Temporal difference method for multi-step prediction: application to power load forecasting

Author

Hwang, Jenq-Neng ; Moon, Seokyong

Author_Institution

Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA

fYear

1991

fDate

23-26 Jul 1991

Firstpage

41

Lastpage

45

Abstract

The authors discuss a power load forecasting system based on a temporal difference (TD) method. The temporal difference method is a class of statistical learning procedure specialized for future prediction. The conventional back propagation (BP) has been successfully applied to power load forecasting in a one-to-one single-step prediction manner. The authors adopt a method which can gradually improve its prediction accuracy through the time evolution. In addition, a modified temporal difference (MTD) method which uses a different error function is evaluated and compared with the original one

Keywords

backpropagation; difference equations; load forecasting; neural nets; power engineering computing; back propagation; multi-step prediction; neural networks; one-to-one single-step prediction; power load forecasting; statistical learning; temporal difference method; Information processing; Information security; Laboratories; Load forecasting; Moon; Neural networks; Power system security; Sections; Statistical learning; Weather forecasting;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks to Power Systems, 1991., Proceedings of the First International Forum on Applications of

Conference_Location

Seattle, WA

Print_ISBN

0-7803-0065-3

Type

conf

DOI

10.1109/ANN.1991.213495

Filename

213495