Title :
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
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;
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
DOI :
10.1109/TD-ASIA.2009.5356988