Daily solar radiation prediction based on wavelet analysis

Peng Zhang, Hirotaka Takano, Junichi Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

22 Citations (Scopus)


Solar radiation is an important factor in forecasting outputs of photovoltaic power systems. A method for solar radiation prediction is proposed based on wavelet transform. The data, including solar radiation and potential input variables, are decomposed into several time-frequency areas via wavelet transform. Given that some variables are relevant in some areas of solar radiation but irrelevant in other areas, we extract input variables from candidates separately in each time-frequency area. We perform principal component analysis (PCA) to extract principal components from input variables and we find their relations to the solar radiation are linear by visualization. Thus, linear regression equation is built to each area respectively, and the final result is the summation of predicted solar radiation from each time-frequency area. A comparison with the method using the same input variables in all time-frequency areas is presented and the results of our proposed method are more accurate.

Original languageEnglish
Title of host publicationSICE 2011 - SICE Annual Conference 2011, Final Program and Abstracts
PublisherSociety of Instrument and Control Engineers (SICE)
Number of pages6
ISBN (Print)9784907764395
Publication statusPublished - 2011
Event50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011 - Tokyo, Japan
Duration: Sept 13 2011Sept 18 2011

Publication series

NameProceedings of the SICE Annual Conference


Other50th Annual Conference on Society of Instrument and Control Engineers, SICE 2011

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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