Title :
Short-term electricity price modeling and forecasting using wavelets and multivariate time series
Author :
Xu, Haiteng ; Niimura, Tak
Author_Institution :
Dept. of Electr. & Comput. Eng., British Columbia Univ., Vancouver, BC, Canada
Abstract :
This work presents a new method to model and forecast the short-term electricity prices. The historical price and load data are first decomposed by wavelet transform, then multivariate time series is applied to model and forecast the wavelet coefficients of next day electricity price. The forecasted price is obtained by reconstructing the wavelet coefficients. The numerical examples of Pennsylvania-New Jersey-Maryland (PJM) spot market data are presented.
Keywords :
power markets; pricing; time series; wavelet transforms; Pennsylvania-New Jersey-Maryland; load data; multivariate time series; short-term electricity price forecast; short-term electricity price modeling; spot market data; wavelet coefficients; wavelet transform; Economic forecasting; Fuel economy; Load forecasting; Power generation economics; Power system economics; Power system modeling; Power system security; Predictive models; Wavelet coefficients; Wavelet transforms;
Conference_Titel :
Power Systems Conference and Exposition, 2004. IEEE PES
Print_ISBN :
0-7803-8718-X
DOI :
10.1109/PSCE.2004.1397570
