Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China

Multivariate statistical and similarity measure based semiparametric modeling of the probability... •A novel semiparametric approach is proposed for electricity demand density forecast.•A new similarity measure strategy is designed based on K–L divergence analysis.•We consider both climate exclude and include conditions for mid-long term forecast.•High predictive accuracy is demonstrated when using the finance related variables.•We analyze possible future demand for China’s energy consumption system until 2020. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Energy Elsevier

Multivariate statistical and similarity measure based semiparametric modeling of the probability distribution: A novel approach to the case study of mid-long term electricity consumption forecasting in China

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Publisher
Elsevier
Copyright
Copyright © 2015 Elsevier Ltd
ISSN
0306-2619
D.O.I.
10.1016/j.apenergy.2015.07.037
Publisher site
See Article on Publisher Site

Abstract

•A novel semiparametric approach is proposed for electricity demand density forecast.•A new similarity measure strategy is designed based on K–L divergence analysis.•We consider both climate exclude and include conditions for mid-long term forecast.•High predictive accuracy is demonstrated when using the finance related variables.•We analyze possible future demand for China’s energy consumption system until 2020.

Journal

Applied EnergyElsevier

Published: Oct 15, 2015

References

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