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- Publisher
- Wiley
- Copyright
- © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
- ISSN
- 1931-4973
- eISSN
- 1931-4981
- DOI
- 10.1002/tee.22050
- Publisher site
- See Article on Publisher Site
Abstract
Short‐term electricity load and price forecasting is an important issue in competitive electricity markets. In this paper, we propose a new direct time series forecasting method based on clustering and next symbol prediction. First, the cluster label sequence is obtained from time series clustering. Then a lossless compression algorithm of prediction by partial match version C coder (PPMC) is applied on this obtained discrete cluster label sequence to predict the next cluster label. Finally, the whole time series values of one‐step‐ahead can be directly forecast from the predicted cluster label. The proposed method is evaluated on electricity time series datasets, and the numerical experiments show that the proposed method can achieve promising results in day‐ahead electricity load and price forecasting. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Journal
IEEJ Transactions on Electrical and Electronic Engineering – Wiley
Published: Mar 1, 2015