Evaluation of price forecast systems for Turkish Electric Market

Author

Taysi, Z. Cihan ; Biricik, Goksel ; Bozkurt, O. Ozgur

Author_Institution

Bilgisayar Muhendisligi Bolumu, Yildiz Teknik Univ., Istanbul, Turkey

fYear

2015

fDate

16-19 May 2015

Firstpage

620

Lastpage

623

Abstract

It is very important to forecast the electric prices in deregulated markets for both producers and brokers. This information is crucial to make effective decisions concerning to production, purchase, maintenance and investment. In this study, we built two different systems for short-term prediction of electricity price in Turkish Electric Market. One of the systems built on ARIMA model, while the other employs a feed forward neural network. Both systems use calendar and historical price information as input. Performance of both systems are compared and it is shown that it is possible to forecast weekly electric price with an average error rate of %8.5.

Keywords

feedforward neural nets; power engineering computing; power markets; pricing; ARIMA model; Turkish electric market; electricity price short-term prediction; feedforward neural network; price forecast system evaluation; Biological system modeling; Economics; Forecasting; Mathematical model; Neural networks; Power systems; Time series analysis; ANN; ARIMA; electric market; electric price; price forecast;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2015 23th

Conference_Location

Malatya

Type

conf

DOI

10.1109/SIU.2015.7129900

Filename

7129900