Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach

Stéphanie Monjoly, Maïna André, Rudy Calif and Ted Soubdhan

Energy, 2017, vol. 119, issue C, 288-298

Abstract: This paper introduces a new approach for the forecasting of solar radiation series at 1 h ahead. We investigated on several techniques of multiscale decomposition of clear sky index Kc data such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD) and Wavelet Decomposition. From these differents methods, we built 11 decomposition components and 1 residu signal presenting different time scales. We performed classic forecasting models based on linear method (Autoregressive process AR) and a non linear method (Neural Network model). The choice of forecasting method is adaptative on the characteristic of each component. Hence, we proposed a modeling process which is built from a hybrid structure according to the defined flowchart. An analysis of predictive performances for solar forecasting from the different multiscale decompositions and forecast models is presented. From multiscale decomposition, the solar forecast accuracy is significantly improved, particularly using the wavelet decomposition method. Moreover, multistep forecasting with the proposed hybrid method resulted in additional improvement. For example, in terms of RMSE error, the obtained forecasting with the classical NN model is about 25.86%, this error decrease to 16.91% with the EMD-Hybrid Model, 14.06% with the EEMD-Hybid model and to 7.86% with the WD-Hybrid Model.

Keywords: Global solar radiation prediction; Multiscale decomposition; Hybrid model; Autoregressive model; Neural network model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544216316668
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:119:y:2017:i:c:p:288-298

DOI: 10.1016/j.energy.2016.11.061

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().