학술논문
Comparison of very short-term load forecasting techniques
Document Type
Periodical
Source
IEEE Transactions on Power Systems IEEE Trans. Power Syst. Power Systems, IEEE Transactions on. 11(2):877-882 May, 1996
Subject
Language
ISSN
0885-8950
1558-0679
1558-0679
Abstract
Three practical techniques-fuzzy logic (FL), neural networks (NN), and autoregressive models-for very short-term power system load forecasting are proposed and discussed in this paper. Their performances are evaluated through a computer simulation study. The preliminary study shows that it is feasible to design a simple, satisfactory dynamic forecaster to predict very short-term power system load trends online. FL and NN can be good candidates for this application.