The probabilistic model and forecasting of power load based on JMAP-ML and Gaussian process-Reference-Cited by-同舟云学术

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The probabilistic model and forecasting of power load based on JMAP-ML and Gaussian process

Published:2018-02-14 Issue:S4 Volume:22 Page:8589-8596
ISSN:1386-7857
Container-title:Cluster Computing
language:en
Short-container-title:Cluster Comput

Author:

Gao Wengen,Chen Qigong,Ge Yuan,Huang YiQing

Funder

National Natural Science Foundation of China

Key Natural Science Research Project of Anhui Province

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Software

Link

http://link.springer.com/article/10.1007/s10586-018-1927-3/fulltext.html

Reference25 articles.

1. Amin, S.M., Wollenberg, B.F.: Toward a smart grid: power delivery for the 21st century. IEEE Power Energy Mag. 3(5), 34–41 (2005)

2. Santacana, E., Rackliffe, G., Tang, L., Feng, X.: Getting smart. IEEE Power Energy Mag. 8(2), 41–48 (2010)

3. Ghosh, A.K., Lubkeman, D.L., Downey, M.J., Jones, R.H.: Distribution circuit state estimation using a probabilistic approach. IEEE Trans. Power Syst. 12(1), 45–51 (1997)

4. Heunis, S.W., Herman, R.: A probabilistic model for residential consumer loads. IEEE Trans. Power Syst. 17(3), 621–625 (2002)

5. Balestrassi, P., Paiva, A., de Souza, A.Z., Turrioni, J., Popova, E.: A multivariate descriptor method for change-point detection in nonlinear time series. J. Appl. Stat. 38(2), 327–342 (2011)

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