Author(s)

Shuang-Hua Cao, Jian-Bo Chen, Wen-Bing Weng, Jia-Cong Cao

College of Environmental Science & Engineering, Donghua University, Shanghai 201620, China.
College of Urban Construction & Environment Engineering, University of Shanghai for Sci. & Tec., Box 484, 516 Jun Gong Rd., Shanghai 200093, China, Tel.: +86 21 55270275, Fax: +86 21 55270686;.

In this works, artificial neural network is com-bined with wavelet analysis for the forecast of solar irradiance. This method is characteristic of the preprocessing of sample data using wavelet transformation for the forecast, i.e., the data se-quence of solar irradiance as the sample is first mapped into several time-frequency domains, and then a chaos optimization neural network is established for each domain. The forecasted so-lar irradiance is exactly the algebraic sum of all the forecasted components obtained by the re-spective networks, which correspond respec-tively the time-frequency domains. On the basis of combination of chaos optimization neural network and wavelet analysis, a model is devel-oped for more accurate forecasts of solar irradi-ance. An example of the forecast of daily solar irradiance is presented in the paper, the historical daily records of solar irradiance in Shanghai constituting the data sample. The results of the example show that the accuracy of the method is more satisfacto

Daily Solar Irradiance Forecast; Wavelet Transformation; Chaos Optimization Neural Networks

Cao, S. , Chen, J. , Weng, W. and Cao, J. (2009) Study of daily solar Irradiance forecast based on chaos optimization neural networks. Natural Science, 1, 30-36. doi: 10.4236/ns.2009.11006.