Power load forecast system for Turkish electric market

Author

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

Author_Institution

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

fYear

2015

fDate

16-19 May 2015

Firstpage

569

Lastpage

572

Abstract

Forecasting the electric load demand in advance is very important in deregulated market conditions to give proper production, purchase, maintenance and investment decisions. Correct price forecasts also depend on accurate load prediction. In this study, effects of calendar, historical price and load data on short-term load forecast for Turkish Deregulated Electricity market are tested using feed forward neural networks. The impact of each data on forecast performance is evaluated and best performance is obtained using a combination of historical and predicted load, calendar information and historical price information.

Keywords

feedforward neural nets; load forecasting; power engineering computing; power markets; Turkish electric market; calendar data; deregulated electricity market; feedforward neural networks; forecast performance; historical price; load data; power load forecast system; short-term load forecast; Forecasting; Load forecasting; Load modeling; Mathematical model; Neural networks; Predictive models; artificial neural networks; electric market; load prediction;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Malatya

Type

conf

DOI

10.1109/SIU.2015.7129888

Filename

7129888