Original scientific paper

SHORT-TERM LOAD FORECASTING BY USING THE ARTIFICIAL NEURAL NETWORK MODEL

Krešimir Tačković ; HEP ODS d.o.o. Elektroslavonija, Osijek, Hrvatska
Vedran Boras ; Sveučilište u Splitu, Prirodoslovno matematički fakultet, Split, Hrvatska
Srete Nikolovski ; Sveučilište Josipa Jurja Strossmayera, Elektrotehnički fakultet, Osijek, Hrvatska

Abstract

The article describes a model for short-term load forecasting by using the artificial neural network, and its application to load forecasting for a concrete distribution area. The artificial neural networks are mostly used in solving the problems of classification and prediction when the relations between input and output variables are highly complex and hard to describe exactly. Considering the stochastic nature and the major impact of weather conditions (temperature, humidity, wind, etc.) on electricity consumption, the application of artificial neural networks is suitable for short-term forecasting the load of an electric power system (EPS). Furthermore, the article describes the used models of artificial neural networks for seasonal and multiple daily load forecasts and presents the load forecast results for a distribution area supplied over the busbars of the substation at the HEP Elekroslavonija Distribution System Operator (HEP ODS).

Keywords

artificial neural networks; forecast models; short-term load forecast

Hrčak ID:

35344

URI

https://hrcak.srce.hr/35344

Publication date:

30.10.2008.

Article data in other languages: croatian

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