Next-day electricity price forecasting on deregulated power market

Author

Toyama, Hirofumi ; Senjyu, Tomonobu ; Areekul, Phatchakorn ; Chakraborty, Shantanu ; Yona, Atsushi ; Funabashi, Toshihisa

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. of the Ryukyus, Nishihara, Japan

fYear

2009

fDate

26-30 Oct. 2009

Firstpage

1

Lastpage

4

Abstract

This paper proposes the approach to reduce the prediction error at occurrence time of peak electricity price, and aims to enhance the accuracy of next day electricity price forecasting. In the proposed method, the weekly variation data is used for input factors of the NN at occurrence time of peak electricity price in order to catch the price variation. Moreover, learning data for the neural network (NN) is selected by rough sets theory at occurrence time of peak electricity price. This method is examined by using the data of PJM electricity market.

Keywords

economic forecasting; neural nets; power engineering computing; power markets; pricing; PJM electricity market; deregulated power market; learning data; neural network; next-day electricity price forecasting; peak electricity price; Accuracy; Asia; Economic forecasting; Electricity supply industry; Electricity supply industry deregulation; Neural networks; Power markets; Predictive models; Rough sets; Weather forecasting; PJM electricity market; electricity price forecasting; neural network; rough set theory; weekly variation data;

fLanguage

English

Publisher

ieee

Conference_Titel

Transmission & Distribution Conference & Exposition: Asia and Pacific, 2009

Conference_Location

Seoul

Print_ISBN

978-1-4244-5230-9

Electronic_ISBN

978-1-4244-5230-9

Type

conf

DOI

10.1109/TD-ASIA.2009.5356988

Filename

5356988