated on the data for the year 1999 for forecasting next-week load profiles. A very good prediction performance is attained as shown in the simulation results, which verify the effectiveness and superiority of the modeling technique.

Key words in English

One-week ahead load forecasting, Multilayer neural networks and Hybrid fuzzy-neural networks (FNN)

Authors

KHAN, M., ŽÁK, L., ONDRŮŠEK, Č.

Released

26.11.2001

ISBN

1210-2717

Periodical

Inženýrská mechanika - Engineering Mechanics

Volume

2001

Number

8

State

Czech Republic

Pages from

44

Pages count

55

Full text in the Digital Library

http://hdl.handle.net/

BibTex

@article{BUT40535,
  author="Muhammad R {Khan} and Libor {Žák} and Čestmír {Ondrůšek}",
  title="FORECASTING WEEKLY ELECTRIC LOAD USING A HYBRID FUZZY-NEURAL NETWORK APPROACH",
  journal="Inženýrská mechanika - Engineering Mechanics",
  year="2001",
  volume="2001",
  number="8",
  pages="55",
  issn="1210-2717"
}